基于分组遗传算法的虚拟机放置方法
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摘要
为解决现有的虚拟机(VM)初始放置目标较为片面,仅考虑1个或者2个方面的问题,该文提出了1种面向多目标优化的VM初始放置方法。综合考虑了资源利用率、功率以及温度3方面因素。基于改进的分组遗传算法生成候选的VM放置方案。采用多目标模糊评估方法筛选出最佳放置方案。仿真实验结果表明,该文方法可以减少约44%的资源浪费、降低3 k W服务器运行功率。
To solve the problem of existing virtual machine placement methods that the initial placement target is one-sided and only focuses on one or two optimization objects,a virtual machine initial placement method for multi-objective optimization is proposed here. Resource usage rate,system power and temperature are considered synthetically. Candidates of virtual machine placement solution are got based on an improved group genetic algorithm. The best virtual machine placement solution is selected by a multi-object fuzzy assessment algorithm. The simulation experiment results show that the proposed method can reduce the wasting of resources by 44% and server operation power by 3 k W.
To solve the problem of existing virtual machine placement methods that the initial placement target is one-sided and only focuses on one or two optimization objects,a virtual machine initial placement method for multi-objective optimization is proposed here. Resource usage rate,system power and temperature are considered synthetically. Candidates of virtual machine placement solution are got based on an improved group genetic algorithm. The best virtual machine placement solution is selected by a multi-object fuzzy assessment algorithm. The simulation experiment results show that the proposed method can reduce the wasting of resources by 44% and server operation power by 3 k W.
引文
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[10]Ramos L,Bianchini R.C-Oracle:Predictive thermal management for data centers[C]//IEEE 14th International Symposium on High Performance Computer Architecture.Salt Lake City,UT,USA:IEEE,2008:111-122.
[11]Rodero I,Viswanathan H,Lee E K,et al.Energy-efficient thermal-aware autonomic management of virtualized HPC cloud infrastructure[J].Journal of Grid Computing,2012,10(3):447-473.
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[2]Chen M T,Hsu C C,Kuo M S,et al.GreenG lue:Power optimization for data centers through resource-guaranteed VM placement[C]//IEEE International Conference on Internet of Things(iT hings),and IEEE Green Computing and Communications(GreenC om)and IEEECyber,Physical and Social Computing(CPSCom).Taipei,China:IEEE,2014:510-517.
[3]张牧.云计算和多维QoS环境中基于蚁群优化算法在虚拟机资源负载均衡问题中的研究[J].计算机科学,2013,40(11A):60-62.Zhang Mu.Research of virtual machine load balancing based on ant colony optimization in cloud computing and muiti-dimensional QoS[J].Computer Science,2013,40(11A):60-62.
[4]潘飞,蒋从锋,徐向华,等.负载相关的虚拟机放置策略[J].小型微型计算机系统,2013,34(3):520-524.Pan Fei,Jiang Congfeng,Xu Xianghua,et al.Placement strategy of virtual machines based on workload characteristics[J].Journal of Chinese Computer Systems,2013,34(3):520-524.
[5]秦启飞,王世振,袁翔,等.云环境下基于CROTS算法的虚拟机放置策略[J].计算技术与自动化,2015,34(1):105-110.Qin Qifei,Wang Shizhen,Yuan Xiang,et al.Chemical reactive optimization for VM consolidation in cloud computing environment[J].Computing Technology and Automation,2015,34(1):105-110.
[6]吴毅华,曹健,李明禄.云计算环境下基于需求预测的虚拟机节能分配方法研究[J].小型微型计算机系统,2013,34(4):778-782.Wu Yihua,Cao Jian,Li Minglu.Energy efficient allocation of virtual machines in cloud computing environments based on demand forecast[J].Journal of Chinese Computer Systems,2013,34(4):778-782.
[7]Sun Meng,Gu Weidong,Zhang Xinchang,et al.A matrix transformation algorithm for virtual machine placement in cloud[C]//2013 12th IEEE International Conference on Trust,Security and Privacy in Computing and Communications(TRUSTCOM 2013).Melbourne,VIC,Australia:2013:1778-1783.
[8]Li Xin,Qian Zhuzhong,Chi Ruiqing,et al.Balancing resource utilization for continuous virtual machine requests in clouds[C]//MIS’12 Proceedings of the 2012Sixth International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing.Washington,DC,USA:IEEE Computer Society,2012:266-273.
[9]Wang Lizhe,Khan S U,Dayal J.Thermal aware workload placement with task-temperature profiles in a data center[J].The Journal of Supercomputing,2012,61(3):780-803.
[10]Ramos L,Bianchini R.C-Oracle:Predictive thermal management for data centers[C]//IEEE 14th International Symposium on High Performance Computer Architecture.Salt Lake City,UT,USA:IEEE,2008:111-122.
[11]Rodero I,Viswanathan H,Lee E K,et al.Energy-efficient thermal-aware autonomic management of virtualized HPC cloud infrastructure[J].Journal of Grid Computing,2012,10(3):447-473.
[12]Elnozahy E N,Kistler M,Rajamony R.Energy-efficient server clusters[J].Lecture Notes in Computer Science,2003,2325:179-197.