With the prevailing of sensors, researches on sensor data stream processing is important from both aspects of theory and application. Complex Event Processing (CEP) is an important technology in processing stream data. With advantages on simplicity and intelligent, CEP has got great attention from both research and industry fields. It is generally adopted to discover semantic information of system interests from application scenarios, such as abnormal detection of action. Using CEP to process sensor data stream, the complex event detection plays an important role in determining sensor applications performance. To process sensor data streams come from the abnormal detection scenario of manufacture process, this thesis mainly focuses on the event-graph model based complex event detection method and its improvements. Following are main contributions of this paper: 1.Complex event model in sensor applications: The event semantic is extended by adding counting constrains to the temporal sequence event algebra. The standard ECA rule model with deadline extension is used as the basis of analyzing real-time complex event detection implementation. Both rule set characteristics and its affection towards the response time and dynamic rules adjustments are studied, so as to improve real-time performance and flexibility for complex event detection. 2.Concurrent event detections scheduling: With the common event nodes between different event-graphs, event-graphs will be merged into an event-graph. However, the common event nodes will produce problems of multiple event detection tasks waiting for the same event instance. As different scheduling order of the common event instance among these concurrent event detections will lead to different complex event detection response time, we proposed the event scheduling method optimization model related to deadline constrain. We get three priority metrics from both aspects of topological particularity and the deadline. Experimental results show that the proposed event scheduling can yield a substantial improvement in complex event detection response time. 3.Parallel complex event processing: Concurrent event detections exist among multiple event graphs. Towards reducing the waiting time among these concurrent event detection tasks, we proposed two algorithms to partition the rule set to different processing nodes and implemented the parallel complex event processing based on these rule set partition algorithms. The global...
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