改进蚁群算法的云计算资源调度模型  

Resources Scheduling Model of Cloud Computing Based on Improved Ant Colony Algorithm

作　　者：邹燕飞[1] 刘淑英[1] 

机构地区：[1]咸阳师范学院计算机学院,陕西咸阳712000

出　　处：《吉林大学学报（理学版）》2017年第3期679-683,共5页Journal of Jilin University:Science Edition

基　　金：陕西省教育科学"十二五"规划项目(批准号:SGH140808);咸阳师范学院专项科研基金(批准号:13XSYK057)

摘　　要：针对当前云计算系统资源调度算法的资源利用率低、浪费严重等缺陷,提出一种基于改进蚁群算法的云计算资源调度优化模型,以获得更理想的云计算资源调度方案.首先对云计算资源调度的工作原理进行分析,建立云计算资源调度优化目标函数;然后利用蚁群优化算法模拟蚁群找到一条从起点到目的地的路径,即云计算资源调度目标函数的最优解,并结合目标函数对蚁群算法进行相应地改进;最后采用MATLAB2014R编程实现云计算资源调度优化模型.实验结果表明,该模型在短时间内可找到云计算资源调度的最优解,使资源利用率得到了改善.Aiming at the defects of low resource utilization rate and serious waste of the resource scheduling algorithm in cloud computing system, in order to obtain a more ideal cloud computing resource scheduling scheme, we proposed an improved ant colony optimization algorithm for cloud computing resource scheduling. Firstly, the working principle of cloud computing resource scheduling was analyzed, and the objective function of cloud computing resource scheduling optimization was established. Secondly, ant colony optimization algorithm was used to simulate the ant colony to find a path from the starting point to the destination, which was the optimal solution of objective function for cloud computing resource scheduling, and ant colony algorithm was improved according to the objective function. Finally, the MATLAB2014R programming was used to optimize resource scheduling model of cloud computing. The experimental results show that the proposed model can find the optimal solution of cloud computing resource scheduling in a short time, which can improve the resource utilization rate.

关 键 词：云计算系统 资源利用率 目标函数 蚁群算法 资源调度方案 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]