基于改进粒子群算法的云计算任务调度策略

云计算环境下的任务调度方法是实现其高效计算的关键步骤,文章针对目前其时间效率低下的问题提出了一种基于改进的粒子群算法的任务调度方法,利用迭代选择算子引入粒子群来完成任务调度的优化。改进的粒子群算法(Improved particle swarm optimization,IPSO),提高了算法的优化能力,尽量避免陷入局部最优,收敛的效果更好从而减少任务调度时间开销。选择CloudSim仿真平台进行模拟,实验结果表明,该改进算法具有寻优能力强、时间耗时少的优点,可用于云计算问题中复杂调度优化的研究与应用。

The Task Scheduler Based on the Improved Particle Swarm Algorithm for the Cloud Computing System

Task scheduling method for cloud computing system is the key steps to achieve its high performance computing,the paper focuses on the low efficiency to propose a new task scheduling method based on improved Particle Swarm Optimization（PSO） algorithm,using the iterative selection operators to add into the particle swarm to finish task scheduling optimization.Improved Particle Swarm Optimization（IPSO）,improves algorithm for the capacity of optimization,as far as possible avoiding a local optimization,better effect of convergence task scheduling which time costs.The CloudSim simulation platform is selected for simulation,experimental results show that the algorithm has the advantage of optimization abilities,and takes less time,It can apply to the task schedule optimization for cloud computing problems in the research.