Robust geographical load balancing for sustainable data centers

Tianyi Chen, Yu Zhang, Xin Wang, Georgios B Giannakis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Scopus citations

Abstract

A systematic framework is put forth in this paper to integrate renewable energy sources (RES), distributed storage units, cooling facilities, as well as dynamic pricing into the workload and energy management tasks for a data center network. To cope with RES uncertainty, the resource allocation task is formulated as a robust optimization problem minimizing the worst-case net cost. The resulting problem is reformulated as a convex program, and then solved in a distributed fashion using the dual decomposition approach. Numerical tests demonstrate the performance gain of the proposed approach over the existing alternative.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3526-3530
Number of pages5
ISBN (Electronic)9781479999880
DOIs
StatePublished - May 18 2016
Event41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016 - Shanghai, China
Duration: Mar 20 2016Mar 25 2016

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume2016-May
ISSN (Print)1520-6149

Other

Other41st IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2016
CountryChina
CityShanghai
Period3/20/163/25/16

Bibliographical note

Funding Information:
Work in this paper was supported by NSF 1509040, 1508993, 1509005, 1423316, 1442686 and 1202135; the China Recruitment Program of Global Young Experts, the Program for New Century Excellent Talents in University, the Innovation Program of Shanghai Municipal Education Commission

Keywords

  • Geo-distributed data centers
  • cloud computing
  • renewable energy
  • robust optimization
  • smart grid

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