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dc.contributor.authorQureshi, Asfandyar
dc.contributor.authorWeber, Rick
dc.contributor.authorBalakrishnan, Hari
dc.contributor.authorGuttag, John V.
dc.contributor.authorMaggs, Bruce
dc.date.accessioned2010-01-22T19:07:23Z
dc.date.available2010-01-22T19:07:23Z
dc.date.issued2009-08
dc.identifier.isbn978-1-60558-594-9
dc.identifier.urihttp://hdl.handle.net/1721.1/50995
dc.description.abstractEnergy expenses are becoming an increasingly important fraction of data center operating costs. At the same time, the energy expense per unit of computation can vary significantly between two different locations. In this paper, we characterize the variation due to fluctuating electricity prices and argue that existing distributed systems should be able to exploit this variation for significant economic gains. Electricity prices exhibit both temporal and geographic variation, due to regional demand differences, transmission inefficiencies, and generation diversity. Starting with historical electricity prices, for twenty nine locations in the US, and network traffic data collected on Akamai's CDN, we use simulation to quantify the possible economic gains for a realistic workload. Our results imply that existing systems may be able to save millions of dollars a year in electricity costs, by being cognizant of locational computation cost differences.en
dc.description.sponsorshipNokiaen
dc.description.sponsorshipNational Science Foundationen
dc.language.isoen_US
dc.publisherAssociation for Computing Machineryen
dc.relation.isversionofhttp://doi.acm.org/10.1145/1592568.1592584en
dc.rightsAttribution-Noncommercial-Share Alike 3.0 Unporteden
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en
dc.sourceAsfandyar Qureshien
dc.titleCutting the Electric Bill for Internet-Scale Systemsen
dc.typeArticleen
dc.identifier.citationQureshi, Asfandyar et al. “Cutting the electric bill for internet-scale systems.” Proceedings of the ACM SIGCOMM 2009 conference on Data communication. Barcelona, Spain: ACM, 2009. 123-134. Print.en
dc.contributor.departmentMassachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratoryen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Scienceen_US
dc.contributor.approverBalakrishnan, Hari
dc.contributor.mitauthorGuttag, John V.
dc.contributor.mitauthorBalakrishnan, Hari
dc.contributor.mitauthorQureshi, Asfandyar
dc.relation.journalProceedings of the ACM SIGCOMM 2009 conference on Data communicationen
dc.eprint.versionAuthor's final manuscript
dc.type.urihttp://purl.org/eprint/type/SubmittedJournalArticleen
eprint.statushttp://purl.org/eprint/status/PeerRevieweden
eprint.grantNumberCNF-0435382en
dspace.orderedauthorsQureshi, Asfandyar; Weber, Rick; Balakrishnan, Hari; Guttag, John; Maggs, Bruceen
dc.identifier.orcidhttps://orcid.org/0000-0003-0992-0906
dc.identifier.orcidhttps://orcid.org/0000-0002-1455-9652
mit.licenseOPEN_ACCESS_POLICYen
mit.metadata.statusComplete


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