PECS: Towards Personalized Edge Caching for Future Service-Centric Networks

作     者：Ming Yan Wenwen Li Chien Aun Chan Sen Bian Chih-Lin I André F. Gygax 

作者机构：School of Information and Telecommunications EngineeringCommunication University of ChinaBeijing 100024China Green Communication Research CenterChina Mobile Research InstituteBeijing 100053China Department of Electrical and Electronic EngineeringUniversity of MelbourneVictoria 3010Australia Department of FinanceFaculty of Business and EconomicsUniversity of MelbourneVictoria 3010Australia 

出 版 物：《China Communications》 (中国通信（英文版）)

年 卷 期：2019年第16卷第9期

页      面：93-106页

核心收录：

学科分类：0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 

基　　金：supported in part by the Fundamental Research Funds for the Central Universities of China (No. 2018CUCTJ078  CUC18A002-2) 

主　　题：big data data mining edge caching content network personalized edge caching 

摘      要：Mobile operators face the challenge of how to best design a service-centric network that can effectively process the rapidly increasing number of bandwidth-intensive user requests while providing a higher quality of experience(QoE). Existing content distribution networks(CDN) and mobile content distribution networks(mCDN) have both latency and throughput limitations due to being multiple network hops away from end-users. Here, we first propose a new Personalized Edge Caching System(PECS) architecture that employs big data analytics and mobile edge caching to provide personalized service access at the edge of the mobile network. Based on the proposed system architecture, the edge caching strategy based on user behavior and trajectory is analyzed. Employing our proposed PECS strategies, we use data mining algorithms to analyze the personalized trajectory and service usage patterns. Our findings provide guidance on how key technologies of PECS can be employed for current and future networks. Finally, we highlight the challenges associated with realizing such a system in 5G and beyond.