Name
Abstract | ||
|---|---|---|
In recent years, high energy consumption has gradually become a prominent problem in a data center. With the advent of cloud computing, computing and storage resources are bringing greater challenges to energy consumption. Virtual machine (VM) initial placement plays an important role in affecting the size of energy consumption. In this paper, we use binary particle swarm optimization (BPSO) algorithm to design a VM placement strategy for low energy consumption measured by proposed energy efficiency fitness, and this strategy needs multiple iterations and updates for VM placement. Finally, the strategy proposed in this paper is compared with other four strategies through simulation experiments. The results show that our strategy for VM placement has better performance in reducing energy consumption than the other four strategies, and it can use less active hosts than others. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1155/2018/9471356 | SCIENTIFIC PROGRAMMING |
Field | DocType | Volume |
Virtual machine,Low energy,Efficient energy use,Computer science,Parallel computing,Binary particle swarm optimization,Energy consumption,Data center,High energy,Cloud computing,Distributed computing | Journal | 2018 |
ISSN | Citations | PageRank |
1058-9244 | 0 | 0.34 |
References | Authors | |
5 | 5 | |