Cutting the Electric Bill for Internet-Scale Systems
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Balakrishnan_Cutting The.pdf
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Author(s)
Qureshi, Asfandyar
Weber, Rick
Balakrishnan, Hari
Guttag, John V.
Maggs, Bruce
Date Issued
August 2009
Journal
ACM SIGCOMM Conference on Data Communications. Proceedings
Publisher
Association for Computing Machinery / ACM Special Interest Group on Data Communications
Citation
Qureshi, 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 ACM
Version
Author's final manuscript
Abstract
Energy 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.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1145/1594977.1592584
