Cutting the electric bill for internet-scale systems
Cutting the electric bill for internet-scale systems
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DOI：
10.1145/1592568.1592584
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发表时间：
2009-08
期刊：
影响因子：
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通讯作者：
Asfandyar Qureshi;Rick Weber;Hari Balakrishnan;John V. Guttag;Bruce M. Maggs
中科院分区：
文献类型：
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作者：
Asfandyar Qureshi;Rick Weber;Hari Balakrishnan;John V. Guttag;Bruce M. Maggs
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.
