[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ Skip to main content
Springer Nature Link
Log in

Nature Inspired Algorithm-Based Improved Variants of DV-Hop Algorithm for Randomly Deployed 2D and 3D Wireless Sensor Networks

  • Published:
Wireless Personal Communications Aims and scope Submit manuscript

Abstract

Localization is a significant challenge in the area of wireless sensor networks (WSNs). Distance Vector Hop (DV-Hop) algorithm is most preferable algorithm due to its low cost, distributed nature, and its feasibility for all kinds of sensor networks, but it suffers from high localization error. In order to reduce the problem of high localization error for 2-dimensional and 3-dimensional WSNs, two Nature Inspired Algorithm based improved variants have been proposed. The first one uses Grey-Wolf optimization (GWO-DV-Hop) to identify a better estimate of average distance per hop and second one, a weighted Grey-Wolf optimization (Weighted GWO-DV-Hop), finds average distance per hop as computed by each beacon node using grey wolf algorithm and then, a weighted approach is applied by each node to get weighted average distance per hop (weights based on distance from each beacon) so as to consider impact of all types of beacons. The results prove the superiority of proposed algorithms over traditional DV-Hop in terms of localization error.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
£29.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price includes VAT (United Kingdom)

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11

Similar content being viewed by others

References

  1. Rawat, P., Singh, K. D., Chaouchi, H., & Bonnin, J. M. (2014). Wireless sensor networks: A survey on recent developments and potential synergies. The Journal of Supercomputing, 68(1), 1–48.

    Article  Google Scholar 

  2. Kaur, A., Kumar, P., & Gupta, G. P. (2017). A weighted centroid localization algorithm for randomly deployed wireless sensor networks. Journal of King Saud University-Computer and Information Sciences https://doi.org/10.1016/j.jksuci.2017.01.007.

    Google Scholar 

  3. Han, G., Xu, H., Duong, T. Q., Jiang, J., & Hara, T. (2013). Localization algorithms of wireless sensor networks: a survey. Telecommunication Systems, 52(4), 2419–2436.

    Article  Google Scholar 

  4. Zhao, J., Xi, W., He, Y., Liu, Y., Li, X., Mo, L., et al. (2013). Localization of wireless sensor networks in the wild: Pursuit of ranging quality. IEEE/ACM Transactions on Networking, 21(1), 311–323.

    Article  Google Scholar 

  5. Kunz, T., & Tatham, B. (2012). Localization in wireless sensor networks and anchor placement. Journal of Sensor and Actuator Networks, 1(1), 36–58.

    Article  Google Scholar 

  6. Girod, L., Bychobvskiy, V., Elson, J., & Estrin, D. (2002). Locating tiny sensors in time and space: a case study. In Proceedings of the 2002 IEEE international conference on computer design: VLSI in computers and processors, Los Alamitos (pp. 214–219).

  7. Harter, A., Hopper, A., Steggles, P., Ward, A., & Webster, P. (2002). The anatomy of a context-aware application. Wireless Networks, 8(2), 187–197.

    Article  MATH  Google Scholar 

  8. Cheng, X., Thaeler, A., Xue, G., & Chen, D. (2004). TPS: a time-based positioning scheme for outdoor wireless sensor networks. In Proceedings of the 23rd IEEE annual joint conference of the ieee computer and communications societies (INFOCOM’04), Hong Kong, China, March 2004 (pp. 2685–2696).

  9. Niculescu, D., & Nath, B. (2003). Ad hoc positioning system (APS) using AoA. In Twenty-second annual joint conference of the ieee computer and communications (Vol. 3, pp. 1734–1743). IEEE Societies.

  10. Bulusu, N., Heidemann, J., & Estrin, D. (2000). GPS-less low cost outdoor localization for very small devices. IEEE Personal Communications Magazine, 7(5), 28–34.

    Article  Google Scholar 

  11. Niculescu, D., & Nath, B. (2001). Ad hoc positioning system. In IEEE on global telecommunications conference (Vol. 5, pp. 2926–2931).

  12. Nagpal, R. (1999). Organizing a global coordinate system from local information on an amorphous computer. A.I. Memo1666, MIT A.I. Laboratory.

  13. Shang, Y., & Ruml, W. (2004). Improved MDS-based localization. In Proceedings of the IEEE Conference on Computer Communications (INFOCOM’04), Hong Kong, March 2004 (pp. 2640–2651).

  14. He, T., Huang, C. D., Blum, B. M., Stankovic, J. A., & Abdelzaher, T. (2003). Range-free localization schemes for large scale sensor netowrks. In Proceedings of the 9th the annual international conference on mobile computing and networking (pp. 81–95). San Diego, Calif, USA: ACM.

  15. Kaur, A., Gupta, G. P., & Kumar, P. (2017). A survey of recent developments in DV-Hop localization techniques for wireless sensor network. Journal of Telecommunication, Electronic and Computer Engineering, 9(2), 61–71.

    Google Scholar 

  16. Tomic, S., & Mezei, I. (2016). Improvements of DV-Hop localization algorithm for wireless sensor networks. Telecommunication Systems, 61(1), 93–106.

    Article  Google Scholar 

  17. Song, G., & Tam, D. (2015). Two novel DV-Hop localization algorithms for randomly deployed wireless sensor networks. International Journal of Distributed Sensor Networks, 11(7), 187670. https://doi.org/10.1155/2015/187670.

    Article  Google Scholar 

  18. Zhang, B., Ji, M., & Shan, L. (2012). A weighted centroid localization algorithm based on DV-hop for wireless sensor network. In Proceedings of the 8th international conference on wireless communications, networking and mobile computing, Shanghai, China (pp. 1–5).

  19. Fang, X. (2015). Improved DV-Hop positioning algorithm based on compensation coefficient. Journal of Software Engineering, 9(3), 650–657.

    Article  Google Scholar 

  20. Peng, B., & Li, L. (2015). An improved localization algorithm based on genetic algorithm in wireless sensor networks. Cognitive Neurodynamics, 9(2), 249–256.

    Article  Google Scholar 

  21. Gui, L., Val, T., Wei, A., & Dalce, R. (2015). Improvement of range-free localization technology by a novel DV-hop protocol in wireless sensor networks. Ad Hoc Networks, 24, 55–73.

    Article  Google Scholar 

  22. Shahzad, F., Sheltami, T. R., & Shakshuki, E. M. (2017). DV-maxHop: A fast and accurate range-free localization algorithm for anisotropic wireless networks. IEEE Transactions on Mobile Computing, 16(9), 2494–2505.

    Article  Google Scholar 

  23. Wang, F., Wang, C., Wang, Z., & Zhang, X. Y. (2015). A hybrid algorithm of GA+ simplex method in the WSN localization. International Journal of Distributed Sensor Networks, 11(7), 731894.

    Article  Google Scholar 

  24. Kumar, S., & Lobiyal, D. K. (2016). Novel DV-Hop localization algorithm for wireless sensor networks. Telecommunication Systems, 64(3), 509–524.

    Article  Google Scholar 

  25. Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46–61.

    Article  Google Scholar 

  26. Kaur, A., Kumar, P., & Gupta, G. P. (2016). A novel DV-Hop algorithm based on Gauss–Newton method. In IEEE international conference on parallel, distributed and grid computing (pp. 625–629).

  27. Keshtgary, M., Fasihy, M., & Ronaghi, Z. (2011). Performance evaluation of hop-based range-free localization methods in wireless sensor networks. ISRN Communications and Networking, 2011, 485486. https://doi.org/10.5402/2011/485486.

    Article  Google Scholar 

  28. Kulaib, A. R., Shubair, R. M., Al-Qutayri, M. A., & Ng, J. W. P. (2015). Improved DV-hop localization using node repositioning and clustering. In 2015 International conference on communications, signal processing, and their applications (ICCSPA) (pp. 1–6). IEEE.

  29. Ping, W. Z., & Chen, X. (2015). Node localization of wireless sensor networks based on DV-hop and Steffensen iterative method. International Journal of Future Generation Communication and Networking, 8(2), 1–8.

    Article  Google Scholar 

  30. Kumar, S., & Lobiyal, D. K. (2017). Novel DV-Hop localization algorithm for wireless sensor networks. Telecommunication Systems, 64(3), 509–524.

    Article  Google Scholar 

  31. Cota-Ruiz, J., Rosiles, J. G., Sifuentes, E., & Rivas-Perea, P. (2012). A low-complexity geometric bilateration method for localization in wireless sensor networks and its comparison with least-squares methods. Sensors, 12(1), 839–862.

    Article  Google Scholar 

  32. Kumar, S., & Lobiyal, D. K. (2013). Improvement over DV-Hop localization algorithm for wireless sensor networks. World Academy of Science, Engineering and Technology, 76(4), 282–293.

    Google Scholar 

  33. Ahmad, T., Li, X. J., & Seet, B. C. (2017). Parametric loop division for 3D localization in wireless sensor networks. Sensors, 17(7), 1697. https://doi.org/10.3390/s17071697.

    Article  Google Scholar 

  34. Keshtgary, M., Fasihy, M., & Ronaghi, Z. (2011). Performance evaluation of hop-based range-free localization methods in wireless sensor networks. ISRN Communications and Networking, 2011. https://doi.org/10.5402/2011/485486.

  35. Singh, M., & Khilar, P. M. (2016). An analytical geometric range free localization scheme based on mobile beacon points in wireless sensor network. Wireless Networks, 22(8), 2537–2550.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India

    Amanpreet Kaur & Padam Kumar

  2. Department of Information Technology, National Institute of Technology, Raipur, India

    Govind P. Gupta

Authors
  1. Amanpreet Kaur
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Padam Kumar
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Govind P. Gupta
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Amanpreet Kaur.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kaur, A., Kumar, P. & Gupta, G.P. Nature Inspired Algorithm-Based Improved Variants of DV-Hop Algorithm for Randomly Deployed 2D and 3D Wireless Sensor Networks. Wireless Pers Commun 101, 567–582 (2018). https://doi.org/10.1007/s11277-018-5704-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11277-018-5704-7

Keywords

Search

Navigation