An Adaptive Job Allocation Strategy for Heterogeneous Multiple Clusters.

[DBLP_Link] [Online_Version]

Abstract:

In this paper we proposal a new scheduling system based on multi-clusters environments. The work we present is Adaptive Job Allocation Strategy (AJAS) in which the scheduler dispatches jobs that with self-scheduling scheme into appropriate resources across multi-clusters. The strategy focuses on how to increase resource utility, jobs via self-scheduling and dispatching jobs to nodes with similar performance capacities, thus equalizing execution times among all the nodes the jobs require. Experimental results show that the proposed approach performs better than previous schemes.
Year: 2009
Pages: 6

Authors:

Chao-Tung Yang

H-index: 14; Papers: 126; Citation: 587 [FOAF]

Homepage: http://web.thu.edu.tw/ctyang/

Expertise: Grid Computing; Computer Networks / Object-Based Systems; Design Model / Response System; Clustering Protocol / Role-Based Access Control Model; Grid Computing / Parallel Data; Web Service;

Keng-Yi Chou

H-index: 0; Papers: 1; Citation: 0 [FOAF]

Expertise:

Chao-Tung Yang, Keng-Yi Chou. An Adaptive Job Allocation Strategy for Heterogeneous Multiple Clusters. 2009. pp.209~214

Other Format:

LNCS: [Top]
Yang, C., Chou, K.: An Adaptive Job Allocation Strategy for Heterogeneous Multiple Clusters. 209-214

IEEE:
C. Yang and K. Chou, "An Adaptive Job Allocation Strategy for Heterogeneous Multiple Clusters", 2009, pp.209-214.

ACM:
Yang, C. and Chou, K. An Adaptive Job Allocation Strategy for Heterogeneous Multiple Clusters. 2009, 209-214.

Latex:
@INPROCEEDINGS{ yang:an, AUTHOR = "Chao-Tung Yang and Keng-Yi Chou", TITLE = "An Adaptive Job Allocation Strategy for Heterogeneous Multiple Clusters.",'09", PAGES = {209-214}, YEAR = {2009} }

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