Energy Efficient Multiresource Allocation of Virtual Machine Based on PSO in Cloud Data Center

被引:41
|
作者
Xiong, An-ping [1 ,2 ]
Xu, Chun-xiang [1 ]
机构
[1] Univ Elect Sci & Technol, Dept Comp Sci & Engn, Chengdu 610054, Peoples R China
[2] Chongqing Univ Posts & Telecommun, Dept Comp Sci & Technol, Chongqing 400065, Peoples R China
基金
中国国家自然科学基金;
关键词
PARTICLE SWARM OPTIMIZATION; COMPUTING ENVIRONMENTS; MANAGEMENT; POWER; CONSOLIDATION;
D O I
10.1155/2014/816518
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Presently, massive energy consumption in cloud data center tends to be an escalating threat to the environment. To reduce energy consumption in cloud data center, an energy efficient virtual machine allocation algorithm is proposed in this paper based on a proposed energy efficient multiresource allocation model and the particle swarm optimization (PSO) method. In this algorithm, the fitness function of PSO is defined as the total Euclidean distance to determine the optimal point between resource utilization and energy consumption. This algorithm can avoid falling into local optima which is common in traditional heuristic algorithms. Compared to traditional heuristic algorithms MBFD and MBFH, our algorithm shows significantly energy savings in cloud data center and also makes the utilization of system resources reasonable at the same time.
引用
收藏
页数:8
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