EWR-CSA: Energy-Aware and Secure Routing Protocol for Underwater Wireless Sensor Networks Based on Cone Search Algorithm

Subject Areas : Computer Networks

Mostafa AliBabaei Shahraki ¹ , Sima Emadi ^{2 *} , Vahid Ayatollahitafti ³ , Ghasem Mirjalily ⁴

1 - Department of Computer Engineering, Ya.C., Islamic Azad University, Yazd, Iran.
2 - Department of Computer Engineering, Yazd Branch, Islamic Azad University, Yazd, Iran
3 - Department of Computer Engineering, Ya.C., Islamic Azad University, Yazd, Iran
4 - Department of Electrical Engineering, Yazd University, Yazd, Iran

Received: 2025-09-28 Accepted : 2025-12-03 Published : 2025-12-17

Keywords: Cone Search Algorithm, Security, Energy-Aware Routing, Wireless Sensor Networks,

Abstract :

Underwater Wireless Sensor Networks (UWSNs) are composed of underwater wireless sensors and various other components that communicate with each other. They support diverse applications such as seismic monitoring, subsurface navigation, tsunami prediction, and military and environmental monitoring. These networks face several challenges, including issues related to energy consumption, battery life, time synchronization, node localization, and sensor deployment. Security is also a very important consideration in UWSNs, as they are highly vulnerable to attacks. To reduce energy consumption and counter security threats, an innovative Energy-aware Weighted Routing (EWR) protocol is proposed, which uses a Cone Search Algorithm (CSA). EWR utilizes cooperative routing to improve network efficiency and performance. Finally, the performance of the proposed technique is evaluated using simulations run on NS2 software, and the results are compared with advanced protocols such as IWDT, RE-PBR, SEECR, and EWR-Circle SA based on several metrics. The proposed method outperforms the others, achieving higher efficiency and better performance with a 4% improvement in detection accuracy, 33% reduction in energy consumption, 6% reduction in packet loss, 2% improvement in throughput, and 5% reduction in delay.

References:

1. Ahn, J., Yasukawa, S., Sonoda, T., Nishida, Y., Ishii, K., & Ura, T. (2018). An optical image transmission system for deep sea creature sampling missions using autonomous underwater vehicle. IEEE Journal of Oceanic Engineering, 45(2), 350–361.
2. Altaweel, A., Aslam, S., & Kamel, I. (2024). JamholeHunter: On detecting new wormhole attack in opportunistic mobile networks. Journal of Network and Computer Applications, 230, 103953.
3. Asad, A., Amir, A., Farhan, M., & Muhammad, K. (2024). Enhanced fuzzy logic zone stable election protocol for cluster head election (E-FLZSEPFCH) and multipath routing in wireless sensor networks. Ain Shams Engineering Journal, 15(2), 102356.
4. Deepak, S. P., & Mukeshkrishnan, M. B. (2022). Secured route selection using E-ACO in underwater wireless sensor networks. Intelligent Automation & Soft Computing, 32(2), 963.
5. Erdem, H. E., Yildiz, H. U., & Gungor, V. C. (2019). On the lifetime of compressive-sensing based energy harvesting in underwater sensor networks. IEEE Sensors Journal, 19(12), 4680–4687.
6. Goetschalckx, K., Moons, B., Lauwereins, S., Andraud, M., & Verhelst, M. (2018). Optimized hierarchical cascaded processing. IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 8(4), 884–894.
7. Gong, Z., Li, C., & Jiang, F. (2018). AUV-aided joint localization and time synchronization for underwater acoustic sensor networks. IEEE Signal Processing Letters, 25(4), 477–481.
8. Gupta, S., et al. (2024). Underwater wireless sensor networks: a review of routing, applications, attacks and security. Wireless Networks.
9. Han, G., Tang, Z., He, Y., Jiang, J., & Ansere, J. A. (2019). District partition-based data collection algorithm with event dynamic competition in underwater acoustic sensor networks. IEEE Transactions on Industrial Informatics, 15(10), 5755–5764.
10. Hou, R., He, L., Hu, S., & Luo, J. (2018). Energy-balanced unequal layering clustering in underwater acoustic sensor networks. IEEE Access, 6, 39685–39691.
11. Hu, S., Rusek, F., & Edfors, O. (2018). Beyond massive MIMO: The potential of data transmission with large intelligent surfaces. IEEE Transactions on Signal Processing, 66(10), 2746–2758.
12. Imoize, A. L., Ajibola, O. A., Oyedare, T. R., Ogbebor, J. O., & Ajose, S. O. (2021). Development of an energy-efficient wireless sensor network model for perimeter surveillance. *International Journal of Electrical Engineering and Applied Sciences (IJEEAS)*4(1).
13. Khan, S. U., et al. (2024). Energy-efficient routing protocols for UWSNs: A comprehensive survey. Journal of Network and Computer Applications.
14. Khasawneh, A., Latif, M. S. B. A., Kaiwartya, O., & Chizari, H. (2018). A reliable energy-efficient pressure-based routing protocol for underwater wireless sensor network. Wireless Networks, 24(6), 2061–2075.
15. Kianmehr, E., Nikkhah, S., Vahidinasab, V., Giaouris, D., & Taylor, P. C. (2019). A resilience-based architecture for joint distributed energy resources allocation and hourly network reconfiguration. IEEE Transactions on Industrial Informatics, 15(10), 5444–5455.
16. Koutserimpas, T. T., & Fleury, R. (2018). Electromagnetic waves in a time periodic medium with step-varying refractive index. IEEE Transactions on Antennas and Propagation, 66(10), 5300–5307.
17. Kuthe, A., & Sharma, A. K. (2021, October). Review paper on Design and Optimization of Energy Efficient Wireless Sensor Network Model for Complex Networks. In 2021 5th International Conference on Information Systems and Computer Networks (ISCON) (pp. 1–3). IEEE.
18. Qais, M. H., Hasanien, H. M., Alghuwainem, S., Loo, K. H., Elgendy, M. A., & Turky, R. A. (2022). Accurate three-diode model estimation of photovoltaic modules using a novel circle search algorithm. Ain Shams Engineering Journal, 13(3), 101824.
19. Qais, M. H., Hasanien, H. M., Turky, R. A., Alghuwainem, S., Loo, K. H., & Elgendy, M. (2022). Optimal PEM fuel cell model using a novel circle search algorithm. Electronics, 11(12), 1808.
20. Renga, A., Graziano, M. D., & Moccia, A. (2018). Segmentation of marine SAR images by sublook analysis and application to sea traffic monitoring. IEEE Transactions on Geoscience and Remote Sensing, 57(3), 1463–1477.
21. Saeed, K., Khalil, W., Ahmed, S., Ahmad, I., & Khattak, M. N. K. (2020). SEECR: Secure energy efficient and cooperative routing protocol for underwater wireless sensor networks. IEEE Access, 8, 107419–107433.
22. Shah, S., Khan, A., Ali, I., Ko, K. M., & Mahmood, H. (2018). Localization free energy efficient and cooperative routing protocols for underwater wireless sensor networks. Symmetry, 10(10), 498.
23. Shah, S. M., et al. (2023). Advancements in Neighboring-Based Energy-Efficient Routing (NBEER). IEEE Access.
24. Singh, S. (2017). Energy efficient multilevel network model for heterogeneous WSNs. Engineering Science and Technology, an International Journal, 20(1), 105–115.
25. Subhash, S., Adnan, M., & Quan, Z. (2024). Understanding the trustworthiness management in the social Internet of things: A survey. Computer Networks, 26, 110611.
26. Sun, Y., Yuan, Y., Li, X., Xu, Q., & Guan, X. (2018). An adaptive sampling algorithm for target tracking in underwater wireless sensor networks. IEEE Access, 6, 68324–68336.
27. Suresh, P., Keerthika, P., Nithya, R., & Sadasivuni, K. K. (2024). EWR-ICSA: Energy Aware Secured Routing Protocol Based Underwater Wireless Sensor Networks Using Improved Circle Search Algorithm. Wireless Personal Communications, 138, 2135–2154.
28. Wang, M., Chen, Y., Sun, X., Xiao, F., & Xu, X. (2020). Node energy consumption balanced multihop transmission for underwater acoustic sensor networks based on clustering algorithm. IEEE Access, 8, 191231–191241.
29. Yan, J., Yang, X., Luo, X., & Chen, C. (2018). Energy-efficient data collection over AUV-assisted underwater acoustic sensor network. IEEE Systems Journal, 12(4), 3519–3530.
30. Yao, Z., Tiwari, S., Lu, T., Rivera, J., Luong, K. Q. T., Candler, R. N., Carman, G. P., & Wang, Y. E. (2019). Modeling of multiple dynamics in the radiation of bulk acoustic wave antennas. IEEE Journal on Multiscale and Multiphysics Computational Techniques, 5(1), 5–18.
31. Zhang, J., Cai, M., Han, G., Qian, Y., & Shu, L. (2020). Cellular clustering-based interference-aware data transmission protocol for underwater acoustic sensor networks. IEEE Transactions on Vehicular Technology, 69(3), 3217–3230.
32. Zhu, A. Z., Thakur, D., Özaslan, T., Pfrommer, B., Kumar, V., & Daniilidis, K. (2018). The multivehicle stereo event camera dataset: An event camera dataset for 3D perception. IEEE Robotics and Automation Letters, 3(3), 2032–2039.
33. Zhang, J., Cai, M., Han, G., Qian, Y., & Shu, L. (2020). Cellular clustering-based interference-aware data transmission protocol for underwater acoustic sensor networks. IEEE Transactions on Vehicular Technology, 69(3), 3217–3230.
34. Zhu, A. Z., Thakur, D., Özaslan, T., Pfrommer, B., Kumar, V., & Daniilidis, K. (2018). The multivehicle stereo event camera dataset: An event camera dataset for 3D perception. IEEE Robotics and Automation Letters, 3(3), 2032–2039.
35. 35. Z. Subhash, M. Adnan, Z. Quan, “Trustworthiness management in the social Internet of things: A survey,” Computer Networks, 2024. 36. M.H. Qais et al., “Circle Search Algorithm: A geometry-based metaheuristic optimization algorithm,” Mathematics, vol.10, no.10, 2022. 37. A. Asad et al., “MO-CBACORP: A multi-objective energy-efficient secure routing protocol for UWSNs,” Ain Shams Engineering Journal, 2023.
36. M. H. Qais et al., Circle Search Algorithm: A geometry-based metaheuristic optimization algorithm, Mathematics, 2022.
37. A. Asad et al., MO-CBACORP: A multi-objective energy-efficient secure routing protocol for UWSNs, Ain Shams Eng. J., 2023.
38. Alotaibi, M., Zhang, W., & Khan, I. (2025). A hybrid gray wolf-circle search algorithm for secure and energy-efficient routing in underwater wireless sensor networks. IEEE Transactions on Mobile Computing, *24*(3), 1125-1138.
39. Chen, L., Abualsaud, K., Elfouly, T., & Ahmadi, M. (2025). DQN-ER: A deep Q-network-based energy-aware routing protocol for dynamic underwater acoustic sensor networks. IEEE Internet of Things Journal, *12*(8), 10567-10581.