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Multi-objective Optimization Approaches Using a CE-ACO Inspired Strategy to Improve Grid Jobs Scheduling

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2 Author(s)
Yi Hu ; Dept. of Comput. Sci. & Technol., Shandong Univ., Jinan, China ; Bin Gong

Grid scheduling is one of the most crucial issue in a grid environment because it strongly affects the performance of the whole system. Taking into account that the issue of allocating jobs on resources is a combinatorial optimization problem, a NP-complete problem, several heuristics have been proposed to provide good performance. In this paper, the proposed approach considers a stochastic optimization called the cross entropy method. The CE method is used to tackle efficiently the initialization sensitiveness problem associated with ant colony algorithm for multi-objective scheduling, which accelerates the convergence rate and improves the ability of searching an optimum solution. Simulation shows that it performs better than the ACO in the integrated performances.

Published in:

ChinaGrid Annual Conference, 2009. ChinaGrid '09. Fourth

Date of Conference:

21-22 Aug. 2009