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《Journal of Sichuan University of Science & Engineering(Natural Science Edition)》 2014-01
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Task Scheduling Algorithm Based on Mutation Operator in Cloud Computing

CHEN Chao;CAI Lecai;GAO Xiang;Department of Automation & Electronic Information,Sichuan University of Science & Engineering;Department of Computer,Sichuan University of Science & Engineering;College of mechanical engineering,Sichuan University of Science & Engineering;  
In order to dispatch a huge number of tasks efficiently,an improved genetic algorithm which includes two types of mutation operations:mutation operation a and mutation operation b,is put forward.Mutation operation a is the genovariation on random position.And in mutation operation b,a gene position that meets certain conditions is found out first,then the value of this position is replaced by the target gene value.The chromosome after mutation operation b is always superior to that before mutation.Mutation operation a is used in earlier time of the algorithm.In later period,algorithm tends to converge to the optimal solution,so mutation operation b is used to improve the convergence speed.To avoid algorithm falling into local solution due to the improved mutation operations,the method that use the matching ratio of chromosomes to select initial population is adopted in the process of population initialization,for which the population can distribute in the whole solution space uniformly.The simulation results show that,the improved algorithm not only makes the final completion time shorter and convergence efficiency higher,but also balances the load to some extent.It can realize task scheduling more effectively.
【Fund】: 物联网技术与应用四川省青年科技创新团队项目(2011JTD0031);; 四川省教育厅重点科研项目(092087);; 四川理工学院研究生创新基金项目(B20306)
【CateGory Index】: TP301.6
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