云平台下动态任务调度人工免疫算法  

Artificial immune algorithm for dynamic task scheduling on cloud computing platform

作　　者：杨镜[1] 吴磊[1] 武德安[1] 王晓敏[2] 刘念伯[2] 

机构地区：[1]电子科技大学数学科学学院,成都611731 [2]电子科技大学计算机科学与工程学院,成都611731

出　　处：《计算机应用》2014年第2期351-356,共6页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61103226;61272526);中央高校基本科研业务专项资金资助项目(ZYGX2010J111;ZYGX2010J074;ZYGX2011J102)

摘　　要：针对云计算领域的任务调度问题,提出了一种基于人工免疫(AI)理论的云计算平台动态任务调度算法。该算法首先利用排队论迅速、粗略地确定云计算平台保持稳态的条件,并为后面的计算提供基础数据;然后利用人工免疫理论中的免疫克隆选择算法,搜索出为集群中各节点上的不同虚拟机分配计算资源的近似最优配置;算法中还加入了适当的负载平衡处理,它使抗体基因更加优良。模拟实验结果表明,该调度算法能有效提高收敛速度和精度,快速搜索到合理配置,提高了集群资源利用率。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.

关 键 词：云计算 人工免疫 动态任务调度 虚拟机 资源配置 排队论 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]