Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : J Iswariya  unnamed

Volume 03 Issue 06 2016

ISSN no:  2348-3121

Page no: 31-34

Abstract – Wireless Sensor network are self-organized and widely distributed networks which are composed of many battery-powered, low-cost wireless sensor nodes deployed in monitoring area. Although WSN’s have limitations in terms of memory and processors, the main constraint is battery problem which limits the lifetime of a network. This work describes using of controlled sink mobility sensor node to increase the lifetime of the sensor node with the support of triangulation localisation techniques in wireless sensor network(WSN) the results show that this localisation algorithm are efficient in improving network life time and providing significantly better lifetime to fixed sink case and random movement strategy.
Many approaches are involved to improve the power energy of network nodes like single hop, multi hop in controlled mobility based WSN without RSSI method. Then they approached with RSSI localization algorithm. The RSSI localization algorithm calculates the distance between nodes by measuring the signal strength but which are not accurate which provides inaccuracy of localization. However, the stability of RSSI is poor.This drawback should be expected to grow further with the proliferation of wireless sensor network applications. Now, proposed method uses the triangultion method to calculate the mobile nodes position. This improves energy efficiency of nodes.

KeywordsControl Mobility; RSSI; Traingulation 


  1. Akyildiz I. F. and I. H. Kasimoglu, “Wireless sensor and actor networks: research challenges,” Ad Hoc Networks, vol. 2, no. 4, pp. 351–367, 2004.
  2. Akyildiz, I. F, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless sensor networks: a survey,”Computer Networks, vol. 38, no. 4, pp. 393–422, 2005.
  3. Bachrach J. and C. Taylor, Localization in Sensor Networks, Massachusetts Institute of Technology, Cambridge, Mass, USA, 2004.
  4. Decuir J., “Two way time transfer based ranging,” Contribution to the IEEE 802. 15. 4a, Ranging Subcommittee, 2004.
  5. Ganesan .D, A. Cerpa, W. Ye, Y. Yu, J. Zhao, and D. Estrin, “Networking issues in wireless sensor networks,” Journal of Parallel and Distributed Computing, vol. 64, no. 7, pp. 799–814, 2004.
  6. Gowrishankar. S, T. G. Basavaraju, D. H. Manjaiah, and S. K. Sarkar, “Issues in wireless sensor networks,” in Proceeding of the World Congress on Engineering (WCE ’08), vol. 1, London, UK, July 2008.
  7. Hach R., “Symmetric double sided two-way ranging,” IEEE 802. 15. 4a, Ranging Subcommittee, 2005.
  8. Hach R., “Symmetric double sided two-way ranging,” IEEE 802. 15. 4a, Ranging Subcommittee, 2005.
  9. Hajlaoui N., I. Jabri, and M. B. Jemaa, “Experimental performance evaluation and frame aggregation enhancement in IEEE 802.11n WLANs,” International Journal of Communication Networks and Information Security, vol. 5, no. 1, pp. 48–58, 2013.
  10.  He T., C. Huang, B. M. Blum, J. A. Stankovic, and T. Abdelzaher, “Range-free localization schemes for large scale sensor networks,” in Proceedings of the 9th ACM Annual International Conference on Mobile Computing and Networking (MobiCom ’03), pp. 81–95, September 2003.
  11.  He T., C. Huang, B. M. Blum, J. A. Stankvic, and T. Abdelzaher, “Range free localization,” 2006.
  12.  Hu F. and X. Cao, Wireless Sensor Networks: Principles and Practice, Auerbach, Boca Raton, Fla, USA, 1st edition, 2010.
  13. Huang Q. and S. Selvakennedy, “A range-free localization algorithm for wireless sensor networks,” inProceedings of the IEEE 63rd Vehicular Technology Conference (VTC ’06), pp. 349–353, School of InformationTechnologies, Melbourne, Australia, July 2006.
  14. Kim E.and K. Kim, “Distance estimation with weighted least squares for mobile beacon-based localization in wireless sensor networks,” IEEE Signal Processing Letters, vol. 7, no. 6, pp. 559–562, 2010.
  15. Langendoen K. and N. Reijers, “Distributed localization in wireless sensor networks: a quantitative comparison,” Computer Networks, vol. 43, no. 4, pp. 499–518, 2003.
  16. Liu D., P. Ning, and W. Du, “Detecting malicious beacon nodes for secure location discovery in wireless sensor networks,” in Proceedings of the 25th IEEE International Conference on Distributed Computing Systems ((ICDCS ’05)), pp. 609–619, June 2005.
  17. Liu J., Y. Zhang, and F. Zao, “Robusr distributed node localization with error management,” inProceeding of the 7th ACM International Symposium on Mobile Ad-Hoc Networking and Computing (MobiHoc ’06), pp. 250–261, Florence, Italy, May 2006.
  18. Manzoor R., Energy efficient localization in wireless sensor networks using noisy measurements [M.S. thesis], 2010.
  19. Manzoor R., Energy efficient localization in wireless sensor networks using noisy measurements [M.S. thesis], 2010.