Optimizing data management in grid environments

Zissimos, A; Doka, K; Chazapis, A; Tsoumakos, D; Koziris, N

dc.contributor.author	Zissimos, A	en
dc.contributor.author	Doka, K	en
dc.contributor.author	Chazapis, A	en
dc.contributor.author	Tsoumakos, D	en
dc.contributor.author	Koziris, N	en
dc.date.accessioned	2014-03-01T02:46:17Z
dc.date.available	2014-03-01T02:46:17Z
dc.date.issued	2009	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/32641
dc.subject	Data Management	en
dc.subject	Data Transfer	en
dc.subject	Flash Crowds	en
dc.subject	Location Service	en
dc.subject	Peer To Peer	en
dc.subject.other	Adaptive mechanism	en
dc.subject.other	Band-width utilization	en
dc.subject.other	Business applications	en
dc.subject.other	Data management	en
dc.subject.other	Flash crowd	en
dc.subject.other	Grid environments	en
dc.subject.other	Integrated architecture	en
dc.subject.other	Peer-to-peer techniques	en
dc.subject.other	Performance bottlenecks	en
dc.subject.other	Replica location services	en
dc.subject.other	Robust datum	en
dc.subject.other	Single point	en
dc.subject.other	Transfer mechanisms	en
dc.subject.other	Two-component	en
dc.subject.other	WAN environment	en
dc.subject.other	Data transfer	en
dc.subject.other	Grid computing	en
dc.subject.other	Information management	en
dc.subject.other	Internet	en
dc.subject.other	Internet protocols	en
dc.subject.other	Wide area networks	en
dc.subject.other	Environmental management	en
dc.title	Optimizing data management in grid environments	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-05148-7_38	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-05148-7_38	en
heal.publicationDate	2009	en
heal.abstract	Grids currently serve as platforms for numerous scientific as well as business applications that generate and access vast amounts of data. In this paper, we address the need for efficient, scalable and robust data management in Grid environments. We propose a fully decentralized and adaptive mechanism comprising of two components: A Distributed Replica Location Service (DRLS) and a data transfer mechanism called GridTorrent. They both adopt Peer-to-Peer techniques in order to overcome performance bottlenecks and single points of failure. On one hand, DRLS ensures resilience by relying on a Byzantine-tolerant protocol and is able to handle massive concurrent requests even during node churn. On the other hand, GridTorrent allows for maximum band-width utilization through collaborative sharing among the various data providers and consumers. The proposed integrated architecture is completely backwards-compatible with already deployed Grids. To demonstrate these points, experiments have been conducted in LAN as well as WAN environments under various workloads. The evaluation shows that our scheme vastly outperforms the conventional mechanisms in both efficiency (up to 10 times faster) and robustness in case of failures and flash crowd instances. © Springer-Verlag 2009.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-05148-7_38	en
dc.identifier.volume	5870 LNCS	en
dc.identifier.issue	PART 1	en
dc.identifier.spage	497	en
dc.identifier.epage	512	en