Power aware scheduling of bag-of-tasks applications with deadline constraints on DVS-enabled clusters

Kyong Hoon Kim, Rajkumar Buyya, Jong Kim

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

274 Scopus citations

Abstract

Power-aware scheduling problem has been a recent issue in cluster systems not only for operational cost due to electricity cost, but also for system reliability. As recent commodity processors support multiple operating points under various supply voltage levels, Dynamic Voltage Scaling (DVS) scheduling algorithms can reduce power consumption by controlling appropriate voltage levels. In this paper, we provide power-aware scheduling algorithms for bagof-tasks applications with deadline constraints on DVSenabled cluster systems in order to minimize power consumption as well as to meet the deadlines specified by application users. A bag-of-tasks application should finish all the sub-tasks before the deadline, so that the DVS scheduling scheme should consider the deadline as well. We provide the DVS scheduling algorithms for both time-shared and space-shared resource sharing policies. The simulation results show that the proposed algorithms reduce much power consumption compared to static voltage schemes.

Original languageEnglish
Title of host publicationProceedings - Seventh IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2007
Pages541-548
Number of pages8
DOIs
StatePublished - 2007
Event7th IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2007 - Rio de Janeiro, Brazil
Duration: 14 May 200717 May 2007

Publication series

NameProceedings - Seventh IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2007

Conference

Conference7th IEEE International Symposium on Cluster Computing and the Grid, CCGrid 2007
Country/TerritoryBrazil
CityRio de Janeiro
Period14/05/0717/05/07

Fingerprint

Dive into the research topics of 'Power aware scheduling of bag-of-tasks applications with deadline constraints on DVS-enabled clusters'. Together they form a unique fingerprint.

Cite this