<p>The composite event detection process in different consumption modes has been proven to be difficult to comprehend. It is believed that visualization of this process can make it easier to grasp. In this final year project, a prototype of a visualization tool that visually displays the composite event detection is developed. The prototype uses time graphs to display the composite events and the chronicle consumption mode is used in the detection of the composite events. Animation is used in the prototype when the composite events are visualized, as it is believed that animation can be of help when learning complex algorithms, such as consumption modes. The prototype is then compared with other similar visualization tools. This prototype addresses factors, which have been identified as playing a central role in the visualization of composite events, that other similar visualization tools do not.</p>

<p>Events play an important role in many computer systems, from small reactive embedded applications to large distributed systems. Many applications react to events generated by a graphical user interface or by external sensors that monitor the system environment, and other systems use events for communication and synchronisation between independent subsystems. In some applications, however, individual event occurrences are not the main point of concern. Instead, the system should respond to certain event patterns, such as "the start button being pushed, followed by a temperature alarm within two seconds". One way to specify such event patterns is by means of an event algebra with operators for combining the simple events of a system into specifications of complex patterns.</p><p>This thesis presents an event algebra with two important characteristics. First, it complies with a number of algebraic laws, which shows that the algebra operators behave as expected. Second, any pattern represented by an expression in this algebra can be efficiently detected with bounded resources in terms of memory and time, which is particularly important when event pattern detection is used in embedded systems, where resource efficiency and predictability are crucial.</p><p>In addition to the formal algebra semantics and an efficient detection algorithm, the thesis describes how event pattern detection can be used in real-time systems without support from the underlying operating system, and presents schedulability theory for such systems. It also describes how the event algebra can be combined with a component model for embedded system, to support high level design of systems that react to event patterns.</p>

Events play an important role in many computer systems, from small reactive embedded applications to large distributed systems. Many applications react to events generated by a graphical user interface or by external sensors that monitor the system environment, and other systems use events for communication and synchronisation between independent subsystems. In some applications, however, individual event occurrences are not the main point of concern. Instead, the system should respond to certain event patterns, such as "the start button being pushed, followed by a temperature alarm within two seconds". One way to specify such event patterns is by means of an event algebra with operators for combining the simple events of a system into specifications of complex patterns. This thesis presents an event algebra with two important characteristics. First, it complies with a number of algebraic laws, which shows that the algebra operators behave as expected. Second, any pattern represented by an expression in this algebra can be efficiently detected with bounded resources in terms of memory and time, which is particularly important when event pattern detection is used in embedded systems, where resource efficiency and predictability are crucial. In addition to the formal algebra semantics and an efficient detection algorithm, the thesis describes how event pattern detection can be used in real-time systems without support from the underlying operating system, and presents schedulability theory for such systems. It also describes how the event algebra can be combined with a component model for embedded system, to support high level design of systems that react to event patterns.

<p>Event Condition Action rule engines have been developed for some time now. Theycan respond automatically to events coming from different sources. Combination ofdifferent event types may be different from time to time and there for it is hard todetermine how the rule engine executes its rules. Especially when the engine is givena large rule set to work with. To determine the behavior is to run tests on the ruleengine and see the final results, but if the results are wrong it can be hard to see whatwent wrong. ruleViz is a program that can look at the execution and visually animatethe rule engine behavior by showing connections between rules and composite events,making it easier for the operator to see what causes the fault. ruleViz is designed toembrace Human Computer Interaction (HCI) methods, making its interfaceunderstandable and easy to operate.</p>

Event Condition Action rule engines have been developed for some time now. Theycan respond automatically to events coming from different sources. Combination ofdifferent event types may be different from time to time and there for it is hard todetermine how the rule engine executes its rules. Especially when the engine is givena large rule set to work with. To determine the behavior is to run tests on the ruleengine and see the final results, but if the results are wrong it can be hard to see whatwent wrong. ruleViz is a program that can look at the execution and visually animatethe rule engine behavior by showing connections between rules and composite events,making it easier for the operator to see what causes the fault. ruleViz is designed toembrace Human Computer Interaction (HCI) methods, making its interfaceunderstandable and easy to operate.

The composite event detection process in different consumption modes has been proven to be difficult to comprehend. It is believed that visualization of this process can make it easier to grasp. In this final year project, a prototype of a visualization tool that visually displays the composite event detection is developed. The prototype uses time graphs to display the composite events and the chronicle consumption mode is used in the detection of the composite events. Animation is used in the prototype when the composite events are visualized, as it is believed that animation can be of help when learning complex algorithms, such as consumption modes. The prototype is then compared with other similar visualization tools. This prototype addresses factors, which have been identified as playing a central role in the visualization of composite events, that other similar visualization tools do not.