基于遗传算法的移动应用缓存迁移优化方法研究  

Research on optimization method of mobile application cache migration based on genetic algorithm

作　　者：郑志娴[1] 张福泉 ZHENG Zhi-xian;ZHANG Fu-quan(College of Information and Intelligent Transportation,Fujian Chuanzheng Communications College,Fuzhou 350007,China;College of Computer and Control Engineering,Minjiang University,Fuzhou 350108,China)

机构地区：[1]福建船政交通职业学院信息与智慧交通学院,福州350007 [2]闽江学院计算机与控制工程学院,福州350108

出　　处：《齐齐哈尔大学学报（自然科学版）》2023年第1期20-25,30,共7页Journal of Qiqihar University(Natural Science Edition)

基　　金：福建省中青年教师教育科研项目“面向移动应用跨平台开发框架的研究与实现”(JAT210719);福建省中青年教师教育科研项目“基于多模态数据融合的行人重识别研究”(JAT210704)。

摘　　要：面对用户提出越来越多的请求任务,本地服务器面临巨大的压力,导致应用缓存任务队列越来越长,出现了严重的拥塞问题。针对这种情况,将移动应用缓存任务迁移到边缘节点成为有效解决途径,由此提出一种基于遗传算法的移动应用缓存迁移优化方法。该研究在系统模型的假设条件设定的前提下,以时延和能耗为目标,构建多目标函数模型并设置两类约束条件。利用遗传算法求解模型最优解,得出移动应用缓存迁移优化方案。结果表明,利用该遗传算法求解的移动应用缓存迁移方案应用下,与其他算法相比时延和能耗均达到最低值,分别为16.34 s和37.85 J,证明了所研究方法的有效性。In the face of more and more requests from users, the local server is under great pressure, which leads to an increasingly long queue of application cache tasks and serious congestion problems. In view of this situation, it is an effective solution to migrate the mobile application cache task to the edge node. Therefore, a mobile application cache migration optimization method based on genetic algorithm is proposed. Under the premise of setting the assumptions of the system model, the research constructs a multi-objective function model with the goal of time delay and energy consumption and sets two kinds of constraints. Genetic algorithm is used to solve the optimal solution of the model,and the mobile application cache migration optimization scheme is obtained. The results show that the delay and energy consumption of the mobile application cache migration scheme solved by genetic algorithm reach the lowest value compared with other algorithms, which are 16.34 s and 37.85 J respectively, which proves the effectiveness of the research method.

关 键 词：遗传算法 移动应用缓存任务 时延 能耗 约束条件 迁移优化方法 

分 类 号：TN929.53[电子电信—通信与信息系统]