基于改进型离散粒子群优化的云计算资源分配方案

发布时间：2018-04-30 07:50

本文选题：云计算 + 资源分配　；参考：《湘潭大学自然科学学报》2017年03期

【摘要】：针对云计算中资源有效分配的问题,提出一种基于改进型离散粒子群优化(IDPSO)算法的云资源分配方案.首先,将传统PSO算法中的运算进行离散化,使其能够应用于资源分配问题.然后,对传统PSO粒子位置更新公式中的惯性权重进行改进,根据当前粒子位置、局部最佳和全局最佳位置的适应度来确定这些权重系数,以此加快粒子的收敛速度.最后,将资源分配方案编码为一个二维粒子,利用IDPSO算法求解最优解.实验结果表明,该方案能够有效降低资源浪费率,具有可行性和有效性.
[Abstract]:To solve the problem of efficient resource allocation in cloud computing, a cloud resource allocation scheme based on improved discrete Particle Swarm Optimization (DPSO) algorithm is proposed. Firstly, the traditional PSO algorithm is discretized so that it can be applied to the resource allocation problem. Then, the inertial weights in the traditional PSO particle position updating formula are improved, and these weights are determined according to the fitness of the current particle position, the local optimum position and the global optimal position, so as to accelerate the convergence rate of the particle. Finally, the resource allocation scheme is coded as a two-dimensional particle, and the optimal solution is solved by IDPSO algorithm. The experimental results show that the proposed scheme can effectively reduce the waste rate of resources and is feasible and effective.
【作者单位】：赣南师范大学科技学院;江西理工大学应用科学学院;
【基金】：江西省教育厅科学技术研究项目(151574)
【分类号】：TP18;TP3

【相似文献】