Telecommunication Systems

, Volume 50, Issue 3, pp 199–213

Range-free wireless sensor networks localization based on hop-count quantization

Article

Abstract

Localization is one of the most important research issues in Wireless Sensor Networks (WSNs). Recently, hop-count-based localization has been proposed as a cost-effective alternative to many expensive hardware-based localization algorithms. The basic idea of many hop-count-based localization algorithms is to seek a transformation from hop-count information to distance (e.g. DV-hop algorithm of Niculescu and Nath in Global Telecommunications Conference, vol. 5, pp. 2926–2931, 2001) or location (e.g. MDS algorithm of Shang et al. in International Symposium on Mobile Ad Hoc Networking and Computing, pp. 201–212, 2003) information. Traditionally, hop-counts between any pair of nodes can only take on integer value regardless of relative positions of nodes in the hop. We argue that by partitioning a node’s one-hop neighbor set into three disjoint subsets according to their hop-count values, the integer hop-count can be transformed into a real number accordingly. The transformed real number hop-count is then a more accurate representation of a node’s relative position than an integer-valued hop-count. In this paper, we present a novel algorithm termed HCQ (hop-count quantization) to perform such transformation. We then use the transformed real number hop-count to solve WSNs localization problems based on the MDS (multidimensional scaling) method. Simulation results show that the performance of the MDS algorithm using the real number hop-count outperforms those which use integer hop-count values.

Keywords

Hop-count quantization Wireless sensor networks Localization Multidimensional scaling 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Niculescu, D., & Nath, B. (2001). Ad hoc positioning system (aps). In Global telecommunications conference (Vol. 5, pp. 2926–2931). Google Scholar
  2. 2.
    Shang, Y., Ruml, W., Zhang, Y., & Fromherz, M. (2003). Localization from mere connectivity. In International symposium on mobile ad hoc networking and computing (pp. 201–212). Google Scholar
  3. 3.
    Akyildiz, I., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: a survey. Computer Networks, 39(4), 393–422. CrossRefGoogle Scholar
  4. 4.
    Shang, Y., & Ruml, W. (2004). Improved mds-based localization. In IEEE Infocom. Google Scholar
  5. 5.
    Shang, Y., Ruml, W., Zhang, Y., & Fromherz, M. (2004). Localization from connectivity in sensor networks. IEEE Transactions on Parallel and Distributed Systems, 15(11). Google Scholar
  6. 6.
    Bulusu, N., Heidemann, J., & Estrin, D. (2000). Gps-less low cost outdoor localization for very small devices. IEEE Personal Communication Magazine, 7(5). Google Scholar
  7. 7.
    Savarese, C., Rabay, J., & Langendoen, K. (2002). Robust positioning algorithms for distributed ad-hoc wireless sensor networks. In USENIX technical annual conference (pp. 317–327), June 2002. Google Scholar
  8. 8.
    Dulman, S., & Havinga, P. (2004). Statistically enhanced localization schemes for randomly deployed wireless sensor networks. In Intelligent sensors, sensor networks and information processing conference (pp. 403–410), December 2004. CrossRefGoogle Scholar
  9. 9.
    Wong, S. Y., Lim, J. G., Rao, S., & Seah, W. K. (2005). Density-aware hop-count localization (dhl) in wireless sensor networks with variable density. In Wireless communications and networking conference (Vol. 3, pp. 1848–1853), March 2005. New York: IEEE. CrossRefGoogle Scholar
  10. 10.
    Yang, S., Yi, J., & Cha, H. (2007). Hcrl: a hop-count-ratio based localization in wireless sensor networks. In IEEE communications society conference on sensor, mesh and ad hoc communications and networks (pp. 31–40), June 2007. CrossRefGoogle Scholar
  11. 11.
    Nagpal, R. (1999). Organizing a global coordinates system from local information on an amorphous computer (Tech. Rep.). Massachusetts Institute of Technology. Google Scholar
  12. 12.
    Nagpal, R., Strobe, H., & Bachrach, J. (2003). Organizing a global coordinate system from local information on an ad hoc sensor network. In IPSN. Google Scholar
  13. 13.
    He, T., Huang, C., Blum, B. M., Stankovic, J. A., & Abdelzaher, T. (2003). Range-free localization schemes for large scale sensor networks. In MobiCom. Google Scholar
  14. 14.
    Giorgetti, G., Gupta, S. K. S., & Manes, G. (2007). Wireless localization using self-organizing maps. In International conference on information processing in sensor networks (pp. 293–302). Google Scholar
  15. 15.
    Tran, D., & Nguyen, T. (2008). Localization in wireless sensor networks based on support vector machines. IEEE Transcation on Parallel and Distributed Systems, 19(7). Google Scholar
  16. 16.
    Bachrach, J., & Taylor, C. (2004). Localization in sensor networks (Tech. Rep.). Massachusetts Institute of Technology. Google Scholar
  17. 17.
    Wang, Y., Wang, X., Wang, D., & Agrawal, D. P. (2008). Range-free localization using expected hop progress in wireless sensor networks. IEEE Transactions on Parallel and Distributed Systems. Google Scholar
  18. 18.
    Doherty, L., Pister, K., & El Ghaoui, L. (2001). Convex position estimation in wireless sensor networks. In INFOCOM (Vol. 3, pp. 1655–1663), April 2001. Google Scholar
  19. 19.
    Biswas, P., & Ye, Y. (2004). Semidefinite programming for ad-hoc wireless sensor network localization. In International symposium on information processing in sensor networks. Google Scholar
  20. 20.
    Borg, I., & Groenen, P. (1997). Modern multidimensional scaling: theory and applications. Berlin: Springer. Google Scholar
  21. 21.
    Ji, X., & Zha, H. (2004). Sensor positioning in wireless ad-hoc sensor network using multidimensional scaling. In IEEE Infocom (Vol. 4). Google Scholar
  22. 22.
    Nhat, V., Vo, D., Challa, S., & Lee, S. (2008). Nonmetric mds for sensor localization. In International symposium on wireless pervasive computing. Google Scholar
  23. 23.
    Wu, H., Wang, C., & Tzeng, N. (2005). Novel self-configurable positioning technique for multihop wireless networks. IEEE/ACM Transactions on Networking, 13(3). Google Scholar
  24. 24.
    Lazos, L., & Poovendran, R. (2006). Hirloc: high-resolution robust localization for wireless sensor networks. IEEE Journal on Selected Areas in Communications, 24(2). Google Scholar
  25. 25.
    Kannan, A. A., Mao, G., & Vucetic, B. (2006). Simulated annealing based wireless sensor network localization. Journal of Computers, 1(2). Google Scholar
  26. 26.
    Kleinrock, L., & Silvester, J. (1978). Optimum transmission radii for packet radio networks or why six is a magic number. In IEEE national telecommunications conference. Google Scholar
  27. 27.
    Kuo, J., & Liao, W. Hop count distribution of multihop paths in wireless networks with arbitrary node density modeling and its applications. IEEE Transactions on Vehicular Technology, 56(4), 2007. Google Scholar
  28. 28.
    Bettstetter, C., & Eberspacher, J. (2003). Hop distances in homogeneous ad hoc networks. In Vehicular technology conference (Vol. 4, pp. 2286–2290). Google Scholar
  29. 29.
    Rubinstein, R., & Kroese, D. (2007). Simulation and the Monte Carlo method (2 ed.). New York: Wiley. CrossRefGoogle Scholar
  30. 30.
    Heath, M. (2001). Scientific computing—an introductory survey. New York: McGraw Hill. Google Scholar
  31. 31.
    Zhao, L., & Liang, Q. (2007).) Hop-distance estimation in wireless sensor networks with applications to resources allocation. EURASIP Journal on Wireless Communication and Networking. Google Scholar

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Di Ma
    • 1
  • Meng Joo Er
    • 1
  • Bang Wang
    • 2
  • Hock Beng Lim
    • 2
  1. 1.School of Electrical Electronic EngineeringNanyang Technological UniversitySingaporeSingapore
  2. 2.Intelligent System CenterNanyang Technological UniversitySingaporeSingapore

Personalised recommendations