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Analyzing Real Cluster Data for Formulating Allocation Algorithms in Cloud Platforms

hal.structure.identifierReformulations based algorithms for Combinatorial Optimization [Realopt]
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
dc.contributor.authorBEAUMONT, Olivier
hal.structure.identifierLaboratoire Bordelais de Recherche en Informatique [LaBRI]
hal.structure.identifierAlgorithmics for computationally intensive applications over wide scale distributed platforms [CEPAGE]
dc.contributor.authorEYRAUD-DUBOIS, Lionel
hal.structure.identifierAlgorithmics for computationally intensive applications over wide scale distributed platforms [CEPAGE]
dc.contributor.authorLORENZO-DEL-CASTILLO, Juan-Angel
dc.date.accessioned2024-04-04T03:19:50Z
dc.date.available2024-04-04T03:19:50Z
dc.date.created2014-10
dc.date.issued2014-11
dc.date.conference2014-10-22
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/194544
dc.description.abstractEnA problem commonly faced in Computer Science research is the lack of real usage data that can be used for the validation of algorithms. This situation is particularly true and crucial in Cloud Computing. The privacy of data managed by commercial Cloud infrastructures, together with their massive scale, make them very uncommon to be available to the research community. Due to their scale, when designing resource allocation algorithms for Cloud infrastructures, many assumptions must be made in order to make the problem tractable. This paper provides deep analysis of a cluster data trace recently released by Google and focuses on a number of questions which have not been addressed in previous studies. In particular, we describe the characteristics of job resource usage in terms of dynamics (how it varies with time), of correlation between jobs (identify daily and/or weekly patterns), and correlation inside jobs between the different resources (dependence of memory usage on CPU usage). From this analysis, we propose a way to formalize the allocation problem on such platforms, which encompasses most job features from the trace with a small set of parameters.
dc.description.sponsorshipSimulation de systèmes de prochaine génération - ANR-11-INFR-0013
dc.language.isoen
dc.title.enAnalyzing Real Cluster Data for Formulating Allocation Algorithms in Cloud Platforms
dc.typeCommunication dans un congrès
dc.identifier.doi10.1109/SBAC-PAD.2014.44
dc.subject.halInformatique [cs]/Calcul parallèle, distribué et partagé [cs.DC]
dc.subject.halInformatique [cs]/Modélisation et simulation
bordeaux.page302 - 309
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleProceedings of the IEEE 26th International Symposium on Computer Architecture and High Performance Computing (SBAC-PAD)
bordeaux.countryFR
bordeaux.conference.cityParis
bordeaux.peerReviewedoui
hal.identifierhal-01094388
hal.version1
hal.invitednon
hal.proceedingsoui
hal.conference.end2014-10-24
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01094388v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.date=2014-11&rft.spage=302%20-%20309&rft.epage=302%20-%20309&rft.au=BEAUMONT,%20Olivier&EYRAUD-DUBOIS,%20Lionel&LORENZO-DEL-CASTILLO,%20Juan-Angel&rft.genre=unknown


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