Energy-aware scheduling schemes for cloud data centers on Google trace data

Ziqian Dong, Wenjie Zhuang, Roberto Rojas-Cessa

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

19 Scopus citations

Abstract

In this paper, we propose the most efficient server first (MESF) task scheduling scheme to minimize the energy consumed by data-center servers. MESF allocates and schedules tasks to servers according to the energy profile of servers. Energy consumed by data-center servers constitutes the largest portion of the total data-center energy consumption. The proposed MESF scheme uses resource allocation information and server energy profiles to schedule tasks to the servers with the least virtual power consumption (VPC) increment. We tested our proposed scheme on a real-world trace data set from Google clusters, and the simulation results show that the proposed MESF task scheduling scheme outperforms the random-based and least allocated server first schemes on energy savings.

Original languageEnglish (US)
Title of host publication2014 IEEE Online Conference on Green Communications, OnlineGreenComm 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479973842
DOIs
StatePublished - May 28 2014
Externally publishedYes
Event2014 IEEE Online Conference on Green Communications, OnlineGreenComm 2014 - Online Only, United States
Duration: Nov 12 2014Nov 14 2014

Publication series

Name2014 IEEE Online Conference on Green Communications, OnlineGreenComm 2014

Other

Other2014 IEEE Online Conference on Green Communications, OnlineGreenComm 2014
CountryUnited States
CityOnline Only
Period11/12/1411/14/14

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications

Keywords

  • Energy
  • Google trace
  • data center
  • scheduling

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