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Geographical load balancing with renewables

Liu, Zhenhua and Lin, Minghong and Wierman, Adam and Low, Steven H. and Andrew, Lachlan L. H. (2011) Geographical load balancing with renewables. ACM SIGMETRICS Performance Evaluation Review, 39 (3). pp. 62-66. ISSN 0163-5999. https://resolver.caltech.edu/CaltechAUTHORS:20161128-151114708

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Abstract

Given the significant energy consumption of data centers, improving their energy efficiency is an important social problem. However, energy efficiency is necessary but not sufficient for sustainability, which demands reduced usage of energy from fossil fuels. This paper investigates the feasibility of powering internet-scale systems using (nearly) entirely renewable energy. We perform a trace-based study to evaluate three issues related to achieving this goal: the impact of geographical load balancing, the role of storage, and the optimal mix of renewables. Our results highlight that geographical load balancing can significantly reduce the required capacity of renewable energy by using the energy more efficiently with "follow the renewables" routing. Further, our results show that small-scale storage can be useful, especially in combination with geographical load balancing, and that an optimal mix of renewables includes significantly more wind than photovoltaic solar.


Item Type:Article
Related URLs:
URLURL TypeDescription
http://dx.doi.org/10.1145/2160803.2160862DOIArticle
http://dl.acm.org/citation.cfm?doid=2160803.2160862PublisherArticle
Additional Information:© 2011 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
NSF CCF-0830511
NSFCNS-0911041
NSFCNS-0846025
Department of Energy (DOE)DE-EE0002890
Army Research Office (ARO)W911NF-08-1-0233
Microsoft ResearchUNSPECIFIED
Bell LabsUNSPECIFIED
Caltech Lee Center for Advanced NetworkingUNSPECIFIED
Australian Research CouncilFT0991594
Issue or Number:3
Record Number:CaltechAUTHORS:20161128-151114708
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20161128-151114708
Official Citation:Zhenhua Liu, Minghong Lin, Adam Wierman, Steven H. Low, and Lachlan L.H. Andrew. 2011. Geographical load balancing with renewables. SIGMETRICS Perform. Eval. Rev. 39, 3 (December 2011), 62-66. DOI=http://dx.doi.org/10.1145/2160803.2160862
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:72339
Collection:CaltechAUTHORS
Deposited By: Kristin Buxton
Deposited On:28 Nov 2016 23:24
Last Modified:03 Oct 2019 16:16

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