Distributing and searching concept hierarchies: An adaptive DHT-based system

Asiki, A; Tsoumakos, D; Koziris, N

dc.contributor.author	Asiki, A	en
dc.contributor.author	Tsoumakos, D	en
dc.contributor.author	Koziris, N	en
dc.date.accessioned	2014-03-01T01:33:10Z
dc.date.available	2014-03-01T01:33:10Z
dc.date.issued	2010	en
dc.identifier.issn	1386-7857	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/20356
dc.subject	Adaptive indexing	en
dc.subject	Concept hierarchies	en
dc.subject	Distributed hash table	en
dc.subject	Grid information system	en
dc.subject.classification	Computer Science, Information Systems	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.subject.other	Aggregation level	en
dc.subject.other	Answering queries	en
dc.subject.other	Concept hierarchies	en
dc.subject.other	Distributed Hash Table	en
dc.subject.other	Drill-down	en
dc.subject.other	Grid information systems	en
dc.subject.other	Grid systems	en
dc.subject.other	Hierarchical data	en
dc.subject.other	Information systems application	en
dc.subject.other	Large amounts of data	en
dc.subject.other	Low costs	en
dc.subject.other	Sudden change	en
dc.subject.other	Hierarchical systems	en
dc.subject.other	Indexing (of information)	en
dc.subject.other	Information systems	en
dc.title	Distributing and searching concept hierarchies: An adaptive DHT-based system	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/s10586-010-0136-5	en
heal.identifier.secondary	http://dx.doi.org/10.1007/s10586-010-0136-5	en
heal.language	English	en
heal.publicationDate	2010	en
heal.abstract	Concept hierarchies greatly help in the organization and reuse of information and are widely used in a variety of information systems applications. In this paper, we describe a method for efficiently storing and querying data organized into concept hierarchies and dispersed over a DHT. In our method, peers individually decide on the level of indexing according to the granularity of the incoming queries. Roll-up and drill-down operations are performed on a per-node basis in order to minimize the required bandwidth for answering queries on variable aggregation levels. We motivate our approach by applying it on a large-scale Grid system: Specifically, we apply our fully decentralized scheme that creates, queries and updates large volumes of hierarchical data on-line and replace the traditional centralized and strictly indexed information systems. Our extensive experimental results support this argument on many diverse configurations: Our system proves very efficient in skewed workloads, both over single and multiple hierarchy levels at the same time. It adapts to sudden changes in popularity and effectively stores and updates large amounts of data at very low cost. © 2010 Springer Science+Business Media, LLC.	en
heal.publisher	SPRINGER	en
heal.journalName	Cluster Computing	en
dc.identifier.doi	10.1007/s10586-010-0136-5	en
dc.identifier.isi	ISI:000280552800003	en
dc.identifier.volume	13	en
dc.identifier.issue	3	en
dc.identifier.spage	257	en
dc.identifier.epage	276	en