Secured Multi-Objective Optimisation-Based Protocol for Reliable Data Transmission in Underwater Wireless Sensor Networks
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Underwater wireless sensor network (UWSN) requirements have increased beyond applications in environmental monitoring and underwater exploration to military surveillance. The complex underwater environment raises many challenges due to high propagation delays, limited bandwidth, high error rates, and dynamic underwater currents. Most traditional clustering algorithms do not consider the multifaceted requirements of UWSNs. In most cases, a single objective is optimised at the cost of other essential factors, such as energy consumption, network robustness, and data transmission reliability. This paper proposes a new UWSN protocol based on the tiger beetle optimisation (TBO) algorithm for multiobjective K-means clustering (TBO-MOK). The protocol comprises adaptive search procedures motivated by tiger beetle hunting behaviors and lightweight AES-based encryption for data security. TBO-MOK is excellent in multiobjective optimisation since it simultaneously considers performance metrics of more than one aspect. Many problems are resolved by TBO-MOK, which optimises all the involved performance metrics to provide balanced energy usage and robust communication links. Comprehensive simulations demonstrate that TBO-MOK outperforms the traditional LEACH, PSO, and GA approaches in grossly enhancing network lifetime, energy efficiency, load balancing, and data transmission reliability. These results show the potential of TBO-MOK to provide a more effective and resilient solution for UWSNs.
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[1] A. Shenbagharaman and B. Paramasivan, 'Trilateration method based node localization and energy efficient routing using rsa for under water wireless sensor network', Sustain. Comput. Informatics Syst., vol. 41, p. 100952, 2024, doi: https://doi.org/10.1016/j.suscom.2023.100952.
[2] A. Saihood and R. Kumar, 'Enhanced Location Based Energy-Efficient Reliable Routing Protocol for Wireless Sensor Networks', Int. J. Inven. Eng. Sci. IJIES, no. May 2013, pp. 13–22, 2013, [Online]. Available: http://www.ijies.org/attachments/File/v1i6/F0216051613.pdf.
[3] R. Alasem, A. Reda, and M. Mansour, 'Location based energy-efficient reliable routing protocol for wireless sensor networks', 10th WSEAS Int. Conf. EHAC’11 ISPRA’11, 3rd WSEAS Int. Conf. Nanotechnology, Nanotechnology'11, 6th WSEAS Int. Conf. ICOAA'11, 2nd WSEAS Int.Conf. IPLAFUN'11, no. January, pp. 180–185, 2011.
[4] B. Saemi and F. Goodarzian, 'Energy-efficient routing protocol for underwater wireless sensor networks using a hybrid metaheuristic algorithm', Eng. Appl. Artif. Intell., vol. 133, p. 108132, 2024, doi: https://doi.org/10.1016/j.engappai.2024.108132.
[5] M. U. Khan, P. Otero, and M. Aamir, 'An Energy Efficient Clustering Routing Protocol Based on Arithmetic Progression for Underwater Acoustic Sensor Networks', IEEE Sens. J., vol. 24, no. 5, pp. 6964–6975, 2024, doi: 10.1109/JSEN.2024.3354252.
[6] Y. Zhang, Z. Liu, and Y. Bi, 'Node deployment of underwater wireless sensor networks using intelligent algorithm and robot collaboration', Sci. Rep., vol. 13, no. 1, p. 15920, 2023, doi: 10.1038/s41598-023-43272-x.
[7] S. He, Q. Li, M. Khishe, A. Salih Mohammed, H. Mohammadi, and M. Mohammadi, 'The of nodes clustering and multi-hop routing protocol using hierarchical chimp for sustainable energy efficient underwater wireless sensor networks', Wirel. Networks, vol. 30, no. 1, pp. 233–252, 2024, doi: 10.1007/s11276-023-03464-9.
[8] N. Kanthimathi and Dejey, 'Balanced and Multi-objective Opportunistic Routing for Underwater Sensor Networks', Wirel. Pers. Commun., vol. 94, no. 4, pp. 2417–2440, 2017, doi: 10.1007/s11277-016-3495-2.
[9] Y. Li, J. Xing, Q. Yang, and H. Shi, 'Localization Research Based on Improved Simulated Annealing Algorithm in WSN', in 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing, 2009, pp. 1–4, doi: 10.1109/WICOM.2009.5301593.
[10] X. Liu, 'Routing Protocols Based on Ant Colony in Wireless Sensor Networks: A Survey', IEEE Access, vol. 5, pp. 26303–26317, 2017, doi: 10.1109/ACCESS.2017.2769663.
[11] A. Saihood, M. A. Al-Shaher, and M. A. Fadhel, 'A New Tiger Beetle Algorithm for Cybersecurity, Medical Image Segmentation and Other Global Problems , Mesopotamian J. CyberSecurity, vol. 4, no. 1, pp. 17–46, 2024, doi: 10.58496/MJCS/2024/003.
[12] Z. Wadud, K. Ullah, A. B. Qazi, S. Jan, F. A. Khan, and N. Minallah, 'An Efficient Routing Protocol Based on Stretched Holding Time Difference for Underwater Wireless Sensor Networks.', Sensors (Basel)., vol. 19, no. 24, Dec. 2019, doi: 10.3390/s19245557.
[13] S. K. Erskine, H. Chi, and A. Elleithy, 'SDAA: Secure Data Aggregation and Authentication Using Multiple Sinks in Cluster-Based Underwater Vehicular Wireless Sensor Network.', Sensors (Basel)., vol. 23, no. 11, Jun. 2023, doi: 10.3390/s23115270.
[14] A. A. Saihood and L. Alzubaidi, 'Deep Reinforcement Learning Methods for Energy-Efficient Underwater Wireless Networking', pp. 212–223, 2020, doi: 10.4018/978-1-7998-3640-7.ch014.
[15] Z. Zhao, C. Liu, X. Guang, and K. Li, 'A Transmission-Reliable Topology Control Framework Based on Deep Reinforcement Learning for UWSNs', IEEE Internet Things J., vol. 10, no. 15, pp. 13317–13332, 2023, doi: 10.1109/JIOT.2023.3262690.
[16] M. Cobanlar, H. U. Yildiz, V. K. Akram, O. Dagdeviren, and B. Tavli, 'On the Tradeoff Between Network Lifetime and k-Connectivity-Based Reliability in UWSNs', IEEE Internet Things J., vol. 9, no. 23, pp. 24444–24452, 2022, doi: 10.1109/JIOT.2022.3188558.
[17] M. Hajare, V. Biradar, and J. A. Shaikh, 'Energy Efficient Underwater Sensor Networks Routing Protocol utilizing Advanced Particle Swarm , in 2023 4th International Conference for Emerging Technology (INCET), 2023, pp. 1–6, doi: 10.1109/INCET57972.2023.10170464.
[18] S. Ullah et al., 'Reliable and Delay Aware Routing Protocol for Underwater Wireless Sensor Networks', IEEE Access, vol. 11, pp. 116932–116943, 2023, doi: 10.1109/ACCESS.2023.3325311.
[19] M. Hajare, V. Biradar, and J. A. Shaikh, 'Robust Opportunistic Routing Solutions for under water Sensor Networks', in 2023 4th International Conference for Emerging Technology (INCET), 2023, pp. 1–9, doi: 10.1109/INCET57972.2023.10169982.
[20] R. Kumar, S. Shekhar, H. Garg, M. Kumar, B. Sharma, and S. Kumar, 'EESR: Energy efficient sector-based routing protocol for reliable data communication in UWSNs', Comput. Commun., vol. 192, pp. 268–278, 2022, doi: https://doi.org/10.1016/j.comcom.2022.06.011.
[21] M. Ismail, H. Qadir, F. A. Khan, S. Jan, Z. Wadud, and A. K. Bashir, 'A novel routing protocol for underwater wireless sensor networks based on shifted energy efficiency and priority', Comput. Commun., vol. 210, pp. 147–162, 2023, doi: https://doi.org/10.1016/j.comcom.2023.07.014.
[22] V. Nivedhitha, A. G. Saminathan, and P. Thirumurugan, 'DMEERP: A dynamic multi-hop energy efficient routing protocol for WSN', Microprocess. Microsyst., vol. 79, p. 103291, 2020, doi: https://doi.org/10.1016/j.micpro.2020.103291.
[23] F. R. Mughal et al., 'A new Asymmetric Link Quality Routing protocol (ALQR) for heterogeneous WSNs', Microprocess. Microsyst., vol. 93, p. 104617, 2022, doi: https://doi.org/10.1016/j.micpro.2022.104617.
[24] Y. Yang, Y. Wu, H. Yuan, M. Khishe, and M. Mohammadi, 'Nodes clustering and multi-hop routing protocol using hybrid chimp and hunger games search algorithms for sustainable energy efficient underwater wireless sensor networks', Sustain. Comput. Informatics Syst., vol. 35, p. 100731, 2022, doi: https://doi.org/10.1016/j.suscom.2022.100731.
[25] S. Pradeep, T. B. B. R. Bapu, R. Rajendran, and R. Anitha, 'Energy Efficient Region based Source Distributed Routing Algorithm for Sink Mobility in Underwater Sensor Network', Expert Syst. Appl., vol. 233, p. 120941, 2023, doi: https://doi.org/10.1016/j.eswa.2023.120941.
[26] M. Ahmed, M. Salleh, and M. I. Channa, 'Routing protocols based on node mobility for Underwater Wireless Sensor Network (UWSN): A survey', J. Netw. Comput. Appl., vol. 78, pp. 242–252, 2017, doi: https://doi.org/10.1016/j.jnca.2016.10.022.
[27] F. Al-Salti, N. Alzeidi, K. Day, and A. Touzene, 'An efficient and reliable grid-based routing protocol for UWSNs by exploiting minimum hop count', Comput. Networks, vol. 162, p. 106869, 2019, doi: https://doi.org/10.1016/j.comnet.2019.106869.
[28] C.-J. Huang, Y.-W. Wang, H.-H. Liao, C.-F. Lin, K.-W. Hu, and T.-Y. Chang, 'A power-efficient routing protocol for underwater wireless sensor networks', Appl. Soft Comput., vol. 11, no. 2, pp. 2348–2355, 2011, doi: https://doi.org/10.1016/j.asoc.2010.08.014.
[29] M. Faheem, M. A. Ngadi, and V. C. Gungor, 'Energy efficient multi-objective evolutionary routing scheme for reliable data gathering in Internet of underwater acoustic sensor networks', Ad Hoc Networks, vol. 93, p. 101912, 2019, doi: https://doi.org/10.1016/j.adhoc.2019.101912.
[30] P. Maheshwari, A. K. Sharma, and K. Verma, 'Energy efficient cluster based routing protocol for WSN using butterfly algorithm and ant colony , Ad Hoc Networks, vol. 110, p. 102317, 2021, doi: https://doi.org/10.1016/j.adhoc.2020.102317.
[31] H. Liu, R. Chen, S. Ding, Z. Jiang, F. Liu, and J. Zhang, 'An energy efficiency routing protocol for UAV-aided WSNs data collection', Ad Hoc Networks, vol. 154, p. 103378, 2024, doi: https://doi.org/10.1016/j.adhoc.2023.103378.
[32] K. K. Patil, T. S. Kumaran, and M. Mathapat, 'OCC-MP: An optimal cluster based congestion aware technique multipath routing protocol in WSN using hybrid evolutionary techniques', Meas. Sensors, vol. 31, p. 101007, 2024, doi: https://doi.org/10.1016/j.measen.2023.101007.
[33] H. Byeon et al., 'A hybrid path finder-based vortex search algorithm for optimal energy-efficient node placing and routing in UWSN', Results Control Optim., vol. 14, p. 100379, 2024, doi: https://doi.org/10.1016/j.rico.2024.100379.
[34] F. Hazzaa, A. Qashou, I. I. Al Barazanchi, R. Sekhar, P. Shah, M. Bachute, and A. S. Abdulbaqi, "Performance analysis of advanced encryption standards for voice cryptography with multiple patterns," Int. J. Saf. Secur. Eng., vol. 14, no. 5, pp. 1439–1446, 2024, doi: 10.18280/ijsse.140511.
[35] NIST SP, K. A. McKay, and K. A. McKay, NIST Special Publication 800: Ascon-Based Lightweight Cryptography Standards for Constrained Devices, unpublished.
[36] M. Allouzi, "TentLogiX: 5-bit chaos-driven S-boxes for lightweight cryptographic systems," unpublished, pp. 1–28.
[37] S. Windarta, S. Suryadi, K. Ramli, B. Pranggono, and T. S. Gunawan, "Lightweight cryptographic hash functions: design trends, comparative study, and future directions," IEEE Access, vol. 10, no. August, pp. 82272–82294, 2022, doi: 10.1109/ACCESS.2022.3195572.
[38] A. D. Dwivedi and G. Srivastava, "Security analysis of lightweight IoT encryption algorithms: SIMON and SIMECK," Internet Things, vol. 21, p. 100677, 2023, doi: 10.1016/j.iot.2022.100677.
[39] F. Hazzaa, M. M. Hasan, A. Qashou, and S. Yousef, "A new lightweight cryptosystem for IoT in smart city environments," Mesopotamian J. CyberSecurity, vol. 4, no. 3, pp. 46–58, 2024, doi: 10.58496/MJCS/2024/015.
[40] T. S. . Mohamed and S. M. . khalifah , Trans., “Integrated A Robust Intelligent System For Secure Network”, BJIoT, vol. 2025, pp. 66–76, Feb. 2025, doi: 10.58496/BJIoT/2025/002.
[41] J. Shin, “Revolutionizing Medical Imaging with Artificial inelegant Real-Time Segmentation for Enhanced Diagnostics”, EDRAAK, vol. 2024, pp. 18–25, Feb. 2024, doi: 10.70470/EDRAAK/2024/003.