Distributed Learning-Based Cache Replacement in Collaborative Edge Networks

作     者：Sun, Zhenfeng Nakhai, Mohammad Reza 

作者机构：Kings Coll London Dept Engn London WC2R 2LS England 

出 版 物：《IEEE COMMUNICATIONS LETTERS》 (IEEE通讯快报)

年 卷 期：2021年第25卷第8期

页      面：2669-2672页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 

主　　题：Collaboration Quality of experience Base stations Optimization Cloud computing Libraries Heuristic algorithms Collaborative edge network distributed content caching Thompson sampling 

摘      要：In this letter, distributed content caching is considered in a collaborative edge caching system where a central infostation broadcasts information about the content migration to all edge nodes. Each edge node is equipped with a small base station for fetching the requested contents from its neighbouring edge nodes and with a storage unit for caching the contents. To achieve efficient content caching and collaboration, an online decision-making problem of maximizing the cache-hit-ratio whilst ensuring the end users quality-of-experience (QoE) is formulated. Furthermore, it is assumed that the content popularity knowledge is not available in advance and has to be leaned regularly over time in an online manner. To this end, we propose a distributed online content-popularity leaning algorithm based on Thompson sampling for updating the cache storage units in real-time. Simulation results demonstrate that the proposed algorithm outperforms the benchmarks in terms of the cache-hit-ratio and QoE in the long run.