New Strategies for Boosting Localization Accuracy in Wireless Sensor Nodes
Keywords:
Wireless Sensor Networks, Secure Node Localization (SABWP-NL) Approach, Bayesian optimization, Dempster-Shafer Evidence Theory.Abstract
Wireless Sensor Networks (WSNs), accurate and energy-efficient localization of sensor nodes remains a challenging task despite significant advancements. Current geolocation algorithms often struggle with scalability, adaptability, and energy efficiency, particularly in large-scale, dynamic environments where node failures or random shifts occur. This paper proposes a novel Secure Node Localization (SABWP-NL) approach, combining Self-Adaptive Binary Waterwheel Plant Optimization (SABWP) and Bayesian optimization to enhance localization accuracy, scalability, energy efficiency, and robustness. The method evaluates node trust using Dempster-Shafer Evidence Theoryto secure localization against rogue nodes and optimizes the localization process through trilateral and multilateration systems. The SABWP-NL approach demonstrates superior performance in terms of localized nodes and localization error compared to existing techniques like BWP, ROA, and AO. Results show that SABWP-NL achieves the highest number of localized nodes and the lowest localization error, making it a promising solution for efficient and secure node localization in WSNs.
References
A. Karthikeyan and G. Aghila, “Survey on localization in wireless sensor networks: An emerging research area,” International Journal of Computer Networks & Communications, vol. 10, no. 1, pp. 75–98, 2018.
W. Z. Khan, Y. Xiang, M. Y. Aalsalem, and Q. Arshad, “Mobile phone sensing systems: A survey,” IEEE Communications Surveys & Tutorials, vol. 15, no. 1, pp. 402–427, 2013. Available From: https://doi.org/10.1109/SURV.2012.031412.00077
H. Yang, X. Wang, L. Zhang, and Y. Jin, “Localization algorithms in wireless sensor networks: A survey,” Wireless Communications and Mobile Computing, 2015. Available From: https://doi.org/10.1007/s11235-011-9564-7
N. Patwari, J. N. Ash, S. Kyperountas, A. O. Hero III, R. L. Moses, and N. S. Correal, “Locating the nodes: Cooperative localization in wireless sensor networks,” IEEE Signal Processing Magazine, vol. 22, no. 4, pp. 54–69, 2005. Available From: https://doi.org/10.1109/MSP.2005.1458287
Z. Yang and Y. Wu, “Localization in wireless sensor networks,” Lecture Notes in Computer Science, vol. 4487, pp. 276–293, 2007. Available from: https://shorturl.at/KC06D
R. Zhang, P. K. Varshney, and K. R. Pattipati, “A robust sequential localization approach in wireless sensor networks,” IEEE Transactions on Signal Processing, vol. 58, no. 8, pp. 3949–3962, 2010.
A. Kumar and R. K. Jha, “Energy efficient routing schemes in WSN: A survey,” IEEE Access, vol. 5, pp. 4590–4620, 2017.
L. Wang, G. Chen, and M. Dong, “Trust evaluation based secure localization algorithm for wireless sensor networks,” Journal of Networks, vol. 8, no. 1, pp. 142–149, 2013.
S. Xiao and S. Liu, “Localization in wireless sensor networks using multi-objective optimization approach,” IEEE Sensors Journal, vol. 14, no. 9, pp. 2836–2846, 2014.
H. Nguyen and P. Minet, “Analysis of localization accuracy in wireless sensor networks with a mobility model,” Wireless Networks, vol. 19, no. 6, pp. 1231–1244, 2013.
A. Savvides, C. C. Han, and M. B. Strivastava, “Dynamic fine-grained localization in ad-hoc networks of sensors,” in Proceedings of the 7th Annual International Conference on Mobile Computing and Networking (MobiCom), 2001, pp. 166–179. Available From: https://doi.org/10.1145/381677.381693
Y. C. Hu, A. Perrig, and D. B. Johnson, “Packet leashes: A defense against wormhole attacks in wireless networks,” in Proceedings of the 22nd Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM), vol. 3, 2003, pp. 1976–1986. Available From: https://doi.org/10.1109/INFCOM.2003.1209219
W. Zhang, X. Liu, G. Chen, and W. He, “Secure localization and authentication in ultra-wideband sensor networks,” IEEE Journal on Selected Areas in Communications, vol. 29, no. 6, pp. 1044–1054, 2011. Available From: https://doi.org/10.1109/JSAC.2005.863855
H. Liu, H. Darabi, P. Banerjee, and J. Liu, “Survey of wireless indoor positioning techniques and systems,” IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 37, no. 6, pp. 1067–1080, 2007. Available From: https://doi.org/10.1109/TSMCC.2007.905750
Y. Li, G. Mao, B. Fidan, and B. D. Anderson, “Wireless sensor network localization techniques,” Computer Networks, vol. 51, no. 10, pp. 2529–2553, 2007. Available From: https://doi.org/10.1016/j.comnet.2006.11.018
T. Alhmiedat, “Fingerprint-based localization approach for WSN using machine learning models,” Applied Sciences, vol. 13, no. 5, p. 3037, 2023. Available From: https://doi.org/10.3390/app13053037
U. Dampage, L. Bandaranayake, R. Wanasinghe, K. Kottahachchi, and B. Jayasanka, “Forest fire detection system using wireless sensor networks and machine learning,” Scientific Reports, vol. 12, no. 1, p. 46, 2022. Available From: https://doi.org/10.1038/s41598-021-03882-9
F. Ojeda, D. Mendez, A. Fajardo, and F. Ellinger, “On wireless sensor network models: A cross-layer systematic review,” Journal of Sensor and Actuator Networks, vol. 12, no. 4, p. 50, 2023. Available From: https://doi.org/10.3390/jsan12040050