HiPPIS: An online P2P system for efficient lookups on d-dimensional hierarchies

Doka, K; Tsoumakos, D; Koziris, N

dc.contributor.author	Doka, K	en
dc.contributor.author	Tsoumakos, D	en
dc.contributor.author	Koziris, N	en
dc.date.accessioned	2014-03-01T02:45:24Z
dc.date.available	2014-03-01T02:45:24Z
dc.date.issued	2008	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32271
dc.subject	Concept hierarchies	en
dc.subject	Data warehousing	en
dc.subject	Distributed hash table	en
dc.subject.other	Concept hierarchies	en
dc.subject.other	Data warehousing	en
dc.subject.other	Distributed Hash Table	en
dc.subject.other	Distributed storage	en
dc.subject.other	Drill-down	en
dc.subject.other	Experimental evaluation	en
dc.subject.other	Lookups	en
dc.subject.other	Multidimensional data	en
dc.subject.other	P2P system	en
dc.subject.other	Prior knowledge	en
dc.subject.other	Query flooding	en
dc.subject.other	Adaptive algorithms	en
dc.subject.other	Knowledge management	en
dc.subject.other	Peer to peer networks	en
dc.subject.other	Technical presentations	en
dc.subject.other	Warehouses	en
dc.subject.other	Data warehouses	en
dc.title	HiPPIS: An online P2P system for efficient lookups on d-dimensional hierarchies	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1145/1458502.1458513	en
heal.identifier.secondary	http://dx.doi.org/10.1145/1458502.1458513	en
heal.publicationDate	2008	en
heal.abstract	In this paper we describe HiPPIS, a system that enables efficient storage and on-line querying of multidimensional 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 workload. Efficient roll-up and drill-down operations take place in order to maximize the 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, both point and aggregate ones, without flooding the network. At the same time, it manages to preserve the hierarchical nature of data. These characteristics are maintained even after sudden shifts in the workload. Copyright 2008 ACM.	en
heal.journalName	International Conference on Information and Knowledge Management, Proceedings	en
dc.identifier.doi	10.1145/1458502.1458513	en
dc.identifier.spage	63	en
dc.identifier.epage	70	en