基于布谷鸟搜索的虚拟机放置算法

姜栋瀚; 林海涛

doi:10.11959/j.issn.1000-0801.2017215

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基于布谷鸟搜索的虚拟机放置算法

研究与开发 | 更新时间：2024-06-05

- 基于布谷鸟搜索的虚拟机放置算法
- Virtual machine placement algorithm based on cuckoo search
- 电信科学 2017年33卷第10期页码：90-98
- 作者机构：
- 作者简介：
  
  [ "姜栋瀚（1992-），男，海军工程大学硕士生，主要研究方向为通信技术与网络。" ]
  [ "林海涛（1974-），男，博士，海军工程大学副教授，主要研究方向为信息网络管理与规划。" ]
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2017215
  中图分类号： TN911
- 网络出版日期：2017-10，
  
  纸质出版日期：2017-10-20
- 稿件说明：
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姜栋瀚, 林海涛. 基于布谷鸟搜索的虚拟机放置算法[J]. 电信科学, 2017,33(10):90-98.

Donghan JIANG, Haitao LIN. Virtual machine placement algorithm based on cuckoo search[J]. Telecommunications science, 2017, 33(10): 90-98.
姜栋瀚, 林海涛. 基于布谷鸟搜索的虚拟机放置算法[J]. 电信科学, 2017,33(10):90-98. DOI： 10.11959/j.issn.1000-0801.2017215.

Donghan JIANG, Haitao LIN. Virtual machine placement algorithm based on cuckoo search[J]. Telecommunications science, 2017, 33(10): 90-98. DOI： 10.11959/j.issn.1000-0801.2017215.

摘要

针对虚拟机放置问题，引入了布谷鸟搜索算法。首先，将虚拟机放置方案映射为鸟巢，并按照适应度高低将其分成顶巢和底巢。其次，通过扰动函数对底巢和顶巢进行扰动。最后，通过选择、迭代得到最佳放置方案。该算法可用于云数据中心的物理机整合，使放置物理机数量最小化。通过Cloudsim进行仿真，仿真结果表明，比起重排序分组遗传算法、分组遗传算法、改进的最小加载和改进的降序首次适应算法，提出的方法不仅避免了局部最优，而且具有更高的性能优势。

Abstract

A cuckoo search algorithm was introduced for virtual machine placement.Firstly

the virtual machine placement program was mapped to the nest

and according to the level

the fitness would be divided into top and bottom nest.Secondly

the bottom nest and the top nest were disturbed by the disturbance function.Finally

by selecting

iterations got the best placement scheme.The algorithm was used for physical integration of cloud data centers

minimizing the number of physical machines placed.The algorithm is simulated by Cloudsim and the results show that the proposed method not only avoids the local optimum

but also has higher performance advantages than the reordered grouping genetic algorithm

the group genetic algorithm

the improved least load algorithm and the improved first fit decrease algorithm.

关键词

Keywords

references

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