MURAL - Maynooth University Research Archive Library



    Imola: A decentralised learning-driven protocol for multi-hop White-Fi


    Facchi, N., Gringoli, F., Malone, David and Patras, Paul (2017) Imola: A decentralised learning-driven protocol for multi-hop White-Fi. Computer Communications, 105. pp. 157-168. ISSN 0140-3664

    [thumbnail of DM-Imola-2017.pdf]
    Preview
    Text
    DM-Imola-2017.pdf

    Download (1MB) | Preview

    Abstract

    In this paper we tackle the digital exclusion problem in developing and remote locations by proposing Imola, an inexpensive learning-driven access mechanism for multi-hop wireless networks that operate across TV white-spaces (TVWS). Stations running Imola only rely on passively acquired neighbourhood information to achieve scheduled-like operation in a decentralised way, without explicit synchronisation. Our design overcomes pathological circumstances such as hidden and exposed terminals that arise due to carrier sensing and are exceptionally problematic in low frequency bands. We present a prototype implementation of our proposal and conduct experiments in a real test bed, which confirms the practical feasibility of deploying our solution in mesh networks that build upon the IEEE 802.11af standard. Finally, the extensive system level simulations we perform demonstrate that Imola achieves up to 4× more throughput than the channel access protocol defined by the standard and reduces frame loss rate by up to 100%.
    Item Type: Article
    Additional Information: The research leading to these results has received funding from the European Commission grant no. H2020-645274 (EU WISHFUL project), was supported in part by a grant from Science Foundation Ireland (SFI), and co-funded under the European Regional Development Fund under grant no. 13/RC/2077.
    Keywords: Decentralised medium access; Reinforcement learning; Multi-hop White-Fi; IEEE 802.11af; Prototype implementation;
    Academic Unit: Faculty of Science and Engineering > Mathematics and Statistics
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 11645
    Identification Number: 10.1016/j.comcom.2016.12.015
    Depositing User: Dr. David Malone
    Date Deposited: 05 Nov 2019 17:37
    Journal or Publication Title: Computer Communications
    Publisher: Elsevier
    Refereed: Yes
    Funders: European Commission, Science Foundation Ireland (SFI), European Regional Development Fund
    Related URLs:
    URI: https://mu.eprints-hosting.org/id/eprint/11645
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

    Repository Staff Only (login required)

    Item control page
    Item control page

    Downloads

    Downloads per month over past year

    Origin of downloads