Mostrar el registro sencillo del ítem

dc.contributorUniversitat Ramon Llull. La Salle
dc.contributor.authorBriones Delgado, Alan
dc.contributor.authorMartín de Pozuelo, Ramon
dc.contributor.authorNavarro Martín, Joan
dc.contributor.authorZaballos Diego, Agustín
dc.date.accessioned2020-05-13T14:27:09Z
dc.date.accessioned2023-10-02T06:37:22Z
dc.date.available2020-05-13T14:27:09Z
dc.date.available2023-10-02T06:37:22Z
dc.date.created2015-12
dc.date.issued2016-03
dc.identifier.urihttp://hdl.handle.net/20.500.14342/3364
dc.description.abstractThe use of hybrid clouds enables companies to cover their demands of IT resources saving costs and gaining flexibility in the deployment of infrastructures by paying under demand these resources. However, considering a scenario with various services to be allocated in more than one cloud, it is necessary to find the distribution of services that minimizes the overall operating costs. This paper researches on the resource allocation methodology to be applied in a multi-cloud scenario based on the findings derived from the framework used for the FINESCE project. The purpose of this work is to define a methodology to assist on the hybrid cloud selection and configuration in the Smart Grid for both generic and highly-constrained scenarios in terms of latency and availability. Specifically, the presented method is aimed to determine which is the best cloud to allocate a resource by (1) optimizing the system with the information of the network and (2) minimizing the occurrence of collapsed or underused virtual machines. Also, to assess the performance of this method and any alternative proposals, a general set of metrics has been defined. These metrics have been refined taking into account the expertise of FINESCE partners in order to shape Smart Grid clouds and reduce the complexity of computation. Finally, using the data extracted from the FINESCE testbed, a decision tree is used to come up with the best resource allocation scheme.eng
dc.format.extent19 p.cat
dc.language.isoengcat
dc.publisherMacrothink Institutecat
dc.relation.ispartofNetwork Protocols and Algorithms, 2016. Vol. 8, 1cat
dc.rightsAttribution 4.0 International
dc.rights© L'autor/a
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceRECERCAT (Dipòsit de la Recerca de Catalunya)
dc.subject.otherOrdinadors -- Memòries virtualscat
dc.titleResource Allocation on a Hybrid Cloud for Smart Gridscat
dc.typeinfo:eu-repo/semantics/articlecat
dc.typeinfo:eu-repo/semantics/publishedVersioncat
dc.rights.accessLevelinfo:eu-repo/semantics/openAccess
dc.embargo.termscapcat
dc.identifier.doihttp://dx.doi.org/10.5296/npa.v8i1.8721cat
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/FP7-ICT-2011/604677cat


Ficheros en el ítem

 

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem

Attribution 4.0 International
Excepto si se señala otra cosa, la licencia del ítem se describe como http://creativecommons.org/licenses/by/4.0/
Compartir en TwitterCompartir en LinkedinCompartir en FacebookCompartir en TelegramCompartir en WhatsappImprimir