Greening Geographical Load Balancing

被引:111
作者
Liu, Zhenhua [1 ]
Lin, Minghong [1 ]
Wierman, Adam [1 ]
Low, Steven [1 ]
Andrew, Lachlan L. H. [2 ]
机构
[1] CALTECH, Dept Comp & Math Sci, Pasadena, CA 94706 USA
[2] Swinburne Univ Technol, Hawthorn, Vic 3122, Australia
关键词
Data centers; demand response; distributed algorithms; geographical load balancing; renewable energy; POWER; ALLOCATION;
D O I
10.1109/TNET.2014.2308295
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
080201 [机械制造及其自动化];
摘要
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.
引用
收藏
页码:657 / 671
页数:15
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