Work

Cutting the electric bill for internet-scale systems

Year: 2009

Type: conference-paper

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.

Source: ACM SIGCOMM Conference (SIGCOMM)

DOI: 10.1145/1592568.1592584

Authors: Asfandyar Qureshi, Rick Weber, Hari Balakrishnan, John Guttag, Bruce Maggs

Institutions: Massachusetts Institute of Technology, Akamai (United States), Carnegie Mellon University

Language: English

Topic: Cloud Computing and Resource Management

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action

Open Access status: green

Funder: National Science Foundation