Application of Deep Neural Networks in Multi-Hop Wireless Sensor Network (WSN) Channel Optimization

[1] He, S., Li, Q., Khishe, M., et al. (2024). The optimization of nodes clustering and multi-hop routing protocol using hierarchical chimp optimization for sustainable energy-efficient underwater wireless sensor networks. Wireless Networks, 30(1), 233-252. He S. Li Q. Khishe M. ( 2024 ). The optimization of nodes clustering and multi-hop routing protocol using hierarchical chimp optimization for sustainable energy-efficient underwater wireless sensor networks . Wireless Networks , 30 ( 1 ), 233 - 252 . Search in Google Scholar

[2] Nguyen, T. V., Nguyen, V. D., da Costa, D. B., et al. (2022). Short-packet communications in multihop networks with WET: Performance analysis and deep learning-aided optimization. IEEE Transactions on Wireless Communications, 22(1), 439-456. Nguyen T. V. Nguyen V. D. da Costa D. B. ( 2022 ). Short-packet communications in multihop networks with WET: Performance analysis and deep learning-aided optimization . IEEE Transactions on Wireless Communications , 22 ( 1 ), 439 - 456 . Search in Google Scholar

[3] Sati, S. O., & Abugharsa, A. (2024). Wireless sensor network hop count theory modeling and deep learning prediction. In 2024 IEEE 4th International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA) (pp. 124-129). IEEE. Sati S. O. Abugharsa A. ( 2024 ). Wireless sensor network hop count theory modeling and deep learning prediction . In 2024 IEEE 4th International Maghreb Meeting of the Conference on Sciences and Techniques of Automatic Control and Computer Engineering (MI-STA) (pp. 124 - 129 ). IEEE . Search in Google Scholar

[4] Esheh, J., & Affes, S. (2024). Improving localization in wireless sensor networks for the Internet of Things using data replication-based deep neural networks. Sensors, 24(19), 6314. Esheh J. Affes S. ( 2024 ). Improving localization in wireless sensor networks for the Internet of Things using data replication-based deep neural networks . Sensors , 24 ( 19 ), 6314 . Search in Google Scholar

[5] Srivastava, A., & Paulus, R. (2023). Coverage hole aware optimal cluster-based routing for wireless sensor network-assisted IoT using hybrid deep recurrent neural network. Concurrency and Computation: Practice and Experience, 35(6), 1-1. Srivastava A. Paulus R. ( 2023 ). Coverage hole aware optimal cluster-based routing for wireless sensor network-assisted IoT using hybrid deep recurrent neural network . Concurrency and Computation: Practice and Experience , 35 ( 6 ), 1 - 1 . Search in Google Scholar

[6] Altowaijri, S. M. (2022). Efficient next-hop selection in multi-hop routing for IoT-enabled wireless sensor networks. Future Internet, 14(2), 35. Altowaijri S. M. ( 2022 ). Efficient next-hop selection in multi-hop routing for IoT-enabled wireless sensor networks . Future Internet , 14 ( 2 ), 35 . Search in Google Scholar

[7] Singh, M., & Shrivastava, L. (2024). Multi-objective optimized multi-path and multi-hop routing based on hybrid optimization algorithm in wireless sensor networks. Wireless Networks, 30(4), 2715-2731. Singh M. Shrivastava L. ( 2024 ). Multi-objective optimized multi-path and multi-hop routing based on hybrid optimization algorithm in wireless sensor networks . Wireless Networks , 30 ( 4 ), 2715 - 2731 . Search in Google Scholar

[8] Radhakrishnan, K., Ramakrishnan, D., Khalaf, O. I., et al. (2022). A novel deep learning-based cooperative communication channel model for wireless underground sensor networks. Sensors, 22(12), 4475. Radhakrishnan K. Ramakrishnan D. Khalaf O. I. ( 2022 ). A novel deep learning-based cooperative communication channel model for wireless underground sensor networks . Sensors , 22 ( 12 ), 4475 . Search in Google Scholar

[9] Yang, Y., Wu, Y., Yuan, H., et al. (2022). Nodes clustering and multi-hop routing protocol optimization using hybrid chimp optimization and hunger games search algorithms for sustainable energy-efficient underwater wireless sensor networks. Sustainable Computing: Informatics and Systems, 35, 100731. Yang Y. Wu Y. Yuan H. ( 2022 ). Nodes clustering and multi-hop routing protocol optimization using hybrid chimp optimization and hunger games search algorithms for sustainable energy-efficient underwater wireless sensor networks . Sustainable Computing: Informatics and Systems , 35 , 100731 . Search in Google Scholar

[10] Anuradha, D., Subramani, N., Khalaf, O. I., et al. (2022). Chaotic search-and-rescue-optimization-based multi-hop data transmission protocol for underwater wireless sensor networks. Sensors, 22(8), 2867. Anuradha D. Subramani N. Khalaf O. I. ( 2022 ). Chaotic search-and-rescue-optimization-based multi-hop data transmission protocol for underwater wireless sensor networks . Sensors , 22 ( 8 ), 2867 . Search in Google Scholar

[11] Lei, J., Tan, D., Ma, X., et al. (2024). Reinforcement learning-based multi-parameter joint optimization in dense multi-hop wireless networks. Ad Hoc Networks, 154, 103357. Lei J. Tan D. Ma X. ( 2024 ). Reinforcement learning-based multi-parameter joint optimization in dense multi-hop wireless networks . Ad Hoc Networks , 154 , 103357 . Search in Google Scholar

[12] Mahapatro, A., & Rayavarapu, V. C. H. S. R. (2023). Anchor-free localization using a deep neural network in wireless sensor networks with multiple sinks. Authorea Preprints. Mahapatro A. Rayavarapu V. C. H. S. R. ( 2023 ). Anchor-free localization using a deep neural network in wireless sensor networks with multiple sinks . Authorea Preprints . Search in Google Scholar

[13] Ma, L., Zhang, N., Chen, X., et al. (2025). A hierarchical traffic offloading mechanism for end-to-end reliability in a multi-hop multi-connection wireless sensor network. IEEE Sensors Journal. Ma L. Zhang N. Chen X. ( 2025 ). A hierarchical traffic offloading mechanism for end-to-end reliability in a multi-hop multi-connection wireless sensor network . IEEE Sensors Journal . Search in Google Scholar

[14] Mohammed, M., Imam Rahmani, M. K., Ahmed, M. E., et al. (2023). Optimized energy-efficient routing protocol for wireless sensor network integrated with IoT: An approach based on deep convolutional neural network and metaheuristic algorithms. Journal of Nanoelectronics and Optoelectronics, 18(3), 367-379. Mohammed M. Imam Rahmani M. K. Ahmed M. E. ( 2023 ). Optimized energy-efficient routing protocol for wireless sensor network integrated with IoT: An approach based on deep convolutional neural network and metaheuristic algorithms . Journal of Nanoelectronics and Optoelectronics , 18 ( 3 ), 367 - 379 . Search in Google Scholar

[15] Gurumoorthy, S., Subhash, P., Pérez de Prado, R., et al. (2022). Optimal cluster head selection in WSN with convolutional neural network-based energy level prediction. Sensors, 22(24), 9921. Gurumoorthy S. Subhash P. Pérez de Prado R. ( 2022 ). Optimal cluster head selection in WSN with convolutional neural network-based energy level prediction . Sensors , 22 ( 24 ), 9921 . Search in Google Scholar

[16] Yu, D., Yuan, T., Qing, H., et al. (2024). Gray wolf optimizer with communication strategy based on DV-Hop for nodes location of wireless sensor networks. IEEE Access. Yu D. Yuan T. Qing H. ( 2024 ). Gray wolf optimizer with communication strategy based on DV-Hop for nodes location of wireless sensor networks . IEEE Access . Search in Google Scholar

[17] Vikhyath, K. B., & Prasad, N. A. (2023). Combined Osprey-Chimp optimization for cluster-based routing in wireless sensor networks: Improved DeepMaxout for node energy prediction. Engineering, Technology & Applied Science Research, 13(6), 12314-12319. Vikhyath K. B. Prasad N. A. ( 2023 ). Combined Osprey-Chimp optimization for cluster-based routing in wireless sensor networks: Improved DeepMaxout for node energy prediction . Engineering, Technology & Applied Science Research , 13 ( 6 ), 12314 - 12319 . Search in Google Scholar

[18] Zhang, Z., Sun, S., Liu, M., et al. (2022). Network lifetime optimization in multi-hop industrial cognitive radio sensor networks. ACM Transactions on Sensor Networks, 19(1), 1-22. Zhang Z. Sun S. Liu M. ( 2022 ). Network lifetime optimization in multi-hop industrial cognitive radio sensor networks . ACM Transactions on Sensor Networks , 19 ( 1 ), 1 - 22 . Search in Google Scholar

[19] Egwuche, O. S., Singh, A., Ezugwu, A. E., et al. (2023). Machine learning for coverage optimization in wireless sensor networks: A comprehensive review. Annals of Operations Research, 1-67. Egwuche O. S. Singh A. Ezugwu A. E. ( 2023 ). Machine learning for coverage optimization in wireless sensor networks: A comprehensive review . Annals of Operations Research , 1 - 67 . Search in Google Scholar

[20] Devulapalli, P. K., Maganti, S. B., Gae, S. K., et al. (2024). Optimal relay selection strategy for energy-efficient cooperative multi-hop image transmission in wireless multimedia sensor network. Cybernetics and Systems, 55(8), 2440-2463. Devulapalli P. K. Maganti S. B. Gae S. K. ( 2024 ). Optimal relay selection strategy for energy-efficient cooperative multi-hop image transmission in wireless multimedia sensor network . Cybernetics and Systems , 55 ( 8 ), 2440 - 2463 . Search in Google Scholar

[21] Mahmood, T., Li, J., Saba, T., et al. (2024). Energy-optimized data fusion approach for scalable wireless sensor network using deep learning-based scheme. Journal of Network and Computer Applications, 224, 103841. Mahmood T. Li J. Saba T. ( 2024 ). Energy-optimized data fusion approach for scalable wireless sensor network using deep learning-based scheme . Journal of Network and Computer Applications , 224 , 103841 . Search in Google Scholar