利用遗传算法完成虚拟机放置策略的优化  

Using Genetic Algorithm for Virtual Machine Placement Optimization

作　　者：徐胜超 XU Sheng-chao(School of Data Science,Huashang College,Guangdong University of Finance&Ecnomics,Guangzhou 511300,China)

机构地区：[1]广东财经大学华商学院数据科学学院,广东广州511300

出　　处：《计算机与现代化》2020年第12期25-31,42,共8页Computer and Modernization

基　　金：国家自然科学基金资助项目(60433040,50577027);广东财经大学华商学院校内导师制项目(2020HSDS04)。

摘　　要：提出基于遗传算法的虚拟机放置方法GA-VMP(Genetic Algorithm based Virtual Machine Placement)。GA-VMP是一种应用于虚拟机迁移过程的优化算法。在物理主机状态检测和虚拟机选择阶段分别选取了鲁棒局部归约检测方法和最小迁移时间选择方法;在最后的虚拟机放置阶段,GA-VMP将遗传算法应用到虚拟机的重新分配过程中形成了一个全新的虚拟机迁移模型。设计云数据中心的能量消耗数学模型,以能量消耗最小作为遗传算法的目标函数。Cloudsim模拟器仿真结果表明:在总体能量消耗、虚拟机迁移次数、服务等级协议违规率等指标上明显降低,平衡指标参数只有少量的增加。仿真结果可为其他企业构造节能云数据中心提供参考作用。A genetic algorithm based approach for virtual machine placement called GA-VMP was proposed.In GA-VMP,local regression robust(LRR)algorithm was adopted to identify critical hosts in the physical host status detection procedure;minimum migration time(MMT)policy was also used for selecting VMs on critical hosts to be migrated.In the virtual placement,genetic algorithm was used to find a near-optimal solution and thus formed a new virtual machine migration model called LRR-MMT-GA.The mathematic model for energy consumption in GA-VMP was also designed and the minimized energy consumption was used as the objective function in genetic algorithm.The experimental results and performance analysis show our strategy leads to a further improvement in energy consumption and virtual machine migration.Our strategy is helpful for other cloud providers to build a low energy consumption cloud data center.

关 键 词：智能计算 物理主机 虚拟机合并 虚拟机分配 遗传算法 

分 类 号：TP393.4[自动化与计算机技术—计算机应用技术]