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dc.creatorFernández Cerero, Damiánes
dc.creatorJakóbik, Agnieszkaes
dc.creatorGrzonka, Danieles
dc.creatorKolodziej, Joannaes
dc.creatorFernández Montes González, Alejandroes
dc.date.accessioned2019-03-01T08:31:13Z
dc.date.available2019-03-01T08:31:13Z
dc.date.issued2018
dc.identifier.citationFernández Cerero, D., Jakóbik, A., Grzonka, D., Kolodziej, J. y Fernández-Montes González, A. (2018). Security supportive energy-aware scheduling and energy policies for cloud environments. Journal of Parallel and Distributed Computing, 119 (september 2018), 191-202.
dc.identifier.issn0743-7315es
dc.identifier.urihttps://hdl.handle.net/11441/83640
dc.description.abstractCloud computing (CC) systems are the most popular computational environments for providing elastic and scalable services on a massive scale. The nature of such systems often results in energy-related problems that have to be solved for sustainability, cost reduction, and environment protection. In this paper we defined and developed a set of performance and energy-aware strategies for resource allocation, task scheduling, and for the hibernation of virtual machines. The idea behind this model is to combine energy and performance-aware scheduling policies in order to hibernate those virtual machines that operate in idle state. The efficiency achieved by applying the proposed models has been tested using a realistic large-scale CC system simulator. Obtained results show that a balance between low energy consumption and short makespan can be achieved. Several security constraints may be considered in this model. Each security constraint is characterized by: (a) Security Demands (SD) of tasks; and (b) Trust Levels (TL) provided by virtual machines. SD and TL are computed during the scheduling process in order to provide proper security services. Experimental results show that the proposed solution reduces up to 45% of the energy consumption of the CC system. Such significant improvement was achieved by the combination of an energy-aware scheduler with energy-efficiency policies focused on the hibernation of VMs.es
dc.description.sponsorshipCOST Action IC1406es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherElsevieres
dc.relation.ispartofJournal of Parallel and Distributed Computing, 119 (september 2018), 191-202.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectCloud computinges
dc.subjectEnergy efficiencyes
dc.subjectIndependent task schedulinges
dc.subjectGenetic algorithmses
dc.subjectVM hibernatinges
dc.subjectCloud securityes
dc.titleSecurity supportive energy-aware scheduling and energy policies for cloud environmentses
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticoses
dc.relation.projectIDIC1406es
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/pii/S0743731518302843es
dc.identifier.doi10.1016/j.jpdc.2018.04.015es
idus.format.extent11es
dc.journaltitleJournal of Parallel and Distributed Computinges
dc.publication.volumen119es
dc.publication.issueseptember 2018es
dc.publication.initialPage191es
dc.publication.endPage202es

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