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Energy-Aware Topology Control Strategy for Human-Centric Wireless Sensor Networks

  • Datos identificativos

    Identificador: PC:633
    Handle: http://hdl.handle.net/20.500.11797/PC633
  • Autores:

    Meseguer, R.
    Molina, C.
    Ochoa, S.
    Santos, R.
  • Otros:

    Autor según el artículo: Meseguer, R. Molina, C. Ochoa, S. Santos, R.
    Departamento: Enginyeria Informàtica i Matemàtiques
    Resumen: The adoption of mobile and ubiquitous solutions that involve participatory or opportunistic sensing increases every day. This situation has highlighted the relevance of optimizing the energy consumption of these solutions, because their operation depends on the devices¿ battery lifetimes. This article presents a study that intends to understand how the prediction of topology control messages in human-centric wireless sensor networks can be used to help reduce the energy consumption of the participating devices. In order to do that, five research questions have been defined and a study based on simulations was conducted to answer these questions. The obtained results help identify suitable mobile computing scenarios where the prediction of topology control messages can be used to save energy of the network nodes. These results also allow estimating the percentage of energy saving that can be expected, according to the features of the work scenario and the participants behavior. Designers of mobile collaborative applications that involve participatory or opportunistic sensing, can take advantage of these findings to increase the autonomy of their solutions.
    Áreas temáticas: Human-centric wireless sensor network;
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Página final: 2643
    Volumen de revista: 14
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.mdpi.com/1424-8220/14/2/2619
    DOI del artículo: https://doi.org/10.3390/s140202619
    Entidad: Universitat Rovira i Virgili.
    Año de publicación de la revista: 2014
    Página inicial: 2619
  • Palabras clave:

    Human-centric wireless sensor network;
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