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Empowering automatic data-center management with machine learning
dc.contributor.author | Berral García, Josep Lluís |
dc.contributor.author | Gavaldà Mestre, Ricard |
dc.contributor.author | Torres Viñals, Jordi |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament de Llenguatges i Sistemes Informàtics |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
dc.date.accessioned | 2013-05-22T11:19:56Z |
dc.date.created | 2013 |
dc.date.issued | 2013 |
dc.identifier.citation | Berral, 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.uri | http://hdl.handle.net/2117/19370 |
dc.description.abstract | The 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.extent | 3 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat |
dc.subject.lcsh | Machine learning -- Industrial applications |
dc.subject.lcsh | Cloud Computing |
dc.title | Empowering automatic data-center management with machine learning |
dc.type | Conference lecture |
dc.subject.lemac | Computació en núvol |
dc.contributor.group | Universitat Politècnica de Catalunya. CAP - Grup de Computació d'Altes Prestacions |
dc.contributor.group | Universitat Politècnica de Catalunya. LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge |
dc.identifier.doi | 10.1145/2480362.2480397 |
dc.description.peerreviewed | Peer Reviewed |
dc.relation.publisherversion | http://dl.acm.org/citation.cfm?id=2480362.2480397&coll=DL&dl=ACM&CFID=331761957&CFTOKEN=84033976 |
dc.rights.access | Restricted access - publisher's policy |
local.identifier.drac | 11806428 |
dc.description.version | Postprint (published version) |
dc.date.lift | 10000-01-01 |
local.citation.author | Berral, J.; Gavaldà, R.; Torres, J. |
local.citation.contributor | ACM Symposium on Applied Computing |
local.citation.pubplace | Coimbra |
local.citation.publicationName | Proceedings on the 28th ACM Symposium on Applied Computing |
local.citation.startingPage | 170 |
local.citation.endingPage | 172 |