基于遗传蚁群算法的雾计算任务调度研究  

TASK SCHEDULING OF FOG COMPUTING BASED ON GENETIC ANT COLONY ALGORITHM

作　　者：王志刚 赵传信 Wang Zhigang;Zhao Chuanxin(School of Computer and Information,Anhui Normal University,Wuhu 241000,Anhui,China)

机构地区：[1]安徽师范大学计算机与信息学院,安徽芜湖241000

出　　处：《计算机应用与软件》2021年第8期291-297,共7页Computer Applications and Software

基　　金：国家自然科学基金面上项目(61871412);安徽省自然科学基金面上项目(1708085MF156)。

摘　　要：雾计算是部署在网络边缘的分布式系统,任务调度是雾计算中最重要的研究问题之一。针对雾计算环境下任务请求的合理调度问题,提出基于雾计算的遗传蚁群算法。算法前期利用遗传算法快速搜索能力避免蚁群算法前期搜索能力不足的问题,后期利用蚁群算法正反馈的特性进行解空间的搜索。仿真实验结果表明,该算法在CPU执行时间和分配内存方面优于传统的遗传算法和蚁群算法。Fog computing is a distributed system deployed on the edge of network,and task scheduling is one of the most important research issues in fog computing.A genetic ant colony algorithm based on fog computing is proposed to solve the problem of reasonable scheduling of user s task request in fog computing environment.In the early stage of this algorithm,the fast searching ability of genetic algorithm was used to avoid the problem of insufficient searching ability in the early stage of ant colony algorithm;in the later stage,the positive feedback characteristic of ant colony algorithm was used to search the solution space.Simulation results show that the algorithm is better than the traditional genetic algorithm and ant colony algorithm in CPU execution time and memory allocation.

关 键 词：遗传蚁群算法 雾计算式 任务调度 

分 类 号：TP3[自动化与计算机技术—计算机科学与技术]