Cluster Computing

, Volume 22, Supplement 2, pp 3059–3067 | Cite as

Adaptive iteration localization algorithm based on RSSI in wireless sensor networks

  • Haijun ChenEmail author
  • Guanzheng Tan


Based on the maximum likelihood method, one novel adaptive iterative localization algorithm is proposed based on the steepest gradient descent. The algorithm regards the cost function as the target function, within the range of the gradient error, the target position can be localized. To improve the convergence speed and the localization accuracy of the algorithm, a searching algorithm of variable step based on sigmoid function is present. To demonstrate the efficiency of the proposed scheme, we carry out large numbers of experiments to learn the performance trend with various network settings. With all the simulations on localization criteria (localization accuracy and localization coverage), we make the comparison on the localization energy. Based on the simulations, the proposed algorithm has certain practical significance to meet the requirement of localization accuracy.


Adaptive iterative localization Wireless sensor networks RSSI 



This research is supported by Natural Science Foundation of Hunan Province of China (No. 2016JJ4045) and Educational Commission of Hunan Province of China (No. 17A114). We thank National Supercomputing Center in Changsha for providing with technical support of this research.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no competing interests.


  1. 1.
    Chong, C.-Y., Kumar, S.P.: Sensor networks evolution, opportunities and challenges. Proc IEEE 91(8), 1247–1256 (2003)Google Scholar
  2. 2.
    Antonio, C., Stefano, C., De, S., et al.: GPS free coordinate assignment and routing in wireless sensor networks [J]. In: IEEE International Conference on Computer Communications, vol. 15(6), p. 150 (2005)Google Scholar
  3. 3.
    Polastre, J., Szewczyk, R., Mainwaring, A., et al.: Analysis of wireless sensor networks for habitat monitoring. Wirel. Sens. Netw. 1(18), 399–423 (2004)Google Scholar
  4. 4.
    Zhen, H., Dongbing, G., Song, Z., et al.: Localization in wireless sensor networks using a mobile anchor node [J]. Comput. Soc. IEEE 26(7), 602–607 (2008)Google Scholar
  5. 5.
    Vieira, M.A.M., Coelho, C.N., da Silva, Jr.: Survey on wireless sensor network devices. In: Proceeding ETFA 03 IEEE Conference on Emerging Technologies and Factory Automation 2003, vol. 1(1), pp. 537–544 (2003)Google Scholar
  6. 6.
    Luanyuan, Li, Chunlin, Liu: A Qos multicast routing protocol for ad-hoc networks. IEEE ITCC 1(4), 609–614 (2005)Google Scholar
  7. 7.
    Pathirana, P.N.: Location based power control for energy critical sensors in a disconnected network. In: IEEE International Conference on Industrial Informatics, vol. 16(18), pp. 653–658 (2006)Google Scholar
  8. 8.
    Yanchao, Z., Wei, L., Wenjing, L., et al.: Location-based compromise-tolerant security mechanisms for wireless sensor networks. IEEE J. Sel. Areas Commun. 24(2), 247–260 (2006)Google Scholar
  9. 9.
    Das S.M., Pucha H., Hu Y.C.: Performance comparison of scalable location services for geographic ad hoc routing. In: 24th Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 2(1), pp. 1228–1239 (2005)Google Scholar
  10. 10.
    Sundar, S., Sanjay, S.: Geographic routing with limited information in sensor networks. Infromation processing in sensor networks. IEEE Trans. Inf. Theory 56(09), 4506–4519 (2010)Google Scholar
  11. 11.
    Hong, Bo, Viktor, K.: Maximum life time data sensing and extraction in energy Constrained networked sensor systems. J. Parallel Distrib. Comput. 66(4), 566–577 (2006)Google Scholar
  12. 12.
    Tubaishat, M., Madria, S.: Sensor networks an overview. IEEE Potentials 22(2), 20–23 (2003)Google Scholar
  13. 13.
    Bahl, P., Padmanabhan, V.: RADAR an in-building RF-based user location and tracking system. In: Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies, vol. 2(1), pp. 775–784 (2000)Google Scholar
  14. 14.
    Chow, Chi Yin, Mokbel, M.F., Tian, He: A privacy-preserving location monitoring system for wireless sensor networks. IEEE Trans. Mob. Comput. 10(1), 94–107 (2011)Google Scholar
  15. 15.
    Ahn, H., Rhee, S.-B.: Simulation of a RSSI-based indoor localization system using wireless sensor network. In: 2010 Proceedings of the 5th International Conference on Ubiquitous Information Technologies and Applications, vol. 12(16), pp. 1–4 (2010)Google Scholar
  16. 16.
    Myint, T.Z., Lynn, N., Ohtsuki, T.: Range-free localization algorithm using local expected hop length in wireless sensor network. In: 2010 International Symposium on Communications and Information Technologies vol. 10(26), pp. 356–361 (2010)Google Scholar
  17. 17.
    He, X., Xiao, Y.: Study on 3D node location algorithm for wireless sensor networks. In: Second International Conference on Mechanic Automation and Control Engineering, vol. 7(15), pp. 5269–5273 (2011)Google Scholar
  18. 18.
    You, Z., Meng, M.Q.-H., Liang, H., et al.: A localization algorithm in wireless sensor networks using a mobile beacon node. In: International Conference on Information Acquisition, vol. 7(11), pp. 420–426 (2007)Google Scholar
  19. 19.
    Priyantha, N.B., Chakraborty, A., Balakrishnan, H.: The cricket location-support system. In: Proceedings of 6th ACM International Conference on Mobile Computing and Networking, vol. 8(3), pp. 32–43 (2000)Google Scholar
  20. 20.
    He, T., Huang, C.D., Blum, B.M., et al: Range-free localization schemes in large scale sensor networks. In: 9th Annual International Conference on Mobile Computing and Networking, pp. 81–95 (2003)Google Scholar
  21. 21.
    Akyildiz, I.F., Su, W., Sankarasubramaniam, Y., et al.: Wireless sensor network A survey. Comput. Netw. 38(04), 393–422 (2003)Google Scholar
  22. 22.
    Hazas, M., War, A.: A novel broadband ultrasonic location system. Ubiquitous Comput. 9(9), 264–282 (2002)Google Scholar
  23. 23.
    Deb, B., Bhainagar, S., Nath, B.: Reliable information forwarding using multiple paths in sensor networks. 28th Annual IEEE Conference on Local Computer Networks, vol. 58(9), pp. 406–415 (2003)Google Scholar
  24. 24.
    Griod, L., Bychovskiy, V., Elson, J., et al.: Locating tiny sensors in time and space A case study. In: IEEE International Conference on Computer Design VLSI in Computers and Processors, vol. 10(2), pp. 214–219 (2002)Google Scholar
  25. 25.
    Capkun, S., Hamdi, M., Hubaux, J.P.: GPS-free positioning in mobile ad-hoc networks. In: Proceedings of the 34th Annual Hawaii International Conference on System Sciences, vol. 1(1), pp. 3390–3481 (2001)Google Scholar
  26. 26.
    Savides, A., Han, C.C., Srivastava, M.B.: Dynamic fine-grained localization in ad-hoc networks of sensors. In: Proceedings of the 7th Annual International Conference on Mobile Computing and Networking, vol. 7(1), pp. 166–179 (2001)Google Scholar
  27. 27.
    Rabaey, M., Ammer, M.J., da Silve, J.L., et al.: Picoradio supports ad hoc ultra-low power wireless networking. Computer 33(7), 42–48 (2008)Google Scholar
  28. 28.
    Wu, C.-H., Lee, K.-C., Chung, Y.-C.: A delaunay triangulation based method for wireless sensor network deployment. In: 12th International Conference on Parallel and Distributed Systems, vol. 1(1), pp. 12–15 (2006)Google Scholar
  29. 29.
    Niculescu, D., Nath, B.: Ad-Hoc Positioning System (APS), vol. 23(3), pp. 439–442 . Rutgers University Department of Computer Science, Piscataway (2001)Google Scholar

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© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of School of Information Science & EngineeringCentral South UniversityChangshaChina
  2. 2.Hunan University of CommerceChangshaChina

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