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Greening geographical load balancing

Liu, Zhenhua and Lin, Minghong and Wierman, Adam and Low, Steven H. and Andrew, Lachlan L. H. (2011) Greening geographical load balancing. In: Proceedings of the ACM SIGMETRICS joint international conference on Measurement and modeling of computer systems. Association for Computing Machinery , New York, NY, pp. 233-244. ISBN 978-1-4503-0814-4 . https://resolver.caltech.edu/CaltechAUTHORS:20120522-080032032

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Abstract

Energy expenditure has become a significant fraction of data center operating costs. Recently, "geographical load balancing" has been suggested to reduce energy cost by exploiting the electricity price differences across regions. However, this reduction of cost can paradoxically increase total energy use. This paper explores whether the geographical diversity of Internet-scale systems can additionally be used to provide environmental gains. Specifically, we explore whether geographical load balancing can encourage use of "green" renewable energy and reduce use of "brown" fossil fuel energy. We make two contributions. First, we derive two distributed algorithms for achieving optimal geographical load balancing. Second, we show that if electricity is dynamically priced in proportion to the instantaneous fraction of the total energy that is brown, then geographical load balancing provides significant reductions in brown energy use. However, the benefits depend strongly on the degree to which systems accept dynamic energy pricing and the form of pricing used.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1145/1993744.1993767DOIUNSPECIFIED
http://dl.acm.org/citation.cfm?doid=1993744.1993767PublisherUNSPECIFIED
Additional Information:© 2012 ACM. This work was supported by NSF grants CCF 0830511, CNS 0911041, and CNS 0846025, DoE grant DE-EE0002890, ARO MURI grant W911NF-08-1-0233, Microsoft Research, Bell Labs, the Lee Center for Advanced Networking, and ARC grant FT0991594.
Funders:
Funding AgencyGrant Number
NSFCCF 0830511
NSFCNS 0911041
NSFCNS 0846025
Department of Energy (DOE)DE-EE0002890
Army Research Office (ARO) Multidisciplinary University Research Initiative (MURI)W911NF-08-1-0233
Microsoft ResearchUNSPECIFIED
Bell LabsUNSPECIFIED
Caltech Lee Center for Advanced NetworkingUNSPECIFIED
ARCFT0991594
Subject Keywords:Algorithms, Performance
Record Number:CaltechAUTHORS:20120522-080032032
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20120522-080032032
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:31580
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:22 May 2012 16:41
Last Modified:03 Oct 2019 03:53

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