An Incentive Mechanism for Improving Energy Efficiency of Colocation Data Centers Based on Power Prediction

Ce Chi, Kaixuan Ji, Avinab Marahatta, Fa Zhang, Youshi Wang, Zhiyong Liu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

Colocation data centers (colocations, for short) are developing rapidly in recent years, resulting in a heavy burden on the power grid and the environment. Due to the special management mode of colocations, even the colocation operators wish to reduce their power demand, they have no authority to control the servers because the servers belong to and are operated by the tenants themselves. To solve the "uncoordinated relationship"issue between operators and tenants, a truthful and feasible incentive mechanism MesPP is proposed in this paper. Different from existing works, MesPP aims at maximizing the energy reduction of colocations with a limited cost budget and can be applied even there is no demand response (DR) program. Meanwhile, power prediction is integrated into MesPP to further improve the energy efficiency of colocations and fairness of the mechanism. To solve the optimization problem, we develop a (1-ϵ)-approximation algorithm. Simulations are performed and show that MesPP can achieve 12.23% more energy saving compared with existing incentive mechanisms.

Original languageEnglish
Title of host publication2020 IEEE Symposium on Computers and Communications, ISCC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728180861
DOIs
Publication statusPublished - Jul 2020
Externally publishedYes
Event2020 IEEE Symposium on Computers and Communications, ISCC 2020 - Rennes, France
Duration: 7 Jul 202010 Jul 2020

Publication series

NameProceedings - IEEE Symposium on Computers and Communications
Volume2020-July
ISSN (Print)1530-1346

Conference

Conference2020 IEEE Symposium on Computers and Communications, ISCC 2020
Country/TerritoryFrance
CityRennes
Period7/07/2010/07/20

Keywords

  • Colocation data center
  • energy efficiency
  • mechanism design
  • power prediction

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