基于竞价模式和智能迭代模式的边缘协作缓存算法研究  

Research on edge collaborative caching algorithm based on bidding mode and intelligent iteration mode

作　　者：李长敏琛 陆飞澎 王燕灵 LI Changminchen;LU Feipeng;WANG Yaning(Hangzhou Dianzi University,Hangzhou 310018,China;Hangzhou Newgrand Technology Co.,Ltd.,Hangzhou 310000,China)

机构地区：[1]杭州电子科技大学,浙江杭州310018 [2]杭州新中大科技股份有限公司,浙江杭州310000

出　　处：《现代电子技术》2024年第12期165-169,共5页Modern Electronics Technique

基　　金：浙江省科技计划项目(2023C01147);杭州市重大科技创新项目(2022AIZD0147)。

摘　　要：为了让用户更快地获取内容,提出一种基于竞价模式和智能迭代模式的综合式边缘协作缓存算法。在竞价算法部分,采用熵权法计算中间值、访问热度、缓存空间和内容热度的权重,并综合计算节点上内容的缓存分数,根据缓存分数进行缓存替换。在迭代算法部分,将网络空间划分为多个子域,每个子域通过混合遗传算法进行周期性计算,并得出子域内内容缓存方案。实验结果表明,所提算法在降低云服务器负载、减少请求平均跳数方面具有明显的优势。In order to enable users to obtain content faster,a comprehensive edge collaborative caching algorithm based on bidding mode and intelligent iteration mode is proposed.In the bidding algorithm section,the entropy weight method is used to calculate the weights of intermediary value,access heat,cache space,and content heat.The cache score of the content on the node is calculated comprehensively,and cache replacement is performed based on the cache score.In the iterative algorithm section,the network space is divided into multiple subdomains,each of which is periodically computed by means of the hybrid genetic algorithm,and a content caching scheme within the subdomains is obtained.The experimental results show that the proposed algorithm has significant advantages in reducing cloud server load and average hop count of requests.

关 键 词：边缘计算 协作缓存 竞价模式 智能迭代模式 熵权法 网络空间 混合遗传算法 

分 类 号：TN919-34[电子电信—通信与信息系统] TP311[电子电信—信息与通信工程]