Cutting the electric bill for internet-scale systems

  • Authors:

  • Asfandyar Qureshi;Rick Weber;Hari Balakrishnan;John Guttag;Bruce Maggs

  • Affiliations:

  • MIT, Cambridge, MA, USA;Akamai Technologies, Cambridge, MA, USA;MIT, Cambridge, MA, USA;MIT, Cambridge, MA, USA;Carnegie Mellon University, Pittsburgh, PA, USA

  • Venue:
  • Proceedings of the ACM SIGCOMM 2009 conference on Data communication
  • Year:
  • 2009

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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.