膜计算改进粒子群优化算法的云资源调度

Cloud resource scheduling based on improved particle swarm optimization algorithm bymembrane computing

云计算环境下的资源合理调度是当前的研究热点，针对粒子群优化算法的不足，引入膜计算理论，提出一种基于膜计算改进粒子群优化算法的云资源调度算法（PSO—MC）。对云资源调度问题进行分析，建立云资源调度的目标函数，受到膜计算的启发，将粒子放入膜中，主膜内粒子进行精细化局部寻优，辅助膜内的粒子进行全局搜索，通过膜区域之间信息传递搜索结果，找到云资源调度问题的最优解，在CloudSim平台对算法进行仿真实验。结果表明，PSO—MC算法减少了任务的平均完成时间，提高了任务处理的效率，使云计算资源调度更加合理。

Resource scheduling in cloud computing environment is the current research focus, aiming at the shortage of tradi tional particle swarm optimization algorithm, it puts forward a cloud computing resource scheduling algorithm based on Particle Swarm Optimization algorithm and Membrane Computing theory （PSOMC）. The cloud resource scheduling problem is ana lyzed to get the cloud resource scheduling objective function, and the membrane system is used as framework, the particles in main membrane are used to the local optimization while the particles in auxiliary membrane mainly used for global search, search results are transferred among different membrane areas to find the cloud resource scheduling optimization solution, the simulation experiment is carried out in CloudSim. The results show that the proposed algorithm can reduce the average completion time of tasks to imnrovethe efficiency of task processing and can get more reasonable cloud computing resource scheduling result.