Articles producció científica> Enginyeria Informàtica i Matemàtiques

Tracking and predicting link quality in wireless community networks

  • Datos identificativos

    Identificador: imarina:5657903
    Autores:
    Millan PMolina CMedina EVega DMeseguer RBraem BBlondia C
    Resumen:
    © 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.
  • Otros:

    Autor según el artículo: Millan P; Molina C; Medina E; Vega D; Meseguer R; Braem B; Blondia C
    Departamento: Enginyeria Informàtica i Matemàtiques
    Autor/es de la URV: Millán Marco, Pedro
    Palabras clave: Time series analysis Link quality tracking Link quality prediction Community networks
    Resumen: © 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.
    Áreas temáticas: Software Hardware and architecture Computer networks and communications
    ISSN: 21619654
    Direcció de correo del autor: pere.millan@urv.cat
    Identificador del autor: 0000-0002-4132-7099
    Fecha de alta del registro: 2024-06-22
    Referencia al articulo segun fuente origial: International Conference On Wireless And Mobile Computing, Networking And Communications. 239-244
    Referencia 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 Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    DOI del artículo: 10.1109/WiMOB.2014.6962177
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2014
    Tipo de publicación: Proceedings Paper
  • Palabras clave:

    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
  • Documentos:

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