Cutting the Electric Bill for Internet-Scale Systems

被引:317
|
作者
Qureshi, Asfandyar [1 ]
Weber, Rick
Balakrishnan, Hari [1 ]
Guttag, John [1 ]
Maggs, Bruce [2 ]
机构
[1] MIT, CSAIL, Cambridge, MA 02139 USA
[2] Carnegie Mellon Univ, Pittsburgh, PA 15213 USA
关键词
Economics; Management; Performance;
D O I
10.1145/1594977.1592584
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:123 / 134
页数:12
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