云平台下多终端自适应负载均衡算法仿真  

Multi-Terminal Adaptive Load Balancing Algorithm Simulation under Cloud Platform

作　　者：耿强[1] 黄雪琴 GENG Qiang;HUANG Xue-qin(Networking Academy,Haikou College of Economics,Haikou 571127,China)

机构地区：[1]海口经济学院网络学院

出　　处：《计算机仿真》2019年第5期386-389,共4页Computer Simulation

基　　金：海南省自然科学基金项目资助(617175);海南省高等学校科学研究资助项目(Hnky2017-63);海南省高等学校科学研究资助项目(Hnky2018-82);海南省教育科学“十三五”规划2017年度课题成果(QJZ20171004)

摘　　要：针对当前方法在实现过程中由于云平台下终端设备较多导致网络资源负载不均衡,吞吐量较小、稳定性较差等问题,提出一种基于模糊循环迭代控制的多终端自适应负载均衡算法,通过构建多终端资源负载时间模型,对终端资源节点所完成终端任务的总时间进行计算,得到云平台下多终端资源负载均衡的目标函数;建立资源权重分配机制,控制多终端输出和输入之间的空间模糊距离,当正态分布概率迭代计算结果最小时,实现了多终端自适应负载均衡。仿真验证,采用方法能够提高平均吞吐量、降低平均延时、提高资源任务分配率和资源利用率,保证多终端自适应负载均衡的稳定性和灵活性。Aiming at the problem that the current method is unbalanced due to the large number of terminal devices under the cloud platform,the throughput is small and the stability is poor,a multi-terminal adaptive load balancing algorithm based on fuzzy loop iterative control is proposed.By constructing a multi-terminal resource load time model,the total time of the terminal tasks completed by the terminal resource node is calculated,and the objective function of multi-terminal resource load balancing under the cloud platform is obtained;the resource weight distribution mechanism is established,and the spatial fuzzy distance between the multi-terminal output and the inputs is controlled.When the iterative calculation result of the normal distribution probability is the smallest,the multi-terminal adaptive load balancing is realized.Simulations show that the proposed method can improve the average throughput,reduce the average delay,improve the resource task allocation rate and resource utilization,and ensure the stability and flexibility of multi-terminal adaptive load balancing.

关 键 词：多终端 负载均衡 平均吞吐量 平均延时 任务分配率 

分 类 号：TP311[自动化与计算机技术—计算机软件与理论]