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dc.contributor.authorKolici, Vladi
dc.contributor.authorHerrero, Albert
dc.contributor.authorXhafa Xhafa, Fatos
dc.contributor.authorBarolli, Leonard
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Ciències de la Computació
dc.date.accessioned2017-05-29T11:39:47Z
dc.date.available2017-05-29T11:39:47Z
dc.date.issued2014
dc.identifier.citationKolici, V., Herrero, A., Xhafa, F., Barolli, L. A study on the performance of Oracle Grid Engine for computing intensive applications. A: International Conference on Intelligent Networking and Collaborative Systems. "2014 International Conference on Intelligent Networking and Collaborative Systems: IEEE INCoS 2014: 10–12 September 2014, University of Salerno, Salerno, Italy: proceedings". Salerno: Institute of Electrical and Electronics Engineers (IEEE), 2014, p. 282-288.
dc.identifier.isbn978-1-4799-6386-7
dc.identifier.urihttp://hdl.handle.net/2117/104994
dc.description(c) 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.description.abstractComputing intensive applications are an important family of applications in distributed computing domain. They have been object of study using different distributed computing paradigms and infrastructures. Such applications distinguish for their demanding needs for CPU computing, independently of the amount of data associated with the problem instance. Among computing intensive applications, there are applications based on simulations, aiming to maximize system resources for processing large computations for simulation. In this paper, we consider an application that simulates scheduling and resource allocation in a Grid computing system using Genetic Algorithms. In such application, a rather large number of simulations is needed to extract meaningful statistical results about the behaviour of the simulation results. We study the performance of Oracle Grid Engine for such application running in a Cluster of high computing capacities. Several scenarios were generated to measure the response time and queuing time under different workloads and number of nodes in the cluster.
dc.format.extent7 p.
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.subjectÀrees temàtiques de la UPC::Informàtica
dc.subject.lcshComputational grids (Computer systems)
dc.subject.lcshComputer algorithms
dc.subject.lcshCloud computing
dc.subject.otherCloud computing
dc.subject.otherComputing intensive applications
dc.subject.otherGenetic algorithms
dc.subject.otherGrid computing
dc.subject.otherOracle Grid Engine
dc.subject.otherScheduling
dc.subject.otherSimulation
dc.titleA study on the performance of Oracle Grid Engine for computing intensive applications
dc.typeConference report
dc.subject.lemacComputació distribuïda
dc.subject.lemacAlgorismes genètics
dc.subject.lemacComputació en núvol
dc.identifier.doi10.1109/INCoS.2014.39
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7057103
dc.rights.accessOpen Access
local.identifier.drac17839594
dc.description.versionPostprint (author's final draft)
local.citation.authorKolici, V.; Herrero, A.; Xhafa, F.; Barolli, L.
local.citation.contributorInternational Conference on Intelligent Networking and Collaborative Systems
local.citation.pubplaceSalerno
local.citation.publicationName2014 International Conference on Intelligent Networking and Collaborative Systems: IEEE INCoS 2014: 10–12 September 2014, University of Salerno, Salerno, Italy: proceedings
local.citation.startingPage282
local.citation.endingPage288


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