Abstract

Energy consumption is an important cost driven by growth of computing power, thereby energy conservation has become one of the major problems faced by cloud system. How to maximize the utilization of physical machines, reduce the number of virtual machine migrations, and maintain load balance under the constraints of physical machine resource thresholds that is the effective way to implement energy saving in data center. In the paper, we propose a multi-objective physical model for virtual machine deployment. Then the improved multi-objective particle swarm optimization (TPSO) is applied to virtual machine deployment. Compared to other algorithms, the algorithm has better ergodicity into the initial stage, improves the optimization precision and optimization efficiency of the particle swarm. The experimental results based on CloudSim simulation platform show that the algorithm is effective at improving physical machine resource utilization, reducing resource waste, and improving system load balance.

Keywords

MSC

68-W99, 68-M01

Cite this article

@article{cai-5054,
  author  = {Shanchen Pang and Dekun Dong and Shuyu Wang},
  title   = {Virtual Machine Deployment Strategy Based on Improved PSO in Cloud Computing},
  journal = {Computing and Informatics},
  volume  = {39},
  number  = {1-2},
  pages   = {83--104},
  year    = {2020},
  issn    = {1335-9150},
  doi     = {10.31577/cai_2020_1-2_83}
}
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