信息网络安全 ›› 2018, Vol. 18 ›› Issue (2): 78-83.doi: 10.3969/j.issn.1671-1122.2018.02.011

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基于多目标混合粒子群算法的虚拟机负载均衡研究

梅东晖, 李红灵()   

  1. 云南大学信息学院,云南昆明650091
  • 收稿日期:2017-09-18 出版日期:2018-02-20 发布日期:2020-05-11
  • 作者简介:

    作者简介:梅东晖(1993—),男,云南,硕士研究生,主要研究方向为云计算与信息安全;李红灵(1966— ),女,云南,副教授,本科,主要研究方向为计算机网络、信息安全。

  • 基金资助:
    国家自然科学基金 [61562090]

Research on Load Balancing of Virtual Machine Based on Multiple Objective Hybrid Particle Swarm Optimization

Donghui MEI, Hongling LI()   

  1. School of Information Science and Engineering, Yunnan University, Kunming Yunnan 650091, China
  • Received:2017-09-18 Online:2018-02-20 Published:2020-05-11

摘要:

负载均衡技术一直都是云资源管理中的重要内容,在对数据中心进行管理和维护时做到负载均衡,能够提高资源的使用效率,有效地减少虚拟机的迁移次数,避免造成系统瓶颈。大多数现有的基于粒子群的虚拟机部署算法在计算适应度时通过权重赋值的方法将虚拟机的多个性能指标整合为一个目标,并且粒子在更新位置的过程中向当前最优解靠近的方法很容易使得最后求得解陷入局部最优。针对以上问题,文章提出了一种基于多目标非劣解的混合粒子群算法来解决虚拟机的负载均衡问题。仿真实验结果表明,该算法相比一般粒子群算法,在负载均衡方面更加有效。

关键词: 虚拟机部署, 混合粒子群, 负载均衡

Abstract:

Load balancing technology is always the important part of cloud resource management, load balancing should be used in management and maintenance of the data center, which can improve the efficiency of resource use, reduce the number of virtual machine migration effectively, avoid the system bottleneck. Most of the existing virtual machine deployment algorithms based on particle swarm integrate the multiple performance objective of the virtual machine into one target by weight assignment when calculating the fitness. Moreover, in the process of updating the position of particles, the method to approach the current optimal solution is very easy to make the final solution trap into the local optimum. In view of the above problems, a hybrid particle swarm optimization based on multi-objective non dominated solution is proposed to solve the load balancing problem of virtual machines. The simulation results show that the proposed algorithm is more effective than the general particle swarm algorithm in load balancing.

Key words: virtual machine deployment, hybrid particle swarm optimization, load balancing

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