Task scheduling in grid computing based on improved immune genetic algorithm
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    Abstract:

    For improving the inefficient of the currentd computing,the decimal real number enco-ding rules wa chosen to generate initial antibody group.Firstly,theimmune genetic algorithm was used to generate the initial pheromone distributionin the collection,then the parallelism of the ant colony algorithm was used for global search,finally the particleswarm optimization(PSO)and ant colony genetic algorithm were compared by using C1oudSim as a simulation platform to simulate.The results indicate that the improved immune genetic algorithm can provide eff cient task scheduling strateav and it can solve the problem more effectively.

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ZHANG Jing-jun, LIU Wen-juan, LIU Guang-yuan. Task scheduling in grid computing based on improved immune genetic algorithm[J].,2013,30(2):80-83

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History
  • Received:January 21,2013
  • Revised:
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  • Online: January 12,2015
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