Subsuming multiple sliding windows for shared stream computation

Patroumpas, K; Sellis, T

dc.contributor.author	Patroumpas, K	en
dc.contributor.author	Sellis, T	en
dc.date.accessioned	2014-03-01T02:53:29Z
dc.date.available	2014-03-01T02:53:29Z
dc.date.issued	2011	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/36351
dc.subject.other	Continuous queries	en
dc.subject.other	Empirical studies	en
dc.subject.other	High throughput	en
dc.subject.other	Maintenance cost	en
dc.subject.other	Memory savings	en
dc.subject.other	Multi-level	en
dc.subject.other	Multiple user	en
dc.subject.other	Sliding Window	en
dc.subject.other	Stream processing	en
dc.subject.other	Time frame	en
dc.subject.other	Information systems	en
dc.subject.other	Maintenance	en
dc.title	Subsuming multiple sliding windows for shared stream computation	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-23737-9_5	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-23737-9_5	en
heal.publicationDate	2011	en
heal.abstract	Shared evaluation of multiple user requests is an utmost priority for stream processing engines in order to achieve high throughput and provide timely results. Given that most continuous queries specify windowing constraints, we suggest a multi-level scheme for concurrent evaluation of time-based sliding windows seeking for potential subsumptions among them. As requests may be registered or suspended dynamically, we develop a technique for choosing the most suitable embedding of a given window into a group composed of multi-grained time frames already employed for other queries. Intuitively, the proposed methodology ""clusters"" windowed operators into common hierarchical constructs, thus drastically reducing the need for their separate evaluation. Our empirical study confirms that such a scheme achieves dramatic memory savings with almost negligible maintenance cost. © 2011 Springer-Verlag Berlin Heidelberg.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-23737-9_5	en
dc.identifier.volume	6909 LNCS	en
dc.identifier.spage	56	en
dc.identifier.epage	69	en