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 applications.However,the edge server is limit...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 applications.However,the edge server is limited with the computation/storage capacity,which causes a low cache hit.Cooperative edge caching jointing neighbor edge servers is regarded as a promising technique to improve cache hit and reduce congestion of the networks.Further,recommender systems can provide personalized content services to meet user’s requirements in the entertainment-oriented mobile networks.Therefore,we investigate the issue of joint cooperative edge caching and recommender systems to achieve additional cache gains by the soft caching framework.To measure the cache profits,the optimization problem is formulated as a 0-1 Integer Linear Programming(ILP),which is NP-hard.Specifically,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 it.Simulation results demonstrate that the proposed framework has superior performance in improving the QoE.展开更多
基金supported in part by National Key R&D Program of China under Grant Nos. 2018YFB2100100 and 2018YFF0214700National NSFC under Grant Nos. 61902044 and 62072060+4 种基金Chongqing Research Program of Basic Research and Frontier Technology under Grant No. CSTC2019-jcyjmsxmX0589Key Research Program of Chongqing Science and Technology Commission under Grant Nos. CSTC2017jcyjBX0025 and CSTC2019jscxzdztzxX0031Fundamental Research Funds for the Central Universities under Grant No.2020CDJQY-A022Chinese National Engineering Laboratory for Big Data System Computing TechnologyCanadian NSERC
文摘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 applications.However,the edge server is limited with the computation/storage capacity,which causes a low cache hit.Cooperative edge caching jointing neighbor edge servers is regarded as a promising technique to improve cache hit and reduce congestion of the networks.Further,recommender systems can provide personalized content services to meet user’s requirements in the entertainment-oriented mobile networks.Therefore,we investigate the issue of joint cooperative edge caching and recommender systems to achieve additional cache gains by the soft caching framework.To measure the cache profits,the optimization problem is formulated as a 0-1 Integer Linear Programming(ILP),which is NP-hard.Specifically,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 it.Simulation results demonstrate that the proposed framework has superior performance in improving the QoE.
