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Event and rule services for achieving a Web-based knowledge network

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Event and rule services for achieving a Web-based knowledge network
Creator:
Lee, Minsoo, 1968-
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English
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xi, 122 leaves : ill. ; 29 cm.

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Subjects / Keywords:
Databases ( jstor )
Electronic commerce ( jstor )
Email ( jstor )
Internet ( jstor )
Subscriptions ( jstor )
Timing devices ( jstor )
Travel agencies ( jstor )
Web pages ( jstor )
Web servers ( jstor )
XML ( jstor )
Computer and Information Science and Engineering thesis, Ph. D ( lcsh )
Dissertations, Academic -- Computer and Information Science and Engineering -- UF ( lcsh )
Expert systems (Computer science) ( lcsh )
Knowledge management ( lcsh )
Rule-based programming ( lcsh )
City of Gainesville ( local )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Thesis:
Thesis (Ph. D.)--University of Florida, 2000.
Bibliography:
Includes bibliographical references (leaves 115-121).
General Note:
Printout.
General Note:
Vita.
Statement of Responsibility:
by Minsoo Lee.

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University of Florida
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The University of Florida George A. Smathers Libraries respect the intellectual property rights of others and do not claim any copyright interest in this item. This item may be protected by copyright but is made available here under a claim of fair use (17 U.S.C. §107) for non-profit research and educational purposes. Users of this work have responsibility for determining copyright status prior to reusing, publishing or reproducing this item for purposes other than what is allowed by fair use or other copyright exemptions. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder. The Smathers Libraries would like to learn more about this item and invite individuals or organizations to contact the RDS coordinator (ufdissertations@uflib.ufl.edu) with any additional information they can provide.
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45125836 ( OCLC )

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EVENT AND RULE SERVICES FOR ACHffiVING A WEB-BASED KNOWLEDGE NETWORK By MINSOO LEE A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2000

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Copyright 2000 by Minsoo Lee

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Dedicated to my dearest father and mother, and my beloved wife, Kyoungha.

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ACKNOWLEDGMENTS I am deeply indebted to Dr. Stanley Y.W. Su, chairman of my supervisory committee, for his continuous guidance, advice, and support throughout the course of my doctoral study. I would like to thank my supervisory committee members Dr. Herman Lam for his constant help and suggestions, Dr. Joachim Hammer and Dr. Abdelsalam Sumi Helal for their kind support, and Dr. Antonio Arroyo for his precious time. I thank our secretary, Sharon Grant, for her cheerful help during my stay at the Database Systems R&D Center. I would like to especially thank my father and mother for their unconditional love and support which helped me overcome many obstacles throughout my studies. I also thank my lovely wife, Kyoungha Hwang, who patiently waited and shared the burdens together while I pursued my research. Finally, I thank all of the colleagues and friends who helped me with inspiring discussions and also making my stay at the Database Systems R&D Center pleasant and enjoyable. I wish them all success in their studies and a bright future. iv

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TABLE OF CONTENTS Eage ACKNOWLEDGMENTS iv LIST OF TABLES viii LIST OF FIGURES ix ABSTRACT x CHAPTERS 1 INTRODUCTION 1 2 RELATED RESEARCH 1 1 2.1. Publishing on the Internet 1 1 2.2. Notification on the Internet 14 2.3. Rules on the Internet 19 3 KNOWLEDGE NETWORK CONCEPT 22 3.1. Preliminaries for the Knowledge Network 22 3.2. Requirements for Designing the Knowledge Network Framework 24 3.3. Key features of the Knowledge Network 25 3.4. Steps for Constructing the Knowledge Network 29 3.4.1. Publishing Data, Applications, Events, and Rules 29 3.4.2. Event Registration 30 3.4.3. Trigger and Rule Specification 31 3.4.4. Event Posting, Filtering, and Rule Execution 31 3.5. An Example of a Simple Web Page 31 3.5.1. Data 32 3.5.2. Methods 32 3.5.3. Events 33 3.5.4. Rules 33 V

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4 KNOWLEDGE MODEL 35 4. 1 . Event Specification 37 4.LL Events Associated with User/System Defined Methods 38 4. L2. Explicitly Posted Event 39 4.1.3. Timer Event 40 4.2. Rule Specification 42 4.2.1. Rule Variables 45 4.2.2. Method Calls to the ETR Server 47 4.2.3. Posting an Event 48 4.2.4. Example Rule 48 4.3. Trigger Specification 49 4.3.1. Events in Trigger Specification 51 4.3.2. Rule Structure in Trigger Specification 55 4.4. Rule Group Specification 59 5 KNOWLEDGE WEB SERVER ARCHITECTURE 61 5.1. Architecture of the Knowledge Web Server 61 5.1.1. Event Manager 62 5.1.2. ETR Server 62 5.1.3. Knowledge Profile Manager 63 5.2. Component Interaction Sequences 65 6 KNOWLEDGE NETWORK CONSTRUCTION, PROCESSING, AND MANAGEMENT 67 6. 1 . Constructing the Knowledge Network 67 6.1.1. Defining and Publishing Events and Rules 67 6. 1 .2. Event Registration 76 6.1.3. Subscriber-side Trigger and Rule Definition 79 6.2. Processing Events, Triggers and Rules 80 6.2.1. Posting Events 80 6.2.2. Trigger and Rule Processing by the subscriber 81 6.3. Event, Trigger and Rule Management 81 6.3.1. Expiring and Deleting Events 81 6.3.2. Editing Triggers and Rules 82 vi

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7 IMPLEMENTATION DETAILS 84 7.1. Detailed Architecture 84 7.1.1. Event Manager 85 7.1.2. Knowledge Profile Manager 85 7.1.3. ETR Server 86 7.2. Detail Component Interaction and Interface 88 7.2.1. Component Interactions for Publishing Events, Triggers, and Rules 88 7.2.2. Component Interactions for Event Registration on Provider Site 89 7.2.3. Component Interactions during Event Registration on Subscriber Site... 90 7.2.4. Component Interactions during Subscriber-Side Trigger and Rule Definition 91 7.2.5. Component Interactions for Posting an Event on the Provider Site 92 7.2.6. Component Interactions for Receiving an Event on the Subscriber Site . 93 7.2.7. Component Interactions within the Knowledge Web Server 94 8 KNOWLEDGE NETWORK APPLICATIONS 95 8.1. Business-to-Customer E-Commerce Scenario 95 8. 1 . 1 . The Gator Travel Agency 95 8.1.2. The Subscribers 97 8.2. Business-to-Business E-Commerce Scenario 100 8.2.1. The IntelliBiz company 101 8.2.2. The Supphers and Buyers 103 8.2.3. The Big Picture 107 9 CONCLUSION 109 APPENDIX BNF FOR RULE LANGUAGE 112 REFERENCES 115 BIOGRAPHICAL SKETCH 122 vii

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LIST OF TABLES Table Page L Subscribers of AirfareSpecialOffer event in Gator Travel Agency scenario 98 2. Subscribers of FlightCancelled event in Gator Travel Agency scenario 100 3. Subscription information of supplier e-CarSpeakers 104 4. Subscription information of supplier CarSeats.com 104 5. Subscription information of buyer MyAutos.com 106 6. Subscription information of buyer SportsCars.com 107 viii

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LIST OF FIGURES Figure Page 1. Architectural framework of the knowledge network 26 2. Steps for constructing the knowledge network 28 3. Example of Gator Travel Agency Web page and event registration form 32 4. Overview of the Active Object Model 35 5. An example of a rule structure 56 6. Example rule execution structure with nested AND and OR operators 58 7. Overview of architectural components in the knowledge Web server 61 8. Component interactions between two knowledge Web servers 64 9. Example of automatically generating event filter registration form 74 10. Detailed architecture of the components of the knowledge Web server 84 11. Architectural components of the ETR Server 87 12. Interaction among components for publishing events, triggers, and rules 88 13. Interaction among components for event registration on provider site 89 14. Interaction among components for event registration on subscriber site 90 15. Interaction among components for defining trigger and rule on subscriber site 91 16. Interaction among components for posting event on provider site 92 17. Interaction among components for receiving event on subscriber site 93 18. Component interactions within the knowledge Web server 94 19. The IntelliBiz home page and registration forms 103 20. The Business-to-Business e-commerce scenario 108 ix

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Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy EVENT AND RULE SERVICES FOR ACHffiVING A WEB-BASED KNOWLEDGE NETWORK By Minsoo Lee May 2000 Chairman: Stanley Y.W. Su Major Department: Computer and Information Science and Engineering The Intemet and the World Wide Web technologies have gained a tremendous amount of popularity among people and organizations because they provide a powerful means for people and organizations to share multi-media data, to do collaborative work, and to perform business transactions. At present, the Intemet is no more than a multi-media data network, which provides tools and services for people to browse and search for data. It does not provide the facilities for automatically delivering the relevant information that are useful for decision making to people or applications. Nor does it provide the means for users to enter and share their "knowledge" that is useful for making the right decisions. This dissertation introduces the concept of a Web-based knowledge network which allows users and

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organizations not only to publish their multi-media data but also to specify their knowledge in terms of events, rules, and triggers that are associated with their data and application systems. Operations on data and application systems may post events to trigger the processing of rules. The knowledge network is constructed by a number of replicable software components, which can be installed at various network sites together with existing Web servers to form the knowledge Web servers. The knowledge Web servers provide several build-time facilities such as a graphical user interface that allows data providers to easily publish their knowledge based on the Active Object Model (AOM), a registration facility that dynamically creates forms which enable users to selectively subscribe to event notifications and connect them to remotely executable rules on the provider-site, a tool to manage the knowledge elements defined by users as providers and/or subscribers. Run-time facilities that carry out the event filtering, event delivery, and trigger and rule processing are also included. Both data providers and consumers' knowledge can be captured and applied to benefit all Internet users in the knowledge network. A prototype knowledge network with the above build-time and run-time features and facilities has been implemented. We have used a number of e-commerce applications to demonstrate the utility of the Web-based knowledge network. xi

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CHAPTER 1 INTRODUCTION In recent years, Internet use has become widely popular among people and organizations that are interconnected through the Internet. The great impact of the Internet can be seen in the changing life styles of many people. The way many people obtain information has now changed to performing just a few mouse clicks on a computer which is connected to the Internet. People can communicate quickly and easily with almost anyone who has access to a computer and the Internet by using e-mail. Many kinds of businesses are aggressively putting their home pages on the Internet; and buying and selling things over the Internet has become common. Entertainment is also being provided through the Internet in the form of games, movies, and music. The Internet is now a vast sea of information where people surf on its waves in search of their desired information. The amount of information being provided and the number of users and businesses being connected on the Internet are constantly increasing. Approximately 1 million hosts were connected to the Internet in 1993, but now more than 40 million hosts exist on the Internet [NW]. The Internet has made it possible for people and organizations to easily share all kinds of data. It has also provided a basic infrastructure to deploy applications built on distributed technologies. As described above, it is evident that we are experiencing an explosive growth in the use of the Internet. But, at the same time, we are recognizing a fundamental problem related to the current Internet technology. This problem is preventing further growth and the development of new applications on the Internet. The problem with the current 1

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2 Internet is that it is merely composed of a network of data. There is an abundance of data stored all over the Internet, but no form of knowledge exists on the Internet to help in the extraction of meaningful data, timely delivery of data, activation of the correct application systems to process the data, timely notifications on the occurrences of events. Here, we define "data" as all facts that are recorded in the Internet and can potentially be used to aid human decision-making, "information" as data of value used in decisionmaking, and "knowledge" as data, events, rules and triggers useful for making decisions, not just any decision but the right decisions which produce correct results. As we look into this problem, we point out several detail limitations of the Internet technology resulting from this problem. Then we describe our knowledge network framework as a solution to the problem and explain how our proposed knowledge network framework alleviates each of these detail limitations. The current Internet can be characterized as a network of data. Data are stored all over the Internet with a physical connection provided by networks. The current architectural framework of this data network is composed of Web servers, browsers, HTML/script language, server side applications, and the HTTP protocol. Web servers contain data in the form of HTML or scripts, which focus only on the display format of data rather than the semantics of the data. Web servers can provide data residing on the servers through server side applications that are developed by programmers. Web servers are deployed worldwide and interconnected through physical networks. Browsers act as clients to the Web servers and access data via the HTTP protocol. Data is requested from a client site and provided by the web server on the remote site via the client-server paradigm. This architectural framework has been successful so far in terms of enabling

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people with access to the Internet to share data. The current limitations resulting from this architecture are the following: First, most of the data transfers on the Internet are based on a pull model. This is mainly due to the client-server paradigm of computing that is widely adopted over the Internet. In the pull model, a client system will perform the pull by initiating a request to a server, and the server will respond to the request by transferring the needed data to the client system. Servers on the Internet are initially isolated from each other and only respond to requests that are given to them. The pull model of data transfer requires a system that is doing the pull to know what to pull and when to pull. Therefore, systems that want to collaborate and receive data from other systems need to have precise knowledge about what interfaces are provided to them by the other systems and may also need to periodically poll other systems to see if data is available on another system. The way people do the browsing on the Internet is also based on the same pull model. The pull model can currently work only with one-to-one interaction. This pull model is highly inefficient because of the one-to-one interaction limitation and may waste processing power and bandwidth from polling, especially when performing collaboration among multiple systems. This mode of interaction cannot scale up to the millions of servers being deployed on the Internet. Second, the current Internet is built upon stateless technologies. Stateless technologies do not store any information about the state of the system, and thus cannot remember anything about previous states of the system. HTTP [Fil97] is a stateless protocol which does not remember anything from previous connections to even the same site. Therefore, every client request is independent of each other. This requires redundant

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4 information to be passed to the web server every time a request is made. HTTP makes it highly inefficient for continued interactions with a web server. On top of this stateless protocol, home pages are being designed with the same approach, where each access to the data on the Web server is independent and not very much is remembered about the surfer. The surfer knows what he is interested in when he visits a home page, and it is most likely that he would want the same or similar data when he visits the home page again. There should be a way for the surfer to explicitly request and also specify what he is interested in and enable the Web servers to capture this knowledge. This knowledge is sensitive information of the surfer and thus must be carefully stored on the Web servers. Some Web servers dealing with a huge amount of data tend to let surfers provide some information about their interest and keep them as user profiles in order to change the display or contents of the home page when visited again. A similar function is provided by a file called cookie that is stored on the surfer's computer. Cookies store the connection information about clients. But all of these solutions for storing the interests of surfers are proprietary solutions developed individually without relying on any kind of general framework, thus resulting in a lot of programming effort that is not reusable nor can it be integrated with other sites in the Internet. Storing this kind of knowledge about the clients within the Web server will enable the Web server to automatically identify those clients that are interested in the data when new data is available on the Internet. Moreover, if the Web server is also equipped with an appropriate communication infrastructure, it can notify the client about the new data. Therefore, a general framework that can store this kind of knowledge in the Web server is needed.

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5 Third, the format of the data published and transmitted over the current Internet is only suitable for the human eye. The information on the Internet is currently provided with a focus on how it should be displayed. This means that humans are needed to interact with the web servers to retrieve information. This severely limits the possible applications that could be developed. If machine processing of data on the Internet were possible, a variety of applications could be developed. By enabling machine processing of the data, knowledge could be easily built into applications for carrying out some tasks instead of requiring human intervention. Such applications are search engines and intelligent agents that can carry knowledge about the tasks with them and travel over the Internet and conmiunicate with each other by exchanging data formats appropriate for machine processing. Also, collaboration among applications on several servers can be more easily supported by making the exchange format suitable for machine processing. Fourth, time-critical notification and processing is impossible on the current Internet. There is no framework for a person (or system) to be notified about new or updated data available on a Web server, and also no method for automatically performing several operations as a response to the new data. Currently, a person can be informed of newly available data on a Web server in the form of e-mail. However, immediately performing an action as a response to the e-mail is not always possible. It would be impossible for a person or group of people to manually react to the huge amount of data being generated on the Internet. Therefore, a mechanism is needed not only to automatically notify a person (or system) of newly available data but also to immediately react to this notification and intelligently perform certain operations without human interactions.

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6 Fifth, embedding executables into a Web server is currently done by low-level program codes, which is not what a typical Web surfer can do. In most cases, developing the executables requires expertise. Typical Web surfers now want to do something with the data that they obtain, but cannot easily specify nor install their knowledge into a system that can automatically perform operations using the obtained data. This is due to the lack of a high-level language and framework that can be easily used by anyone to support this functionality. As the use of the Internet is rapidly spreading through people with limited technical expertise, a way for easily specifying and installing their decisionmaking and action performing procedures as knowledge in a high-level fashion is increasing in demand. The current detail limitations stated above result from the problem that the current Internet architecture is a data network. We propose a novel framework, a knowledge network architecture, to solve the problem. The knowledge network allows both consumers and providers of data to express their knowledge in forms of events, rules, and triggers that are associated with data and data processing. The contributed knowledge can be incorporated into the current data network. Events are any things of interest (e.g., data states, software system operations, signals from external devices) that occur in the knowledge network. The occurrence of an event will cause the notification of users or software systems which have registered for the event. An event can carry data over the Internet to its subscriber. Rules represent a granule of control and logic using a high-level language. Each rule specifies some condition that needs to be evaluated in order to determine whether or not to execute a structure of operations or an alternative structure of operations. Triggers are specifications that relate events with rules or rule structures.

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7 making it possible to fire rules upon the occurrences of events. The trigger specifications provide a very flexible way of linking events with potentially complex structures of rules to capture semantically rich and useful knowledge. The knowledge network is composed of several key concepts: publishing events and rules, event filters, push-based event delivery, knowledge profile, and processing of triggers and rules. These key features are incorporated into an extension of the current Web server, namely, the knowledge Web server. Information providers can use the publishing mechanism to put events and rules on their Web pages, which allows Web surfers to register themselves as subscribers to certain event notifications and also connect the event notifications to those rules that are published. Event filters are used to support the personalized subscription of the events, where meaningless event instances will be filtered out and only the specific subset of event instances of interest will be notified. In the knowledge network, events are delivered via a push-based mechanism to subscribers' knowledge Web servers to provide a more active and scalable mode of conmiunication among the web servers. Also, the providers and subscribers of information can specify and store and manage their knowledge (i.e., events, triggers, and rules) in knowledge profiles. Triggers and rules are executed within the knowledge Web servers to perform the validation of complex relationships among events, scheduling among rules, and finally execute various operations via rules. The proposed knowledge network remedies the previously identified limitations of the current Internet technology. The following describes the advantages of a knowledge network in contrast to a data network. First, a knowledge network employs the push technology for information dissemination instead of the inefficient pull model of

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8 interactions among current web servers. However, pulling information is still permitted. The push approach supports scalability by allowing information providers to efficiently serve a large number of subscribers over the Internet. It also enables a large number of web servers to collaborate. Second, knowledge Web servers store detailed information about the subscriber's interest in the form of event filters. This saves bandwidth by not clogging up the network with irrelevant event notifications, and makes it possible to push events and their associated data to the subscribers only if they are relevant to them. Third, knowledge specifications are represented in XML [Bray98] format, which includes the semantics of the information rather than just the display formats. Knowledge specifications can be interchanged among knowledge Web servers, and machine processing of data carried by the event becomes possible. Fourth, timely and automatic reaction to events is possible because events are linked to rules by triggers; and rules are automatically executed when an event of interest occurs. Fifth, rules are specified in a high-level language, which makes it easy for a typical web surfer or an information provider to add his/her knowledge into the knowledge Web server. A knowledge network can be used for a variety of applications and also provide the essential framework for future applications based on the Internet. Some examples are: virtual enterprises, intelligent supply-chain management systems, intelligent agents used in e-commerce, military command/control systems, web-based workflow systems, cooperative information systems, replication servers, web data integration systems, intelligent information dissemination systems. It is possible to support these collaborative and distributed applications over the Internet by designing and implementing the knowledge network.

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9 The main contributions of this work can be summarized as follows. First, an event, trigger, rule model, and language is designed to provide a high-level specification of event notification, parallel rule execution, and control/logic representation for Internet applications. Second, a graphical user interface (GUI) editor and code generator are implemented to assist the application developer in inputting and editing high-level events, triggers, and rules and eventually generating the low-level code required for execution. Third, event filtering and push-based event delivery mechanisms are provided to enhance the performance of event notification. These mechanisms are future trends of the Internet technology because bandwidth usage and scalability are important. Fourth, an EventTrigger-Rule (ETR) server, which can automatically execute provider side or subscriber side rules upon receiving an event and can also perform scheduling of various rule execution sequences—including parallel execution sequences—is implemented. The replicable ETR server eliminates human intervention in processing massive amounts of data, and provides scalability in processing a large number of rules. Fifth, mechanisms to support dynamic changes of events, triggers, and rules are developed. These mechanisms help the management of events, triggers, and rules on the Internet where they are subject to frequent changes. The mechanisms allow the changes to be done without bringing down the system or interfering with the tasks being carried out at the time of change. The GUI editor and code generator were improved to support this capability, and a dynamic class loader was additionally implemented. Sixth, a specification and efficient processing mechanism for event history is developed in order to allow complex relationships among distributed servers to be modeled and efficiently evaluated during trigger processing. Lastly, a platform-independent and integrated component developed with Java, which can

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10 be added into any standard web server, is implemented in order to support the rapidly emerging collaborative applications that interconnect web servers via events and rules. The organization of the remainder of this dissertation is as follows. In Chapter 2, some related research on events and rules on the Internet are surveyed. In Chapter 3, the basic concept of the knowledge network is explained to provide an overview of the framework. In Chapter 4, an Active Object Model (AOM), which is the basis for providing event and rule service on the Internet, is presented. Chapter 5 describes the overall architecture of the integrated component that is to be added into the web servers. Chapter 6 discusses the design of the system related to the knowledge network construction (i.e., defining events, triggers, and rules), processing (the events, triggers, and rules), and management. Chapter 7 gives the implementation details about the component modules. In Chapter 8, example scenarios that demonstrate the usefulness of the knowledge network are provided. Finally, Chapter 9 gives a summary of the work with suggestions for future work.

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CHAPTER 2 RELATED RESEARCH Our work on the design and development of a knowledge network involves several emerging fields of research and technology. The key technologies that have motivated us to pursue this research are the publishing and sharing of data on the Internet, notification services via the Internet, and the rule technology. 2.1. Publishing on the Internet The advance in Internet technology has been enormous in a short period of time. The Internet now connects millions of Web servers world-wide. Anyone who has access to the Internet can easily look for whatever they need on the Internet. The concept of client-server computing is now widely accepted, even to computer novices, in the form of browsers and Web servers. The Internet is indeed changing the life style of people and the way companies perform their business globally. The biggest reason that the Internet has become so popular is its capability to provide anybody in the world having access to the Internet with virtually any information they need. The amount of data on the Internet is tremendous and is still rapidly increasing. The technology to allow people and companies to publish this kind of data started out as HTML (HyperText Markup Language) [HTML]. The HTML language allows a person to display text, pictures, animation, and even embed sound files into a home page in any way he or she designs it. However, HTML is a static display, which does not perform interactive or sophisticated operations in the way a simple program can. Therefore, CGI [CGI], JavaScript [JavaS], applets [Applet], and servlets [Serv] have been 11

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12 introduced to provide additional capabilities to HTML. They give the information provider a means not only to display his/her data to the users but also to interact with the surfers on the Internet. The information providers in this case need to develop codes or scripts that can be embedded into the home page or Web server. Currently, the Java language has gained quite a lot of interest in the distributed computing area, and its platform independence feature makes the concept of applets a very powerful alternative to developing downloadable client side programs. Applets, together with servlets, which are server side programs, can form a very flexible and powerful client-server application. All of these technologies that are related to publishing data and developing programs on the Internet have proven to be very useful and successful thus far. The main problem that we now face is that these technologies are based on only human interactions, such as displaying data on a screen or pushing a button to initiate an operation. This is because HTML can specify how to display data, but it does not give any information about what is being displayed. Therefore, a machine (or program) reading the HTML file cannot find out what the content of the home page is. This creates a major obstacle to applications such as search engines, and data extraction/gathering utilities. To this end, XML (Extensible Markup Language) [Bray98] has been proposed and is currently one of the hottest subjects in research. XML allows users to create their own DTD (Document Type Definition), which is a template that contains a set of tags defined by the user. An XML document uses these tags to wrap specific parts of the documents. These tags specify the semantics of the data that is contained within each part of a document. By knowing the semantics of the tags, the XML document can be processed by a machine (or program), which can easily extract information from the document. As XML only specifies the content of the document and not the display

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13 format, another document which specifies the rules for displaying each tagged part of the XML document is needed, namely, XSL (Extensible Stylesheet Language) [Oasis]. XML relies on DOM (Document Object Model) [DOM99], which models a document as a tree of objects. These objects altogether form a semi-structured document, which can be easily parsed and also navigated. By giving the document a structure, the browser can easily identify specific parts of the document and handle simple user interactions with the document without going all the way to the Web server just to perform a simple interaction. This is the concept of DHTML (Dynamic HTML) [DHTML]. DHTML makes a home page more active, and most of the user interactions can be handled on the client site rather than the server site. RDF (Resource Description Framework) [RDF98] is an effort to use meta-data to describe data on the Web. The term meta-data in this case means data about data, such as a library catalog, which is meta-data for the books in the library. RDF is basically a framework to describe resources. Anything that has a URI (Universal Resource Identifier) can be a resource, and the resources are described by a set of property types and values, where a property type may be "Author" and the value may be "John." The format used is similar to XML, making it possible to be processed by a machine (or program). It supports interoperability by allowing applications to describe and interchange machine-understandable information on the Web. The past and current research in the Internet area has mostly focused on publishing data. As discussed above, publishing data for displaying to the human eye started the Internet revolution, and then came the interactive scripts and programs to make the data more alive. The next issue was to make published data more machineunderstandable. In our work, we would like to introduce another dimension to publishing

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14 on the Web: publishing knowledge. In this work, knowledge is represented by events and rules specified by Internet users and embedded into the network system. Knowledge enhances the active capability of the Internet. Knowledge is not just data sitting on the system, but data that can be timely shared through events and associated rules to create a very active system. Therefore, the publishing of knowledge not only involves displaying the events and rules (either in a human-readable format or a machine-understandable format), but also provides a mechanism to subscribe to events, deliver events, and process rules. 2.2. Notification on the Internet The basic communication paradigm on the Internet so far has been based on the pull model of interaction. Browsers pull data from a Web server at the request of a user. The pull model of interaction is basically the client-server paradigm, which is very simple to implement. Although the pull model of interaction is currently prevalent on the Web, there are serious limitations. The pull model is a passive approach to obtaining data. No data other than the data requested at the time of the request will be provided. Therefore, in the Internet environment where an enormous amount of data exists, there is a limitation on the amount of data that a user can access and process because every access must be initiated by the user. To remedy this problem, a data delivery model based on the push model began to gain interest in the research community. The push model of interaction allows subscribers to specify their interest in certain data, and these preferences are kept on the server. The server will then push the data of interest to the subscribers based on their preferences. This model of interaction makes it possible for subscribers to receive data in a timely fashion without additional effort. This approach has an additional advantage of scalability

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15 when the same data needs to be disseminated to a large number of subscribers, because it can avoid the point-to-point request/response connection overhead. Some early work on push-based systems were Teletext [Amma85, Wong85], Datacycle at Bellcore [Herm87, Bowe92], and Boston Community Information System (BCIS) at MIT [Giff90]. These early efforts focused on information broadcasting. The Teletext system provided results on one-way, two-way, and hybrid broadcasts. The Datacycle project used a repetitive broadcast medium. BCIS broadcasted information over FM channels. The first widespread push-based system was the PointCast system [Point], which created a huge worldwide interest in the push technology in 1996. Although PointCast looks as if it is performing its communications using the push model, the actual implementation of how it works is based on the pull model. A large number of PointCast data centers, which are servers that have updated data, are geographically dispersed around the U.S. Each of the PointCast client software that is running on the subscriber's machine is actually polling the data centers periodically to download the data that the subscriber is interested in. Marimba's Castanet [Marim99], Netscape's Netcaster [Nets99], and Backwebs Polite Agent [Back99] are also push-technology-based products. These products also work in a similar way as PointCast, and therefore have their own smart ways to reduce the overhead of downloading by making use of the idle time of users. Also, a standard for the push technology called Channel Definition Format (CDF) [CDF97] has been developed by Microsoft and submitted to the W3 Consortium. It allows publishers to specify channels, the contents, and the update schedule for pushing the data.

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16 Event notifications are also a form of the push-based technology. The concept of events is now commonly accepted in many areas. Events can represent a thing that is happening at some time in a high-level format. The difference between the data push described above and the event push is that the event push systems are actually implemented in accordance with the push model. Also, event data are usually much smaller than huge chunks of data. Several efforts related to designing a protocol to support event notification on the Internet have recently gained a considerable amount of interest. The Basic Lightweight Information Protocol (BLIP) [BLIP98] provides real-time, reliable, transactional, message queuing services based on the publish/subscribe model of communication. It can be used for both notification services and delivery of MIME. Microsoft's General Event Notification Architecture Base (GENA) [Coh98] defines a notification architecture that transmits notifications between HTTP (HyperText Transfer Protocol) resources. Products that support event notification services have been introduced, each with their own proprietary solution. The Keryx Notification Service [Keryx] by KeryxSoft, a group in Hewlett Packard Laboratories, Bristol, provides a language and platform independent infrastructure implemented in Java to distribute notifications on the Internet. Notifications are considered as structured information describing the events. The target applications are distributed agents, workflow, World-Wide-Web (WWW) site management, personal communication services, and distributed virtual environments. Vitria's Businessware Communicator [Vitria] allows applications to publish business events to multiple information channels, while other applications can subscribe to the business events of interest. Multiple Quality-of-Service (QOS) levels and security protocols are also supported. WebLogic Events [WebL] allows any WebLogic

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17 application on the network to register for interest in an event and also install action codes that is to be executed when the event occurs. WebLogic applications generate event messages, which the WebLogic Events server will receive, and if an application has registered for the event it will execute the installed action. The user-encoded actions can be things such as sending an e-mail, paging, or updating the database. Because the Internet is an open community and it connects people and companies all over the world, it is desirable to work with standards rather than with proprietary solutions. Future event notification systems may be built upon communication infrastructures that are more compliant with standards. Some of the following infrastructures strongly encourage the usage of XML and HTTP, which possibly is a good foundation for future event notification systems. WebBroker [WebB98] developed by DataChannel is a distributed object communication framework extended to the web, and it adopts some of the features of OMG's CORBA and Microsoft's COM+. It uses HTTP as the transport protocol, XML as the syntax for specifying object interfaces and message formats, and URIs as addresses for software objects. It is implemented as a servlet that can be embedded into Web servers. The interface-based communication paradigm makes communications transparent by having a client side proxy and a server side skeleton, where the proxy and skeleton are similar to stubs in CORBA. The main advantage of WebBroker is that it has blended the distributed object communication framework into Web standards. Webmethod's B2B [WebM] is another product that uses XML and HTTP as a solution to inter-company integration for supporting scalable business-to-business applications. Veo Systems [Meltz98] uses the XML as an exchange format, which is currently targeted for trading in e-commerce over the Internet.

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18 In order for the push technology to work, one of the essential problems to solve is to establish a good open standard. The standard should not only decide how to communicate but also deal with the important issues of security. But, as shown above, even for the underlying communication framework, a variety of mechanisms are being proposed and implemented. It may take some time for a standard of the push technology to be developed and be widely accepted. All of the efforts for the push technology seemed to be promising initially, but soon afterwards, a serious problem was recognized. The data that is pushed is not only poorly organized but also too much data is being pushed to subscribers. In many cases, a lot of data that is not of the subscriber's interest was being pushed. The excitement for the push technology has calmed down, but still more research is continuing in this area. This technology is still regarded as an ongoing effort, but seems to be the only way to deal with the massive data on the Internet. We therefore have undertaken our research on the basis of push-based concepts with the anticipation of a better solution and an improved implementation in the future. An approach to solve the problem of the abundant data being pushed to subscribers is to employ filtering techniques. If subscribers can provide more specific information to the server about their interest, irrelevant data can be filtered out before being sent to the subscribers. Some work in this area has been performed with respect to text documents within SIFT (Stanford Information Filtering Tool) [Yan93a, Yan93b]. The SIFT server keeps client profiles, which consist of keywords and weights. The SIFT server will then use a highly efficient indexing technique to perform the filtering of the large amount of text against the keywords in the client profiles. The connections from the document source to the SIFT server and again to the SIFT client are all push-based.

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19 point-to-point, and initiated aperiodically (i.e., doesn't follow a pre-arranged schedule). WebLogic also incorporates a form of event filtering by using a topic tree. The topic tree is a tree of events where each subscriber can register for interest in a specific event node. The events close to the root are more general events, whereas, the events at the branches are more specific events. When an event occurs, the event flows through the branch towards the root, activating the event nodes of interest to the subscribers. This makes it possible to allow the subscribers to register in a finer granularity of events. WebLogic requires the subscribers to perform some coding to do the registration. Our work emphasizes the use of event filtering for enhancing the usefulness of pushing events. We focus on developing a more efficient and powerful event filtering method that can filter events based on the attributes using a number of powerful operators. Moreover, we propose an approach, which is immediately deployable on the Internet, and does not require any user programming for event registration. 2.3. Rules on the Internet Thus far, the Internet has connected the world in a very passive way by using the pull model of interaction. All information requests and operations need to be explicitly initiated by somebody. Employing the event push model with event filtering on the Internet is one step towards making the Web more active. Using the push model, events can be delivered to each Web site. But what do we do with the events? If a person needs to be sitting in front of a computer to do something with the events, we are not making sufficient use of the possible advantages of the technology provided to us. The next step is to design an executable program that can react to these events without any need of human intervention. These executable programs should also be very easy to specify using a high-level language. This is why rules are needed.

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20 The concept of rules has originally emerged in the research area of artificial intelligence and expert systems. The declarative and simple forms of rules were appropriate to model knowledge and started out as the condition-action (CA) type of rules. The condition-action type of rules has the semantics of "when a condition is true, perform the action." Expert systems such as 0PS5 [Brown85] or CLIPS [Giarr91] use this type of rules. The rules were soon incorporated into databases to create a new category of databases, namely, active databases. Some examples of these active database systems are HiPAC [Day88], Ode [Geh91], Sentinel [Chak94c], Ariel [Hans96], OSAM*.KBMS [Su93], Postgres [Sto91], and Starburst [Hass90]. ECA (EventCondition-Action) rules have been used in many of these systems. ECA rules are composed of three parts: event, condition, and action. The semantics of an ECA rule is, "When an event occurs, check the condition. If the condition is true then execute the action." The event provides a finer control as to when to evaluate the condition and gives more active capabilities to the database systems. Rules can automatically perform security and integrity constraint checking, alert people of important situations, enforce business policies and regulations. Using rules in the distributed environment has been researched in the context of providing autonomy for sites and also enhancing the performance of processing rules [Ceri92]. Cooperative information systems have also recently started to make use of rules as a glue-component for putting together heterogeneous systems [Bem97, Su95]. Some initial approaches toward using rules to integrate servers on the Internet have been experimented. WebRules [Ben97] is a framework developed at the Israel Institute of Technology. The WebRules server has a set of built-in events that can notify remote systems, and has a library of system calls that can be used in a rule to hook up

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21 Web servers; however, the approach requires a skilled programmer to be able to create the rules. The WebRules server uses a S2S/HTTP protocol, which is an extended version of HTTP. The framework focuses on connecting companies that own Web servers rather than individuals surfing on the Internet. It does not consider the push concept nor event filters. Moreover, composite events also are not considered. Composite events are an important tool for interconnecting several servers with a complex relationship. Nevertheless, it is the most influential work that motivated our research in knowledge networks. WebLogic also includes a basic form of rules, which are called actions. These actions need to be provided to the WebLogic server at the time when an application is registering for an event. These actions are actually specified with program codes rather than a high-level specification. Thus, the developer of the action needs to deal with system-level issues. Agents that are being deployed on the Internet also incorporate rules as their basic form of knowledge. The SIM_AGENT tool kit [Slom96] is an example, which employs a condition-action rule-based programming style. IBM's Agent Builder Environment (ABE) [ABE] provides an open architecture where additional functions can easily be added. ABE includes a rule-based reasoning system. Our approach for embedding knowledge, more specifically events, rules and triggers, into the Web servers can make the Web more active. We focus on how to make this infrastructure easier to deploy and use, scalable enough to connect millions of servers, and powerful enough to incorporate complex reactions. Dynamic change of rules during the run-time operation of Web servers is also investigated to ensure uninterrupted operation of the servers.

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CHAPTER 3 KNOWLEDGE NETWORK CONCEPT The main goal of the knowledge network is to share the knowledge available on the Internet among the users of the hitemet. This would promote efficient exchange of knowledge and the development of more organized and interconnected knowledge among individual expertise that is currently isolated from other Web sites and users. To explain the concept of the knowledge network more clearly, we start with a few preliminary definitions. After these preliminary definitions, the requirements for the design of the framework, the key features, and the steps for constructing the knowledge network are presented to provide a comprehensive understanding of the concept. 3.1. Preliminaries for the Knowledge Network We start with defining the concept of knowledge which is frequently used in a broad area of research and technology. Then, the data network, which specifies the current Internet architecture, and our definition of the knowledge network are discussed. These concepts form the basis of our work • Definition 1. Knowledge: In the cognitive sciences, knowledge is referred to as a permanent structure of information stored in memory [Rob99]. Various definitions exist based on the different viewpoints on knowledge. Here, we define knowledge based on the nature of the content rather than the representation. There are two types of knowledge: procedural and declarative. The procedural type of knowledge consists of skills acquired through interacting with the environment and is what we call 22

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23 "know-how". Declarative knowledge is based on facts and is concerned with the properties of objects, persons, and events and their relationships. Although the mental processing and representation of knowledge are complex activities and the research community's understanding of this field is on-going, our approach is to model both the declarative and procedural knowledge via events, triggers, and rules. Definition 2. Data Network: The data network is composed of all kinds of data (i.e., texts, formatted data, graphs, audio, videos) that are recorded in the Internet. These data may or may not involve in some form of human decision and reasoning processes. Those that do (i.e., data of value for decision making) become "information" to the users of the data. The data network itself does not have any capability to actively respond to new data nor the intelligence to reason nor make decisions using the data. The main goal of the data network is to share data among users on the Internet but always requires human intervention for reasoning or decision making tasks to create new and more valuable data. Definition 3. Knowledge Network: The knowledge network is composed not only of data elements but also knowledge elements which can be used to perform automatic reasoning and decision-making tasks. In this work, knowledge elements are presented by events, triggers, and rules. The events encapsulate timely information of what is happening on the Internet and makes the knowledge network actively responsive without human intervention. The rules express the decision-making factors allowing the intelligence of humans to be embedded into the knowledge network. The triggers model complex relationships among events and rules, checking histories of events and enabling various reasoning or activation sequences to reflect the complex

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24 decision making process. The knowledge network has a goal not just of sharing data but also sharing knowledge to make the Internet into a more active, collaborative, and intelligent infrastructure. To summarize our view, "data" is defined as all forms of media that are recorded in the Internet and can potentially be used to aid human decision-making, while "information" is data of value used in decision-making. And "knowledge" is data, events, rules and triggers useful for making the right decisions. 3.2. Requirements for Designing the Knowledge Network Framework The knowledge network should satisfy the following requirements. First, the knowledge network should allow publishing not only data but also events and rules, and the specification of triggers that links events to rules. Second, the knowledge network should support an event notifying mechanism that is push-based in order to be efficient and scalable. Third, the knowledge network should support event filtering to reduce irrelevant data delivery. Fourth, the knowledge network should support automatic execution of triggers and rules connected to the event notifying mechanism. Fifth, the knowledge network should provide a mechanism to easily define and manage the events, triggers, and rules for each user on the Internet. Sixth, the knowledge network should dynamically adapt to changes such as adding, deleting, and modifying the rules or events in order not to affect the standard server operations. Last, the knowledge network components should be easily incorporated into standard Web servers and provide platform independence.

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25 3.3. Key features of the Knowledge Network The knowledge network can enhance active collaboration of Web servers and users on the Internet by providing a framework to (1) publish data, applications, constraints, events, and rules, (2) register for subscription of events and deliver events to subscribers, (3) define rules on subscribed events. The framework to accomplish these tasks is based on the idea of providing a component that can be plugged into any standard Web server. This should allow the Web servers that need to collaborate to have a synametric architecture. Another technology that is needed to support this framework is event, trigger, and rule processing capability being built into the component. This is the major part that should be developed in order to provide any type of intelligent, distributed and collaborative infrastructure. The idea of using user profiles is also adopted to support a wide variety of users on the Internet who wish to have their own individually customized applications. The architectural framework of the knowledge network shown in Figure 1 is used to explain the key features of the knowledge network: publishing events and rules, event filters, push-based event delivery, knowledge profile, and processing of triggers and rules. In Figure 1, several Web servers are interconnected through the Internet. Each server is extended with several components that form the basis of the knowledge network. Only the extensions to the Web server are shown in the figure for simplicity. We refer to a Web server with these extensions as a knowledge Web server (KWS). Assume that the knowledge Web server ATakes the role of a data provider who is user A and knowledge Web servers B and C are maintained by two different users, namely, user B and user C, who need information from the knowledge Web server A. The active users

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26 A, B, and C are each residing on the sites for the KWS A, KWS B, and KWS C with a browser interface to the systems and the Internet. Trigger & Rule Processor R2 Rl Event & Filter Processor Event & Filler Processor R3 Knowledge Profiles User A Publish Events, Rules E], E2. Rl, R2 Knowledge Web Server A O Event ^ Trigger Rule \Z/ Filter INTERNET Trigger & Rule Processor Publish Events, Rules Knowledge Profiles UserB Knowledge Web Server B Event & Filter Processor R4 Trigger & Rule Processor Publish Events, Rules Knowledge Profiles UserC Knowledge Web Server C Figure 1 . Architectural framework of the knowledge network. Data providers can provide data and define events and rules, and publish them on web pages. Publishing of events will enable Web surfers to know what kind of data can be delivered to them in a timely manner. Interested Web surfers can register for the events and become subscribers of the event. Rules published by data providers can perform several operations on the knowledge Web server of the data provider. Subscribers of events can conveniently select these rules that will be executed remotely on the data provider's knowledge Web server when the subscribed event occurs. Figure 1 shows that the knowledge Web server A has published two events El and E2, and two rules Rl and R2. User B has subscribed to event El and linked it to rule Rl, while user C has subscribed to event E2 and linked it to rule R2.

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27 Event filter templates are provided by data providers to allow event subscribers to more precisely specify the subset of the event occurrences in which they are interested. The subscribers can give various conditions on the values that the event carries. Only those event instances that satisfy the condition will be delivered to the subscriber. By using event filters, only meaningful data will be provided to the subscribers. Thus, network traffic can be significantly reduced. Figure 1 shows that the event filter Fl is installed on event El by user B, while the event filter F2 is installed on event E2 by the user C. In a knowledge network, events are delivered via a push-based mechanism to subscribers' knowledge Web servers. When the event occurs, the push mechanism is activated in order to deliver the event to a large number of knowledge Web servers in a timely fashion. This push-based mechanism can radically change the paradigm of how interactions on the Internet are performed. Moreover, the combination of event pushing with the event filtering creates a more powerful communication infrastructure for the knowledge network. Figure 1 shows the extension related to the push-based event delivery combined with the event filtering in each knowledge Web server. The providers and subscribers of knowledge can specify and store their knowledge (i.e., events, triggers, and rules) in knowledge profiles. Each knowledge Web server is extended with a component that can provide a web-based graphical user interface to the provider or subscriber of knowledge to edit their knowledge profile. The knowledge profile is persistently stored. The events, triggers, and rules stored in the knowledge profile are provided to other run-time components of the knowledge Web

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28 server. Figure 1 shows the knowledge profiles existing on different knowledge Web servers. Triggers and rules are executed within the knowledge Web server when an event linked to it has occurred. Processing the triggers involves checking of complex relationships among event occurrences and also the scheduling of several rules. Rules can activate various operations on the Web server. The execution of a rule may again cause new events to occur, resulting in a chained execution of rules. Figure 1 shows the processing components for triggers and rules residing within each knowledge Web server. Knowledge Web server B will execute rule R3 upon receiving filtered event El, and knowledge Web server C will execute rule R4 upon receiving filtered event E2. Figure 2. Steps for constructing the knowledge network.

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29 3.4. Steps for Constructing the Knowledge Network The knowledge network is constructed through a process involving a series of steps that need to be followed by the providers and subscribers participating in the knowledge network. This section explains each of the steps in the order they occur. Figure 2 shows an example for a single provider and single subscriber participating in the construction of the knowledge network. This simplified view of the construction process is used as the example to be explained throughout this section. 3.4. 1. Publishing Data, Applications, Events, and Rules Currently, a user (or organization), say A, that has data and applications (i.e., methods that may be connected to a database in his/her home directory) can publish this data and application on his/her home page. Using the knowledge network concept, user A can also publish the events that can be raised from his/her own data and applications and allow other Web surfers to subscribe to those events. The definition of the events are input into the knowledge profile to enable the knowledge Web server to process the events. All other knowledge elements described in this section are also input into the knowledge profile. User A can easily hookup the event to his/her home page afterwards. An event filtering mechanism may also be provided by user A. Subscribers will later on give some value ranges for the filters during the event registration step (to be explained in Section 3.4.2), and when the event is being posted, the system checks if the event attribute values satisfy these given value ranges prior to sending out the event to the subscriber. Rules that are applied to user A's data can also be published for use by various applications that require meta-data (e.g., in e-commerce applications.) Several parameterized rules that can be triggered by user A's own events may also be published. The subscriber of user A's event can link the event to the parameterized rules during

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30 event registration so that automatic rule processing can be conducted on the provider site (i.e., user A's site) with the guarantee that these operations are authorized and safe for user A's own Web server. This is shown as steps ® and ® in Figure 2. 3.4.2. Event Registration Another user, say B, is surfing on the web and discovers the homepage of user A and finds an event of interest. User B then accesses the event registration form and registers for an event that user A has published on his/her home page. User B may subscribe to the event to be sent out either as an e-mail notification or a pushed event to his/her knowledge Web server. At the time of registration, user B may also provide values that are to be used later on for filtering out irrelevant events. If some parameterized rules linked to the subscribed event are supported by the event provider, the user B may select some rules to be executed on the event provider's site. An example of such a rule could be changing user B's subscription information (i.e., discontinue subscription of an event after some specified number of postings) automatically after sending the event. The event registration steps are shown as steps (D to ® in Figure 2. After user B performs this registration, the event that occurs later on will be filtered and then either be sent out as an e-mail notification or be posted to the knowledge Web server on which the user B has his/her own knowledge profile. The knowledge profile should contain the events that the user B has subscribed to as well as the triggers and rules that are defined for the event. User B can also defined additional triggers and rules that are to be processed at his/her own knowledge Web server when an event notification has reached the knowledge Web server. This is further described in the following subsection.

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31 3.4.3. Trigger and Rule Specification After subscribing to an event, user B may then access the Knowledge Profile Manager--a module which manages the user's knowledge profile (event subscription, trigger and rule definition information)--of his/her own knowledge Web server and specify the additional triggers and rules that should be executed upon the occurrences of the events he/she has subscribed to. Several events that user B has subscribed to may be linked to a set of rules, forming composite events and structures of rules. In Figure 2, these steps are shown as ® and ®. 3.4.4. Event Posting, Filtering, and Rule Execution Service providers will later generate events that first go through a filtering process to identify the relevant subscribers of the event. Once the subscribers are identified, rules on the provider's site can be executed. These rules are remote executable rules, which are intended to allow remote users to have a limited capability to execute units of code on the provider's site. The event is then posted either as an e-mail message to the subscriber or an event notification to the subscriber's knowledge Web server. If the subscriber has some triggers and rules defined on his/her own knowledge Web server linked to the event, the event will trigger the execution of these rules which may perform some operations within the subscriber's web server and/or generate another event that can be again posted to another site. This is step ® in Figure 2. 3.5. An Example of a Simple Web Page An example web page of the Gator Travel Agency, which publishes data, applications, events, constraints, and rules, is shown in Figure 3. An example event registration form is also shown.

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32 The basic concept is that each page is an object. An object on the Internet can be referred to by its URL. The example shows that each object can have data, methods, events, and rules (along with triggers). [Data] Gator Travel Agency Special Offer! Airfares are reduced to Europe. Other Links [Methods] MakeReservations CheckAvailability [Events] TicketSpecialOfferEvent FlightCancelled [Rules] StopSubscriptionOfEvent RefundCancelledFlight FlightCancelled Event Registration Form Filter ° Flight Number Notification ° Subscriber E-mail [ ° Subscriber URL C Rule ° RefundCancelledFlight TimeLimitToNextFlight UserName Figure 3. Example of Gator Travel Agency Web page and event registration form. 3.5.1. Data All of the items on the homepage are regarded as data. These are attribute values of the object. There is a title attribute with the value of "Gator Travel Agency," a notice attribute with the value of "Special Offer! Airfares are reduced to Europe." Links to other pages may be regarded as a special type of attribute of the object, and can make the currently displayed object a composite object. 3.5.2. Methods Each object (page) can embed methods that can be exported. The methods can be thought of as applications that can be used by whoever accesses the object. The methods

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33 may be actually implemented as applets or servlets. If the method needs parameters, a message box may pop up within an applet when the method name is clicked. If an input parameter is a primitive type (i.e., int, char, boolean, String), then the value may be directly typed in (such as 1000, 'g', true, "hello"). URLs may also be given as parameters for the method. For servlets, parameters may be provided through the HTTP request. 3.5.3. Events The object can post events, and those events are published together on the Web page. By clicking on the event name, an implicit method (which is not explicitly exported) of the event registration object (which can be implemented as a servlet) is invoked and takes the registration information from a subscriber of the event. Figure 3 shows an example event registration form for the FlightCancelled event. 3.5.4. Rules Rules that are defined by the object are exposed. These rules may be tied to events by triggers when a subscriber goes through the event registration process. The rules are predefined but have the flexibility of customization by allowing some parameter values to be defined by the event subscriber at the registration time. In other words, the rules can be tailored to fit the individual user's needs. In the following example, the customizable parameters in the rule RefundCancelledFlight are UserTimeLimit and User. Rule: RefundCancelledFlight Condition: NextAvailableFlightTime(cancelled_flight_no) > UserTimeLimit Action: MakeRefund ( User, flight_no )

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34 The remote user can define these customizable parameter values and install the rules. The rules may also receive some parameter values from events. In this case, the event parameter to rule parameter mapping needs to be specified in the trigger. Figure 3 shows an example of how the RefundCancelledFlight rule is included in the event registration form of the FlightCancelled event. Note that the parameters UserTimeLimit and User are renamed in the form as TimeLimitToNextFlight and UserName in order to give the user a better understanding of the parameters. A description of the rule or the rule definition itself can also be provided in the registration form, if necessary.

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CHAPTER 4 KNOWLEDGE MODEL The Active Object Model (AOM) is an extension of the traditional object model and is intended to model various resources (i.e., data entities, events, constraints, actionoriented rules, triggers, and component systems) of distributed objects in a heterogeneous, distributed network. Different from the traditional object model, which capmres the structural properties of objects in terms of their attributes (or properties) and their behavioral properties in terms of methods, AOM extends these properties to include events (similar to the object model of Java Beans), constraints which are declarative forms of assertions, condition-action-altemative-action (CAA) rules, and triggers which relate events and rules. Furthermore, AOM allows the nesting of schemas to encapsulate the structural and behavioral properties and knowledge specifications of a set of classes into a hierarchical component architecture. Schema Classes Schemas Knowledge Spec (for Schema) Class Attributes Methods Knowledge Spec (for Class) Knowledge Spec Events Triggers Rules Constraints Figure 4. Overview of the Active Object Model. 35

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36 The basic building block of AOM is the object class. As shown in Figure 4, an object class defines the properties of a set of like objects in terms of attributes, methods and an optional knowledge specification. The knowledge specification consists of events, constraints, CAA rules and triggers. A trigger specifies what events and event history would cause the firing of a structure of rules. The knowledge specification of a class is used to define the constraints and rules that govern the operations on the objects of the class. In other words, it specifies knowledge that is tightly coupled to the class. A set of object class specifications forms a schema. Additionally, a schema may optionally contain a knowledge specification, which defines events, constraints, CAA rules and triggers that govern the interoperation of the objects of the classes defined in a schema (see Figure 4). Thus, a schema can be defined to capture the structural and behavioral properties and knowledge specifications of a component in a component architecture. Since components in a component architecture may constitute a higher level component, AOM allows the nesting of schemas in a schema to any number of levels. At any level, a knowledge specification can be given to define the events, constraints, rules and triggers that are applicable to the objects of the classes defined in the schemas of the same and lower levels. A component can be visualized as a set of classes and their knowledge specifications defined and used within a single system, or systems on a subdomain of the network, or an arbitrary group of systems on the network. In the following sections, we shall present the event, rule and trigger specifications of AOM. Constraints are declarative assertions that are applied on attributes or method executions within or among classes. Their specifications are similar to the condition specifications of CAA rules. We, therefore, will not separate them from

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37 CAA rules in the following discussion. Attribute and method specifications are similar to those of the traditional object model and they are not presented in the following sections. In fact, it may be desirable to de-couple the knowledge specification from the traditional object specification in terms of attributes and methods. The knowledge specification language or GUI developed for event, rule and trigger specifications can then be coupled with some existing object modeling tools to implement the full capabilities of the AOM. 4. 1 . Event Specification AOM distinguishes three types of events with respect to how they are raised: namely, events associated with methods, explicitly posted events and timer events. The general syntax of the event specification language is given below. [IN schema_name / schema_name :: class_name ] EVENT [DESCRIPTION event_name(type pari, type par2, type parN) text_description] TYPE METHOD / EXPLICIT / TIMER [COUPLING MODE BEFORE / AFTER / ON_COMMIT / INSTEAD_OF / DECOUPLED ] [OPERATION method_name ] [AT [ '[' start_time ']' ] MM/dd/yyyy:hh:mm:ss [ '['end_time ']' ] [EVERY [ '[' start_time ']' ] (,MM/dd/yyyy:hh:mm:ss )* nn time measure [ '['end_time ']' [RETURNS retum_type]

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38 Not all the clauses shown in the aggregated general syntax are applicable to an event type. We shall explain the three event types and provide examples to show their syntactic structures in the following subsections. 4.1.1. Events Associated with User/System Defined Methods An event can be defined and associated with a method execution. Once defined, an event posting statement (which is a method call to an event manager) can be automatically generated to post the event at a proper place of program execution relative to the activation of the method. An event can be posted "before" or "after" the method is executed, or at the "commit" time of the transaction in which the method is activated. The associated transaction manager will post the events related to the commit time. These different ways of posting an event with respect to a method execution have been called by the database community as "coupling modes." Events with the above coupling modes are always posted synchronously, which means that the program code, which posts an event of this type, will wait for a response from the event and rule server that handles the event. Another coupling mode, which is called de-coupled, allows a program to post an event and continue its execution without waiting for a response from a server. An event with this couphng mode is posted asynchronously. Thus, the coupling mode of an event specification implicitly determines whether the event should be posted synchronously or asynchronously. In addition to the above modes, an event can have a mode called "instead of." This mode allows an event to trigger the execution of some rule(s) instead of the original method; however, the rule(s) may include the original method in addition to other operations. This mode is very useful for "customizing" the behavior of a component system modeled by a class.

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39 An event can have parameters, which are the parameters given to the associated method. When an event is posted, parameter values will be passed to rules that are triggered by the event. This allows the object that posts the event to pass some data for use in rule processing. For an event that is posted synchronously and needs a return type, the return type of the associated method is assumed. The syntax of a method-associated event is shown below: schema_name :: class_name EVENT event_name [DESCRIPTION text_description] TYPE METHOD COUPLING MODE BEFORE/AFTER/ON.COMMIT/ INSTEAD_OF/DECOUPLED OPERATION method_name 4.1.2. Explicitly Posted Event An event can be defined without being tied to a method. This type of event can be posted within an application program or a method body of an object class. The posting of an event would create an instance of the event type. An explicit event can be posted synchronously or asynchronously by a method call to an event manager. This type of event can also carry parameters. This provides a way for a program to pass data to rules for use in rule processing. If the event is posted asynchronously, data is not expected to return and the return type is ignored. If it is posted synchronously, the RETURNS statement defines the return type. This type of event can be defined at a schema level or within a specific class. If this type of event is defined within a specific class, it is posted only within the methods of

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40 the class. Otherwise, the event may be posted within any class of the schema. The syntax of this type of event specification is given below: IN schema_name / schema_name :: class_name EVENT event_name (type par 1 , type par2, . . . , type parN) [DESCRIPTION description_text] TYPE EXPLICIT [RETURNS retum_type] 4.1.3. Timer Event The timer event is an event posted by a Timer at some pre-specified time point or in some time interval. The Timer can be a dedicated server that keeps track of the global time, or if this facility does not exist, just a local module that keeps track of the local time. Three types of timer events are distinguished. The first type is an absolute timer event, which means that an event is posted by the Timer at an explicitly specified time point. The time is given in the MM/dd/yyyy:hh:mm:ss:nnn format, where MM is the month, dd is the day, yy is the year, hh is the hour, mm is the minute, ss is the second, and nnn is the millisecond. If hh:mm:ss:nnn is not given, the default value of 00:00:00:000 is assumed. A blank space in a field defaults to 0. The syntax of this absolute time event is given below with an example. EVENT event_name [DESCRIPTION description_text] TYPE TIMER AT MM/dd/yyyy:hh:mm:ss:nnn (,MM/dd/yyyy:hh:mm:ss:nnn )* EVENT my_important_times DESCRIPTION this event is for some important times of interest TYPE TIMER AT 01/22/1999, 02/23/2000:02:45:30::

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41 The second type of timer event is the absolute recurring timer event, which is an event that is repeatedly posted every month or every day or every time interval. This type of event uses a "*" to express the repeating time points. As an example, if "*" is given in the month field, it means that the event is posted every month. This type of event can also have a starting time and an ending time. Together, they specify the time window in which the event should be actively posted. The keyword "NOW" can be used as the starting time to indicate that the event should be posted immediately. The following gives the syntax and an example stating that the event should be posted every 30 minutes of every hour on the 10th day of every month in 1998 starting from May 2, 1998, until November 1, 1998. EVENT event_name [DESCRIPTION description_text] TYPE TIMER AT [ '[' start_time']' ] inin/dd/yyyy:hh:mm:ss:nnn (,mm/dd/yyyy:hh:mm:ss:nnn )* [ '[' end_time']' ] EVENT my_repeating_event [DESCRIPTION description_text] TYPE TIMER AT [5/2/1998] */10/1998:*:30:: [11/1/1998] The third type of timer event is the relative recurring timer event, which specifies that an event should be posted by the Timer every several seconds, minutes or hours. This event specification uses a separate keyword EVERY, and also allows for the specification of a start time and an end time. The syntax is as follows: The allowable time units for time_measure are milliseconds, seconds, minutes, hours, or days.

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42 EVENT event_name [DESCRIPTION description_text] TYPE TIMER EVERY [ '[' start_time ']' ] nn time_measure [ '[' end_time ']' ] An example for posting an event every 2 minutes starting from March 20, 1998, is given below: EVENT every_2_minutes_event DESCRIPTION this event is posted every 2 minutes and continues forever TYPE TIMER EVERY [3/20/1998] 2 minutes All of the above timer events are asynchronously posted. 4.2. Rule Specification CAA (Condition-Action-Altemative Action) rules provide a very general way for specifying integrity and security constraints, business rules and policies, regulations that are relevant to the operation of a real or virtual enterprise. Each CAA rule represents a small granule of control and logic needed to enforce a constraint, business rule, or policy. A number of these rules, when executed in a certain order or structure, can represent a larger granule of control and logic. By defining and processing rules, it is possible to automatically enforce various constraints on objects of a class, objects among classes in the same schema, or objects among classes in different schemas. A rule can have a number of parameters just like a procedure call and perform some desired operations. When the rule is invoked, it first checks the condition part of

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43 the rule. If the condition is true, the operations specified in the ACTION clause are executed. Otherwise, the operations specified in the ALT ACTION clause are executed. The overall syntax of a rule is as follows. IN schenia_name / schema_name::class_name RULE rule_name (parameter list) [RETURNS retum_type ] [DESCRIPTION description_text] [TYPE DYNAMIC/STATIC] [STATE ACTIVE/SUSPENDED] [RULEVAR rule variable declarations] [CONDITION guarded expression] [ACTION operation block] [ALT ACTION operation block] [EXCEPTION exception & exception handler block] The optional clauses are surrounded by brackets. The IN clause specifies where the rule is defined (i.e., in which class or schema level). The rule_name is a unique identifier for the rule. The list of parameters is specified together with the rule_name. The DESCRIPTION clause contains a text string describing what the rule does. The TYPE clause is used to specify if the rule is to be frequently modified (i.e., DYNAMIC) or is not likely to change once defined (i.e., STATIC). This information can be used to internally generate the most efficient code for the rule. The STATE clause specifies if the rule should initially be active or suspended. Suspended rules can be activated at runtime by other rules or under a program control. Active rules can be deactivated (or suspended) at run-time. Note that the state specification of a rule does not reflect the current state of the rule in the system, as the current state can be changed after the rule is defined. The current state information is managed as an internal attribute of the rule and

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44 is separated from the rule definition. The RULEVAR clause allows the rule to have variables defined. Also, variables, which need to be persistent, are declared within this clause. The CONDITION clause is specified using a guarded expression. A guarded expression can be divided into two parts: the guard part and the condition expression part. The guard part is composed of a sequence of expressions all of which must be true in order to continue the processing of the rule. If any of the expressions within the guard evaluates to false, the processing of the rule is discontinued and the rule is skipped. The expressions within the guard are evaluated in a sequential order, and if all of the expressions evaluate to true, the condition expression part of the CONDITION clause will be processed. The condition expression is the final condition that is to be checked in order to decide whether to go to the ACTION clause or the ALT ACTION clause. The reason for employing the guarded expression is that it allows for efficient and ordered processing of pre-requisite conditions, which must be satisfied in order for the rule processing to be meaningful. A simple example of a CONDITION clause with a guarded expression is given below. CONDITION [ flag = TRUE, count > 0 ] count * 2 < quantity The guard part is surrounded by the brackets, and the condition expression part is the expression 'count * 2 < quantity'. A rule processing system first checks if the expression 'flag = TRUE' evaluates to True. If not, the entire rule is skipped. Otherwise, it checks if 'count > 0' evaluates to True. If not, the rule is skipped. Otherwise, the condition expression is evaluated. If the condition expression is True, the entire guarded expression is True. Otherwise, the guarded expression is False. Therefore, a guarded

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45 expression returns one of these three values: Skip, True or False. Note that the guard part is optional. Without it, the condition expression returns True or False. The ACTION clause and ALT ACTION clause consist of operations to be carried out. The EXCEPTION clause specifies what to do when an exception, such as a division by zero or the failure of an operation, occurs within the rule. The exception model is similar to the exception model of the programming language Java. The type of exception and the method to handle this type of exception is specified as pairs in the EXCEPTION clause. The exception types are defined as classes and the exception handlers may exist within a specific exception handler class or a user-defined class. A rule can also return a value, which can be a primitive type or a user-defined type. The return type is specified by the RETURNS clause. The value to be returned is specified in return statements in the ACTION and ALT ACTION clauses. In a rule specification, the CONDITION clause can be omitted. In that case, the ACTION clause must be given and will be unconditionally processed. When the CONDITION clause is given, either the ACTION clause or the ALT ACTION clause may be omitted, but not both. An omitted ACTION clause or ALT ACTION clause means that no operation is to be executed by the clause. 4.2.1. Rule Variables Variables for rules can be declared using the RULEVAR clause. There are three types of variables that are considered useful for rules. First, temporary variables for a rule may be defined. These temporary variables are the same as local variables defined within the scope of the rule. No special keywords are needed to declare this type of variables. These variables can have data types similar to those provided by the Java language (in the java.lang or java.util packages) such as int. String. Also, user-defined

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46 types are allowed. Second, persistence is often required for storing rule information, so that the rule can have a state that can be passed on from one instantiation of the rule to another instantiation of the same rule. A persistent rule variable is similar to the static variable as defined in the Java or C++ programming language, i.e., a single instance of this variable is shared among all the instances of the same rule. The keyword 'persistent' is used for this type of variable. Third, existing objects such as CORBA objects may need to be referenced in a rule. This is to support a special case where a CORBA infrastructure may be additionally attached to the Web server and the ETR server (our implementation of the rule server) may at the same time be acting as a CORBA client and/or server to this CORBA infrastructure. In order to allow this tj^e of variable to be declared and used, we define a third type of variable, which uses the keyword 'existing'. Parameters needed to identify an existing object are specified using a constructor style call. An example of a simple declaration for three variables in the RULEVAR clause is given below: RULEVAR int i; //temporary persistent int limit; // persistent and static existing CORBA_object CobjC'Serverl 1"); // existing CORBA object It is possible to specify the desired initial value of a persistent variable, when the variable is first created and stored. This can be done by specifying the parameters in parentheses beside the variable name, similar to a constructor call. A simple example is shown below: RULEVAR persistent int limit (0) ; This declaration will initialize the value of the limit variable to 0 only when this variable is first created and stored. Note that this initialization of the value will only

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47 occur "once" when the variable is created in the persistent store. Subsequent executions of the same rule will only read the variable from the persistent store, as the variable is already created and stored in the persistent store. An example for initializing a persistent variable, which is an instance of a composite class, is given below. Assume that "Part" is a class, which needs a "String" and a "Project" instance to initialize its values. And "Project" is again a class, which needs a "String" and an "Integer" to initialize its values. RULEVAR persistent Part pi ( "CylinderPart", ("EnginePjt", 5020) ); The parameters needed for pi are the String "CylinderPart" and a "Project" object, which is initialized by the parameters surrounded by the nested parentheses. The "Project" initialization parameters are "EnginePjt" and 5020. As a result, the needed Project instance is first created, and then this instance and the "CylinderPart" String are used to initialize the Part instance pi. Afterwards, this variable can be used in the same way as an ordinary variable would be used in the CONDITION, ACTION or ALTERNATEACTION part. Note that persistent rule data is data shared by different instantiations of the same rule type. Data that is shared among different types of rules can be stored into a global persistent repository, which could be a database providing querying capability. Since this level of sharing data can be easily done by a global repository, we do not focus on this level of sharing in the rule language. 4.2.2. Method Calls to the ETR Server Rule commands can be used in the ACTION or ALT ACTION clauses. Rule commands are method calls to the ETR server. Commands which enable, disable, or delete rules and rule groups, are shown below: Enable_rule ( String rule_name )

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48 Disable_rule ( String rule_name ) Delete_rule ( String rule_name ) Enable_group ( String group_name ) Disable_group ( String group_name ) Delete_group ( String group_name ) The concept of rule groups will be explained later. All of the above method calls will be directed to the local ETR server that processes the rules. 4.2.3. Posting an Event A rule can also post an event synchronously or asynchronously in the ACTION and ALT ACTION parts by using the following statements: PostSync(event_variable); PostAsync(event_variable); The event_variable is declared in the RULEVAR and the event parameters are set via assignment statements in the action/alternative action part of the rule. 4.2.4. Example Rule A sample rule is given below to show how a rule can be defined. The rule is basically evaluating the programmer salaries of companies located only in San Jose, and it returns the result of the evaluation. During the evaluation, different criteria of evaluating the salaries are applied based on the revenue (or size) of the company. It additionally posts an event containing the evaluation results when it finds a large size company. The BNF for clarifying the rule syntax is given in the Appendix. RULE salary_rule (int company_revenue. String location, Employee emp) RETURNS String DESCRIPTION "evaluate programmer salaries of companies in SanJose, applying different criteria based on company revenue" RULEVAR String result, // declare temporary object

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49 NotifyingEvent found_large_company_event; persistent large_count; // declare persistent object existing MyCORBAServer my_server("m012"); // declare existing object CONDITION [company_revenue > 0, location = "SanJose", "emp.job= programmer"] company_re venue > $ 1 00,000,000 ACTION large_count = large_count +1 ; // update persistent value result = my_server.EvaluateLargeCompany( company_revenue, emp.salary); // CORBA call found_large_company_event.revenue = company_re venue; found_large_company_event.Evaluation = result; PostAsync( found_large_company_event ); Return result; // optional retum value ALT ACTION result = my_server.EvaluateSmallCompany( company_revenue, emp.salary); // CORBA call Retum result; // optional retum value 4.3. Trigger Specification Triggers relate events with mles. A trigger specifies an event stmcture that would fire a stmcture of mles. An event stmcture has two parts, namely, a TRIGGEREVENT part and an EVENTHISTORY part. The TRIGGEREVENT part specifies a number of altemative events each of which, when posted, would trigger the evaluation of the event history specified in the EVENTHISTORY part. If the event history is evaluated to Tme, the stmcture of mles specified by the trigger is processed. Otherwise, the stmcture of mles will not be processed. The TRIGGEREVENT part is purposely kept very simple. It allows the logical OR of a number of simple events (that is, any one of the events specified in the list, when posted, will trigger the evaluation of the EVENTHISTORY).

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50 The EVENTHISTORY part can be a complex event expression stating the interrelationship of a number of events that have been posted. For example, "El and E2 but not E3" have been posted or "E5 occurred before E4 within a specified time window". The EVENHISTORY part expresses a "composite event", a term used in the active database literature. This separation of TRIGGEREVENT and EVENTHISTORY provides a way to more specifically name the events that will trigger the evaluation of a more complex event expression, thus avoiding the repeated evaluation of the complex event expression. This is different from the event specification of some existing EGA rule systems in which, when a composite event is specified, all the events mentioned in the composite event all implicitly become the trigger events. In the above two composite event examples. El, E2, E3, E4 and E5 are implicitly the trigger events in more traditional EGA rule systems, i.e., the posting of any one of the events will trigger the evaluation of its corresponding composite event. In some applications, one may want to specify that only the posting of E2 should trigger the evaluation of "El and E2 but not E3" and only the posting of E4 will trigger the evaluation of "E5 occurred before E4 within a specified time window". The separation of TRIGGEREVENT and EVENTHISTORY allows more explicit specification of what triggers the evaluation of an event history. The structure of rules, given in the RULESTRUC clause, can be a linear structure or a general graph structure. In a linear structure, the rules are processed sequentially, following the rule order. In a graph structure, rules can be executed sequentially, in parallel, or with synchronization points. The parameters of the TRIGGEREVENT can be

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51 passed to the rules in a RULESTRUC and the trigger would include the specification of their mappings. The overall syntax of the trigger is as follows: TRIGGER trigger_name ( trigger_parameter_list ) TRIGGEREVENT events connected by OR EVENTHISTORY event expression RULESTRUC structure of rules using subsets of the trigger_parameter_list RETURNS retum_type : rule_in_rulestruct The TRIGGEREVENT or EVENTHISTORY can be omitted, but not both. If the TRIGGEREVENT is omitted, the default is the OR of all the events referenced in an EVENTHISTORY expression. 4.3.1. Events in Trigger Specification The event specification consists of the two parts, which are described in more detail in the following two subsections. • TRIGGEREVENT This part specifies which event triggers the actual processing of the EVENTHISTORY expression. Only the parameters of the events specified in the TRIGGEREVENT part are passed. Recall that when the TRIGGEREVENT is omitted, the default mode is ORing all of the events in the EVENTHISTORY. In this case, the parameters of the events are not passed because there is no event specified in the TRIGGEREVENT part. The rules that are triggered in this case do not depend on event parameters passed. If the parameters are to be passed, the parameters which correspond to each of the trigger event parameters should be specified in the parameter list of the TRIGGER clause, and the data types of these parameters must match with those of each trigger event as shown below.

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52 Assume that El and E2 have the following matching parameter lists (i.e., parameters with the common data types exist between the two events). El (int j 1 , classX j2, String j3, int j4) E2(String kl, int k2, classX k3) The trigger event part defined on these two events can be specified as the following. The parameters passed by the trigger events are specified as parameters of the trigger. Here, vl, v2 and v3 correspond to jl, j2 and j3 of El, and also to k2, k3 and kl of E2, respectively. TRIGGER sample_trigger (int vl , classX v2. String v3) TRIGGEREVENT El (vl, v2, v3, j4) OR E2 (v3, vl, v2) The trigger events can only be connected with OR as shown below. TRIGGEREVENT El OR E2 OR E3 OR E4 • EVENTHISTORY Events of the past can be tested to allow for composite event processing. The history of events can be checked, but parameters of the historical events cannot be passed to the rules. If we allow for historical events to pass parameters, we must be able to differentiate between the various occurrences of the event history instances and decide which event instances compose the event history instance. This is called parameter contexts in other research systems [Chak94b] that focus on the processing of composite events. This can be very complicated, and still an easier semantics of parameter contexts is needed to actually apply them to real world applications. We shall consider the inclusion of this capability in a future version of the knowledge specification language and its implementation. In this version, we focus on keeping the semantics of the event history as simple as possible. Therefore, only the truth value of the event history will be

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53 checked. A simple way to access actual event parameters in an event history is by accessing them within the rule via a method call to the event history processor which logs all of the event instances. Historical events can be expressed using logical or sequence operators to combine simple events into a composite event. The syntax of a historical event is given below. Historical_event := [ '[' start_ time ']' ] Composite_event [ '[' end_time ']' ] Composite_event := Composite_event Ev_op Composite_event 1 Simple_event Ev_op := Lx)gical_op I Sequence_op Logical_op := AND '[' time_window ']' I AND I OR I NOT Sequence_op := >'[' time_window ']' I > A time window for processing the EVENTHISTORY can be specified. The following example specifies that only the event history from 20 to 10 days before the posting of a trigger event is considered in the EVENTHISTORY clause. If during that time window both El and E2 have occurred, the EVENTHISTORY will return True. EVENTHISTORY [-20 day] El ANDE2 [-10 day] The time window can be specified relative to the trigger event using a '-' sign which indicates time points "before" the trigger event occurs. Or, a calendar format time can be given to specify the absolute time points of the window independent of the time the trigger event occurs. The keyword 'NOW can be used to denote the time of the triggering event. The logical operators are AND, OR and NOT. The AND operator can have an optional time window specified within brackets (i.e., [ ] ) following the operator. Two events connected by the AND[time window] operator means that, if the two operand events occur within the given time window, the composite event has occurred. If the

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54 time window is not specified, it defaults to the time window specified for the whole EVENTHISTORY clause. The point of time at which a composite event defined by an AND operator occurs, is the time when the later event of the two operands occurs. This point of time is important for evaluating an AND expression that has a time window specification. The OR operator means that if any of the operand events has occurred, the composite event is regarded as having occurred. The NOT operator is used to assure that a specific event did not occur during the time window given by the EVENTHISTORY clause. The following examples show some historical events that use AND, OR and NOT logical operators. El AND[5min] E2 El AND E2 E4 OR E6 NOT E7 The sequence operator denoted by '>' can have an optional time limit for the sequence. For example, assume we want to check the occurrence of some historical events "El occurs before E2 and the time between these two events does not exceed 2 minutes". We can use the following expression: El >[2 min] E2 The sequence may also be cascaded : E2 >[30 sec] E4 >[2 min] E5 The time that a composite event defined by a sequence is considered to have occurred is the time the last event in the sequence occurs.

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55 A historical event can be expressed with a mixture of logical operators and sequence operators. A couple of examples are given below. ( El AND[2 sec] E2 ) >[3 sec] ( E3 OR E5 ) ( El >[2 min] E4 ) AND ( E5 >[3 sec] E6 ) 4.3.2. Rule Structure in Trigger Specification Recall that a CAA rule represents a small granule of logic and control. A number of CAA rules together can implement a larger granule of logic and control. The RULESTRUC clause of a trigger specification allows a structure of CAA rules to be triggered when the event specification is satisfied. It specifies the rule execution order and maps the parameters of the events to the individual rules. There are two basic operators for specifying the execution order. The first operator '>' is used to specify a sequential order of rule execution, and the second operator ',' is used to specify a parallel execution. For example, the following expression means that rules Rl, R2, R3, and R4 are to be executed sequentially following the specified order. Rl > R2 > R3 > R4 Note that the '>' operator can be cascaded. It is also straightforward to specify a parallel execution of rules. The following example shows that rules Rl, R2, R3, and R4 are to be executed in parallel: (R1,R2, R3,R4) For expressing a more complicated rule structure, the structure can be broken into pieces, which are divided by ';' and each piece is specified using the concept of fan-in and fan-out.

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56 Event R1 R2 R3 R8 R9 Figure 5. An example of a rule structure. Assume that the rule execution structure shown in Figure 5 is desired. The semantics of the rule execution in the graph is the AND semantics, which means that each rule must wait for all of its predecessors to finish before it can execute. Rule R8 must wait for both R4 and R5 to finish before it can execute. The above structure can be specified as follows: Rl > R7 ; R2 > R4 ; R3 > (R5, R6) ; AND ( R4, R5 ) > R8 ; AND ( R5, R6 ) > R9 The sequential executions such as Rl > R7 and R2 > R4 are specified as before. A fan-out is used to specify that, after the execution of R3, rules R5 and R6 can start their execution independently. The following two fan-in sequences are also specified. After both R4 and R5 finish their execution, R8 can then start. And after both R5 and R6 finish their execution, R9 can then start its execution.

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57 Any kind of complex rule structure can be decomposed using this fan-in and fanout mechanism. The fan-out is only used when the destination rules (R5, R6 in the above example) of the fan-out have a common single originating rule (R3 in the above example). The fan-out may be specified in various ways (i.e., in the above structure it may be specified as R3>R5 ; R3>R6); whereas, specifying the fan-in exactly as it is shown in the structure is mandatory for assuring the correctness of the specification. In the above example, only the AND semantics are used for fan-in. To allow more flexibility in defining a rule execution structure, we allow the OR semantics to be included into the fan-in construct. The OR semantics means that when a subset of the predecessors of a rule are finished, the rule can start its execution. In the previous example, to say R8 needs to wait for only one of the two rules R4 and R5 to finish, we can use the following expression: OR[l](R4, R5)>R8 The 'OR[l]' means that the fan-in needs only to wait for one of the predecessors to finish. The number of rules to wait for can be specified in the brackets. Some other examples are: 0R[2] (R1,R2,R3,R4,R5,R6) > R7 OR[3](Rl,R2,R3,R4,R5,R6,R7,R8) > RIO The '0R[2] ' means 'wait for two out of Rl, R2, .... R5 and R6', and '0R[3]' means 'wait for three out of Rl, R2, R7 and R8'. These AND and OR operators can be nested to specify a more complicated execution structure, as shown in Figure 6. The textual representation of the graph is given below: AND ( R4, R5, R6, 0R[2] (R1,R2,R3) ) > R7

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58 R1 R2 \ 0FI[2] R3 R4 R7 Figure 6. Example rule execution structure with nested AND and OR operators The same rule may appear more than once in a single RULESTRUC. In that case, a rule alias mechanism is needed to differentiate between these different occurrences of the same rule. Rule Rl may be executed at the beginning of the RULESTRUC and also at the end of the RULESTRUC. In this case, a simple naming method is to use Rl and Rl~l to differentiate them in a RULESTRUC. Additional occurrences of Rl can be denoted such as Rl~2, Rl~3, Rl~4. One thing that needs to be considered in the execution of a RULESTRUC is when a rule is disabled or deleted from the rule system. When a rule is disabled at run-time, the execution of the rule is skipped within the RULESTRUC. The successor of the disabled rule will inherit all of the relationships that the disabled rule has with its predecessors. As an example, if rule R5 is disabled in Figure 5, the rule server will bypass the processing of R5 when R3 is completed. As soon as R6 is completed, it will then process rule R9 without considering R5. If a rule is deleted, then every occurrence of the rule in all the RULESTRUCs will be bypassed.

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59 Since event parameters can be passed to rules, the mapping of event parameters to the individual rules within a RULESTRUC need to be specified. The following example shows how the mapping is done: TRIGGER sample_trigger2 ( int v 1 , int v2, classX v3 ) TRIGGEREVENT El(vl,v2,v3) OR E2(v3,v2,vl) EVENTHISTORY [03/10/1998::::] E5 >[2min] ( E3 AND E6 ) [-10 hours] RULESTRUC Rl(vl,v2) > R2(v3,vl) > R3(vl,v2,v3) RETURNS int : Rl In the example, Rl uses event parameters vl and v2, R2 uses v3 and vl, and R3 uses vl, v2 and, v3. The original values of event parameters that are passed to the trigger are passed to the individual rules. Of course, the mapped parameters of the rules must be type compatible with the event parameters. A trigger can return a value after executing the RULESTRUC. This returned value is also the value returned to the event that was posted synchronously to cause the processing of the trigger. The value can be a return value from one of the rules participating in the RULESTRUC. If the rule that generates the return value is disabled, the default return value is null. The above trigger returns an integer value that is generated by Rl. 4.4. Rule Group Specification In a complex application environment, many rules may be required to capture various constraints, business rules, policies and regulations. However, not all the rules are useful for a particular situation. It would be ideal to provide a mechanism to activate or deactivate some subsets of rules dynamically. For this purpose, the concept of rule groups is introduced in our rule specification language. Rules can be grouped to allow

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60 for easy activation or deactivation of a set of niles. A rule can participate in one or multiple groups or may not belong to any group in this case, it belongs to the default group. When an application activates a rule group, all the rules in that group become active (i.e., can be triggered by some events if they participate in the rule structures of some triggers). However, within an activated group of rules, individual rules could have been deactivated. When an event and rule server is in the process of processing the rules specified in a rule structure in response to the posting of an event, it will check if each rule in the rule structure should be processed or not. The algorithm for deciding the execution status of a rule is as follows: (1) If the rule is active (i.e., the rule has not been explicitly deactivated), then go to (2). Otherwise, the processing of the rule is bypassed. (2) If there exists a group that the rule is a member of and the group is active, then the rule is processed. Otherwise (i.e., all the groups that the rule is a member of have been deactivated), the rule is bypassed. Note that if the rule is only a member of the default group, it is processed because the default group is always active. An example for defining a rule group is : RULEGROUP rule_groupl MEMBER R1,R2,R3 STATUS ACTIVE The STATUS clause specifies if the group is initially active or suspended at the definition time.

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CHAPTER 5 KNOWLEDGE WEB SERVER ARCHITECTURE The infrastructure to support the knowledge network concept is composed of a large number of knowledge Web servers on the Internet. Each knowledge Web server has the capability to interact with users and other knowledge Web servers. The knowledge Web server includes additional modules to extend the capability of the current Web servers. We will discuss the architecture and the detailed components of the knowledge Web server in the following sections. 5.1. Architecture of the Knowledge Web Server The general architecture of the knowledge Web server is shown in Figure 7. Internet Knowledge Profile Owner Knowledge Web Server Figure 7. Overview of architectural components in the knowledge Web server. 61

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62 Each knowledge Web server has an Event Manager, an ETR Server, and a Knowledge Profile Manager, which are additional components installed on a typical Web server. Because these components are installed on each Web server, the whole infrastructure based on the Internet will have a symmetric architecture. 5.1.1. Event Manager The Event Manager handles the incoming and outgoing events to and from the Web server. When a new event is defined through the Knowledge Profile Manager (to be explained in subsection 5.1.3.), the meta-data for the event is given to the Event Manager in order to enable it to recognize and handle the event. The Event Manager provides an interface to allow the local applications to connect to itself and generate an event. Also, the Event Managers can communicate with each other for the purpose of sending and receiving events. The Event Manager is also responsible for performing event filtering before it sends out events to the subscribers in order to support a selective subscription of events. It also includes the event registration capability for remote clients to register their interest in subscribing to certain events provided by the knowledge Web server. During the registration, the Event Manager may contact the ETR Server to install parameterized rules. Also, when the Event Manager receives an event from a remote web server, it passes it to the local ETR Server to initiate the processing of triggers and rules. 5.1.2. ETR Server The ETR Server processes the triggers and rules in the knowledge Web server. Triggers and rules are defined by users who are authorized to login to the local Knowledge Profile Manager as a knowledge provider or subscriber. The trigger and rule definitions that are input through the Knowledge Profile Manager are provided to the ETR Server and are transformed into internal data structures used for executing the

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63 triggers and rules. The Event Manager also gives information about parameters for parameterized rules provided by subscribers of events during the event registration process. Note that a limitation on the capability of rule installation by remote users is needed for security reasons. The ETR Server receives events from the local Event Manager and performs the trigger and rule processing. On receiving an event, the ETR Server can immediately identify the trigger related to the event, efficiently process the event history, and schedule the rules specified in the trigger. The ETR Server executes rules that are composed of method calls, which may execute local or remote applications, or invoke methods of distributed objects. The rule can also generate an event to trigger other rules. 5.1.3. Knowledge Profile Manager Each user that has data and applications on the web server has a knowledge profile that is maintained by the Knowledge Profile Manager. The knowledge profile stores information about events, triggers, and rules. The knowledge profile for a specific data (or service) provider contains the events, triggers and rules that were defined by the data (or service) provider. Also, users can think of the knowledge Web server as his/her agent server. A knowledge profile for the user will show what events the user has subscribed to, and also the trigger and rules that were defined on the subscribed event. A Meta-data Manager module within the Knowledge Profile Manager provides persistence for storing the user knowledge profiles. The knowledge profile is updated when new events, triggers, and rules are defined. When a new event is defined, its definition is passed on to both the ETR Server and the Event Manager to enable the components to recognize the event and perform

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64 installation operations. For trigger and rule definitions, they only need to be passed to the ETR Server. A special user of the system may be regarded as the super-user of the knowledge Web server. For the purpose of maintaining system level information about the knowledge Web server, a super-user knowledge profile may exist to deal with the management of system-level events, triggers and rules. Some of this system-level knowledge may also be published on a specific web page. The super-user also manages the user accounts on the knowledge Web servers. Data Provider (owns profile on server A) Client (owns proHle on server B) Provider's Data & Applications Install trigger. rule Install trigger. rule Data & Applications Knowledge Web Server A Knowledge Web Server B Figure 8. Component interactions between two knowledge Web servers.

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65 5.2. Component Interaction Sequences The architectural components described above are replicated within each Web server on the Internet, which makes the infrastructure symmetric. But during the interaction between the knowledge Web servers, although the components are identical, they can have different functional responsibilities based on their roles in the interaction. Figure 8 shows two interacting knowledge Web servers: the left one as the provider of events and data, and the right one as a client to events and data. The activities that occur between two interacting knowledge Web servers are divided into two phases: knowledge network construction (or build-time) activities and knowledge network processing (or run-time) activities. The construction activities are denoted by solid arrows and the processing activities are denoted by dotted arrows. Circled numbers indicate the sequence of the activities that occur. The knowledge network construction activities include: ® The data provider installs events, triggers, and provider-side rules. The provider-side rules can be executed on the provider's server if desired by an event subscriber. ® The event and event filter template installation is carried out by the Event Manager. Event filter templates enable subscribers to specify event filter instances during the registration process performed by step ®. ® Provider-side parameterized rules are given to the ETR Server. The event and trigger information is also provided to the ETR Server. ® A client accesses the web page of the data provider and registers for the subscription of an event and specifies an event filter. Provider-side rules are

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66 also selected. After the registration has been successfully performed, the event subscription information is forwarded to the subscriber's site. (D The client accesses his own knowledge profile and installs additional triggers and rules related to the subscribed event to be processed at the client site. The knowledge network processing activities include: ® The data provider generates an event to be posted to the subscribers, which is first filtered by the Event Manager. ® If a subscriber of the event had tied the event to a provider-side rule during the registration, the relevant rule is now executed on the provider's knowledge Web server. ® The event is posted over the Internet to the subscribers of the event and the Event Manager on the subscriber site receives it. ® The event received is forwarded to the Knowledge Profile Manager and can be kept in the subscriber's profile for the purpose of logging the events to be viewed later on. ® The event received is given to the ETR Server to execute any relevant subscriber-specified triggers and rules.

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CHAPTER 6 KNOWLEDGE NETWORK CONSTRUCTION, PROCESSING, AND MANAGEMENT The knowledge network concept can be realized with the architecture composed of knowledge Web servers described in the previous section. The issues and details of our approach regarding the construction of the knowledge network, the processing that occurs within the framework, and the management of the knowledge network are discussed in this section. 6.1. Constructing the Knowledge Network Constructing the knowledge network includes several stages that add some type of knowledge into the framework. The stages are identified as: (1) defining and publishing new events, triggers, and rules in the knowledge network by the provider, (2) performing event registration by the subscriber, and (3) defining triggers and rules by the subscriber. The issues regarding this stage are very important, as this stage is the starting point for incorporating the knowledge into the Internet. 6.1.1. Defining and Publishing Events and Rules A knowledge provider can define new events that he/she would like to post over the Internet. The detailed description about these events will also be provided on the provider's web page. By publishing these events on a web page, users on the Internet can browse the event descripfion and subscribe to the event by registering themselves as subscribers to the event. Provider-side rules are intended to allow subscribers of events to automatically execute rules on the provider's knowledge Web server when the 67

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68 subscribed event occurs. Rules can be defined by the provider and displayed within event registration forms. During the registration process, after the subscriber enters all information needed for subscribing to an event in the event registration form, he/she can also select a subset of the rules given by the provider. In order to support the definition and publishing of events and provider-side rules, the following issues need to be considered. First, there should exist authorization levels for publishing knowledge in the knowledge Web server. Some users should have the authority to publish on the knowledge Web server while others should not. Second, defining events, filters, and provider-side rules should be easy for even novice users, hi other words, low-level program coding should be avoided. Third, mechanisms to prevent name conflicts and type mismatches for event names and event parameters must be devised within the Internet community. Fourth, registration form generation should be handled automatically by the underlying system instead of the user needing to create separate HTML pages and scripts for it. Fifth, the underlying system needs to be able to effectively support provider-side parameterized rules without creating a huge number of almost identical rules customized for each subscriber. Considering these issues, our approach to support the definition and publishing of events and provider-side rules is described below in the order that the publishing is performed. (1) Log into the knowledge profile in provider mode When logging into the knowledge profile, the authorization level is checked to determine if the user can work in the subscriber mode and/or the provider mode. The authorization levels are set by the administrator of the knowledge Web server. Provider levels are given to users that provide data and knowledge on the knowledge Web server.

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69 Once logged in as a provider, the user can now define events, event filter templates (i.e., templates describing a filter defined by a provider), provider-side rules, and event registration forms. (2) Define events In order to define an event, the event name, event parameters, and generating mechanism need to be specified. These can be done using the implemented Knowledge Profile Manager GUI, which is easy to use for even novice users. The definitions will be stored in persistent store and also be used for installing run-time components such as generating event Java classes within the system. The event name may be considered as any unique string that could identify it on the knowledge Web server. Different providers on the same system may want to use the same event name. This would create a conflict in the event name space of the knowledge Web server. One way to make each provider transparent from each other on the same knowledge Web server is to append the provider name to the event name as a prefix. Another issue that may arise in the Internet conmiunity is related to guidelines in defining the event name to prevent conflicts over the whole Internet. Because different knowledge Web servers may possibly use the same event name, the event name space would be hard to manage and result in chaos. Thus, a prefix can be used such as the web server address to make the event names unique over the whole Internet. Therefore, a prefix combining the web server address and the provider id would be appended to the desired event name to create the final Internet-unique event name. Another approach would be to establish an ontology on the event names to be universally used over the Internet. This requires the

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70 cooperation among the whole Internet community, which would be difficult to achieve but provides the most benefits to the Internet community. The event parameters can have any names. There are no particular restrictions on the event parameter names. The parameter types need to be considered more carefully. Primitive data types can be used for the parameter types. The primitive data types are considered as those built in by the Java language. User-defined classes can also be used for event parameter types. If user-defined classes are used, they must also be passed over to other knowledge Web servers in order to properly receive and interpret the events containing these classes. Again, conflicts may occur among the class names between different knowledge Web servers. There are a couple of approaches for this issue. First, only events containing well-defined classes may be passed, as these classes may be defined in a commonly accepted ontology and can have an identical class used over the whole Internet. This makes things cleaner and results in less redundant class definitions. But complex types that are not defined in the ontology cannot be used as event parameters, or the complex type must be somehow disassembled into several parameters of the event if needed to be passed. Second, all classes defined on each knowledge Web server should include a prefix of the server address and the provider id, similar to event names discussed above. This will make class names unique over the Internet and make it easier to pass them to other web servers without creating any conflict among existing events. However, this approach can create many redundancies and complicated class names. For our purpose of showing the concept of Internet event and rule services, we assume that the first approach is taken due to its simplicity.

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71 The event generating mechanism can be specified in several ways. The events can be generated by several different components attached to the Web server or within the Web server. Some examples are: (1) the Web server can generate an event when a specific Web page is being accessed. (2) An active DBMS attached to the Web server can be used to dynamically create Web pages on the fly. This DBMS can generate events when a method is executed on its data. These methods can be update operations on the Web page data, making it possible to generate events for Web page updates. (3) A CORBA server may be attached to the Web server and can relay events that are generated within the ORB. The ETR Server may also be a CORBA server that can interact with other CORBA servers on the ORB. Events that are coupled with methods of CORBA servers can be defined and installed into the ORB or CORBA servers. (4) A daemon program may be monitoring some data (i.e., a file) that is not stored in a database, and also can generate events when the data is changed. This type of daemon program may be provided for Web pages stored as files. (5) Any general program may generate an event and provide it to the Event Manager on the provider's knowledge Web server. For this case, the event generation mechanism need not perform any task, as the event generation is solely the responsibility of external programs. For all the other event generation mechanisms (1) to (4) specified above, there are specific tasks to be carried out, which are related to the event generating modules, such as making a request to the web server, coupling events to methods within the active DBMS, coupling events to methods within the CORBA servers, and informing the daemon to monitor data. Once the event is defined, the Event Manager will install all of the relevant code for processing the newly defined event. Each of these event specifications will

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72 additionally be stored into persistent storage and used by the Knowledge Profile Manager for defining event filter templates in the next step. (3) Define the event filter template When publishing an event, a subscriber may not be interested in subscribing to all of the event instances that will be posted by the provider. For example, assume that there is an Airfare Special Offer event being posted, but the subscriber is actually only interested in airfares for flights that depart from Orlando, FL. This is a subset of the Airfare Special Offer event. If the provider allows the subscriber to give some values to indicate which subset of events he/she is interested in, a filter which screens out all irrelevant events for that particular subscriber can be established. In order to support this, the provider must give to the subscriber a parameterized filter. In other words, a filter with some undefined values is created and given by the provider. For the Airfare Special Offer event, a parameterized filter on the departure place attribute of the event can be created. This will let the subscriber to input (or choose from a list) the actual value of the departure place. This kind of parameterized filter on the event can be displayed on the event registration Web page by printing out the departure place attribute with a blank box beside it. The subscriber can input the value Orlando into the blank box. The parameterized filter created by the provider is also called an event filter template, which maps directly to an actual input form. The provider creates an event filter template as follows. First, picking the event on which he/she desires to provide an event filter template. Second, one or more attributes of the event are selected. Third, for each of the attributes, an operator is specified by the provider, such as an equal, range, greater (or less) than, single value

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73 selection, multiple value selection. The operator decides how the event filter template will be displayed to the subscriber. The equal operator means that the subscriber should specify the exact value of the event attribute, which is of interest to the subscriber. This will be displayed as a single blank box to the subscriber requesting input. The range operator means that the subscriber should specify the minimum and maximum values for the event attribute which are of interest to the subscriber. Two blank boxes indicating the maximum and minimum value will be displayed to the subscriber for the range operator. The greater (or less) than operator requires the subscriber to provide a lower bound (or upper bound) of the event attribute. This results in a single blank box being displayed to the subscriber requesting a lower bound or upper bound value to be input. The single selection operator allows the subscriber to select one of the values that the provider has pre-defined. Thus, the subscriber can select only one value among the multiple candidates. This results in a drop-down box, which includes all of the candidate values. The multiple selection operator is similar to the single selection operator except that it allows the subscriber to select multiple values rather than just a single value, meaning that the subscriber can receive events that have attribute values falling into any of the multiple selected values. The multiple selection operator is displayed as multiple radio buttons that can be individually selected and unselected. The event filter template specification results in an XML file, which is used by the Knowledge Profile Manager to define the event registration form, and by the Event Manager during event registration to interpret the file and display the parameterized filters defined by the provider. Figure 9 shows an example of an event filter template for the CheapAirplaneTicket event, defined in XML (shown on the left side of the figure), as

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74 well as the corresponding HTML form automatically generated during registration time from the XML file (shown on the right). For the attribute Departing, a single selection operator filter is specified, with a predefined list of values: New York, Los Angeles, Atlanta, San Francisco, and Seattle. The user can select a single value from the combobox of the corresponding HTML form. Also, Figure 9 shows an example of the multipleselection-operator filter on the attribute Destination. The user can check several choices from the predefined list of cities. XML file HTML form Filters for CheapAirplaneTicket CheapAirplaneTicket 1 Departing String New York, Los Angeles, Atlanta, San Francisco, Seattle 2 Destination String Orlando, Miami, Tampa 3 < AtrrNamo Price String Range 1 AND 2 AND 3 4 Registration Form for CheapAirplaneTicket Departing: 1 New York Destination: Orlando EZ] Miami Tampa Price: 1 l< Price < 1 1 Register | Figure 9. Example of automatically generating event filter registration form. (4) Define the provider-side rules In addition to events, provider-side rules can be defined and the specification of the rules can be published on the event registration form. Therefore, when a user

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75 subscribes to an event, he can also select rules to be automatically executed on the provider's knowledge Web server at the time the event is posted. The definition of rules can be easily done through the Knowledge Profile Manager GUI. Provider-side rules, the same as subscriber-side rules, have the format of the rules defined in our rule model having a rule name, rule parameters, rule variables, condition clause, action clause, alternate action clause, and return type. The classes and methods used in the rule body must be accessible by the ETR Server by storing those classes under a designated directory of the ETR Server. Therefore, not only standard classes provided in Java but also user-defined classes can be used within the rules. The provider also needs to define triggers, each of which links the published event with a single published rule. Although the subscriber may see only the rule, the trigger that links the event to the rule is what is actually used in the underlying system during registration. If a provider-side rule is selected by the subscriber during the event registration, the subscriber's id is attached to the relevant trigger. These provider-side rules are not only installed in the ETR Server but also kept in an XML file, which is used by the Knowledge Profile Manager for managing the rules and the Event Manager to display the rules within the event registration form. (5) Define skeleton of event registration form Each web page can contain a link to an event registration form, which publishes the event information that can be subscribed to by remote users. The event registration form also contains a form to input event subscription information (i.e., user id, password, notification method as either e-mail or event push, subscribing Internet address, e-mail address), and filter specifications, along with a set of rules that can be automafically

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I 76 executed on the provider side when the event occurs. Each event registration form only deals with a single event. The event registration form is dynamically generated by the knowledge Web server by parsing a document called the skeleton of the event registration form. The skeleton of the event registration form is defined by, first, picking the event and event filter template to be displayed; second, provider-side rules to be displayed are also selected and stored into an XML file. All other things are automatically taken care of by the underlying system. Thus, two files in XML will be used; one to display the event part and the other for the rule part. These two files are given to the Registration Servlet within the Event Manager, which dynamically creates the event registration form. These two files are interpreted at run-time and transformed into two HTML pages and then merged to create a Web page displaying the contents of the event registration form. 6.1.2. Event Registration As described in the previous section, providers can publish events on their Web pages. A user on the Internet can then view a Web page and subscribe to the event by accessing the event registration form and providing the filtering information that determines the receipt of future notifications of the event. Also, provider-side rules may be selected. The following issues are relevant to the process of event registration. First, the information needed to allow the subscriber to receive an event should be decided. It should be more than just an e-mail address when using event notifications. Second, security issues about personal information exposure should be considered carefully. Third, the display format of the provider-side rules should be easily understandable to a subscriber. Fourth, the subscribed information should not only be kept in the provider

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77 site but also forwarded to the subscriber site to allow the subscriber site to be prepared for event notifications. Our approach to performing the event registration is described below: (1) Access the event registration form While surfing on the web, the user comes to a Web page with an interesting event published. He/she can click on the link that leads him/her to the event registration form. Each event has its own event registration form. This form is dynamically created by the Event Manager of the knowledge Web server. (2) Install an event filter The subscriber will insert values that are required for installing an event filter. Some of the values may be input as text, selected from a list, or selected by checkboxes. These values will be used to filter out irrelevant events for the subscriber. (3) Input the subscriber information The subscriber must input information relevant to receiving the event. A user id must be provided that can be identified on the subscriber's system, and a password is provided for security reasons. This user id and password may also be used on the provider's system for later identifying the subscriber that registered and for pulling up his registration information so that it could be modified by the subscriber. The event can be delivered as an e-mail or an event object notification. The method of event delivery is selected by the subscriber. If the e-mail method is selected, a valid e-mail address must be provided. Otherwise, the URL of the Event Manager on the subscriber's site must be specified.

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78 Another interesting feature that may be added is to allow the subscriber to specify a period in which he wishes to subscribe to the event. The events may be immediately subscribed to or may be delayed until a specific time. (4) Select provider-side rules In addition to being notified of the occurrence of an event, provider-side rules can be executed when the relevant event is posted. The rules that are eligible to be executed when the event occurs are displayed together on the event registration form. Multiple rules can be selected. But, how can the semantics of provider side rules be easily understood by a subscriber and installed easily by the subscriber? Basically, the complexity of the rules should not be revealed to the subscribers, but what the rule is capable of should be clearly exposed. This could be in the form of a good natural language description of the rule for novice users or the actual rule specification for advanced users. The installation process should mostly be a simple selection operation, if the input of any rule parameter values is not required. If the rule requires a value to be input, a simple combo box or text box is displayed for each customizable parameter of the parameterized rule. These values are stored in a table within the ETR Server. The selected rules will form a parallel trigger on the provider's site and be entered into the ETR Server. (5) Forward the event registration information Following the whole process of event registration, the subscribed event information must be forwarded to the Event Manager on the subscriber side. The information should include the event specification, the URL of the event registration form, the user id and password used for event registration.

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79 6.1.3. Subscriber-side Trigger and Rule Definition After registering for subscription of several events, the subscriber can now log into his knowledge profile as a subscriber and define triggers and rules related to the subscribed events. These triggers and rules will be installed in the ETR Server on the subscriber's site. The steps that are generally taken are: (1) Log into knowledge profile as subscriber. (2) Define subscriber-side rules. (3) Define subscriber-side triggers. (1) Log into knowledge profile as subscriber Once the subscriber has logged into his profile as a subscriber, several tasks can be carried out. The events that the subscriber had registered for will show up on the knowledge profile. The event names and parameters, along with the event registration URL, the user id and password that were used during event registration are all displayed. The event instances that were received so far by the subscriber's knowledge Web server may also be viewed. An event alias may also be displayed for each event in order to differentiate among events of the same type that were registered for multiple times, each with different event filters installed. (2) Define subscriber-side rules The subscriber-side rules can be defined in the same way as provider-side rules are defined. The rule will show up in the relevant user's knowledge profile when logged in as a subscriber. The rules are then generated into code and installed into the ETR Server. (3) Define subscriber-side triggers The subscriber-side triggers are defined using the subscribed events and the subscriber-side rules. A trigger can relate a set of these events with a set of the rules. The triggering events, event history, and rule structure are specified within the trigger. The

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80 rule structure can be a sequential structure, a parallel structure, or an AND-OR synchronized structure. The parameter mapping from events to rules is also specified in the trigger. After the trigger is defined, it is given to the ETR Server. 6.2. Processing Events, Triggers and Rules Once the construction phase of the knowledge network is finished and the knowledge elements are populated into the framework, the run-time processing of events, triggers, and rules take place. The event is generated at the provider's knowledge Web server. This event is posted to the subscribers. It also executes provider-side rules. Upon receiving the event, the subscriber-side rules are executed. 6.2. 1 Posting Events The events are generated on the provider's knowledge Web server in several ways : (1) Web server generated, (2) Active DBMS generated, (3) CORBA server generated, (4) Daemon program generated, or (5) External application generated. Regardless of how an event is generated, the Event Manager on the provider side will receive an event instance. The provider's Event Manager will then use a special data structure to efficiently look up the subscribers who installed filters that are relevant to the generated event instance. The data structures used here are the widely used Inverted Index for discrete value filtering and the Range Index Table, which is used to efficiently match a value against multiple range conditions. The event is then posted from the provider to each of the subscribers. If the subscriber specified the delivery mechanism as e-mail, it is posted by e-mail. Otherwise, it is delivered by an event notification from the provider's Event Manager to the subscriber's Event Manager.

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81 If the subscriber selected a provider-side rule, the event is also posted to the provider site itself. This event notification fires the rules that were selected by the subscriber on the provider's site. 6.2.2. Trigger and Rule Processing bv the subscriber When the Event Manager on the subscriber's knowledge Web server receives the event notification, it will automatically forward it to the ETR Server on the subscriber's web server. The ETR Server will then check who the subscriber of the event is, and execute the triggers and rules defined by the subscriber. The trigger execution involves evaluating the event history, mapping the parameters from the events to the individual rules specified in the trigger, and scheduling of the rules according to the structure specified. The execution of a rule may in turn generate another event, which will create a chain reaction among web servers. The rule also may activate local applications, based on how it is defined. 6.3. Event, Trigger and Rule Management Events, triggers, and rules that have been defined may not permanently exist nor remain valid. Thus, they need to be managed after they are defined. The techniques introduced in this chapter are extensions to our framework to support the management of events, triggers and rules. 6.3. 1 . Expiring and Deleting Events An event log can be kept on the subscriber's knowledge Web server to enable the subscriber to view the instances of the subscribed events. The problem of having an event log is that it will continue to grow and eventually take up a large amount of storage space.

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82 In order to alleviate this problem, an expiration mechanism of events may be used. Each of the events may contain an expiration date, which specifies the date from which the event becomes meaningless. The expiration date can be used to automatically purge events from the event log. A daemon can periodically go through the event log and perform the purging based on the expiration date. Another problem with subscribing to events is the fact that the provider may delete the event from his knowledge Web server and no longer post the events. In this case, the subscriber does not know that the event will no longer be posted and will keep the triggers related to the subscribed event. A mechanism to inform the subscriber of the deletion of the event on the provider site should be devised. One approach is to make use of the same infrastructure to support this capability. A special event, namely, management event, which is pre-defined by the system, is the only additional thing needed. This event can carry the event name that has been deleted from the provider's site. When a provider deletes an event from his system, this special type of event will be posted to all of the subscribers of the deleted event. Then each of the subscribers can perform some operations to clean up the unnecessary data structures related to the deleted event, such as the event table and trigger tables. Triggers and rules, namely management triggers and management rules, can be tied to these events to perform such operations. Additional operations can be carried out by specifying them in the management rules. 6.3.2. Editing Triggers and Rules Triggers and rules defined by a subscriber may need to be changed afterwards. The editing of triggers involves taking out or adding new rules into the structure, or modifying the execution sequence of the rules. This can be done through the Knowledge Profile Manager. The ETR Server is informed about the changes and modifies its internal

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83 data structures. The editing of rules involves not only changing the knowledge profile but also the generation of the new rule code. The new rule code must also be dynamically loaded into the ETR Server. The ETR Server is capable of reloading the new rules without being brought down and also the currently running rule instances are not affected by the change. In other words, dynamic reloading of rule code is carried out.

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CHAPTER 7 IMPLEMENTATION DETAILS In Chapter 5, an overview of the architecture of the knowledge Web server was given. This chapter elaborates in more details on how each of the components is implemented and how these components interact. 7.1. Detailed Architecture The detailed architecture of the knowledge Web server is shown in Figure 10. There are three key components as described in the previous sections: Event Manager, Knowledge Profile Manager, and ETR Server. Event Infrastructure APIs EventMgr EventListener & Authentication Filter Processor Event Distributor Install Event Posting Event Classes Subscribei Event Registration (Servlet) i Registration Form Knowledge Profile Manager (Servlet) Rule Codes MetaMgr for Event, Trigger, Rule Install Event Generation Web access Monitor DBMS CORBA: Figure 10. Detailed architecture of the components of the knowledge Web server. 84

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85 7. 1 1 Event Manager The Event Manager [Gru99] deals with accepting event registrations and delivering the events to subscribers of the event. It is composed of an Event Registration Servlet, which can generate an HTML form for the registration of events and providerside rules and also stores the subscription information into a persistent storage. The internal format of the registration form is in XML format. The Event Registration Servlet will read the XML files and create an HTML form, which displays the event, event filter input, and provider-side rule selection. The Event Manager also includes a Filter Processor, which allows certain undesired events to be screened out before being sent to a subscriber. The Filter Processor uses a special data structure to perform event filtering based on specific event parameter values provided by the subscribers. The Event Distributor activates the Filter Processor and carries out the process of delivering the events to subscribers. The Event Listener will accept events from other systems and forward the events to the ETR Server. Java classes that are needed for sending/receiving the events are maintained in a persistent store. 7. 1 .2. Knowledge Profile Manager The Knowledge Profile Manager [Par99] consists of an applet and a servlet, which allow both the provider and subscriber events, triggers, and rules to be displayed/defined through a browser interface. The Knowledge Profile Manager stores the event, trigger, and rule information into a Metadata Manager, which manages the persistent storage of this information. The Knowledge Profile Manager also creates XML files used for the event registration forms. These XML files are stored in a special directory that is also accessible by the Event Registration Servlet of the Event Manager.

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86 When the provider defines an event, the related event generation mechanism can be identified and the code for generating the event can be automatically installed. Examples are method associated events for CORBA infrastructures, events generated from active databases, events generated from web servers. The event delivery mechanism is isolated from the definition mechanism. Therefore, the Knowledge Profile Manager will notify the event installer within the Event Manager about the event class, so that the related code for delivering the events can be generated. 7.1.3.ETR Server The ETR Server executes triggers and rules at run-time. It can schedule complex rule structures based on a sequential, parallel, or AND-OR synchronized structure specified in a trigger. A block diagram of the ETR Server is shown in Figure 1 1 . The ETR Server has an Event Hash Table, Trigger Hash Table, Dispatcher, Rule Group Manager, Rule Code Loader, dynamically created Rule Schedulers and Event History Processor. The Event Hash Table stores information about which events map to which trigger, and the Trigger Hash Table stores information about the parameter mapping and rule execution sequence for each trigger. The Rule Group Manager maintains the information about which rule is currently activated, and the Rule Code Loader can load the rule code dynamically and execute them at run-time. When an event is notified to the ETR Server, the dispatcher looks up the Event Hash Table and finds the triggers that are related to the event. A Rule Scheduler is dispatched to start processing a trigger. The Rule Scheduler, which is created at run-time for each invoked trigger, performs the scheduling and parameter mapping tasks while interacting with the Rule Group Manager, and whenever a rule code is changed and need to be reloaded or executed it calls the Rule Code Loader.

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87 The ETR Server has the capability of grouping rules that can be more easily enable or disabled. The grouping of rules is managed by the Rule Group Manager. Dynamic rule change is also possible at run-time without bringing down the server. A rule can be changed and immediately installed without affecting the previously running rules. Additional code for the Java class loader was written to support this capability, resulting in our own Rule Code Loader. The rule code is stored in a persistent store as Java classes. The internal data structures of the ETR Server are also stored in a persistent store. The ETR Server can also process complex relationships among the event occurrences using the Event History Processor. The Event History Processor can accumulate event occurrences and evaluate an event history expression to check if a certain relationship among events exists within the past history. This evaluation is invoked during the trigger processing before the rule structure is executed. Notify Event ETR Server Dispatcher X Rule Scheduler RuleG roup M anager Event Hash Table Trigger Hash Table Event History Processor RuleCodeLoader Rule Codes Figure 11. Architectural components of the ETR Server.

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88 1.2. Detail Component Interaction and Interface This section explains how the components interact with each other through their interfaces during the various stages of event, trigger, rule publishing and processing. 7.2.1. Component Interactions for Publishing Events, Triggers, and Rules Figure 12 shows the interactions among the components that are carried out when a provider publishes events, triggers and rules. When the provider wants to publish events, triggers and rules, he first accesses the Knowledge Profile Manager. Through the Knowledge Profile Manager, a provider can define events, triggers and rules, which are then transformed into an XML file format. The XML file format is later used to dynamically create and display an event registration form. The event, trigger, and rule information are all stored into the Metadata Manager. The event definitions are given to the Event Manager so that the appropriate code needed for event delivery (e.g., event classes in Java) can be generated. The ETR Server also installs the triggers and rules into its system and is ready to fire the provider-side rules. Event Infrastructure APIs Knowledge Profile Manager (Servlet) ETR Server ' Rule Codes Install Trigger, Rule *M etaM gr for Event, Trigger, Rule Profile per U ser Install Event Generation |Web access 1 MonitorjDBMS|cORBA Figure 12. Interaction among components for publishing events, triggers, and rules.

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89 1.22. Component Interactions for Event Registration on Provider Site The interactions among the components on a provider site when a subscriber registers for an event are shown in Figure 13. The subscriber will access the event registration form via the Event Registration Servlet, which reads the event, trigger, and rule information that is in XML format. The subscriber will input the event filter information and subscriber information and also select certain provider-side rules. The event filter information along with the subscriber information are given to the Event Manager to be stored into persistent store and also update the data structures used for efficient filter processing. The information about the event such as the event class that is needed for event delivery is passed to the remote subscriber site by the Event Manager. The provider-side rules that were selected by the subscriber are installed within the ETR Server along with the subscriber id. Event Infrastructure APIs Provider Site Expor EventMgr EventListener & Authentication Filter Processor Event Distributor Install Event Posting export event HTTP Event Registratio (Servlet) ent subscription info Registration Form Registration Form per Event Event, Rule XML Knowledge Profile Manager (Servlet) ETR Server Rule Codes Install Trigger.Rule MetaMgr for Event, Trigger, Rule Install Event Generation Web access Monitor DBMS CORBA Figure 13. Interaction among components for event registration on provider site.

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90 123. Component Interactions during Event Registration on Subscriber Site The interactions among the components on a subscriber site while a subscriber registers for an event are shown in Figure 14. The Event Manager on the provider site of the event will pass to the subscriber site the event information needed for receiving the event. The subscriber's id is also passed along at this time. The Event Manager on the subscriber site will store the event information and perform additional code generation if needed for receiving the event. The subscriber's id and the event that was subscribed to will be added to the persistent store, which contains all the event subscription information. The subscriber can later on define triggers and rules on those subscribed events. Event Infrastnicftire APIs Subscriber Site EventMgr EventListener & Authentication Filter Processor Event Distributor Install Event Posting Import event Event Classes Event XML Subscribei Event subscription info Event Registration (Servlet) Registration Form Knowledge Profile Manager (Servlet) Rule Codes MetaMgr for Event, Trigger, Rule Install Event Generation Web access Monitor DBMS CORBA Figure 14. Interaction among components for event registration on subscriber site.

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91 7.2.4. Component Interactions during Subscriber-Side Trigger and Rule Definition The interactions among the components on a subscriber site while a subscriber defines triggers and rules on a subscribed event are shown in Figure 15. The subscriber first accesses its Knowledge Profile Manager. The Knowledge Profile Manager displays the events for which he/she has subscribed. The subscriber can then define triggers and rules related to these subscribed events. Once these are defined, they are stored into the Metadata Manager and also installed in the ETR Server on the subscriber site. Event Infrastructure APIs Subscriber Site HTTP EventMgr EventListener & Authentication Filter Processor Event Distributor Install Event Posting Event Classes Subscribei Event subscriptic n info Event Registration (Servlet) Knowledge Profile Manager (Servlet) Profile per User Install Trigger.Rule MetaMgr for Event, Trigger, Rule Install Event Generation Web access Monitor DBMS CORBA Figure 15. Interaction among components for defining trigger and rule on subscriber site.

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92 1.2.5. Component Interactions for Posting an Event on the Provider Site The interactions among the components on a provider site while posting an event are shown in Figure 16. The event is generated by any mechanism that is supported by the system. In the figure, the CORBA event service is shown. Once the event is generated, it is passed to the Event Manager. The Event Manager will then perform the filtering and post the event to the subscribers of the event. During this process, the Event Manager uses the subscription information and the event classes. The event is also given to the ETR Server that resides in the provider site in order to fire provider-side rules that were selected by the subscribers. Event Infrastructure APIs Provider Site se id EventMgr EventListener & Authentication Filter Processor Event Distributor Install Event Posting Event Classes Subscribei Event Registration (Servlet) Registration Form 3 Knowledge Profile Manager (Servlet) Execute Rule ETR Server Rule Codes Install Event Generation MetaMgr for Event, Trigger, Rule Generate event Web access Monitor DBMS CORBA Figure 16. Interaction among components for posting event on provider site.

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93 1.2.6. Component Interactions for Receiving an Event on the Subscriber Site The interactions among the components on a subscriber site when receiving an event are shown in Figure 17. The event is delivered to the Event Manager on the subscriber site. The Event Manager may then log the event into a persistent store. It will then pass the event to the ETR Server. The ETR Server looks up triggers and rules that are defined by the subscriber and executes the rules. Event Infrastructure APIs Subscriber Site Install Event Posting Event Registration (Servlet) Registration Form Knowledge Profile Manager (Servlet) MetaMgr for Event, Trigger, Rule Install Event Generation Web access Monitor DBMS CORBA Figure 17. Interaction among components for receiving event on subscriber site.

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94 12.1. Component Interactions within the Knowledge Web Server Figure 18 shows all of the interactions that take place within the knowledge Web server. As described in detail in the previous sections, the interactions take place at different stages of the whole process. Event Infrastructure APIs Provider I Subscriber Site se id Install in Infrastrupture < — Expor to T( ceiver EventMgr EventListener & Authentication Filter Processor Event Distributor Install Event Posting export event HTTP Import event Execute Rule Event Registratioi (Servlet) Registration Form per Event HTTP Knowledge Profile Manager (Servlet) Profile per User ETR Server Rule Codes Install Trigger.Rule Install Event Generation Web access Monitor DBMS MetaMgr for Event, Trigger, Rule Generate event CORBA Figure 18. Component interactions within the knowledge Web server.

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CHAPTER 8 KNOWLEDGE NETWORK APPLICATIONS To illustrate the usefulness of knowledge networks, we have developed two example e-commerce applications to demonstrate the presented concepts and technologies: a business-to-customer scenario based on a travel agency named "Gator Travel Agency", and a business-to-business e-commerce scenario based on a company named "IntelliBiz". Due to the space limitation, the scenarios will be kept simple, but will be sufficient to explain the possible applications of all the key components and features of a knowledge network. The scenarios assume that there exists a knowledge Web server hosting the home page of the Gator Travel Agency, and the IntelliBiz, respectively. 8.1. Business-to-Customer E-Commerce Scenario Business-to-customer e-commerce is a very popular type of e-commerce. The Gator Travel Agency scenario described in this section illustrates how the knowledge network technologies can enhance this type of e-commerce. 8.1.1. The Gator Travel Agency The events that are published on the home page of the Gator Travel Agency are as follows. The parameters of the events are shown within the parenthesis. • AirfareSpecialOffer ( departure_city, destination_city, price, period ): This event is posted when a special offer on airfares is announced. The event notification includes 95

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96 the departure city, destination city, price, and the time period in which this special offer is valid. FlightCancelled ( flight_no, reason ): This event notifies that a flight has been cancelled. The flight number and the reason for the cancellation are provided through the event parameters. FlightDelay ( flight_no, reason, delay_time): This event notifies that a flight has been delayed. The flight number and the reason for the delay are provided through the event parameters. The event filters provided for each of the events are as follows: AirfareSpecialOffer departure_city, destination_city, price, period: The AirfareSpecialOffer event can be filtered based on the departure city, destination city, price, and the period. Using filters, the subscriber of the event can specify which specific subset of the AirfareSpecialOffer events he/she would like to receive. • FlightCancelled flight_no: The FlightCancelled event can be filtered based on the flight number. For example, a subscriber is interested only in the flights for which he/she has made reservations. • FlightDelayed flight_no: The FlightDelayed event can be filtered based on the flight number. As with the FlightCancelled event, a subscriber would only be interested in the flights for which he/she has made reservations. The provider-side rules for each event are given as follows. • AirfareSpecialOffer Book ( names, departure_date_time, retum_date_time ): This is a rule provided by the travel agency which can automatically book a ticket for the special offer.

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97 • FlightCancelled Refund, Rebook( next_nearest_flag, next_direct_flag): Refund is a rule which automatically refunds the airfare to the subscriber if the traveler considers the flight to be not worth rebooking. Rebook is a rule which performs an automatic rebooking based on the traveler's preference such as the next earliest flight, or the next flight that is a direct flight without connections. • FlightDelayed Refund: This rule automatically refunds the airfare to the traveler. 8. 1 .2. The Subscribers In the scenario, there are several subscribers. Each subscriber demonstrates a different usage of the knowledge Web server. Subscriber CI maintains a knowledge Web server that publishes the lowest airfares available on the Internet. It also maintains a separate mirror site SI, which has the identical information as Cl's site. CI subscribes to the event AirfareSpecialOffer. CI compares the price information that is received through the event with the prices stored on its own knowledge Web server using the rule Rl. If CI finds that the newly announced ticket prices are lower than the ones stored in its knowledge Web server, it immediately updates its prices. It also notifies the mirror site S 1 about this fact by posting an event to SI. Si will then automatically update its prices using the rule RS. This scenario shows the advantage of our approach by chaining the events and rules to propagate information to several servers in a timely and intelligent fashion. Subscriber C2 wants to be notified via e-mail, but he wants to immediately book the ticket when the airfare and seats are available. Therefore, he also selects the Book rule provided by the Gator Travel Agency. This scenario shows how the rules on the

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98 Table 1. Subscribers of AirfareSpecialOffer event in Gator Travel Agency scenario. Sub Subscribed Event Subscriber site Explanation scri [Filter] Trigger bers {notify method) and Rule [TriggerEvent] ytLveni tiisiory ) [Kule C: condition A: action] CI AirfareSpecial [AirfareSpecialOrierJ Witnin rule Kl, is a Offer ( ) mirror KWi> tor CI that [] stores the best ticket (event ) {Rl prices. <> C: price < Also, i> 1 has rule Ki) Stored_price E : update_price A: update C : true Stored_price; A : update Price in DB; Notify event Update_price To KWS SI;) C2 A • c O '1 AirfareSpecial C2 just wants to get Offer notified by e-mail, but [ Departure_city=Orlando, has a provider side rule destination_city=L.A., that books the ticket price < 200, 3/0I/00 C3 AirfareSpecial [AirfareSpecialOffer C3 wants to fly through Offer OR LowPrice] L.A Paris Tokyo, and I i--'epanure_ciiy— L,.A., ( ) combines the special destination_city=Pans, offers from two travel pricc<. agencies. //ui/wu<.perioa< //zu/uuj L.. true rV. DOOK DOlU o T • LowPnce r Denarture citv=Paris LowPrice event comes destination_city=Tokyo, from a site S2 in Europe price < 600, which specializes in Asia 7/25/00

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99 provider site can easily allow the automatic execution of code on the provider site without needing a subscriber to define additional rules on his subscribing site. Subscriber C3 is going to travel from L.A. to Paris and then to Tokyo. She wants to purchase the tickets with the lowest airfare throughout her entire trip. She finds out that the Gator Travel Agency specializes in tickets from U.S to Europe, and that another travel agency, S2, specializes in tickets from Europe to Asia. She therefore subscribes to special offers from both travel agencies. When both travel agencies combined provide a discounted price that will cover her entire trip, she books both of the offers via her personalized booking agent. This scenario shows how event notifications can be combined to generate more meaningful and useful information and also automatically perform some actions when this meaningful information is generated using the event history concept in a trigger specification. Subscriber C4 subscribes to two events provided by the Gator Travel Agency. These events trigger the same rule on the subscriber site. If a flight is cancelled or delayed, C4 wants the pick-up personnel at the airport to be notified. This scenario shows the flexibility of how different events can be linked to the same rule using the notion of triggering events defined in a trigger. C5 subscribes to two events and associates a different rule to each event. Also, for the FightCancelled event, a combination of provider site and subscriber site rules are used to perform the desired actions. When the FlightCancelled event occurs, the provider site rule rebooks the flight. On the subscriber site, a rule is triggered to adjust the schedule of C5 by a scheduler agent. Therefore, various ways to combine and perform rule executions are possible using the knowledge Web servers.

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100 Table 2. Subscribers of FlightCancelled event in Gator Travel Agency scenario. Sub scri UClo Subscribed Event [Filter] Subscriber site Trigger and Rule FTripp^er Fventl (Event History) {Rule C: condition A: action} Explanation C4 FlightCancelled [Flight_no=C01255] (event) ^ — ^ FlightDelayed [Flight_no=C01255] (event) o [FlightDelayed OR FlightCancelled] () {R4 C: true A: Send e-mail (or page) Pickup personnel at Airport; } C4 subscribes to two events and ties the same rule to the events C5 FlightCancelled rFlipht nn-DT 67991 (event) [FlightDelayed] \ ) {R5-1 E:FlightCancelled C: true A: Adjust Schedule; } C5 has subscribed to 2 events and has a different trigger and rule for each of them FlightDelayed [Flight_no=DL6722] (event) <> [FlightCancelled] ( ) {R5-2 E:FlightDelayed C: delay>3hr A: Adjust Schedule; } 8.2. Business-to-Business E-Commerce Scenario The business-to-business e-commerce is currently one of the most rapidly growing application areas on the Internet. The knowledge network concept can be used to further enhance the business-to-business e-commerce by adding active capabilities and intelligence to the Internet.

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101 8.2.1. The IntelliBiz company The IntelliBiz company performs the Business-to-Business e-commerce service by connecting suppliers of products and/or services to buyers who are seeking these products and/or services. They publish a list of suppliers and buyers on their company's home pages categorized by the products and services. A new supplier can go through a supplier registration process and give information about the types of product or service the company provides along with the company contact information. New buyers go through a separate registration process and give information about the product or service for which they are seeking. IntellizBiz provides the services to allow businesses to easily find each other and forms a virtual marketplace of products and services at the business level. The IntelliBiz company has several types of events to which the suppliers or buyers can subscribe. The description of these events and the supported filters are as follows: • NewSupplier (String ID, String e-mail. String URL, String product. Range price): This event is posted when a new supplier registers with the IntelliBiz company. The information about the supplier is encapsulated in the event parameters. Buyers can subscribe to this event to obtain the information about the new suppliers. Filters on this event are supported for the product and price_range attributes. • NewBuyer (String ID, String e-mail. String URL, String product. Range price): This event is posted when a new buyer registers with the IntelliBiz company. The event parameters encapsulate the buyer information. Suppliers can subscribe to this event to

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102 obtain this important information about newly registered buyers in a timely manner. Filters on this event are supported for the product and price_range attributes. • RFQ (String ID, String BuyerURL, String product. String quantity. String delivery_date): This event represents an RFQ (Request For Quote) which is generated by a buyer who is looking for a specific product and wants to collect quotes from the suppliers registered with IntelliBiz. This event is originally generated and posted by a buyer to the IntelliBiz company. The IntelliBiz company will then post this event to any of the suppliers who have subscribed to this event through IntelliBiz. Filters on this event are supported for the product attribute. The IntelliBiz company also has a parameterized rule (provider-side rule) that the subscribers of the events can make use of while registering for the subscription of the event. • NotifyBuyer(String SupplierlD, String SupplierE-mail, String SupplierURL) : This rule will send an e-mail notification to a new buyer to introduce a new supplier. A supplier can select this rule to be installed when the supplier subscribes to the NewBuyer event. The parameter within this rule is the buyer's e-mail address to be used to send the e-mail notification. This rule is later invoked when a new buyer comes in and performs the registration task which posts the NewBuyer event. • NotifySupplier(String BuyerlD, String BuyerE-mail, String BuyerURL) : This rule does exactly the same thing as the NotifyBuyer rule except that the buyer and the supplier roles are reversed. This rule will send an e-mail notification to a new supplier to introduce a buyer. A buyer can select this rule to be installed when the buyer

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103 subscribes to the NewSupplier event. This rule is later invoked when a new supplier comes in and performs the registration task which posts the NewSupplier event. The home page and the registration forms for the buyers and suppliers are shown in Figure 19. The event registration forms for the NewBuyer event and NewSupplier event are also shown. Home Page IntelHBiz Suppliers e-CarSpeaker CarSeats.com Register NewSupplie Buyers MvAutos.com SportsCars.com Register NewBuyer Supplier Registration ID e-mail URL Product Price Event Subscriptiqp NewBuyer RFQ Buyer Registration ID e-mail URL Product Price Event Subscription NewSupplier Filter Product ... Price Notify Event object E-mail Rules NotifyBuyer Filter Product ... Price Notify Event object E-mail Rules NotifySupplier Figure 19. The IntelliBiz home page and registration forms. 8.2.2. The Suppliers and Buyers In our scenario, we assume that there are two suppliers, two buyers and the IntelliBiz company. All of these companies have their own web sites. The suppliers are as follows: • e-CarSpeakers : This Internet company specializes in selling audio speakers for cars. • CarSeats.com : This company sells car seats over the Internet. The buyers are as follows:

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104 • MyAutos.com : This company is a new manufacturer of economic class family sedans. • SportsCars.com : This company is a sports car manufacturer. The subscribed events and filters along with the triggers and rules that are defined for each of the suppliers are as follows: Table 3. Subscription information of supplier e-CarSpeakers. IntelliBiz Site (Publisher) e-CarSpeakers Site (Subscriber) Subscribed Event Filter Provider Trigger Rule Event Rule [EventJ(Rule) NewBuyer Product=Speaker Notify [NewBuyer] AlertMarketing AND Buyer (AlertMarketing) C: true; Price.morethan(300) A: Store in DB; Alert Marketing dept.; RFQ Product=Speaker [RFQ] GenQuote (also exist AND (GenQuote) C: true on other Quantity > 20 A: Generate Quote; sites) Post QuoteEvent; Table 4. Subscription information of supplier CarSeats.com. IntelliBiz Site (Publisher) CarSeats.com Site (Subscriber) Subscribed Event Filter Provider Trigger Rule Event Rule [Event](Rule) NewBuyer Product=Seats AND price. lessthan(3(X)) Notify Buyer RFQ Product=Seats [RFQ] GenQuote (also exist AND (GenQuote) C: true on other Quantity > 100 A: Generate Quote; sites) Post QuoteEvent;

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105 The e-CarSpeakers company subscribes to the two events NewBuyer and RFQ. The filter installed for the NewBuyer event checks for the product to be speakers and also restricts the price range to be more than $300. The NotifyBuyer rule is also selected on the provider side. On the e-CarSpeakers site, the trigger relates the NewBuyer event to the AlertMarketing rule. The AlertMarketing rule will store the buyer information into the database and also alert the marketing department about the new buyer. The RFQ event is not only subscribed on the IntelliBiz site but also from other potential web sites that can post the event to the e-CarSpeakers company. The company filters out all but the product being speakers and having a quantity constraint of more than 20 speakers. The RFQ event is tied to the GenQuote rule on the e-CarSpeakers web site. The GenQuote rule will generate the quote accordingly and post the QuoteEvent to whoever generated the RFQ event. The GenQuote rule will extract the buyer's URL from the RFQ event and use it to post the QuoteEvent back to the buyer. Explanations of the CarSeats.com events, triggers, and rules are similar to the e-CarSpeakers web site except that, for the NewBuyer event, it does not perform any operation on its web site. Using the knowledge network, the suppliers can effectively contact those buyers of interest with the events and filtering concepts and further initiate local operations such as alerting people and invoking applications within their companies via rules. The subscribed events and filters along with the triggers and rules that are defined for each of the buyers are as follows: The MyAutos.com company subscribes to the two events NewSupplier and QuoteEvent. The QuoteEvent can come from any website participating in a quote submission. When the NewSupplier event is posted, the MyAutos.com has put a filter

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106 that checks if the product is a speaker and also if the price is less than $500. If an event satisfying this filter is posted, the provider side rule NotifySupplier is invoked and then the event is delivered to the MyAutos.com web site. The MyAutos.com company is very cautious about posting its RFQs and only wants to post it individually to the suppliers that have good credit rather than posting its RFQ through the IntelliBiz web site and receiving many quotes from relatively small companies. Therefore, the NewSupplier event is linked to the EvalSupplier rule, which performs a credit check and then proceeds to send out an RFQ individually to the supplier. The capability of defining rules on each of the local web sites allows personal information or policies to be kept secure and undisclosed. The QuoteEvent is an event that is posted in response to the RFQ encapsulating a quote that is generated by a supplier. The QuoteEvent is linked to the ProcessQuote rule through a trigger. The ProcessQuote rule will check the number of quotes and see if it is the best quote received. If it is the best quote, then the quote accepting process is initiated. Table 5. Subscription information of buyer MyAutos.com. IntelliBiz Site /any Site (Publisher) MyAutos.com Site (Subscriber) Subscribed Event Event Filter Provider Rule Trigger [Event](Rule) Rule New Supplier (IntelliBiz site) Product=Speaker AND Price.lessthan(500) Notify Supplier [NewSupplier] (EvalSupplier) EvalSupplier C: Credibility = good; A: Save in DB; Post RFQ to Supplier; Quote Event (any site) [QuoteEvent] (ProcessQuote) ProcessQuote C: [Count>10] Quote=best A: Post AcceptQuote;

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107 The SportsCars.com web site has similar events, triggers and rules except that for the QuoteEvent it has two triggers. The first trigger also includes an event history expression denoted as EH and checks if two important quotes QEl and QE2 have arrived. If they both have arrived, the quote comparison can be done by the ProcessQuote rule. Otherwise the quote is just saved in the database via the SaveRule. Table 6. Subscription information of buyer SportsCars.com. IntelliBiz Site /any Site (Publisher) SportsCars.com Site (Subscriber) Subscribed Event Event Filter Provider Rule Trigger [TriggerEventJ ( EventHistory) Rule New Supplier (IntelliBiz site) Product=Seats AND price.lessthan(300) Notify Supplier Quote Event (any site) [QuoteEvent] (QEl AND QE2) ProcessQuote C: true; A: Compare with QEl and QE2; [QuoteEvent] 0 SaveRule C: true; A: Save in DB; 8.2.3. The Big Picture An overall diagram, which puts all of these knowledge elements together, is shown in Figure 20. The links in the figure show how the events are posted and the triggers and rules are executed on each of the supplier and buyer sites. The filters (which

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108 were described in detail in the previous section) are not shown in order to simplify the diagram. The figure shows how the IntelliBiz web site links the buyers and the suppliers through the knowledge network. InteUiBiz Figure 20. The Business-to-Business e-commerce scenario. As shown in the above scenario, the knowledge network provides an ideal infrastructure for collaboration and for adding knowledge into the web to make it more intelligent and applicable to the emerging areas of Internet applications such as ecommerce.

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CHAPTER 9 CONCLUSION In this dissertation, we have presented the concept, architecture, functionalities, implementation techniques and some application examples of a knowledge network. This work was motivated by the limitations we observed in the existing Internet and Web technologies for supporting the emerging applications such as e-commerce and enterprise integration. We propose to extend the existing InternetWeb infrastructure by adding event and rule services as a part of the information infrastructure. Events, rules and triggers, which relate events to the evaluation of event history and the activation of rules, can be used to capture human and enterprise knowledge in the Internet, making the Internet a knowledge network instead of a data network. The event, event filter, event history and rule processing capabilities of the knowledge network offer very powerful and useful services to enable the timely delivery of relevant data and activation of operations. The knowledge network can be realized by installing a number of knowledge Web servers at some selected sites in the Internet. Each knowledge Web server consists of the following components in addition to a Web server. An Event Manager performs event filtering, notification and management. An ETR Server performs trigger processing , which includes the evaluation of event history (or composite events) and the activation of rules. Dynamic rules are supported by this component. Additionally, a Knowledge Profile Manager manages the profile of users and/or enterprises registered with the server. It also provides a web-based graphical user interface for specifying, 109

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no storing, and installing knowledge into a knowledge Web server. The functions provided by these components extend the capabilities of the Internet infrastructure and are important for supporting collaborative and distributed applications built on the Internet. The knowledge network approach combines the advantages of publish/subscribe, event filtering, and rule processing. Its advantages are summarized below. The approach allows knowledgeable users to easily build a distributed application by providing highlevel event and rule specifications instead of low-level programming. It uses a publish/subscribe model of data delivery, which not only saves bandwidth by sending data only to interested consumers of the data but also provides scalability by using the push technology. The implementation of the essential components is platform independent; any web server can be extended to process events and rules. The knowledge network provides the connectivity among distributed code segments. Rules distributed over knowledge Web servers can be invoked in a chained fashion. In other words, the processing of rules can post events, and events can trigger the processing of both local and remote rules. Knowledge represented by events and rules can thus be systematically applied as a result of data accesses and operations in the Internet. There are some issues that need to be addressed in the future research. First, there are security issues related to event delivery and rule triggering. Since event notifications can initiate the execution of rules, which may activate application systems, the potential damages caused by not having the proper security control on event and rule processing can be substantial. Second, in this work, we assume that knowledge providers and consumers of an application domain use the same ontology. That is, the terms used in defining objects and their associated events and rules are understood by all users in that

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Ill application domain. This assumption is not realistic because different users may have different interpretations and understanding of the same terms. These differences need to be resolved by some ontological mappings. Third, rules contributed by different users and/or organizations may have contradictions, cyclic conditions, redundancies, and subsumptions among them. Techniques for validating the distributed knowledge base have to be introduced and applied to detect these problems. Fourth, event and rule libraries can be pre-established for different application domains so that all users can take advantages of their contents. For example, it will be useful to establish a library of events and rules for e-trading toys and another for cars so that knowledge useful for different business domain can be captured and used by general users. Fifth, event notifications can be very time consuming when a very large number of people and organizations have subscribed to the same events. Techniques for efficient delivery of events and the data associated with the events are needed.

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APPENDIX BNF FOR RULE LANGUAGE rule := IN schema_or_class_name RULE rule_interface [RETURNS type_retum] [DESCRIPTION description_text] [TYPE type_value] [STATE state_value] [RULEVAR rule_var_ decl] rule_body [EXCEPTION exception_block] rule_body := cond_clause action_clause altaction_clause I cond_clause action_clause // altaction is empty I cond_clause altaction_clause // action is empty I action clause cond_cIause := CONDITION guarded_exp action_clause := ACTION op_block altaction_clause := ALTACTION op_block //IN schema_or_class_name := schema_name_list I schema_name_list '.' class_name schema_name_list := schema_name I schema_name_list '.' schema_name // RULE rule_interface := rule_name I rule_name ( parameter_list ) rule_name := id parameterjist := empty I a_parameter I parameterjist, a_parameter a_parameter := type_name id type_name := JAVA_type I user_def_type // rule parameters from event JAVA_type := java.lang_types I java.util_types // basic types user_def_type := CORBA_object_type // extended types having EDL // RETURNS type_retum := JAVA_type I user_def_type // TYPE type_value := STATIC I DYNAMIC 112

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113 // STATE state_value := ACTIVE I SUSPENDED // RULEVAR rule_var_decl := empty 1 rule_var_decl decl_a_var decl_a_var := var_type type_name2 id init_param ';' var_type := empty I persistent I existing type_name2 := JAVA_ type I user_def_type // rule variables init_param := empty I '(' literal ')' literal := integer_value I float_value I string_value I null // CONDITION guarded_exp := [ '[' guard ']' ] expression guard := guard_member {, guard_member }* guard_member := expression expression := expression 'OR' AND_expression I AND_expression AND_expression := AND_expression 'AND' NOT_expression I NOT_expression NOT_expression := 'NOT' basic_expression I basic_expression basic_expression := comparison_expression I query_expression I 'TRUE' I 'FALSE' I '(' expression ')' comparison_expression := method_invoke // should return TRUE / FALSE I comp_operand comp_op comp_operand comp_op := '=' I '!=' I '<' I '>' I '<=' I '>=' comp_operand := method_invoke I attribute_of_variable I literal method_invoke := attribute_of_variable . method_name (method_pars_in_cond) attribute_of_variable := variable_in_cond I variable_in_cond { . attribute_name } * method_pars_in_cond := m_parameter { , m_parameter } * m_parameter := methodjnvoke I attribute_of_variable I literal variable_in_cond := id // variable in CONDITION can be rule parameter or, // rule variable which is initialized such as // persistent, existing, or initialized local variable. query_expression := Exist ( query_proc_id Query ( oql_query_string ) ) I Exist ( cursor_var = query_proc_id Query (oql_query_with_binding) ) query_proc_id := empty I query_proc_var '.' oql_query_string := " from_where_query " // OQL* query returning IIDs oql_query_with_binding := " select_from_where_query_with_name_binding " // OQL* query returning objects // ACTION, ALTACTION op_block := operation ; { operation ; } * retum_operation retum_operation := empty I RETURN attr_of_var_in_action I RETURN method_of_var_in_action I RETURN literal

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114 operation := assignment I exec_method I oql_query_in_action I rule_command I post_event assignment := attr_of_var_in_action '=' right_hand_assign right_hand_assign := attr_of_var_in_action I method_of_var_in_action I literal attr_of_var_in_action := var_in_action { . attribute_name } * method_of_var_in_action := attr_of_var_in_action . method_name ( method_pars_in_action ) method_pars_in_action := m_parameter_action { , m_parameter_action }* m_parameter_action := method_of_var_in_action I attr_of_var_in_action var_in_action := id // variable in ACTION can be rule parameter or, // rule variable which is assigned value such as // persistent, existing, or assigned local variable. oql_query_in_action := query_proc_id oql_query oqLquery := oql_insert I oql_update I oql_delete // OQL* insert,update,delete queries rule_command := rule_server_id rule_comm rule_server_id := empty I rule_server_var '.' rule_comm := rule_enable I rule_disable I rule_delete I group_enable I group_disable I group_delete post_event := event_var '.' 'PostAsynch()' I event_var '.' 'PostSynch()' var_in_action = event_var '.' 'PostSynchO' // for values returned //EXCEPTION exception_block := { '(' exception_type ',' exception_handler '(' exception_par ')' ' )' }+

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BIOGRAPHICAL SKETCH Minsoo Lee was bom on December 18, 1968, in Masan, Korea. He received his Bachelor of Science degree in Computer Engineering from Seoul National University, Seoul, Korea, in February 1992. He then joined the Database Research Lab of the Department of Computer Engineering at Seoul National University, and received his Master of Science degree in August 1995. He worked as a researcher for one year at the Media Communications Research Lab of LG Electronics, Seoul, Korea. He joined the Department of Computer and Information Science and Engineering at the University of Florida in August 1996 to pursue a Doctor of Philosophy degree, and since then has worked as a research assistant in the Database Systems Research and Development Center of the department. His research interests include query optimization, parallel database systems, active database systems, Web information systems, and data warehouses. 122

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I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Stanley Y.W. Su, Chairman Professor of Computer and Information Science and Engineering I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Herman Lam, Cochairman Associate Professor of Electrical and Computer Engineering I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Abdelsalam Helal Associate Professor of Computer and Information Science and Engineering I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. Joachim Hammer Assistant Professor of Computer and Information Science and Engineering

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I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. A. Antonio Arroyo Associate Professor of Electrical and Computer Engineering This dissertation was submitted to the Graduate Faculty of the College of Engineering and to the Graduate School and was accepted as partial fulfillment of the requirements for the degree of Doctor of Philosophy. May 2000 M. J. Ohanian Dean, College of Engineering Winfred M. Phillips Dean, Graduate School

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I certify that I have read this study and that in my opinion it conforms to acceptable standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation for the degree of Doctor of Philosophy. A. Antonio Arroyo Associate Professor of Electrical and Computer Engineering This dissertation was submitted to the Graduate Faculty of the College of Engineering and to the Graduate School and was accepted as partial fulfillment of the requirements for the degree of Doctor of Philosophy. May 2000 M. J. Ohanian Dean, College of Engineering Winfred M. Phillips Dean, Graduate School