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Range Free Localization for Three Dimensional Wireless Sensor Networks Using Multi Objective Particle Swarm Optimization

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Abstract

Accurate and fast localization of randomly deployed sensor nodes is needed for many applications in wireless sensor networks. Localization also benefits in recognizing the geographically area where an event took place. There is no meaning of any event information without the knowledge of its location coordinates. DV-Hop is one of the main range free localization technique, which estimates the position of nodes using distance vector. Particle swarm optimization is suitable for the localization issues because of its fast computing speed and high precision. To further reduce the positioning error, the traditional DV-Hop localization algorithm based on single objective optimization algorithm is converted into a multi objective optimization algorithm. In our proposed scheme, we have considered six different single objective functions and three different multi objective functions. In this paper, a multi objective particle swarm optimization based DV-Hop localization is proposed in 3-dimensional wireless sensor networks. The proposed functions has been evaluated on the basis of computation time, average localization error and localization error variance. The simulation results show that our proposed multi objective function performs better as compared to traditional single objective function.

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References

  1. Cortez-González, J., Ruiz-Ibarra, E., Espinoza-Ruiz, A., Castro, L. A., & Mass-Sanchez, J. (2016). Weighted hyperbolic DV-hop positioning node localization algorithm in WSNs. Wireless Personal Communications, 96(4), 5011–5033. https://doi.org/10.1007/s11277-016-3727-5.

    Article  Google Scholar 

  2. Gao, W., Ge, Y., Wang, S., Li, Y., Lou, K., Jiang, M., et al. (2017). Improved DV-Hop Localization Algorithm Based on Anchor Weight and Distance Compensation in Wireless Sensor Network. International Journal of Signal Processing, Image Processing and Pattern Recognition, 9(12), 167–176. https://doi.org/10.14257/ijsip.2016.9.12.16.

    Article  Google Scholar 

  3. Gui, L., Zhang, X., Ding, Q., Shu, F., & Wei, A. (2017). Reference anchor selection and global optimized solution for DV-hop localization in wireless sensor Networks. Wireless Personal Communications, 96(4), 5995–6005. https://doi.org/10.1007/s11277-017-4459-x.

    Article  Google Scholar 

  4. Gupta, V., & Singh, B. (2018). Study of range free centroid based localization algorithm and its improvement using particle swarm optimization for wireless sensor networks under log normal shadowing. International Journal of Information Technology, 1, 1. https://doi.org/10.1007/s41870-018-0201-5.

    Article  Google Scholar 

  5. Kanwar, V., & Kumar, A. (2020a). DV-Hop-based range-free localization algorithm for wireless sensor network using runner-root optimization. Journal of Supercomputing, 1, 0123456789. https://doi.org/10.1007/s11227-020-03385-w.

    Article  Google Scholar 

  6. Kanwar, V., & Kumar, A. (2020b). DV—Hop based localization methods for additionally deployed nodes in wireless sensor network using genetic algorithm. Journal of Ambient Intelligence and Humanized Computing, 1, 0123456789. https://doi.org/10.1007/s12652-020-01907-1.

    Article  Google Scholar 

  7. Kanwar, V., & Kumar, A. (2020c). Multiobjective optimization-based DV-hop localization using NSGA-II algorithm for wireless sensor networks. International Journal of Communication Systems, 1, 1–14. https://doi.org/10.1002/dac.4431.

    Article  Google Scholar 

  8. 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 

  9. Kumar, G., Rai, M. K., Saha, R., & Kim, H. J. (2018). An improved DV-Hop localization with minimum connected dominating set for mobile nodes in wireless sensor networks. International Journal of Distributed Sensor Networks, 14(1), 2018. https://doi.org/10.1177/1550147718755636.

    Article  Google Scholar 

  10. Kumar, R., Kumar, S., Shukla, D., Raw, R. S., & Kaiwartya, O. (2014). Geometrical localization algorithm for three dimensional wireless sensor networks. Wireless Personal Communications, 79(1), 249–264. https://doi.org/10.1007/s11277-014-1852-6.

    Article  Google Scholar 

  11. 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 

  12. Mekelleche, F., & Haffaf, H. (2017). Classification and comparison of range-based localization techniques in wireless sensor networks. Journal of Communications, 12(4), 221–227. https://doi.org/10.12720/jcm.12.4.221-227.

    Article  Google Scholar 

  13. Najeh, T., Sassi, H., & Liouane, N. (2018). A novel range free localization algorithm in wireless sensor networks based on connectivity and genetic algorithms. International Journal of Wireless Information Networks, 25(1), 88–97. https://doi.org/10.1007/s10776-017-0375-y.

    Article  Google Scholar 

  14. Oguejiofor, O., Aniedu, A., Ejiofor, H., & Okolibe, A. (2013). Trilateration Based localization Algorithm for Wireless Sensor Network. International Journal of Innovative Science and Modern Engineering, 10, 21–27.

    Google Scholar 

  15. Pandey, S., & Varma, S. (2016). A range based localization system in multihop wireless sensor networks: A distributed cooperative Approach. Wireless Personal Communications, 86(2), 615–634. https://doi.org/10.1007/s11277-015-2948-3.

    Article  Google Scholar 

  16. Rashid, H., & Turuk, A. K. (2013). Localization of wireless sensor networks using a single anchor node. Wireless Personal Communications, 72(2), 975–986. https://doi.org/10.1007/s11277-013-1050-y.

    Article  Google Scholar 

  17. Shalaby, M., Shokair, M., & Messiha, N. W. (2017). Performance Enhancement of TOA Localized Wireless Sensor Networks. Wireless Personal Communications, 95(4), 4667–4679. https://doi.org/10.1007/s11277-017-4112-8.

    Article  Google Scholar 

  18. Sharma, G., & Kumar, A. (2017). Improved DV-Hop localization algorithm using teaching learning based optimization for wireless sensor networks. Telecommunication Systems, 67, 163–178. https://doi.org/10.1007/s11235-017-0328-x.

    Article  MathSciNet  Google Scholar 

  19. 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 

  20. Singh, M., Bhoi, S. K., & Khilar, P. M. (2017). Geometric constraint-based range-free localization scheme for wireless sensor networks. IEEE Sensors Journal, 17(16), 5350–5366. https://doi.org/10.1109/JSEN.2017.2725343.

    Article  Google Scholar 

  21. Singh, S. P., & Sharma, S. C. (2018a). A PSO Based Improved Localization Algorithm for Wireless Sensor Network. Wireless Personal Communications, 98(1), 487–503. https://doi.org/10.1007/s11277-017-4880-1.

    Article  Google Scholar 

  22. Singh, S. P., & Sharma, S. C. (2018b). Implementation of a PSO Based Improved Localization Algorithm for Wireless Sensor Networks. https://doi.org/10.1080/03772063.2018.1436472.

  23. Sun, Z., Tao, L., Wang, X., & Zhou, Z. (2015). Localization algorithm in wireless sensor networks based on multiobjective particle swarm optimization. International Journal of Distributed Sensor Networks, 11(8), 716291. https://doi.org/10.1155/2015/716291.

    Article  Google Scholar 

  24. Wang, P., Xue, F., Li, H., Cui, Z., Xie, L., & Chen, J. (2019). A multi-objective dv-hop localization algorithm based on NSGA-II in internet of things. Mathematics, 7(2), 1. https://doi.org/10.3390/math7020184.

    Article  Google Scholar 

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  1. Department of Electronics and Communication Engineering, National Institute of Technology, Hamirpur, India

    Vivek Kanwar & Ashok Kumar

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  1. Vivek Kanwar
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  2. Ashok Kumar
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Correspondence to Vivek Kanwar.

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Kanwar, V., Kumar, A. Range Free Localization for Three Dimensional Wireless Sensor Networks Using Multi Objective Particle Swarm Optimization. Wireless Pers Commun 117, 901–921 (2021). https://doi.org/10.1007/s11277-020-07902-1

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