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ICDEW '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering Workshops
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Complex Event Processing (CEP) systems are designed to process large amount of information by simultaneously evaluating multiple queries over event streams. Two main requirements imposed by the users of the CEP systems are: (1) ability to process high throughput event data and (2) ability to answer queries with very low latency. In order to meet above requirements CEP systems are becoming increasingly distributed. Distribution of queries as well as event streams across multiple nodes facilitates increasing the throughput of CEP systems while simultaneously maintaining low response times. The widespread adoption of cloud computing and the accompanying pay-as-you-go model has added new dimensions to the problem of complex event processing in a distributed system. Nowadays, it is not only important to be able to scale the processing out to a large number of nodes, it is also equally important to be able to scale the processing down, as soon as the load or user requirements decrease. The ability to scale processing up and down along with the load and user requirements is called elasticity. The goal of the thesis described in this paper is to develop a component allowing for elastic scaling of distributed CEP systems in response to variations in the load and contractual obligations regarding the quality of service. To this end, the thesis described in this paper will address following three major topics: (1) multi query optimization, (2) operator placement in distributed environments, and (3) cost efficiency. This paper outlines the state of art for the three aforementioned topics and presents the overall draft of the solution for the problem of the elastic complex event processing.