Greening Geographical Load Balancing
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.
© 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.