改进蚁群算法的云计算资源调度模型

发布时间：2018-01-05 18:07

本文关键词：改进蚁群算法的云计算资源调度模型　出处：《吉林大学学报(理学版)》2017年03期 　论文类型：期刊论文

【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.
[Abstract]:In view of the shortcomings of the current resource scheduling algorithm of cloud computing system, such as low resource utilization and serious waste, a cloud computing resource scheduling optimization model based on improved ant colony algorithm is proposed. In order to obtain a more ideal cloud computing resource scheduling scheme. Firstly, the working principle of cloud computing resource scheduling is analyzed, and the optimization objective function of cloud computing resource scheduling is established. Then the ant colony optimization algorithm is used to simulate the ant colony to find a path from the starting point to the destination, that is, the optimal solution of the target function of cloud computing resource scheduling, and the corresponding improvement of the ant colony algorithm combined with the objective function. Finally, MATLAB2014R programming is used to implement the cloud computing resource scheduling optimization model. The experimental results show that the model can find the optimal solution of cloud computing resource scheduling in a short time. Improved resource utilization.
【作者单位】：咸阳师范学院计算机学院;
【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)
【分类号】：TP18
【正文快照】： 云计算系统通过互联网把分散在不同区域的计算机、存储资源及一些终端设备如打印机等组织在一起,构成一台高性能的虚拟计算机,且具有较高的可靠性和灵活性.资源调度是云计算系统应用中的关键技术,设计性能优异的云计算资源调度模型是提高云计算系统资源利用率,避免资源浪费的

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