基于混沌蚁群算法的云计算应用优化研究

以改进蚁群算法应用在云计算中的不足为目的,讨论了蚁群算法基本原理和云计算下应用的缺陷.提出一种适合云计算的混沌蚁群改进算法,该算法通过Logistic映射产生混沌量,根据混沌遍历性和有界性对蚁群算法初始路径进行混沌初始化,同时加入混沌扰动调整算法信息素更新策略,改进了蚁群算法收敛速度慢和易陷入局部最优的缺点.最后通过CloudSim搭建仿真云环境并进行算法调度实验,通过横向对比标准蚁群算法和Dijkstra算法,证明混沌蚁群算法在执行效率和相对标准差等方面优于其他算法,更加适合于云计算环境.

A Research on Application Optimization of Cloud Computing Based on Chaos Ant Colony Algorithm

According to the characteristics of cloud computing, this paper discusses the basic principle of Ant Colony Algorithm and the application of cloud computing in the cloud environment resource scheduling. An Ant Colony Algorithm suitable for cloud computing is Put forward by Chaos, generated by logistic map chaotic,according to the amount of chaos to chaos initialization path and adding chaotic disturbance information to adjust the pheromone update strategy,an improvement of the limitation of the Ant Colony Algorithm is realized. Through the cloudsim, a cloud simulation environment is built and experiments are conducted. Through horizontal comparisionof the Ant Colony Algorithm and Dijkstra Algorithm,it is proved that the Chaos Ant Colony Algorithm is better than other algorithms in execution efficiency and the relative standard deviation,and thus more suitable for the cloud computing environment.