Energy-efficiency virtual machine placement based on binary gravitational search algorithm
Energy-efficiency virtual machine placement based on binary gravitational search algorithm
复制标题
基于二分引力搜索算法的节能虚拟机放置
DOI：
10.1007/s10586-019-03021-0
复制
发表时间：
2019-11-28
影响因子：
4.4
通讯作者：
Tian, Yu-Chu
中科院分区：
文献类型：
--
作者：
Abdessamia, Foudil;Zhang, Wei-Zhe;Tian, Yu-Chu
云计算是通过互联网托管和提供服务的非凡范式。它吸引了最臭名昭著的商业公司，并导致其用户从简单的最终用户到越来越多地通过云中部署其系统的公司。提供需求的资源数量变得巨大。因此，非常需要能源供应。我们所知道的世界高度关注生活及其世界各个方面的环境和能源效率。为了处理数据中心中的能源浪费，研究使用虚拟机放置作为确保云合并并减少功率浪费的主要关键。提出了几种用于虚拟机放置的方法。本文提出了一种基于二元重力搜索算法（BGSA）的解决方案，以在异质数据中心的虚拟机放置。在这项工作中，我们将BGSA方法比较了与粒子群优化，首先合适，最合适和最差合适的数据中心中的虚拟机拟合。结果表明，与其他策略相比，节能的显着差异。获得的结果为我们的方法提供了优势，并随着虚拟机数量的增加而获得了更好的响应。
Cloud computing is a remarkable growing paradigm for hosting and offering services through the Internet. It attracted the most notorious business companies and resulted to an exponential increase of its users from simple end users to companies that deploy more and more of their system over the cloud. The amount of resources to provide the demand became tremendous. therefore, a great need energy supply. The world as we know is highly concerned about the environment and the energy-efficiency in all aspect of life and the domain of IT is one them. To deal with energy wastage in data centers, researches use Virtual machine placement as a main key to assure cloud consolidation and reduce power wastage. Several approaches were proposed for Virtual machine placement. This paper proposes a solution based on Binary gravitational search algorithm (BGSA) for the virtual machine placement in the heterogeneous data center. In this work, we compared the BGSA method to fit with virtual machines in data centers with particle swarm optimization, First-fit, Best-fit, and worst-fit. results showed significant difference of energy save comparing to other strategies. The results obtained gave the advantage to our approach and its better response with the increase of number of virtual machines.