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Sensor node localization with improved hop-size using PSODESA optimization

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Abstract

Localization is a significant issue in sensor network. Numerous applications rely on accurate node localization. The various variant of DV-Hop techniques developed by researchers to enhance the efficiency of the position of sensor nodes. In this work, an improved range-free PSODESADV-Hop localization approach is proposed based on “DV-Hop”. The proposed PSODESADV-Hop approach is separated into three stages. The first stage is similar to the original “DV-Hop” method. In stage two, an efficient approach for the computation of hop-size is determined. In addition, an adjustment factor for hop-size refinement is included. In the third stage, hybrid optimization (PSODESA) approach is applied for the localization of unidentified nodes. The experimental results demonstrate that the error in localization and error variance are reduced in proposed PSODESADV- Hop localization technique. It also improves localization accuracy when compared with existing localization algorithms such as “DV-Hop”, Improved “DV-Hop”, PSO “DV-Hop”, and DEI “DV-Hop”. The implementation of the proposed PSODESADV-Hop technique is performed for two scenarios: In the first scenario, simulation results are obtained for the localization error of the unidentified nodes without using hybrid optimization approach. In this scenario, the influence of total sensor nodes, beacons percent and communication radius on localization error have been examined. In another scenario, hybrid PSODESA optimization approach has been used. The influence of total sensor nodes, beacons percent and Communication radius on localization error have been studied.

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References

  1. Khelifi, F., Bradai, A., Benslimane, A., Rawat, P., & Atri, M. (2019). A Survey of Localization Systems in Internet of Things. Mobile Networks and Applications., 24, 761–785. https://doi.org/10.1007/s11036-018-1090-3

    Article  Google Scholar 

  2. Yick, J., Mukherjee, B., & Ghosal, D. (2008). Wireless sensor network survey. Computer Networks., 52, 2292–2330. https://doi.org/10.1016/j.comnet.2008.04.002

    Article  Google Scholar 

  3. Akyildiz, I. F., Su, W., Sankarasubramaniam, Y., & Cayirci, E. (2002). Wireless sensor networks: A survey. Computer networks., 38(4), 393–422.

    Article  Google Scholar 

  4. Capkun, S., Hamdi, M., & Hubaux, J.-P. (2002). GPS-free Positioning in Mobile Ad Hoc Networks. Cluster Computing., 5, 157–167.

    Article  Google Scholar 

  5. Zhang, Y., Wu, W., & Chen, Y. (2005). A range-based localization algorithm for wireless sensor networks. Journal of Communications and Networks., 7(4), 429–437.

    Article  Google Scholar 

  6. Xie, P., You, K., Song, S., & Wu, C. (2019). Distributed range-free localization via hierarchical nonconvex constrained optimization. Signal Processing., 164, 136–145. https://doi.org/10.1016/j.sigpro.2019.06.009

    Article  Google Scholar 

  7. Niculescu, D., Nath, B.: Ad hoc positioning system (APS). In GLOBECOM'01. IEEE global telecommunications conference (Cat. No. 01CH37270), 5, (pp. 2926–2931). IEEE, 2001. https://doi.org/10.7282/T37S7SDR

  8. Xie, H., Li, W., Li, S., Xu, B.: An improved DV-Hop localization algorithm based on RSSI auxiliary ranging. In 2016 35th Chinese Control Conference (CCC), (pp. 8319–8324). IEEE, 2016.

  9. 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, 25–31. https://doi.org/10.1007/s11235-013-9673-6

    Article  Google Scholar 

  10. Cheng, W., Li, J., & Li, H. (2012). An improved APIT location algorithm for wireless sensor networks (pp. 113–119). In Advances in electrical engineering and automation.

    Google Scholar 

  11. Niculescu, D., & Nath, B. (2003). DV based positioning in ad hoc networks. Telecommunication Systems., 22(1), 267–280.

    Article  Google Scholar 

  12. Li, J., Gao, M., & Pan, J. S. (2021). A parallel compact cat swarm optimization and its application in DV-Hop node localization for wireless sensor network. Wireless Networks, 27(3), 2081–2101. https://doi.org/10.1007/s11276-021-02563-9

    Article  Google Scholar 

  13. Yu, X., & Hu, M. (2019). Hop-count quantization ranging and hybrid cuckoo search optimized for DV-HOP in WSNs. Wireless Personal Communications, 108(4), 2031–2046. https://doi.org/10.1007/s11277-019-06507-7

    Article  Google Scholar 

  14. Shi, Q., Xu, Q., & Zhang, J. (2019). An improved DV-Hop scheme based on path matching and particle swarm optimization algorithm. Wireless Personal Communications, 104(4), 1301–1320. https://doi.org/10.1007/s11277-018-6084-8

    Article  Google Scholar 

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

    Article  Google Scholar 

  16. Abd, El., Ghafour, M. G., Kamel, S. H., & Abouelseoud, Y. (2021). Improved DV-Hop based on Squirrel search algorithm for localization in wireless sensor networks. Wireless Networks, 27(4), 2743–59. https://doi.org/10.1007/s11276-021-02618-x

    Article  Google Scholar 

  17. Kumar, S., Kumar, S., & Batra, N. (2021). Optimized distance range free localization algorithm for WSN. Wireless Personal Communications, 117(3), 1879–1907. https://doi.org/10.1007/s11277-020-07950-7

    Article  Google Scholar 

  18. Cai, X., Wang, P., Cui, Z., Zhang, W., & Chen, J. (2020). Weight convergence analysis of DV-hop localization algorithm with GA. Soft Computing, 24(23), 18249–18258. https://doi.org/10.1007/s00500-020-05088-z(0123456789()

    Article  MATH  Google Scholar 

  19. Kanwar, V., & Kumar, A. (2021). DV-hop localization methods for displaced sensor nodes in wireless sensor network using PSO. Wireless Networks, 27(1), 91–102. https://doi.org/10.1007/s11276-020-02446-5

    Article  Google Scholar 

  20. 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 

  21. Messous, S., & Liouane, H. (2020). Online sequential DV-hop localization algorithm for wireless sensor networks. Mobile Information Systems. https://doi.org/10.1155/2020/8195309

    Article  Google Scholar 

  22. Messous, S., Liouane, H., Cheikhrouhou, O., & Hamam, H. (2021). Improved recursive DV-hop localization algorithm with RSSI measurement for wireless sensor networks. Sensors, 21(12), 4152. https://doi.org/10.3390/s21124152

    Article  Google Scholar 

  23. Girod, L., Bychkovskiy, V., Elson, J., Estrin, D 2002 Locating tiny sensors in time and space: A case study. In Proceedings. IEEE International Conference on Computer Design: VLSI in Computers and Processors, (pp. 214–219). IEEE

  24. Bao, X., Bao, F., Zhang, S., Liu, L.: An improved DV-Hop localization algorithm for wireless sensor networks. 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM) (pp. 1–4). IEEE, 2010.

  25. Dai, Y., Wang, J., Zhang, C.: Improvement of DV-Hop localization algorithms for wireless sensor networks. In 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM) (pp. 1–4). IEEE, 2010.

  26. Goyat, R., Rai, M. K., Kumar, G., Kim, T. H., & Saha, R. (2019). Energy efficient range-free localization algorithm for wireless sensor networks. Sensors (Switzerland)., 19(16), 3603. https://doi.org/10.3390/s19163603

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  30. Chen, X., & Zhang, B. (2012). Improved DV-hop node localization algorithm in wireless sensor networks. International Journal of Distributed Sensor Networks., 8(8), 213980. https://doi.org/10.1155/2012/213980

    Article  Google Scholar 

  31. Liu, L., Han, G., Chan, S. & Guizani, M. (2018). An SNR-assured anti-jamming routing protocol for reliable communication in industrial wireless sensor networks. IEEE Communications Magazine, 56(2), 23–29. https://doi.org/10.1109/MCOM.2018.1700615

    Article  Google Scholar 

  32. Cui, L., Xu, C., Li, G., Ming, Z., Feng, Y., & Lu, N. (2018). A high accurate localization algorithm with DV-Hop and differential evolution for wireless sensor network. Applied Soft Computing Journal., 68, 39–52. https://doi.org/10.1016/j.asoc.2018.03.036

    Article  Google Scholar 

  33. Peng, B., & Li, L. (2015). An improved localization algorithm based on genetic algorithm in wireless sensor networks. Cognitive Neurodynamics., 9, 249–256. https://doi.org/10.1007/s11571-014-9324-y

    Article  Google Scholar 

  34. Han, D., Yu, Y., Li, K. C., & de Mello, R. F. (2020). Enhancing the sensor node localization algorithm based on improved DV-Hop and DE algorithms in wireless sensor networks. Sensors (Switzerland)., 20(2), 343. https://doi.org/10.3390/s20020343

    Article  Google Scholar 

  35. Mirsadeghi, E., & Khodayifar, S. (2021). Hybridizing particle swarm optimization with simulated annealing and differential evolution. Cluster Computing., 24, 1135–1163. https://doi.org/10.1007/s10586-020-03179-y

    Article  Google Scholar 

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Authors and Affiliations

  1. SC&SS, Jawaharlal Nehru University, New Delhi, 110067, India

    Maheshwari Niranjan, Swechchha Gupta & Buddha Singh

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  1. Maheshwari Niranjan
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  2. Swechchha Gupta
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  3. Buddha Singh
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Niranjan, M., Gupta, S. & Singh, B. Sensor node localization with improved hop-size using PSODESA optimization. Wireless Netw 29, 1911–1934 (2023). https://doi.org/10.1007/s11276-023-03242-7

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