Wireless Sensor Networks are changing our lives by making all objects around us “smart” and thus creating an Internet-of-Things (IoT). Location information is indispensable for all these things to be really “smart”. GPS and some other hardware based techniques can provide good location information but GPS signal availability, cost, and energy consumption limit their adoption. Location information can also be estimated accurately without hardware support if accurate distance information between nodes is available. Many distance measurement techniques are being investigated. In this paper, a transitional region based distance estimation method for neighboring nodes is proposed. Inside the sender's transitional region, the receiver receives packets reversible to the distance to the sender. Intuitively, the further away, the lower chance to receive. Our mathematical analysis shows that the distance from sender is close to linearly related to receivers' packet reception ratio for most of the transitional region. Our simulation shows that our proposed approach is viable and is superior to RSSI based approach.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Transitional Region Based Distance Estimation for Wireless Sensor Networks


    Beteiligte:
    Liang, Chunchao (Autor:in) / Liu, Chang (Autor:in) / Pasko, Brian (Autor:in)


    Erscheinungsdatum :

    01.08.2018


    Format / Umfang :

    356501 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Analyzing the transitional region in low power wireless links

    Zuniga, M. / Krishnamachari, B. | IEEE | 2004


    Sensor selection algorithm based on weighted distance in wireless sensor networks tracking

    Hai, W. / Wei, Z. / Bin, T. | British Library Online Contents | 2008




    Estimation in Wireless Sensor Networks With Security Constraints

    Xiaoxi Guo / Leong, Alex S. / Dey, Subhrakanti | IEEE | 2017