Online querying of concept hierarchies in P2P systems

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dc.contributor.author Doka, K en
dc.contributor.author Asiki, A en
dc.contributor.author Tsoumakos, D en
dc.contributor.author Koziris, N en
dc.date.accessioned 2014-03-01T02:45:43Z
dc.date.available 2014-03-01T02:45:43Z
dc.date.issued 2008 en
dc.identifier.issn 03029743 en
dc.identifier.uri http://hdl.handle.net/123456789/32337
dc.subject Adaptive Algorithm en
dc.subject Concept Hierarchy en
dc.subject Distributed Storage en
dc.subject Experimental Evaluation en
dc.subject Indexation en
dc.subject IT Management en
dc.subject P2p System en
dc.subject Prior Knowledge en
dc.subject.other Applications. en
dc.subject.other Concept hierarchies en
dc.subject.other Distributed storages en
dc.subject.other Experimental evaluations en
dc.subject.other P2P systems en
dc.subject.other Prior knowledges en
dc.subject.other Query flooding en
dc.subject.other Query workloads en
dc.subject.other Querying of datums en
dc.subject.other Remarkable performances en
dc.subject.other Adaptive algorithms en
dc.subject.other Direction of arrival en
dc.subject.other Internet en
dc.subject.other Radio direction finding systems en
dc.subject.other Online systems en
dc.title Online querying of concept hierarchies in P2P systems en
heal.type conferenceItem en
heal.identifier.primary 10.1007/978-3-540-88871-0_16 en
heal.identifier.secondary http://dx.doi.org/10.1007/978-3-540-88871-0_16 en
heal.publicationDate 2008 en
heal.abstract In this paper we describe HIS, a system that enables efficient storage and querying of data organized into concept hierarchies and dispersed over a network. Our scheme utilizes an adaptive algorithm that automatically adjusts the level of indexing according to the granularity of the incoming queries, without assuming any prior knowledge of the query workload. Efficient roll-up and drill-down operations increase the exact-match query ratio by shifting to the most favorable hierarchy level. Combined with soft-state indices created after query misses, our system achieves maximization of performance by minimizing query flooding. Extensive experimental evaluations show that, on top of the advantages that a distributed storage offers, our method answers the large majority of incoming queries without flooding the network and at the same time it manages to preserve the hierarchical nature of data. It shows remarkable performance especially for skewed workloads, which are frequently documented in the majority of Internet-scale applications. These characteristics are maintained even after sudden shifts in the workload. © 2008 Springer 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 10.1007/978-3-540-88871-0_16 en
dc.identifier.volume 5331 LNCS en
dc.identifier.issue PART 1 en
dc.identifier.spage 212 en
dc.identifier.epage 230 en

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