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dc.contributor.authorLiu, M.
dc.contributor.authorRay, M.
dc.contributor.authorZhang, D.
dc.contributor.authorRundensteiner, E.
dc.contributor.authorDougherty, D. J.
dc.contributor.authorGupta, C.
dc.contributor.authorWang, S.
dc.contributor.authorArı, İsmail
dc.descriptionDue to copyright restrictions, the access to the full text of this article is only available via subscription.
dc.description.abstractComplex Event Processing (CEP) over event streams has become increasingly important for real-time applications ranging from healthcare to supply chain management. In such applications, arbitrarily complex sequence patterns as well as non existence of such complex situations must be detected in real time. To assure real-time responsiveness for detection of such complex pattern over high volume high-speed streams, efficient processing techniques must be designed. Unfortunately the efficient processing of complex sequence queries with negations remains a largely open problem to date. To tackle this shortcoming, we designed optimized strategies for handling nested CEP query. In this demonstration, we propose to showcase these techniques for processing and optimizing nested pattern queries on streams. In particular our demonstration showcases a platform for specifying complex nested queries, and selecting one of the alternative optimized techniques including sub-expression sharing and intermediate result caching to process them. We demonstrate the efficiency of our optimized strategies by graphically comparing the execution time of the optimized solution against that of the default processing strategy of nested CEP queries. We also demonstrate the usage of the proposed technology in several healthcare services.
dc.description.sponsorshipHP Labs Innovation Program ; NSF
dc.publisherThe ACM Digital Library
dc.relation.ispartofEDBT '12 Proceedings of the 15th International Conference on Extending Database Technology
dc.titleRealtime healthcare services via nested complex event processing technologyen_US
dc.typeConference paperen_US
dc.contributor.departmentÖzyeğin University
dc.contributor.authorID(ORCID 0000-0002-6159-0484 & YÖK ID 43541) Arı, İsmail
dc.contributor.ozuauthorArı, İsmail
dc.subject.keywordsExecution strategy
dc.subject.keywordsSupply chain management
dc.subject.keywordsNested sequence
dc.subject.keywordsMonitoring application
dc.relation.publicationcategoryConference Paper - International - Institutional Academic Staff

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