一种求解云计算资源优化的改进蝙蝠算法  

A Novel Improved Bat Algorithm for Cloud Computing Resources Scheduling Optimization

作　　者：张燕[1] 顾才东[1] 

机构地区：[1]苏州市职业大学计算机工程学院,江苏苏州215104

出　　处：《科技通报》2014年第11期117-121,130,共6页Bulletin of Science and Technology

基　　金：苏州市科技计划项目(SGZ2013133)

摘　　要：为了最大限度优化云计算资源分配中的执行速度,平均响应时间和系统利用率,提出一种基于高斯差分变异蝙蝠算法(GDMBA)的云计算资源调度优化方法。首先引入高斯差分变异改进蝙蝠算法,避免蝙蝠个体陷入局部最优,改进后的算法加快了收敛速度,提高了收敛精度,然后采用GDMBA对资源调度进行寻优。仿真实验表明,GDMBA有效提高了算法性能,在云计算的资源调度中有效优化了云计算系统中的资源调度能力,提高了云计算资源的利用率。In order to best optimize the processing speed, average response time, and system efficiency of cloud computing＇s resource scheduling, a novel cloud resource scheduling optimization algorithm is proposed based on Gaussian Differential Mutation Bat Algorithm （GDMBA）. At first, Gaussian differential mutation is employed in the improved Bat algorithm to prevent individual bats from being trapped in localized optima, to accelerate the converging speed, and to enhance the converging accuracy. Afterwards, GDMBA is employed to optimize the resource dispatching. Simulated experiment shows that GDMBA has significantly improved the algorithm＇s overall performance, significantly optimized the resource allocation capability in cloud computing system, and remarkably raised the resource utilization efficiency of the cloud computing.

关 键 词：云计算 资源调度 蝙蝠算法 高斯变异 差分 

分 类 号：TP301.6[自动化与计算机技术—计算机系统结构]