BIROn - Birkbeck Institutional Research Online

    Popularity-based video caching techniques for cache-enabled networks: a survey

    Yoo, Paul (2019) Popularity-based video caching techniques for cache-enabled networks: a survey. IEEE Access 7 , pp. 27699-27719. ISSN 2169-3536.

    [img] Text
    Cache.pdf - Author's Accepted Manuscript
    Restricted to Repository staff only

    Download (1MB)
    [img]
    Preview
    Text
    26766.pdf - Published Version of Record

    Download (9MB) | Preview

    Abstract

    The proliferation of the mobile Internet and connected devices, which offer a variety of services at different levels of performance is a major challenge for the fifth generation of wireless networks and beyond. Innovative solutions are needed to leverage recent advances in machine storage/memory, context awareness, and edge computing. Cache-enabled networks and techniques such as edge caching are envisioned to reduce content delivery times and traffic congestion in wireless networks. Only a few contents are popular, accounting for the majority of viewers, so caching them reduces the latency and download time. However, given the dynamic nature of user behavior, the integration of popularity prediction into caching is of paramount importance to better network utilization and user satisfaction. In this paper, we first present an overview of caching in wireless networks and then provide a detailed comparison of traditional and popularity-based caching. We discuss the attributes of videos and the evaluation criteria of caching policies. We summarize some of the recent work on proactive caching, focusing on prediction strategies. Finally, we provide insight into the potential opportunities and challenges as well as some open research problems enable the realization of efficient deployment of popularity-based caching as part of the next-generation mobile networks.

    Metadata

    Item Type: Article
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Depositing User: Paul Yoo
    Date Deposited: 20 Mar 2019 17:22
    Last Modified: 20 Oct 2019 22:43
    URI: http://eprints.bbk.ac.uk/id/eprint/26766

    Statistics

    Downloads
    Activity Overview
    90Downloads
    24Hits

    Additional statistics are available via IRStats2.

    Archive Staff Only (login required)

    Edit/View Item Edit/View Item