The Journal of Supercomputing

, Volume 69, Issue 1, pp 98–120 | Cite as

A localization algorithm for large scale mobile wireless sensor networks: a learning approach

  • Samira Afzal
  • Hamid Beigy


Localization is a crucial problem in wireless sensor networks and most of the localization algorithms given in the literature are non-adaptive and designed for fixed sensor networks. In this paper, we propose a learning based localization algorithm for mobile wireless sensor networks. By this technique, mobility in the network will be discovered by two crucial methods in the beacons: position and distance checks methods. These two methods help to have accurate localization and constrain communication just when it is necessary. The proposed method localizes the nodes based on connectivity information (hop count), which doesn’t need extra hardware and is cost efficient. The experimental results show that the proposed algorithm is scalable with a small set of beacons in large scale network with a high density of nodes. The given algorithm is fast and free from a pre-deployment requirement. The simulation results show the high performance of the proposed algorithm.


Wireless sensor network Support vector machine  Localization problem Learning algorithms 



The authors would like to thank the anonymous reviewers for their valuable comments and suggestions which improved the paper.


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  1. 1.Department of Computer EngineeringSharif University of TechnologyTehranIran
  2. 2.Department of Computer EngineeringSharif University of Technology, International Campus Kish IslandIran

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