Agent-Mediated genetic super-scheduling in grid environments

Authors:
Gang Chen;Zhonghua Yang;Simon See;Jie Song
Affiliations:
Information Communication Institute of Singapore, School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore;Information Communication Institute of Singapore, School of Electrical and Electronics Engineering, Nanyang Technological University, Singapore;Asia Pacific Science and Technology Center, Sun Microsystems Inc.;Asia Pacific Science and Technology Center, Sun Microsystems Inc.
Venue:
PDCAT'04 Proceedings of the 5th international conference on Parallel and Distributed Computing: applications and Technologies
Year:
2004

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Abstract

Super-scheduling in a dynamic grid environment is a very challenging issue that remains to be solved before a grid can be deployed and effectively utilized. In this paper we investigate a paradigm based on genetic algorithms (GA) to efficiently solve the scheduling problem. This GA paradigm is architecturally combined with the multiagent system (MAS) paradigm to form a flexible super-scheduling system. A three-layered scheduling architecture is presented and the corresponding realization of a multiagent-based system is described. The experiment shows that the better scheduling results are obtained for the adopted metrics of flow time and job stretch.