Cutting the Electric Bill for Internet-Scale Systems

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Cutting the Electric Bill for Internet-Scale Systems

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by Asfandyar Qureshi , John Guttag , Rick Weber , Bruce Maggs , Hari Balakrishnan

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203 - 3 self

BibTeX

@MISC{Qureshi_cuttingthe,
    author = {Asfandyar Qureshi and John Guttag and Rick Weber and Bruce Maggs and Hari Balakrishnan},
    title = {Cutting the Electric Bill for Internet-Scale Systems},
    year = {}
}

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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. Categories andSubject Descriptors

Keyphrases

electric bill internet-scale system electricity price energy expense realistic workload important fraction historical electricity price electricity cost akamai cdn transmission inefficiency geographic variation network traffic data regional demand difference possible economic gain significant economic gain data center operating cost locational computation cost difference different location generation diversity

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