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Sixth International Conference on Grid and Cooperative Computing (GCC 2007)
An Improved Genetic Algorithm with Limited Iteration for Grid Scheduling
Urumchi, Xinjiang, China
August 16-August 18
ISBN: 0-7695-2871-6
Hao Yin, Sichuan University
Huilin Wu, Sichuan University
Jiliu Zhou, Sichuan University
In Grid environment the numbers of resources and tasks to be scheduled are usually variable. This kind of characteristics of grid makes the scheduling approach a complex optimization problem. Genetic algorithm (GA) has been widely used to solve these difficult NPcomplete problems. However the conventional GA is too slow to be used in a realistic scheduling due to its time-consuming iteration. This paper presents an improved genetic algorithm for scheduling independent tasks in grid environment, which can increase search efficiency with limited number of iteration by improving the evolutionary process while meeting a feasible result.
Citation:
Hao Yin, Huilin Wu, Jiliu Zhou, "An Improved Genetic Algorithm with Limited Iteration for Grid Scheduling," gcc, pp.221-227, Sixth International Conference on Grid and Cooperative Computing (GCC 2007), 2007
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