An advanced architecture for a commercial grid infrastructure

Litke, A; Panagakis, A; Doulamis, A; Doulamis, N; Varvarigou, T; Varvarigos, E

dc.contributor.author	Litke, A	en
dc.contributor.author	Panagakis, A	en
dc.contributor.author	Doulamis, A	en
dc.contributor.author	Doulamis, N	en
dc.contributor.author	Varvarigou, T	en
dc.contributor.author	Varvarigos, E	en
dc.date.accessioned	2014-03-01T01:19:53Z
dc.date.available	2014-03-01T01:19:53Z
dc.date.issued	2004	en
dc.identifier.issn	0302-9743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/15747
dc.subject	Large Scale	en
dc.subject	Prediction Model	en
dc.subject.classification	Computer Science, Theory & Methods	en
dc.title	An advanced architecture for a commercial grid infrastructure	en
heal.type	journalArticle	en
heal.identifier.primary	10.1007/978-3-540-28642-4_4	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-540-28642-4_4	en
heal.language	English	en
heal.publicationDate	2004	en
heal.abstract	Grid Infrastructures have been used to solve large scale scientific problems that do not have special requirements on QoS. However, the introduction and success of the Grids in commercial applications as well, entails the provision of QoS mechanisms which will allow for meeting the special requirements of the users-customers. In this paper we present an advanced Grid Architecture which incorporates appropriate mechanisms so as to allow guarantees of the diverse and contradictory users' QoS requirements. We present a runtime estimation model, which is the heart of any scheduling and resource allocation algorithm, and we propose a scheme able to predict the runtime of submitted jobs for any given application on any computer by introducing a general prediction model. Experimental results are presented which indicate the robustness and reliability of the proposed architecture. The scheme has been implemented in the framework of GRIA IST project (Grid Resources for Industrial Applications). © Springer-Verlag 2004.	en
heal.publisher	SPRINGER-VERLAG BERLIN	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
heal.bookName	LECTURE NOTES IN COMPUTER SCIENCE	en
dc.identifier.doi	10.1007/978-3-540-28642-4_4	en
dc.identifier.isi	ISI:000224955400004	en
dc.identifier.volume	3165	en
dc.identifier.spage	32	en
dc.identifier.epage	41	en