摘要
为了实现云计算系统的负载均衡,最大化系统的吞吐量,提出了一种基于量子优化的云服务器负载均衡算法。该算法将量子优化的方法应用到粒子聚类中,提出了基于量子理论的无监督的聚类方法,类似于量子与势能变化的原理,通过粒子分布的势能函数来确定聚类中心。提出了服务器的任务调度策略,分析了系统处于最佳状态时最短的任务处理时间和最大联合吞吐量。最后结合量子优化原理实现了服务器的负载均衡。实验仿真结果表明,在提升服务器的负载均衡率和吞吐量优化上,该算法都具有较好的性能。
In order to achieve load balancing cloud computing system to maximize system throughput,this paper proposed cloud server load balancing algorithm based on quantum optimization. It applied the algorithm optimization method to quantum particle clustering,and proposed clustering method based on the principles of quantum theory unsupervised,to determine the cluster centers by the potential energy function,which was similar quantum particle distribution and the potential change. And proposing scheduling policy server,the task of analyzing the shortest processing time when the system was in the best condition and the maximum combined throughput. Finally,the principle of quantum optimization to be achieve load balancing server. Simulation results show that the upgrade server load balancing and throughput optimization,the algorithm has better performance.
出处
《计算机应用研究》
CSCD
北大核心
2015年第10期3128-3130,共3页
Application Research of Computers
基金
国家自然科学基金资助项目(U1204613)
关键词
云服务器
量子优化
负载均衡
任务调度策略
cloud server
quantum optimization
load balancing
task scheduling strategy
