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GAGPC : An Algorithm to Optimize Multiple Continuous Queries on Data Streams  

Suh Young-Kyoon (한국과학기술정보연구원 NTIS 사업단 통합기술개발팀)
Son Jin-Hyun (한양대학교 컴퓨터공학과)
Kim Myoung-Ho (한국과학기술원 전산학과)
Publication Information
Journal of KIISE:Databases / v.33, no.4, 2006 , pp. 409-422 More about this Journal
Abstract
In general, there can be many reusable intermediate results due to the overlapped windows and periodic execution intervals among Multiple Continuous Queries (MCQ) on data streams. In this regard, we propose an efficient greedy algorithm for a global query plan construction, called GAGPC. GAGPC first decides an execution cycle and finds the maximal Set(s) of Related execution Points (SRP). Next, GAGPC constructs a global execution plan to make MCQ share common join-fragments with the highest benefit in each SRP. The algorithm suggests that the best plan of the same continuous queries may be different according to not only the existence of common expressions, but the size of overlapped windows related to them. It also reflects to reuse not only the whole but partial intermediate results unlike previous work. Finally, we show experimental results for the validation of GAGPC.
Keywords
Multiple Continuous Queries (MCQ); Data Streams; Sensor Network;
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