Energy Efficient Multiresource Allocation of Virtual Machine Based on PSO in Cloud Data Center
Author(s) -
An-ping Xiong,
Chunxiang Xu
Publication year - 2014
Publication title -
mathematical problems in engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.262
H-Index - 62
eISSN - 1026-7077
pISSN - 1024-123X
DOI - 10.1155/2014/816518
Subject(s) - particle swarm optimization , data center , cloud computing , energy consumption , computer science , heuristic , virtual machine , mathematical optimization , local optimum , efficient energy use , algorithm , energy (signal processing) , engineering , artificial intelligence , mathematics , statistics , electrical engineering , operating system
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
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