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

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.

Key words: cloud computing, Particle Swarm Optimization(PSO) algorithm, resource schedule, CloudSim platform

中图分类号: 

• TP311