Task and server assignment for reduction of energy consumption in datacenters

Ning Liu, Ziqian Dong, Roberto Rojas-Cessa

Research output: Contribution to conferencePaperpeer-review

14 Scopus citations

Abstract

Energy consumption of cloud data centers accounts for a major operational cost. This paper presents an optimization model for task scheduling to minimize task processing time and energy consumption in data centers for cloud computing. We formulate an integer programming optimization problem to minimize the expected energy consumption of homogenous tasks in a data center with a large number of servers and propose the most-efficient-server first greedy task scheduling algorithm to minimize energy expenditure. We show that the proposed task scheduling can minimize the energy expenditure while bounding the average task waiting time. We present a simulation of the proposed task scheduling scheme to show an optimum number of servers to achieve small task processing times and to minimize energy consumption.

Original languageEnglish (US)
Pages171-174
Number of pages4
DOIs
StatePublished - Nov 1 2012
EventIEEE 11th International Symposium on Network Computing and Applications, NCA 2012 - Cambridge, MA, United States
Duration: Aug 23 2012Aug 25 2012

Other

OtherIEEE 11th International Symposium on Network Computing and Applications, NCA 2012
Country/TerritoryUnited States
CityCambridge, MA
Period8/23/128/25/12

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

Keywords

  • Cloud computing
  • Energy
  • Green Cloud
  • Task Scheduling

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