云数据中心基于贪心算法的虚拟机迁移策略

Greedy algorithm-based virtual machine migration strategies in cloud data center

为了节省云数据中心的能量消耗,提出了几种基于贪心算法的虚拟机(VM)迁移策略。这些策略将虚拟机迁移过程划分为物理主机状态检测、虚拟机选择和虚拟机放置三个步骤,并分别在虚拟机选择和虚拟机放置步骤中采用贪心算法予以优化。提出的三种迁移策略分别为:最小主机使用效率选择且最大主机使用效率放置算法MinMax_Host_Utilization、最大主机能量使用选择且最小主机能量使用放置算法MaxMin_Host_Power_Usage、最小主机计算能力选择且最大主机计算能力放置算法MinMax_Host_MIPS。针对物理主机处理器使用效率、物理主机能量消耗、物理主机处理器计算能力等指标设置最高或者最低的阈值,参考贪心算法的原理,在指标上超过或者低于这些阈值范围的虚拟机都将进行迁移。利用CloudSim作为云数据中心仿真环境的测试结果表明,基于贪心算法的迁移策略与CloudSim中已存在的静态阈值迁移策略和绝对中位差迁移策略比较起来,总体能量消耗少15%,虚拟机迁移次数少60%,平均SLA违规率低5%。

In order to save the energy consumption in cloud data center,some greedy algorithms-based Virtual Machine(VM)migration strategies were proposed.In these strategies,the virtual migration process was divided into physical host status detection,virtual machine selection and virtual machine placement,and the greedy algorithm was adopted in the process of virtual selection and virtual placement respectively.The three proposed migration strategies were:Minimum Host Utilization selection,Maximum Host Utilization placement(MinMax_Host_Utilization);Maximum Host Power Usage selection,Minimum Host Power Usage placement(MaxMin_Host_Power_Usage);Minimum Host MIPS selection,Maximum Host MIPS placement(MinMax_Host_MIPS).The maximum or minimum thresholds were set for the processor utilization efficency,the energy consumption and the processor computing power of physical host.According to the principle of greedy algorithm,the virtual machines with indicators higher or lower than the thresholds should be migrated.With CloudSim as the simulated cloud data center,the test results show that compared with the static threshold and median absolute deviation migration strategies existing in CloudSim,the proposed strategies have the total energy consumption reduced by 15%,the virtual machine migration number decreased by 60%,and the average SLA violation rate lowered about 5%.