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- Title
Optimal machine placement based on improved genetic algorithm in cloud computing.
- Authors
Lu, Jiawei; Zhao, Wei; Zhu, Haotian; Li, Jie; Cheng, Zhenbo; Xiao, Gang
- Abstract
In cloud computing, virtual machine placement (VMP) is an important process that identifies the most appropriate physical machine to host the virtual machines (VMs). Nevertheless, determining how to place VMs within the data center to provide high availability and good performance is a difficult challenge for cloud providers. In this paper, with the goal of optimizing the availability and the energy consumption of the cloud data center, an improved genetic algorithm (I-GA) is proposed to solve VMP problem. This new algorithm presents a virtual hierarchy architecture model to combine with the genetic algorithm. The model is able to achieve a near-optimal solution in resolving the availability and energy consumption concerns by innovating the initial population generation step of the I-GA. Finite element analysis is applied as background and CloudSim is used as the experiment simulation. The simulated results demonstrate the significant improvement of the data center's energy efficiency and the successful maintenance of its high availability. The results are also highly competitive compared to the benchmark results of other VMP algorithms.
- Subjects
GENETIC algorithms; FINITE element method; CLOUD computing; ENERGY consumption; GENETIC models; MACHINERY; SERVER farms (Computer network management)
- Publication
Journal of Supercomputing, 2022, Vol 78, Issue 3, p3448
- ISSN
0920-8542
- Publication type
Article
- DOI
10.1007/s11227-021-03953-8