通信学报 ›› 2014, Vol. 35 ›› Issue (1): 72-81.doi: 10.3969/j.issn.1000-436x.2014.01.009

• 学术论文 • 上一篇    下一篇

IaaS环境下改进能源效率和网络性能的虚拟机放置方法

董健康,王洪波,李阳阳,程时端   

  1. 北京邮电大学 网络与交换技术国家重点实验室,北京 100876
  • 出版日期:2014-01-25 发布日期:2017-06-17
  • 基金资助:
    国家自然科学基金资助项目;中央高校基本科研业务费专项基金资助项目;软件开发环境国家重点实验室开放课题基金资助项目

Improving energy efficiency and network performance in IaaS cloud with virtual machine placement

Jian-kang DONG,Hong-bo WANG,Yang-yang LI,Shi-duan CHENG   

  1. State Key Laboratory of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China
  • Online:2014-01-25 Published:2017-06-17
  • Supported by:
    The National Natural Science Foundation of China;The National High Technology Research and Development Program of China;The Fundamental Research Funds for the Central Universities;The Open Fund of the State Key Laboratory of Software Development Environment

摘要:

现在的虚拟机放置研究大多集中在物理服务器能源能耗或网络设备能耗的优化,然而随着这些资源的过度聚合,有可能会带来应用性能的下降。提出了一种虚拟机放置方案,主要有2个目的:最小化激活物理机和网络设备的个数来减少数据中心能源消耗;最小化最大链路利用率来改善网络性能。此方案在优化网络性能的同时,减少物理服务器和网络设备的能耗,使得能源效率与网络性能达到平衡。设计了一种新的二阶段启发式算法来求解,首先,利用基于最小割的层次聚类算法与最佳适应算法相结合来优化能源效率,然后,利用局部搜索算法再次优化虚拟机位置来最小化最大链路利用率。仿真实验结果表明,所提方案取得了良好的效果。

关键词: IaaS, 虚拟机放置, 网络性能, 能源效率

Abstract:

The existing virtual machine(VM) placement schemes mostly reduce energy consumption by optimizing utilization of physical server or network element.However,the aggressive consolidation of these resources may lead to network performance degradation.In view of this,a VM placement scheme was proposed to achieve two objectives.One is to minimize the number of activating physical machines and network elements to reduce the energy consumption,and the other is to minimize the maximum link utilization to improve the network performance.This scheme is able to reduce the energy consumption caused by physical servers and network equipment while optimizing the network performance,making a trade off between energy efficiency and network performance.A novel two-stage heuristic algorithm for a solution was designed.Firstly,the hierarchical clustering algorithm based on minimum cut and best fit algorithm was used to optimize energy efficiency,and then,local search algorithm was used to minimize the maximum link utilization.The simulations show that this solution achieves good results.

Key words: IaaS, virtual machine placement, network performance, energy efficient

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