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Distributed Learning-based Cache Replacement in Collaborative Edge Networks

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Article number9435369
Pages (from-to)2669-2672
Number of pages4
Issue number8
Accepted/In press2021
PublishedAug 2021

Bibliographical note

Publisher Copyright: © 1997-2012 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

King's Authors


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.

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