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基于MPSO算法的云计算资源调度策略
引用本文:刘万军,张孟华,郭文越.基于MPSO算法的云计算资源调度策略[J].计算机工程,2011,37(11):43-44,48.
作者姓名:刘万军  张孟华  郭文越
作者单位:1. 辽宁工程技术大学软件学院,辽宁,葫芦岛,125105
2. 辽宁工程技术大学电子与信息工程学院,辽宁,葫芦岛,125105
摘    要:针对云计算服务集群资源调度和负载平衡的优化问题,提出一种基于改进的粒子群优化算法的云计算资源调度策略。将动态多群体协作和变异粒子逆向飞行思想引入到粒子群优化算法中,从而控制全局搜索和局部搜索,尽量避免陷入局部最优。在CloudSim 平台进行模拟测试,结果表明,该调度策略有效且执行效率较高。

关 键 词:云计算  粒子群优化算法  资源调度  CloudSim  平台
收稿时间:2010-11-12

Cloud Computing Resource Schedule Strategy Based on MPSO Algorithm
LIU Wan-jun,ZHANG Meng-hua,GUO Wen-yue.Cloud Computing Resource Schedule Strategy Based on MPSO Algorithm[J].Computer Engineering,2011,37(11):43-44,48.
Authors:LIU Wan-jun  ZHANG Meng-hua  GUO Wen-yue
Affiliation:b(a.School of Software;b.College of Electronics and Information Engineering,Liaoning Technical University,Huludao 125105,China)
Abstract:Aiming at the optimization problem of the cloud computing's service cluster resource schedule and loading balance,this paper presents cloud computing resource schedule strategy based on Modified Particle Swarm Optimization(MPSO) algorithm.In order to control the global search and local search effectively,and to avoid falling into local optimal,it introduces dynamic multi-group collaboration and the reverse of the flight of mutation particles to the Particle Swarm Optimization(PSO) algorithm.By extending the cloud computing emulator CloudSim platform to test the simulation,the results show that this method is effective,and the operation efficiency is high.
Keywords:cloud computing  Particle Swarm Optimization(PSO) algorithm  resource schedule  CloudSim platform
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