Adaptive Control in Grid Computing Resource Scheduling

摘要：

In this article, we present a method of improving the genetic algorithms in the task scheduling of grid environment due to the dynamic variability characteristic of grid. First, we review the crossover probability Pc and mutation probability Pm, the key parameters affecting the performance of genetic algorithm. Next, using the adaptive thinking and population fitness which represents the performance of grid resource scheduling, we present an adaptive genetic algorithm, giving a reasonable way to select crossover probability and mutation probability. It helps Pc and Pm can be adjusted automatically with the change of the population fitness; therefore we can get a good resource scheduling. Finally, we describe the results of the test, showing that the improved adaptive genetic algorithms can make the grid resource scheduling have good population fitness.

作者: Jia-bin Yuan Jiao-min Luo Bo-jia Duan

作者单位: Nanjing University of Aeronautics and Astronautics, Postfach 21 00 16 30 yudao street nanjing jiangsu province, China

会议类型: 国际会议

会议名称: The Second International Conference on High Performance Computing and Applications(第二届高性能计算及应用国际会议)

会议地点: 上海

会议语种:英文

页码: 528-533

在线出版日期: 2009-08-10（万方平台首次上网日期，不代表论文的发表时间）