基于改进量子粒子群算法的云计算资源调度

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

资源调度优化是云计算系统应用中的关键技术,针对标准量子粒子群优化算法收敛速度慢、求解效率低的缺陷,提出一种基于改进量子粒子群算法的云计算资源调度方法。首先在分析云计算资源调度研究现状的基础上,建立了相应的数学模型,然后采用量子粒子群优化算法对其进行求解,在求解过程中,对平均最优位置进行随机扰动,协助粒子逃离局部最优解,最后采用通过仿真实验对其性能进行分析。结果表明,该文方法可以有效提高云计算资源的利用率,保证它们之间负载均衡,具有较好的应用价值。

Resources scheduling is the key technology in the application of the cloud computing system. In view of the defects of slow convergence speed and low efficiency of the standard quantum particle swarm optimization algorithm,a cloud computing resource scheduling method based on the improved quantum particle swarm optimization is proposed. A mathematical model is established based on the analysis of the present situation of cloud computing resources scheduling. The quantum particle swarm optimization algorithm is used to solve the problem in which the average optimal position is randomly disturbed to help particles escape from the local optimal solution. The experiment is used to test and analyze its performance. The results show that the proposed method can effectivelyimprove the utilization of cloud computing resources,ensuring the load balance and good application value.