Mobile and Ubiquitous Systems: Computing, Networking, and Services. 7th International ICST Conference, MobiQuitous 2010, Sydeny, Australia, December 6-9, 2010, Revised Selected Papers

Research Article

Probabilistic Distance Estimation in Wireless Sensor Networks

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  • @INPROCEEDINGS{10.1007/978-3-642-29154-8_39,
        author={Ge Huang and Fl\^{a}via Delicato and Paulo Pires and Albert Zomaya},
        title={Probabilistic Distance Estimation in Wireless Sensor Networks},
        proceedings={Mobile and Ubiquitous Systems: Computing, Networking, and Services. 7th International ICST Conference, MobiQuitous 2010, Sydeny, Australia, December 6-9, 2010, Revised Selected Papers},
        proceedings_a={MOBIQUITOUS},
        year={2012},
        month={10},
        keywords={Probability Model Estimating Distance Wireless Sensor Networks},
        doi={10.1007/978-3-642-29154-8_39}
    }
    
  • Ge Huang
    Flávia Delicato
    Paulo Pires
    Albert Zomaya
    Year: 2012
    Probabilistic Distance Estimation in Wireless Sensor Networks
    MOBIQUITOUS
    Springer
    DOI: 10.1007/978-3-642-29154-8_39
Ge Huang1, Flávia Delicato2, Paulo Pires2, Albert Zomaya1
  • 1: The University of Sydney
  • 2: Federal University of Rio Grande do Norte

Abstract

Since all anchor-based range-free localization algorithms require estimating the distance from an unknown node to an anchor node, such estimation is crucial for localizing nodes in environments as wireless sensor networks. We propose a new algorithm, named EDPM (Estimating Distance using a Probability Model), to estimate the distance from an unknown node to an anchor node. Simulation results show that EDPM reaches a slightly higher accuracy for distance estimation than the traditional algorithms for regularly shaped networks, but reveals significantly higher accuracy for irregularly shaped networks.