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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.

Keywords
Probability Model Estimating Distance Wireless Sensor Networks
Published
2012-10-10
http://dx.doi.org/10.1007/978-3-642-29154-8_39
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