A task scheduling policy for heterogeneous MapReduce cluster

Chui Ming Chiu, Sheng Wei Huang, Tzu Chi Huang, Ce Kuen Shieh, Ming Fong Tsai, Lien Wu Chen

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

Abstract

MapReduce is a programming model and its associated run-time system proposed in 2004, which can process large scale of data in clusters with simple program logic. MapReduce has a potential problem running on a cooperative cluster which is combined with machines having different configurations. The problem will cause unexpected performance degradations and should be avoided. In this paper, a task scheduling policy is proposed to take higher utilization of all computing nodes in heterogeneous clusters.

Original languageEnglish
Title of host publicationIntelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014
EditorsWilliam Cheng-Chung Chu, Stephen Jenn-Hwa Yang, Han-Chieh Chao
PublisherIOS Press
Pages420-429
Number of pages10
ISBN (Electronic)9781614994831
DOIs
Publication statusPublished - 2015 Jan 1
EventInternational Computer Symposium, ICS 2014 - Taichung, Taiwan
Duration: 2014 Dec 122014 Dec 14

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume274
ISSN (Print)0922-6389

Other

OtherInternational Computer Symposium, ICS 2014
CountryTaiwan
CityTaichung
Period14-12-1214-12-14

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

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