Decentralized Collaborative Caching in Ultra-Dense Networks
IEEE WIRELESS COMMUNICATIONS LETTERS(2024)
Abstract
This letter investigates the decentralized collaborative edge caching problem in ultra-dense networks (UDNs) via sharing observed information. Different from existing works which assume that each small base station (SBS) exchanges information with fixed neighboring SBSs, this letter considers that each SBS adaptively selects a set of helpful SBSs to exchange information for caching coordination. To realize the caching coordination in real time, we use bandit learning to select helpful information and adopt an actor-critic framework to learn the caching policy from its selected SBSs. In particular, each SBS makes its caching decision via the actor network, and utilizes the critic network to evaluate the caching decision based on the exchanged information. Simulation results show that the proposed algorithm outperforms other benchmark algorithms with lower information exchange overhead. It is also interesting to find that exchanging information with more nearby SBSs may not help to improve the performance when the content popularity is heterogeneously distributed in different SBSs' regions.
MoreTranslated text
Key words
Reliability,Information exchange,Delays,Collaboration,Ultra-dense networks,Schedules,Real-time systems,Decentralized edge caching,information exchange,deep reinforcement learning
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined