DC FieldValueLanguage
dc.contributor.authorSalam, Humaira Abdul-
dc.contributor.authorDavoli, Franco-
dc.contributor.authorCarrega, Alessandro-
dc.contributor.authorTimm-Giel, Andreas-
dc.date.accessioned2019-03-18T13:58:32Z-
dc.date.available2019-03-18T13:58:32Z-
dc.date.issued2019-01-16-
dc.identifier.citation2018 28th International Telecommunication Networks and Applications Conference, ITNAC 2018: 8615319 1-6 (2019-01-16)de_DE
dc.identifier.isbn978-153867177-1de_DE
dc.identifier.urihttp://hdl.handle.net/11420/2191-
dc.description.abstractPower management and load balancing in data centers are becoming critical with the growing size of the infrastructure. In front of an increasing number of cloud networks, virtual machines (VMs) and containers, smart management and control decisions are required, in order to instantiate or mobilize these virtual components. As regards reducing power consumption, it is also essential to consolidate virtual resources on the minimum possible number of servers compatible with performance requirements. In such a dynamic scenario, estimating the power that can be ascribed to a specific virtual component and its relation with the offered workload could be beneficial for optimized resource scheduling. Predicting the power consumption caused by a specific virtual component is however challenging. In this paper, two power models that relate a VM workload with the fraction of power consumed attributable to the VM are developed based on power profiling of a server. The accuracy of the proposed models is improved approximately by 3% compared to other existing models. © 2018 IEEE.en
dc.language.isoende_DE
dc.subjectpower modelingde_DE
dc.subjectpower profilingde_DE
dc.subjectregression modelde_DE
dc.subjectVirtual machinede_DE
dc.subject.ddc004: Informatikde_DE
dc.subject.ddc620: Ingenieurwissenschaftende_DE
dc.titleTowards Prediction of Power Consumption of Virtual Machines for Varying Loadsde_DE
dc.typeinProceedingsde_DE
dc.type.dinicontributionToPeriodical-
dcterms.DCMITypeText-
tuhh.abstract.englishPower management and load balancing in data centers are becoming critical with the growing size of the infrastructure. In front of an increasing number of cloud networks, virtual machines (VMs) and containers, smart management and control decisions are required, in order to instantiate or mobilize these virtual components. As regards reducing power consumption, it is also essential to consolidate virtual resources on the minimum possible number of servers compatible with performance requirements. In such a dynamic scenario, estimating the power that can be ascribed to a specific virtual component and its relation with the offered workload could be beneficial for optimized resource scheduling. Predicting the power consumption caused by a specific virtual component is however challenging. In this paper, two power models that relate a VM workload with the fraction of power consumed attributable to the VM are developed based on power profiling of a server. The accuracy of the proposed models is improved approximately by 3% compared to other existing models. © 2018 IEEE.de_DE
tuhh.publisher.doi10.1109/ATNAC.2018.8615319-
tuhh.publication.instituteKommunikationsnetze E-4de_DE
tuhh.type.opusInProceedings (Aufsatz / Paper einer Konferenz etc.)-
tuhh.institute.germanKommunikationsnetze E-4de
tuhh.institute.englishKommunikationsnetze E-4de_DE
tuhh.gvk.hasppnfalse-
dc.type.drivercontributionToPeriodical-
dc.type.casraiConference Paper-
tuhh.container.startpage1de_DE
tuhh.container.endpage6de_DE
dc.relation.conference28th International Telecommunication Networks and Applications Conferencede_DE
tuhh.container.articlenumber8615319de_DE
local.status.inpressfalsede_DE
item.grantfulltextnone-
item.creatorGNDSalam, Humaira Abdul-
item.creatorGNDDavoli, Franco-
item.creatorGNDCarrega, Alessandro-
item.creatorGNDTimm-Giel, Andreas-
item.openairecristypehttp://purl.org/coar/resource_type/c_5794-
item.fulltextNo Fulltext-
item.openairetypeinProceedings-
item.creatorOrcidSalam, Humaira Abdul-
item.creatorOrcidDavoli, Franco-
item.creatorOrcidCarrega, Alessandro-
item.creatorOrcidTimm-Giel, Andreas-
item.languageiso639-1en-
item.cerifentitytypePublications-
crisitem.author.deptKommunikationsnetze E-4-
crisitem.author.deptKommunikationsnetze E-4-
crisitem.author.orcid0000-0003-0383-0096-
crisitem.author.orcid0000-0002-5944-7582-
crisitem.author.orcid0000-0002-5998-6113-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
crisitem.author.parentorgStudiendekanat Elektrotechnik, Informatik und Mathematik-
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