Task Matching and Scheduling by using Self-Adjusted Genetic Algorithms
Gird computing is a new computing-framework to meet the growing computational demands .Grid computing provides mechanisms for sharing and accessing large and heterogeneous collections of remote resources. However, how to scheduling the subtasks in these heterogeneous resources is a critical problem. This paper puts forward a task scheduling algorithm based on genetic algorithm. It first generates a fitness Junction through weighted least connection algorithm, and than generates a new group of individuals through genetic operation such as reproduction, crossover, mutation, etc. It approaches optimization gradually through frequent evolutions. Finally, the simulation results of the algorithm and conclusion are given.
Genetic algorithm grid computing task scheduling
Changwu Zhu Shangping Dai Zhi Liu
Department of Computer Science Hua Zhong Normal University Wuhan 430079,China Department of Computer Science Junxie Shiguan School Wuhan 400084, China
国际会议
Firth IEEE International Conference on Cognitive Informatics(第五届认知信息国际会议)
北京
英文
908-911
2006-07-17（万方平台首次上网日期，不代表论文的发表时间）