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- W2157260973 abstract "Detecting complexpatterns ineventstreams, i.e., complex event processing (CEP), hasbecomeincreasingly impor- tantformodernenterprises toreact quickly tocritical situations. Inmanypractical cases business events aregenerated basedon pre-defined business logics. Henceconstraints, suchasoccurrence andorderconstraints, often holdamongevents. Reasoning using these knownconstraints enables ustopredict thenon-occurrences ofcertain future events, thereby helping ustoidentify andthen terminate thelongrunning queryprocesses thatareguaranteed tonotleadtosuccessful matches. Inthiswork,we focusonexploiting eventconstraints to optimize CEPoverlarge volumes ofbusiness transaction streams. Since theoptimization opportunities arise atruntime, wedevelop a runtime queryunsatisfiability (RunSAT) checking technique thatdetects optimal points forterminating queryevaluation. To assure efficiency ofRunSATchecking, wepropose mechanisms toprecompute thequeryfailure conditions tobechecked at runtime. Thisguarantees a constant-time RunSATreasoning cost, makingourtechnique highly scalable. We realize our optimal querytermination strategies byaugmenting thequery withEvent-Condition-Action rulesencoding thepre-computed failure conditions. Thisresults inaneventprocessing solution compatible withstate-of-the-art CEP architectures. Extensive experimental results demonstrate thatsignificant performance gains areachieved, while theoptimization overhead issmall." @default.
- W2157260973 created "2016-06-24" @default.
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- W2157260973 date "2008-01-01" @default.
- W2157260973 modified "2023-09-27" @default.
- W2157260973 title "RuntimeSemanticQuery Optimization forEvent StreamProcessing" @default.
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