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dc.contributor.CRUESPUNIVERSIDADE ESTADUAL DE CAMPINASpt_BR
dc.identifier.isbnpt_BR
dc.contributor.authorunicampPiga, Leonardo de Paula Rosapt_BR
dc.contributor.authorunicampBergamaschi, Reinaldo Alvarengapt_BR
dc.contributor.authorunicampRigo, Sandropt_BR
dc.typeArtigopt_BR
dc.titleEmpirical and analytical approaches for web server power modelingpt_BR
dc.title.alternativept_BR
dc.contributor.authorPiga L.pt_BR
dc.contributor.authorRigo S.pt_BR
dc.contributor.authorBergamaschi R.A.pt_BR
unicamp.authorPiga, L., Institute of Computing, University of Campinas UNICAMP, Av. Albert Einstein, 1251 - Cidade UniversitariaCampinas, SP, Brazilpt_BR
unicamp.authorBergamaschi, R.A., Institute of Computing, University of Campinas UNICAMP, Av. Albert Einstein, 1251 - Cidade UniversitariaCampinas, SP, Brazilpt_BR
unicamp.authorRigo, S., Institute of Computing, University of Campinas UNICAMP, Av. Albert Einstein, 1251 - Cidade UniversitariaCampinas, SP, Brazilpt_BR
dc.subjectCentros de processamento de dadospt_BR
dc.subjectServidores da Webpt_BR
dc.subjectMacromodelagem de potênciapt_BR
dc.subjectEnergia elétrica - Conservaçãopt_BR
dc.subjectArquitetura de computadorpt_BR
dc.subject.otherlanguageData processing service centerspt_BR
dc.subject.otherlanguageWeb serverspt_BR
dc.subject.otherlanguagePower macromodelingpt_BR
dc.subject.otherlanguageElectric power conservationpt_BR
dc.subject.otherlanguageComputer architecturept_BR
dc.description.abstractPower-aware computing has emerged as a significant concern in data centers. In this work, we develop empirical models for estimating the power consumed by web servers. These models can be used by on-the-fly power-saving algorithms and are imperative for simulators that evaluate the power behavior of workloads. To apply power saving methodologies and algorithms at the data center level, we must first be able to measure or estimate the power and performance of individual servers running in the data centers. We show a novel method for developing full system web server power models that reduces non-linear relationships among performance measurements and system power and prunes model parameters. The web server power models use as parameters performance indicators read from the machine internal performance counters. We evaluate our approach on an AMD Opteron-based web server and on an Intel i7-based web sever. Our best model displays an average absolute error of 1.92 % for Intel i7 server and 1.46 % for AMD Opteron as compared to actual measurements, and 90th percentile for the absolute percent error equals to 2.66 % for Intel i7 and 2.08 % for AMD Opteron.en
dc.description.abstractPower-aware computing has emerged as a significant concern in data centers. In this work, we develop empirical models for estimating the power consumed by web servers. These models can be used by on-the-fly power-saving algorithms and are imperative for spt_BR
dc.relation.ispartofCluster Computing: the journal of networks, software tools and applicationspt_BR
dc.relation.ispartofabbreviationpt_BR
dc.publisher.cityNew York, NYpt_BR
dc.publisher.countryEstados Unidospt_BR
dc.publisherSpringer pt_BR
dc.date.issued2014pt_BR
dc.date.monthofcirculationpt_BR
dc.identifier.citationCluster Computing. Springer New York Llc, v. 17, n. 4, p. 1279 - 1293, 2014.pt_BR
dc.language.isoengpt_BR
dc.description.volume17pt_BR
dc.description.issuenumber4pt_BR
dc.description.issuesupplementpt_BR
dc.description.issuepartpt_BR
dc.description.firstpage1279pt_BR
dc.description.lastpage1293pt_BR
dc.rightsfechadopt_BR
dc.rightsfechadopt_br
dc.sourceSCOPUSpt_BR
dc.identifier.issn1386-7857pt_BR
dc.identifier.eissnpt_BR
dc.identifier.doi10.1007/s10586-014-0373-0pt_BR
dc.identifier.urlhttps://link.springer.com/article/10.1007/s10586-014-0373-0pt_BR
dc.description.sponsorshipFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOpt_BR
dc.description.sponsorship1Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)pt_BR
dc.description.sponsordocumentnumber2010/05389-5pt_BR
dc.date.available2015-06-25T17:51:37Z
dc.date.available2015-11-26T14:09:03Z-
dc.date.accessioned2015-06-25T17:51:37Z
dc.date.accessioned2015-11-26T14:09:03Z-
dc.description.provenanceMade available in DSpace on 2015-06-25T17:51:37Z (GMT). No. of bitstreams: 1 2-s2.0-84911812005.pdf: 1728123 bytes, checksum: 6bc11bcb0df0266b48b309b6a856e04e (MD5) Previous issue date: 2014en
dc.description.provenanceMade available in DSpace on 2015-11-26T14:09:03Z (GMT). No. of bitstreams: 2 2-s2.0-84911812005.pdf: 1728123 bytes, checksum: 6bc11bcb0df0266b48b309b6a856e04e (MD5) 2-s2.0-84911812005.pdf.txt: 57401 bytes, checksum: 654284874ff51a5db1668db3d59b76d3 (MD5) Previous issue date: 2014en
dc.identifier.urihttp://www.repositorio.unicamp.br/handle/REPOSIP/86114
dc.identifier.urihttp://repositorio.unicamp.br/jspui/handle/REPOSIP/86114-
dc.identifier.idScopus2-s2.0-84911812005pt_BR
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dc.description.conferencenomept_BR
dc.description.conferencedatept_BR
dc.description.conferencepatrocinadorpt_BR
dc.description.conferencelocalpt_BR
dc.contributor.departmentsem informaçãopt_BR
dc.contributor.departmentsem informaçãopt_BR
dc.contributor.departmentDepartamento de Sistemas de Computaçãopt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.contributor.unidadeInstituto de Matemática, Estatística e Computação Científicapt_BR
dc.contributor.unidadeInstituto de Computaçãopt_BR
dc.subject.keywordPower modelpt_BR
dc.subject.keywordAbsolute percent errorpt_BR
dc.subject.keywordContext switchpt_BR
dc.subject.keywordDisk powerpt_BR
dc.subject.keywordMiscellaneous componentpt_BR
dc.identifier.source2-s2.0-84911812005pt_BR
dc.creator.orcidsem informaçãopt_BR
dc.creator.orcidsem informaçãopt_BR
dc.creator.orcid0000-0002-9539-6874pt_BR
dc.type.formpt_BR
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