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How Bad is Selfish Caching?

Published: 02 July 2019 Publication History

Abstract

Caching networks can reduce the routing costs of accessing contents by caching contents closer to users. However, cache nodes may belong to different entities and behave selfishly to maximize their own benefits, which often lead to performance degradation for the overall network. In this paper, we model the selfish behaviors of cache nodes as selfish caching games on arbitrary directed graphs with heterogeneous content popularity. We study the existence of a pure strategy Nash equilibrium (PSNE) in selfish caching games, and analyze its efficiency in terms of social welfare. We show that a PSNE does not always exist in arbitrary-topology caching networks. However, if the network does not have a mixed request loop, i.e., a directed loop in which each edge is traversed by at least one content request, we show that a PSNE always exists and can be found in polynomial time. We then show that the efficiency of Nash equilibria, captured by the price of anarchy (PoA), can be arbitrarily poor if we allow arbitrary content request patterns. However, when cache nodes have homogeneous request patterns, we show that the PoA is bounded even allowing arbitrary topologies. We further analyze the selfish caching games for cache nodes with limited computational capabilities, and show that an approximate PSNE exists with bounded PoA in certain cases of interest.

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    cover image ACM Conferences
    Mobihoc '19: Proceedings of the Twentieth ACM International Symposium on Mobile Ad Hoc Networking and Computing
    July 2019
    419 pages
    ISBN:9781450367646
    DOI:10.1145/3323679
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 02 July 2019

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    Author Tags

    1. Selfish caching games
    2. directed graphs
    3. price of anarchy

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    Funding Sources

    • research grants by Intel Corp.
    • General Research Fund from Hong Kong UGC
    • Presidential Fund from the Chinese University of Hong Kong, Shenzhen
    • National Science Foundation grant
    • research grants by Cisco Systems

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    Overall Acceptance Rate 296 of 1,843 submissions, 16%

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    • (2024)Coalitional FL: Coalition Formation and Selection in Federated Learning With Heterogeneous DataIEEE Transactions on Mobile Computing10.1109/TMC.2024.337532523:11(10494-10508)Online publication date: Nov-2024
    • (2023)Sampling-Based Caching for Low Latency in Distributed Coded Storage SystemsIEEE Transactions on Services Computing10.1109/TSC.2023.331831516:6(4275-4287)Online publication date: Nov-2023
    • (2023)Stable Service Caching in MECs of Hierarchical Service Markets With Uncertain Request RatesIEEE Transactions on Mobile Computing10.1109/TMC.2022.314987022:7(4279-4296)Online publication date: 1-Jul-2023
    • (2021)Selfish Caching Games on Directed GraphsIEEE/ACM Transactions on Networking10.1109/TNET.2020.304794029:2(709-722)Online publication date: Apr-2021
    • (2020)To Cache or Not to Cache: Stable Service Caching in Mobile Edge-Clouds of a Service Market2020 IEEE 40th International Conference on Distributed Computing Systems (ICDCS)10.1109/ICDCS47774.2020.00051(421-431)Online publication date: Nov-2020
    • (2020)Beyond Herd Immunity Against Strategic AttackersIEEE Access10.1109/ACCESS.2020.29836528(66365-66399)Online publication date: 2020

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