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Monte-Carlo Localization for Mobile Wireless Sensor Networks

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Mobile Ad-hoc and Sensor Networks (MSN 2006)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 4325))

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Abstract

Localization is crucial to many applications in wireless sensor networks. This article presents a range-free anchor-based localization algorithm for mobile wireless sensor networks that builds upon the Monte Carlo Localization algorithm. We improve the localization accuracy and efficiency by making better use of the information a sensor node gathers and by drawing the necessary location samples faster. Namely, we constrain the area from which samples are drawn by building a box that covers the region where anchors’ radio ranges overlap. Simulation results show that localization accuracy is improved by a minimum of 4% and by a maximum of 73%, on average 30%, for varying node speeds when considering nodes with knowledge of at least three anchors. The coverage is also strongly affected by speed and its improvement ranges from 3% to 55%, on average 22%. Finally, the processing time is reduced by 93% for a similar localization accuracy.

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Author information

Authors and Affiliations

  1. Delft University of Technology, The Netherlands

    Aline Baggio & Koen Langendoen

Authors
  1. Aline Baggio
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  2. Koen Langendoen
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Editor information

Editors and Affiliations

  1. Department of Computing, Hong Kong Polytechnic University, Kowloon, Hong Kong, China

    Jiannong Cao

  2. SITE, University of Ottawa, Ontario K1N 6N5, Canada and EECE, University of Birmingham, UK

    Ivan Stojmenovic

  3. Department of Computer Science, City University of Hong Kong,  

    Xiaohua Jia

  4. Department of Computer Science and Engineering, University of Texas at Arlington, P.O. Box 19015, 76019, Arlington, TX, USA

    Sajal K. Das

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© 2006 Springer-Verlag Berlin Heidelberg

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Baggio, A., Langendoen, K. (2006). Monte-Carlo Localization for Mobile Wireless Sensor Networks. In: Cao, J., Stojmenovic, I., Jia, X., Das, S.K. (eds) Mobile Ad-hoc and Sensor Networks. MSN 2006. Lecture Notes in Computer Science, vol 4325. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11943952_27

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  • DOI: https://doi.org/10.1007/11943952_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49932-9

  • Online ISBN: 978-3-540-49933-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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