Articles producció científica> Enginyeria Informàtica i Matemàtiques

Tracking and predicting link quality in wireless community networks

  • Dades identificatives

    Identificador: imarina:5657903
    Handle: https://hdl.handle.net/20.500.11797/imarina5657903
    Autors:
    Millan PMolina CMedina EVega DMeseguer RBraem BBlondia C
    Resum:
    © 2014 IEEE. Community networks have emerged under the mottos of break the strings that are limiting you, don't buy the network, be the network or a free net for everyone is possible. Such networks create a measurable social impact as they provide to the community the right and opportunity of communication. As any other network that mixes wired and wireless links, the routing protocol must face several challenges that arise from the unreliable nature of the wireless medium. Link quality tracking helps the routing layer to select links that maximize the delivery rate and minimize traffic congestion. Moreover, link quality prediction has proved to be a technique that surpasses link quality tracking by foreseeing which links are more likely to change its quality. In this work, we focus on link quality prediction by means of a time series analysis. We apply this prediction technique in the routing layer of large-scale, distributed and decentralized networks. We demonstrate that this type of prediction achieves about a success probability of about 98% in both the short and long term.

  • Altres:

    Autor segons l'article: Millan P; Molina C; Medina E; Vega D; Meseguer R; Braem B; Blondia C
    Departament: Enginyeria Informàtica i Matemàtiques
    Autor/s de la URV: Millán Marco, Pedro
    Paraules clau: Time series analysis Link quality tracking Link quality prediction Community networks
    Resum: © 2014 IEEE. Community networks have emerged under the mottos of break the strings that are limiting you, don't buy the network, be the network or a free net for everyone is possible. Such networks create a measurable social impact as they provide to the community the right and opportunity of communication. As any other network that mixes wired and wireless links, the routing protocol must face several challenges that arise from the unreliable nature of the wireless medium. Link quality tracking helps the routing layer to select links that maximize the delivery rate and minimize traffic congestion. Moreover, link quality prediction has proved to be a technique that surpasses link quality tracking by foreseeing which links are more likely to change its quality. In this work, we focus on link quality prediction by means of a time series analysis. We apply this prediction technique in the routing layer of large-scale, distributed and decentralized networks. We demonstrate that this type of prediction achieves about a success probability of about 98% in both the short and long term.
    Àrees temàtiques: Software Hardware and architecture Computer networks and communications
    ISSN: 21619654
    Adreça de correu electrònic de l'autor: pere.millan@urv.cat
    Identificador de l'autor: 0000-0002-4132-7099
    Data d'alta del registre: 2024-06-22
    Referència a l'article segons font original: International Conference On Wireless And Mobile Computing, Networking And Communications. 239-244
    Referència de l'ítem segons les normes APA: Millan P; Molina C; Medina E; Vega D; Meseguer R; Braem B; Blondia C (2014). Tracking and predicting link quality in wireless community networks.
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2014
    Tipus de publicació: Proceedings Paper

  • Paraules clau:

    Computer Networks and Communications,Hardware and Architecture,Software
    Time series analysis
    Link quality tracking
    Link quality prediction
    Community networks
    Software
    Hardware and architecture
    Computer networks and communications

  • Documents:

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