Improved 3-dimensional DV-hop localization algorithm based on information of nearby nodes

Abstract

DV-Hop, a range-free localization algorithm, has been one of the most popular localization algorithm. It is easy and inexpensive to implement. Therefore, in the literature, many improved variants of this algorithm exist. However, poor location accuracy and higher power consumption by DV-Hop algorithm always open new avenues for research on this algorithm and makes it a favorite among the researchers. In this paper, we have proposed an Improved 3-Dimensional DV-Hop algorithm based on the information of nearby nodes (I3D-DVLAIN). In the algorithm, by calculating hopsize at the unknown nodes, we eliminate one communication among the nodes, which reduces power consumption in the network. The hopsize calculation and location estimation is done by using only the nearby anchor nodes, which minimizes the network usage and decreases the computational effort. For the selection of nearby anchor nodes, we introduce a new method. Further, for localization, a novel method is used for solving the system of distance equations that restricts propagation of inherent error in the distance and increases localization accuracy. Furthermore, by mathematically analyzing the propagation of error in solving the system of equations, we prove the superiority of I3D-DVLAIN over other compared algorithms. The results obtained through simulation and complexity analysis of the computation and communication further strengthens our observations about the superiority of the proposed algorithm.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

References

  1. 1.

    Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer Networks, 38(4), 393–422. https://doi.org/10.1016/S1389-1286(01)00302-4.

    Article  Google Scholar 

  2. 2.

    Boukerche, A., Oliveira, H. A. B. F., Nakamura, E. F., & Loureiro, A. A. F. (2008). Localization systems for wireless sensor networks. In A. Boukerche (Ed.), Algorithms and protocols for wireless sensor networks (pp. 307–340). New York: Wiley. https://doi.org/10.1002/9780470396360.ch11.

    Google Scholar 

  3. 3.

    Kumar, S., & Lobiyal, D. K. (2013). An advanced DV-Hop localization algorithm for wireless sensor networks. Wireless Personal Communications, 71(2), 1365–1385. https://doi.org/10.1007/s11277-012-0880-3.

    Article  Google Scholar 

  4. 4.

    Guo, Y., Han, Q., & Kang, X. (2019). Underwater sensor networks localization based on mobility-constrained beacon. Wireless Networks. https://doi.org/10.1007/s11276-019-02023-5.

    Article  Google Scholar 

  5. 5.

    Bulusu, N., Heidemann, J., & Estrin, D. (2000). GPS-less low-cost outdoor localization for very small devices. IEEE Personal Communications, 7(5), 28–34. https://doi.org/10.1109/98.878533.

    Article  Google Scholar 

  6. 6.

    Čapkun, S., Hamdi, M., & Hubaux, J. P. (2001). GPS-free positioning in mobile ad-hoc networks. Proceedings of the Hawaii International Conference on System Sciences. https://doi.org/10.1109/HICSS.2001.927202.

    Article  Google Scholar 

  7. 7.

    Hofmann-Wellenhof, B., & Lichtenegger, H. C. J. E. (2012). Global positioning system: Theory and practice. Berlin: Springer.

    Google Scholar 

  8. 8.

    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. https://doi.org/10.1007/s11235-011-9564-7.

    Article  Google Scholar 

  9. 9.

    Boukerche, A., Oliveira, H., Nakamura, E., & Loureiro, A. (2009). DV-Loc: A scalable localization protocol using Voronoi diagrams for wireless sensor networks. IEEE Wireless Communications, 16(2), 50–55. https://doi.org/10.1109/MWC.2009.4907560.

    Article  Google Scholar 

  10. 10.

    Chowdhury, T. J. S., Elkin, C., Devabhaktuni, V., Rawat, D. B., & Oluoch, J. (2016). Advances on localization techniques for wireless sensor networks: A survey. Computer Networks. https://doi.org/10.1016/j.comnet.2016.10.006.

    Article  Google Scholar 

  11. 11.

    Abd El Aziz, M. (2017). Source localization using TDOA and FDOA measurements based on modified cuckoo search algorithm. Wireless Networks, 23(2), 487–495. https://doi.org/10.1007/s11276-015-1158-y.

    Article  Google Scholar 

  12. 12.

    Oliveira, L. L., Oliveira, L. A., Silva, G. W. A., Timoteo, R. D. A., & Cunha, D. C. (2019). An RSS-based regression model for user equipment location in cellular networks using machine learning. Wireless Networks, 25(8), 4839–4848. https://doi.org/10.1007/s11276-018-1774-4.

    Article  Google Scholar 

  13. 13.

    Jin, R., Che, Z., Xu, H., Wang, Z., & Wang, L. (2015). An RSSI-based localization algorithm for outliers suppression in wireless sensor networks. Wireless Networks, 21(8), 2561–2569. https://doi.org/10.1007/s11276-015-0936-x.

    Article  Google Scholar 

  14. 14.

    Han, S., Lee, S., Lee, S., Park, J., & Park, S. (2010). Node distribution-based localization for large-scale wireless sensor networks. Wireless Networks, 16(5), 1389–1406. https://doi.org/10.1007/s11276-009-0210-1.

    Article  Google Scholar 

  15. 15.

    Boushaba, M., Hafid, A., & Benslimane, A. (2009). High accuracy localization method using AoA in sensor networks. Computer Networks, 53(18), 3076–3088. https://doi.org/10.1016/j.comnet.2009.07.015.

    Article  MATH  Google Scholar 

  16. 16.

    Li, C., Zhang, H., Hao, B., & Li, J. (2011). A survey on routing protocols for large-scale wireless sensor networks. Sensors, 11(4), 3498–3526. https://doi.org/10.3390/s110403498.

    Article  Google Scholar 

  17. 17.

    Cabero, J. M., Olabarrieta, I., Gil-López, S., del Ser, J., & Martín, J. L. (2014). Range-free localization algorithm based on connectivity and motion. Wireless Networks, 20(8), 2287–2305. https://doi.org/10.1007/s11276-014-0741-y.

    Article  Google Scholar 

  18. 18.

    Ma, D., Er, M. J., & Wang, B. (2010). Analysis of hop-count-based source-to-destination distance estimation in wireless sensor networks with applications in localization. IEEE Transactions on Vehicular Technology, 59(6), 2998–3011. https://doi.org/10.1109/TVT.2010.2048346.

    Article  Google Scholar 

  19. 19.

    Zhao, J., Zhao, Q., Li, Z., & Liu, Y. (2013). An improved weighted centroid localization algorithm based on difference of estimated distances for wireless sensor networks. Telecommunication Systems, 53(1), 25–31. https://doi.org/10.1007/s11235-013-9673-6.

    MathSciNet  Article  Google Scholar 

  20. 20.

    Xu, L., Wang, K., Jiang, Y., Yang, F., Du, Y., & Li, Q. (2011). A study on 2D and 3D weighted centroid localization algorithm in wireless sensor networks. In 2011 3rd international conference on advanced computer control, ICACC 2011 (Vol. 978, pp. 155–159). https://doi.org/10.1109/ICACC.2011.6016388.

  21. 21.

    Niculescu, D., & Nath, B. (2020). Ad hoc positioning system (APS). In GLOBECOM’01. IEEE global telecommunications conference (Cat. No.01CH37270) (Vol. 5, pp. 2926–2931). IEEE. https://doi.org/10.1109/GLOCOM.2001.965964.

  22. 22.

    Cheng, W. H., Li, J., & Li, H. (2012). An improved APIT location algorithm for wireless sensor networks. In J. Kacprzyk (Ed.), Advances in intelligent and soft computing, AISC (Vol. 139, pp. 113–119). Berlin: Springer. https://doi.org/10.1007/978-3-642-27951-5_17.

    Google Scholar 

  23. 23.

    Nagpal, R., Shrobe, H., & Bachrach, J. (2003). Organizing a global coordinate system from local information on an ad hoc sensor network. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2634, 333–348. https://doi.org/10.1007/3-540-36978-3_22.

    Article  MATH  Google Scholar 

  24. 24.

    Gui, L., Val, T., & Wei, A. (2011). Improving localization accuracy using selective 3-anchor DV-hop algorithm. IEEE Vehicular Technology Conference. https://doi.org/10.1109/VETECF.2011.6093011.

    Article  Google Scholar 

  25. 25.

    Kumar, S., & Lobiyal, D. K. (2017). Novel DV-Hop localization algorithm for wireless sensor networks. Telecommunication Systems, 64(3), 509–524. https://doi.org/10.1007/s11235-016-0189-8.

    Article  Google Scholar 

  26. 26.

    Hu, Y., & Li, X. (2013). An improvement of DV-Hop localization algorithm for wireless sensor networks. Telecommunication Systems, 53(1), 13–18. https://doi.org/10.1007/s11235-013-9671-8.

    Article  Google Scholar 

  27. 27.

    Zhao, L., Zhang, K., & Jia, Y. (2020). An improved localization algorithm based on DV-Hop. In J. Kacprzyk (Ed.), Advances in intelligent systems and computing, AISC (Vol. 1084, pp. 590–595). Berlin: Springer. https://doi.org/10.1007/978-3-030-34387-3_72.

    Google Scholar 

  28. 28.

    Cai, X., Wang, P., Du, L., Cui, Z., Zhang, W., & Chen, J. (2019). Multi-objective three-dimensional DV-Hop localization algorithm with NSGA-II. IEEE Sensors Journal, 19(21), 10003–10015. https://doi.org/10.1109/JSEN.2019.2927733.

    Article  Google Scholar 

  29. 29.

    Liu, G., Qian, Z., & Wang, X. (2019). An improved DV-Hop localization algorithm based on hop distances correction. China Communications, 16(6), 200–214. https://doi.org/10.23919/j.cc.2019.06.016.

    Article  Google Scholar 

  30. 30.

    Shen, S., Yang, B., Qian, K., She, Y., & Wang, W. (2019). On improved DV-hop localization algorithm for accurate node localization in wireless sensor networks. Chinese Journal of Electronics, 28(3), 658–666. https://doi.org/10.1049/cje.2019.03.013.

    Article  Google Scholar 

  31. 31.

    Kumar, S., & Lobiyal, D. K. (2014). Power efficient range-free localization algorithm for wireless sensor networks. Wireless Networks, 20(4), 681–694. https://doi.org/10.1007/s11276-013-0630-9.

    Article  Google Scholar 

  32. 32.

    Huang, Y., Luo, Y., Lai, H., & Huang, Y. (2019). A new localisation strategy with wireless sensor networks for tunnel space model. International Journal of High Performance Computing and Networking, 14(3), 249. https://doi.org/10.1504/ijhpcn.2019.102124.

    Article  Google Scholar 

  33. 33.

    Hadir, A., Zine-Dine, K., Bakhouya, M., & el Kafi, J. (2019). Novel localisation algorithms in wireless sensor networks. International Journal of Wireless and Mobile Computing, 16(1), 80–96. https://doi.org/10.1504/IJWMC.2019.097439.

    Article  Google Scholar 

  34. 34.

    Messous, S., Liouane, H., & Liouane, N. (2020). Improvement of DV-Hop localization algorithm for randomly deployed wireless sensor networks. Telecommunication Systems, 73(1), 75–86. https://doi.org/10.1007/s11235-019-00592-6.

    Article  Google Scholar 

  35. 35.

    Yu, K., Hedley, M., Sharp, I., Guo, Y. J., Sabale, K., Mini, S., et al. (2019). Node positioning in ad hoc wireless sensor networks. Wireless Networks, 5(1), 641–646. https://doi.org/10.1007/s11276-017-1538-6.

    Article  Google Scholar 

  36. 36.

    Sharp, I., & Yu, K. (2013). Enhanced least-squares positioning algorithm for indoor positioning. IEEE Transactions on Mobile Computing, 12(8), 1640–1650. https://doi.org/10.1109/TMC.2012.124.

    Article  Google Scholar 

  37. 37.

    Chen, X., & Zhang, B. (2014). 3D DV-hop localisation scheme based on particle swarm optimisation in wireless sensor networks. International Journal of Sensor Networks, 16(2), 100–105. https://doi.org/10.1504/IJSNET.2014.065869.

    Article  Google Scholar 

  38. 38.

    Kumar, A., Khosla, A., Saini, J. S., & Sidhu, S. S. (2015). Range-free 3D node localization in anisotropic wireless sensor networks. Applied Soft Computing Journal, 34, 438–448. https://doi.org/10.1016/j.asoc.2015.05.025.

    Article  Google Scholar 

  39. 39.

    Sharma, G., & Kumar, A. (2018). Fuzzy logic based 3D localization in wireless sensor networks using invasive weed and bacterial foraging optimization. Telecommunication Systems, 67(2), 149–162. https://doi.org/10.1007/s11235-017-0333-0.

    Article  Google Scholar 

  40. 40.

    Xu, Y., Zhuang, Y., & Gu, J. J. (2015). An improved 3D localization algorithm for the wireless sensor network. International Journal of Distributed Sensor Networks. https://doi.org/10.1155/2015/315714.

    Article  Google Scholar 

  41. 41.

    Kaur, A., Kumar, P., & Gupta, G. P. (2018). Nature inspired algorithm-based improved variants of DV-hop algorithm for randomly deployed 2D and 3D wireless sensor networks. Wireless Personal Communications, 101(1), 567–582. https://doi.org/10.1007/s11277-018-5704-7.

    Article  Google Scholar 

  42. 42.

    Gou, P., Liu, X., Sun, M., & He, B. (2020). A three-dimensional localization algorithm with multiple communication radii and hybrid intelligence. In Proceedings2020 international conference on intelligent transportation, big data and smart city, ICITBS 2020 (pp. 477–481). Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/ICITBS49701.2020.00103.

  43. 43.

    Sharma, G., & Kumar, A. (2018). Improved range-free localization for three-dimensional wireless sensor networks using genetic algorithm. Computers & Electrical Engineering, 72, 808–827. https://doi.org/10.1016/j.compeleceng.2017.12.036.

    Article  Google Scholar 

  44. 44.

    Kanwar, V., & Kumar, A. (2020). DV-Hop based localization methods for additionally deployed nodes in wireless sensor network using genetic algorithm. Journal of Ambient Intelligence and Humanized Computing. https://doi.org/10.1007/s12652-020-01907-1.

    Article  Google Scholar 

  45. 45.

    Yanfei, J., Kexin, Z., & Liquan, Z. (2020). Improved DV-Hop location algorithm based on mobile anchor node and modified hop count for wireless sensor network. Journal of Electrical and Computer Engineering, 2020, 1–9. https://doi.org/10.1155/2020/9275603.

    Article  Google Scholar 

  46. 46.

    Goyat, R., Rai, M. K., Kumar, G., Kim, T. H., & Saha, R. (2019). Energy efficient range-free localization algorithm for wireless sensor networks. Sensors. https://doi.org/10.3390/s19163603.

    Article  Google Scholar 

  47. 47.

    Taylor, J. R. (1997). An introduction to error analysis. Journal of the Acoustical Society of America, 101, 330. https://doi.org/10.1121/1.418074.

    Article  Google Scholar 

  48. 48.

    Wu, P., Su, S., Zuo, Z., Guo, X., Sun, B., & Wen, X. (2019). Time difference of arrival (TDOA) localization combining weighted least squares and firefly algorithm. Sensors. https://doi.org/10.3390/s19112554.

    Article  Google Scholar 

  49. 49.

    Zhao, W., Shao, F., Ye, S., & Zheng, W. (2018). LSRR-LA: An anisotropy-tolerant localization algorithm based on least square regularized regression for multi-hop wireless sensor networks. Sensors, 18(11), 3974. https://doi.org/10.3390/s18113974.

    Article  Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Shrawan Kumar.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Kaushik, A., Lobiyal, D.K. & Kumar, S. Improved 3-dimensional DV-hop localization algorithm based on information of nearby nodes. Wireless Netw (2021). https://doi.org/10.1007/s11276-020-02533-7

Download citation

Keywords

  • Wireless sensor networks (WSN)
  • Localization
  • DV-Hop
  • Nearby anchor nodes
  • Error propagation