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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.accessioned2011-05-04T19:04:49Z
dc.date.available2011-05-04T19:04:49Z
dc.date.issued2009-08
dc.identifier.isbn978-1-60558-594-9
dc.identifier.urihttp://hdl.handle.net/1721.1/62585
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_US
dc.description.sponsorshipNokia Corporationen_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Grant CNF–0435382)en_US
dc.language.isoen_US
dc.publisherAssociation for Computing Machinery / ACM Special Interest Group on Data Communicationsen_US
dc.relation.isversionofhttp://dx.doi.org/10.1145/1594977.1592584en_US
dc.rightsCreative Commons Attribution-Noncommercial-Share Alike 3.0en_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceMIT web domainen_US
dc.titleCutting the Electric Bill for Internet-Scale Systemsen_US
dc.typeArticleen_US
dc.identifier.citationQureshi, Asfandyar et al. “Cutting the Electric Bill for Internet-scale Systems.” Proceedings of the ACM SIGCOMM 2009 Conference on Data Communication - SIGCOMM ’09. Barcelona, Spain, 2009. 123. Copyright c2009 ACMen_US
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.mitauthorQureshi, Asfandyar
dc.contributor.mitauthorBalakrishnan, Hari
dc.contributor.mitauthorGuttag, John V.
dc.relation.journalACM SIGCOMM Conference on Data Communications. Proceedingsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
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_US
mit.metadata.statusComplete


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