Articles producció científica> Enginyeria Informàtica i Matemàtiques

Time Series Analysis to Predict End-to-End Quality of Wireless Community Networks

  • Datos identificativos

    Identificador: imarina:5809701
    Autores:
    Milian, PereAliagas, CariesMolina, CarlosDimogerontakis, EmmanouilMeseguer, Roc
    Resumen:
    Community Networks have been around us for decades being initially deployed in the USA and Europe. They were designed by individuals to provide open and free “do it yourself” Internet access to other individuals in the same community and geographic area. In recent years, they have evolved as a viable solution to provide Internet access in developing countries and rural areas. Their social impact is measurable, as the community is provided with the right and opportunity of communication. Community networks combine wired and wireless links, and the nature of the wireless medium is unreliable. This poses several challenges to the routing protocol. For instance, Link-State routing protocols deal with End-to-End Quality tracking to select paths that maximize the delivery rate and minimize traffic congestion. In this work, we focused on End-to-End Quality prediction by means of time-series analysis to foresee which paths are more likely to change their quality. We show that it is possible to accurately predict End-to-End Quality with a small Mean Absolute Error in the routing layer of large-scale, distributed, and decentralized networks. In particular, we analyzed the path ETX behavior and properties to better identify the best prediction algorithm. We also analyzed the End-to-End Quality prediction accuracy some steps ahead in the future, as well as its dependency on the hour of the day. Besides, we quantified the computational cost of the prediction. Finally, we evaluated the impact of the usage for routing of our approach versus a simplified OLSR (ETX + Dijkstra) on an overloaded network.
  • Otros:

    Autor según el artículo: Milian, Pere; Aliagas, Caries; Molina, Carlos; Dimogerontakis, Emmanouil; Meseguer, Roc
    Departamento: Enginyeria Informàtica i Matemàtiques
    e-ISSN: 2079-9292
    Autor/es de la URV: Aliagas Castell, Carlos / Millán Marco, Pedro / Molina Clemente, Carlos María
    Palabras clave: Time-series analysis End-to-end quality prediction Community networks
    Resumen: Community Networks have been around us for decades being initially deployed in the USA and Europe. They were designed by individuals to provide open and free “do it yourself” Internet access to other individuals in the same community and geographic area. In recent years, they have evolved as a viable solution to provide Internet access in developing countries and rural areas. Their social impact is measurable, as the community is provided with the right and opportunity of communication. Community networks combine wired and wireless links, and the nature of the wireless medium is unreliable. This poses several challenges to the routing protocol. For instance, Link-State routing protocols deal with End-to-End Quality tracking to select paths that maximize the delivery rate and minimize traffic congestion. In this work, we focused on End-to-End Quality prediction by means of time-series analysis to foresee which paths are more likely to change their quality. We show that it is possible to accurately predict End-to-End Quality with a small Mean Absolute Error in the routing layer of large-scale, distributed, and decentralized networks. In particular, we analyzed the path ETX behavior and properties to better identify the best prediction algorithm. We also analyzed the End-to-End Quality prediction accuracy some steps ahead in the future, as well as its dependency on the hour of the day. Besides, we quantified the computational cost of the prediction. Finally, we evaluated the impact of the usage for routing of our approach versus a simplified OLSR (ETX + Dijkstra) on an overloaded network.
    Áreas temáticas: Signal processing Physics, applied Hardware and architecture Engineering, electrical & electronic Engenharias iv Electrical and electronic engineering Control and systems engineering Computer science, information systems Computer networks and communications
    Acceso a la licencia de uso: thttps://creativecommons.org/licenses/by/3.0/es/
    ISSN: 08834989
    Direcció de correo del autor: carlos.molina@urv.cat pere.millan@urv.cat carles.aliagas@urv.cat carles.aliagas@urv.cat
    Identificador del autor: 0000-0003-1955-0128 0000-0002-4132-7099
    Fecha de alta del registro: 2024-09-07
    Volumen de revista: 8
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.mdpi.com/2079-9292/8/5/578
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Electronics. 8 (5): 578-
    Referencia de l'ítem segons les normes APA: Milian, Pere; Aliagas, Caries; Molina, Carlos; Dimogerontakis, Emmanouil; Meseguer, Roc (2019). Time Series Analysis to Predict End-to-End Quality of Wireless Community Networks. Electronics, 8(5), 578-. DOI: 10.3390/electronics8050578
    DOI del artículo: 10.3390/electronics8050578
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2019
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Computer Networks and Communications,Computer Science, Information Systems,Control and Systems Engineering,Electrical and Electronic Engineering,Engineering, Electrical & Electronic,Hardware and Architecture,Physics, Applied,Signal Processing
    Time-series analysis
    End-to-end quality prediction
    Community networks
    Signal processing
    Physics, applied
    Hardware and architecture
    Engineering, electrical & electronic
    Engenharias iv
    Electrical and electronic engineering
    Control and systems engineering
    Computer science, information systems
    Computer networks and communications
  • Documentos:

  • Cerca a google

    Search to google scholar