RecCac:Recommendation-Empowered Cooperative Edge Caching for Internet of Things

作     者：HAN Suning LI Xiuhua SUN Chuan WANG Xiaofei Victor C.M.LEUNG HAN Suning;LI Xiuhua;SUN Chuan;WANG Xiaofei;Victor C.M.LEUNG

作者机构：Chongqing UniversityChongqing 400000China Tianjin UniversityTianjin 300072China Shenzhen UniversityShenzhen 518000China The University of British ColumbiaVancouver V6T 1Z4Canada 

出 版 物：《ZTE Communications》 (中兴通讯技术（英文版）)

年 卷 期：2021年第19卷第2期

页      面：2-10页

学科分类：1305[艺术学-设计学（可授艺术学、工学学位）] 080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 13[艺术学] 0809[工学-电子科学与技术（可授工学、理学学位）] 081104[工学-模式识别与智能系统] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 081001[工学-通信与信息系统] 081101[工学-控制理论与控制工程] 0811[工学-控制科学与工程] 

基　　金：supported in part by National Key R&D Program of China under Grant Nos. 2018YFB2100100 and 2018YFF0214700 National NSFC under Grant Nos. 61902044 and 62072060 Chongqing Research Program of Basic Research and Frontier Technology under Grant No. CSTC2019-jcyjmsxmX0589 Key Research Program of Chongqing Science and Technology Commission under Grant Nos. CSTC2017jcyjBX0025 and CSTC2019jscxzdztzxX0031 Fundamental Research Funds for the Central Universities under Grant No.2020CDJQY-A022 Chinese National Engineering Laboratory for Big Data System Computing Technology Canadian NSERC 

主　　题：IoT recommender systems cooperative edge caching soft caching 

摘      要：Edge caching is an emerging technology for supporting massive content access in mobile edge networks to address rapidly growing Internet of Things(IoT)services and content ***,the edge server is limited with the computation/storage capacity,which causes a low cache *** edge caching jointing neighbor edge servers is regarded as a promising technique to improve cache hit and reduce congestion of the ***,recommender systems can provide personalized content services to meet user’s requirements in the entertainment-oriented mobile ***,we investigate the issue of joint cooperative edge caching and recommender systems to achieve additional cache gains by the soft caching *** measure the cache profits,the optimization problem is formulated as a 0-1 Integer Linear Programming(ILP),which is ***,the method of processing content requests is defined as server actions,we determine the server actions to maximize the quality of experience(QoE).We propose a cachefriendly heuristic algorithm to solve *** results demonstrate that the proposed framework has superior performance in improving the QoE.