CSE Publications - Report Abstract
CSE-2004-10
Title : Towards an Integrated Model for Event and Stream Processing
Type : Technical Report
Author(s) : Qingchun Jiang, Raman Adaikkalavan, and Sharma Chakravarthy
Abstract : Event processing in the form of ECA rules has been researched extensively from the situation monitoring viewpoint to detect changes in a timely manner and to take appropriate actions. Several event specification languages and processing models have been developed, analyzed, and implemented. More recently, data stream processing has been receiving a lot of attention to deal with applications that generate large amounts of data in real-time at varying input rates and to compute functions over multiple streams that satisfy quality of service (QoS) requirements. A few systems based on the data stream processing model have been proposed to deal with change detection and situation monitoring. However, current data stream processing models lack the notion of composite event specification and computation, and they cannot be readily combined with event detection and rule specification, which are necessary and important for many applications. In this paper, we analyze the similarities and differences between the event and data stream processing models. Although research seems to address these two as separate topics, there are a number of similarities and differences between the two models. We argue that for many of the applications considered for stream processing, event and rule processing are needed and are not currently supported. On the contrary, event processing systems concentrate on complex event and rule processing in a DBMS environment and do not consider complex stream processing. By synthesizing these two and combining their strengths, we argue that the integrated model will be better than the sum of its parts. We then propose our integrated model and its functionality to combine the capabilities of both models for applications that not only need to monitor changes through continuous queries (CQs), but also to express and process complex events generated by CQs. We introduce the notion of a semantic window, which significantly extends the current window concept for CQs, and stream modifiers in order to extend current stream computation model for complicated change detection. We further discuss the extension of event specification to include CQs. Finally, we discuss the implementation of our integrated model using the extended data stream processing system with a local event detector.