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Greening Geographical Load Balancing

Liu, Zhenhua and Lin, Minghong and Wierman, Adam and Low, Steven and Andrew, Lachlan L. H. (2014) Greening Geographical Load Balancing. IEEE/ACM Transactions on Networking, 23 (2). pp. 657-671. ISSN 1063-6692. doi:10.1109/TNET.2014.2308295.

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Energy expenditure has become a significant fraction of data center operating costs. Recently, “geographical load balancing” has been proposed to reduce energy cost by exploiting the electricity price differences across regions. However, this reduction of cost can paradoxically increase total energy use. We explore whether the geographical diversity of Internet-scale systems can also 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 three distributed algorithms for achieving optimal geographical load balancing. Second, we show that if the price of electricity is proportional to the instantaneous fraction of the total energy that is brown, then geographical load balancing significantly reduces brown energy use. However, the benefits depend strongly on dynamic energy pricing and the form of pricing used.

Item Type:Article
Related URLs:
URLURL TypeDescription DOIArticle
Low, Steven0000-0001-6476-3048
Additional Information:© 2014 IEEE. Manuscript received March 25, 2013; revised December 16, 2013; accepted January 23, 2014; approved by IEEE/ACM TRANSACTIONS ON NETWORKING Editor A. Capone. This work was supported by the NSF under Grants CCF 0830511, CNS 0911041, and CNS 0846025; the DoE under Grant DE-EE0002890; the ARO MURI under Grant W911NF-08-1-0233; Microsoft Research; Bell Labs; the Lee Center for Advanced Networking; and the ARC under Grants FT0991594 and DP130101378. This is an extension of a conference paper in the ACM International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS), San Jose, CA, USA, June 7–11, 2011.
Funding AgencyGrant Number
NSFCCF 0830511
NSFCNS 0911041
NSFCNS 0846025
Department of Energy (DOE)DE-EE0002890
Army Research Office (ARO)W911NF-08-1-0233
Microsoft ResearchUNSPECIFIED
Caltech Lee Center for Advanced NetworkingUNSPECIFIED
Australian Research Council (ARC)FT0991594
Australian Research Council (ARC)DP130101378
Subject Keywords:Data centers, demand response, distributed algorithms, geographical load balancing, renewable energy
Issue or Number:2
Record Number:CaltechAUTHORS:20150112-084413455
Persistent URL:
Official Citation:Liu, Z.; Lin, M.; Wierman, A.; Low, S.; Andrew, L.L.H., "Greening Geographical Load Balancing," Networking, IEEE/ACM Transactions on , vol.23, no.2, pp.657,671, April 2015 doi: 10.1109/TNET.2014.2308295 doi: 10.1109/TNET.2014.2308295 URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:53549
Deposited By: Tony Diaz
Deposited On:13 Jan 2015 17:05
Last Modified:10 Nov 2021 20:03

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