面向云数据中心能效优化的虚拟机放置算法

摘要

针对云数据中心能耗和服务器内部资源负载不均衡问题,提出一种面向云数据中心能效优化的虚拟机放置算法.建立多维资源模型、能耗模型和负载均衡度量指标,在分组遗传算法基础上,采用资源利用率多维标准差控制参量,设计适应度函数引导搜索解空间,通过定义基因评估参数并结合传统启发式算法对交叉、变异等方面进行优化,提高搜索最优解的效率.实验结果表明,该算法可以有效降低启用物理机的数目,最小化数据中心能耗,提高数据中心整体能效.%Aiming at problems of energy consumption and imbalance exist in server's internal source load of cloud computing center,a virtual machine placement algorithm was presented,which could optimize the energy-efficiency of cloud data center.Based on the grouping genetic algorithm,the energy consumption model and load balance measurement index were established.A multi-dimensional fitness function was constructed on the foundation of standard deviation and resource utilization,which could guide the solution searching.Inspired by the traditional heuristic algorithm of gene evaluation parameters,the optimized crossover and mutation were provided to improve solution quality.Experimental results show that the proposed algorithm reduces the number of physical machines and minimize the energy consumption so as to increase the overall efficiency of data center.