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dc.contributor.authorBerral García, Josep Lluís
dc.contributor.authorGavaldà Mestre, Ricard
dc.contributor.authorTorres Viñals, Jordi
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2013-05-22T11:19:56Z
dc.date.created2013
dc.date.issued2013
dc.identifier.citationBerral, J.; Gavaldà, R.; Torres, J. Empowering automatic data-center management with machine learning. A: ACM Symposium on Applied Computing. "Proceedings on the 28th ACM Symposium on Applied Computing". Coimbra: 2013, p. 170-172.
dc.identifier.urihttp://hdl.handle.net/2117/19370
dc.description.abstractThe Cloud as computing paradigm has become nowadays crucial for most Internet business models. Managing and optimizing its performance on a moment-by-moment basis is not easy given as the amount and diversity of elements involved (hardware, applications, workloads, customer needs...). Here we show how a combination of scheduling algorithms and data mining techniques helps improving the performance and profitability of a data-center running virtualized web-services. We model the data-center's main resources (CPU, memory, IO), quality of service (viewed as response time), and workloads (incoming streams of requests) from past executions. We show how these models to help scheduling algorithms make better decisions about job and resource allocation, aiming for a balance between throughput, quality of service, and power consumption.
dc.format.extent3 p.
dc.language.isoeng
dc.subjectÀrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
dc.subject.lcshMachine learning -- Industrial applications
dc.subject.lcshCloud Computing
dc.titleEmpowering automatic data-center management with machine learning
dc.typeConference lecture
dc.subject.lemacComputació en núvol
dc.contributor.groupUniversitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions
dc.contributor.groupUniversitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge
dc.identifier.doi10.1145/2480362.2480397
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://dl.acm.org/citation.cfm?id=2480362.2480397&coll=DL&dl=ACM&CFID=331761957&CFTOKEN=84033976
dc.rights.accessRestricted access - publisher's policy
drac.iddocument11806428
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
upcommons.citation.authorBerral, J.; Gavaldà, R.; Torres, J.
upcommons.citation.contributorACM Symposium on Applied Computing
upcommons.citation.pubplaceCoimbra
upcommons.citation.publishedtrue
upcommons.citation.publicationNameProceedings on the 28th ACM Symposium on Applied Computing
upcommons.citation.startingPage170
upcommons.citation.endingPage172


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