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Delay-aware distributed caching scheme in edge network

Published: 24 November 2020 Publication History

Abstract

Edge caching has been emerged to avoid redundant data transmission to the cloud by caching the popular contents on edge networks. While existing solutions for edge caching have focused on optimizing the hit ratio at the edge, they did not address the burden on edge servers under a massive content requests circumstance. The massive amount of content requests can cause the waiting delay at the edge server, leading to an unexpected long content delivery delay. Therefore, in this paper, we propose the distributed edge caching scheme that can reduce the content delivery delay by considering the waiting delay at the edge server.

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X.Xu, C.Fen, S.Sha, T.Zhan and J.Loo. Proactive Edge Caching in Content-Centric Networks with Massive Dynamic Content Requests. IEEE Access 8 (Mar. 2020), 59906--59921.
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Cited By

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  • (2023)Stateless Q-learning algorithm for service caching in resource constrained edge environmentJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-023-00506-712:1Online publication date: 13-Sep-2023

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    cover image ACM Conferences
    CoNEXT '20: Proceedings of the 16th International Conference on emerging Networking EXperiments and Technologies
    November 2020
    585 pages
    ISBN:9781450379489
    DOI:10.1145/3386367
    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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    New York, NY, United States

    Publication History

    Published: 24 November 2020

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    Author Tags

    1. caching
    2. edge network
    3. massive content requests

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    • Research-article

    Funding Sources

    • National Research Foundation of Korea (NRF)

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    CoNEXT '20
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    Overall Acceptance Rate 198 of 789 submissions, 25%

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    • (2023)Stateless Q-learning algorithm for service caching in resource constrained edge environmentJournal of Cloud Computing: Advances, Systems and Applications10.1186/s13677-023-00506-712:1Online publication date: 13-Sep-2023

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