Localization Control to Locate Mobile Sensors

  • Buddhadeb Sau
  • Srabani Mukhopadhyaya
  • Krishnendu Mukhopadhyaya
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4317)


Localization is an important issue for Wireless Sensor Networks in a wireless sensor network. A mobile sensor may change its position rapidly and thus require localization calls frequently. It is important to control the number of localization calls, as it is rather expensive. The existing schemes for reducing the frequency of localization calls for mobile sensors uses the technique of extrapolation which involves simple arithmetic calculations. We propose a technique to control the localization that gives much better result. The proposed method involves very low arithmetic computation overheads. We find analytical expressions for the estimated error if the rate of localizations is specified. Simulation studies are carried out to compare the performances of the proposed method with the methods proposed by Tilak et al.


Wireless sensor network localization mobility localization control target tracking 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Akyldiz, I.F., Su, W., Sankarasubramaniam, Y., Cayh’ci, E.: Wh’eless Sensor Networks: A Survey. Computer Networks 38(4), 393–422 (2002)CrossRefGoogle Scholar
  2. 2.
    Bulusu, N., Heidemann, J., Estrin, D.: GPS-less Low Cost Outdoor Localization For Very Small Devices. IEEE Personal Communications Magazine 7(5), 28–34 (2000)CrossRefGoogle Scholar
  3. 3.
    Meguerdichian, S., Koushanfar, F., Qu, G., Potkonjak, M.: Exposure In Wireless Ad-Hoc Sensor Networks. In: Proc. 7th Int. Conf. on Mobile Computing and Networking (MobiCom 2001), Rome, Italy, July 2001, pp. 139–150 (2001)Google Scholar
  4. 4.
    Raghunathan, V., Schurgers, C., Park, S., Srivastava, M.B.: Energy-aware wireless microsensor networks. IEEE Signal Processing Magazine 19(2), 40–50 (2002)CrossRefGoogle Scholar
  5. 5.
    Thrun, S., Fox, D., Burgard, W., Dellaert, F.: Robust Monte Carlo Localization for Mobile Robots. Artificial Intelligence (2001)Google Scholar
  6. 6.
    Juang, P., Oki, H., Wang, Y., Martonosi, M., Peh, L.S., Rubenstein, D.: Energy-efficient computing for wildlife tracking: design tradeoffs and early experiences with zebranet. In: Proc. of 10th Int. Conf. on Architectural Support for Programming Languages and Operating Systems (ASPLOS-X), pp. 96–107. ACM Press, New York (2002)CrossRefGoogle Scholar
  7. 7.
    Tilak, S., Kolar, V., Abu-Ghazaleh, N.B., Kang, K.D.: Dynamic Localization Control for Mobile Sensor Networks. In: IEEE Int. Workshop on Strategies for Energy Efficiency in Ad-Hoc and Sensor Networks (IEEEIWSEEASN 2005) (2005)Google Scholar
  8. 8.
    Bergamo, P., Mazzini, G.: Localization in Sensor Networks with Fading the Mobility. IEEE PIMRC (September 2002)Google Scholar
  9. 9.
    Hu, L., Evans, D.: Localization in Mobile Sensor Networks. In: MobiCom, September 26-October 1 (2004)Google Scholar
  10. 10.
    Bettstetter, C., Wagner, C.: The spatial node distribution of the random waypoint mobility model. In: Proceedings of German Workshop on Mobile Ad Hoc networks (WMAN), March 2002, Ulm, Germany (2002)Google Scholar
  11. 11.
    Network Simulator:

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Buddhadeb Sau
    • 1
  • Srabani Mukhopadhyaya
    • 2
  • Krishnendu Mukhopadhyaya
    • 3
  1. 1.Dept. of Maths.Jadavpur UniversityKolkataIndia
  2. 2.BIT MesraKolkataIndia
  3. 3.ACMUIndian Statistical InstituteKolkataIndia

Personalised recommendations