Artificial immune algorithm for dynamic task scheduling on cloud computing platform
YANG Jing1,WU Lei1,WU Dean1,WANG Xiaomin2,LIU Nianbo2
1. School of Mathematical Sciences, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China； 2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China
Abstract：In the field of cloud computing, it is a key problem that how task schedules. This paper presented an artificial immune algorithm for dynamic task scheduling on cloud computing platform. Firstly, the algorithm used the queuing theory to determine the conditions of cloud computing platform to maintain steady-state, and provided the basic data for the following algorithm. Then, this paper used the clone selection algorithm to search out the approximate optimal configuration which calculated resources for different virtual machines of different nodes in the cluster. Finally, proper load balancing processing algorithm joined with immune theory improved the antibody genes. The results of simulation experiment show that, this algorithm can effectively improve the convergence speed and accuracy, search reasonable allocation quickly and improve the cluster resource utilization.
杨镜 吴磊 武德安 王晓敏 刘念伯. 云平台下动态任务调度人工免疫算法[J]. 计算机应用, 2014, 34(2): 351-356.
YANG Jing WU Lei WU Dean WANG Xiaomin LIU Nianbo. Artificial immune algorithm for dynamic task scheduling on cloud computing platform. Journal of Computer Applications, 2014, 34(2): 351-356.
2014, Vol. 34 
