Deep Q-Learning Based Adaptive MAC Protocol with Collision Avoidance and Efficient Power Control for UWSNs
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| Publicat a: | Journal of Marine Science and Engineering vol. 13, no. 3 (2025), p. 616 |
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| Autor principal: | |
| Altres autors: | , , , , , |
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MDPI AG
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| Accés en línia: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 022 | |a 2077-1312 | ||
| 024 | 7 | |a 10.3390/jmse13030616 |2 doi | |
| 035 | |a 3181550751 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231479 |2 nlm | ||
| 100 | 1 | |a Wazir Ur Rahman |u National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China; <email>wazirrahman@hrbeu.edu.cn</email> (W.U.R.); <email>qiaogang@hrbeu.edu.cn</email> (Q.G.); <email>wasiqali@hrbeu.edu.cn</email> (W.A.); <email>adil@hrbeu.edu.cn</email> (M.A.); Key Laboratory of Marine Information Acquisition and Security, Harbin Engineering University, Ministry of Industry and Information Technology, Harbin 150001, China; College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China | |
| 245 | 1 | |a Deep Q-Learning Based Adaptive MAC Protocol with Collision Avoidance and Efficient Power Control for UWSNs | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Underwater wireless sensor networks (UWSNs) widely used for maritime object detection or for monitoring of oceanic parameters that plays vital role prediction of tsunami to life-cycle of marine species by deploying sensor nodes at random locations. However, the dynamic and unpredictable underwater environment poses significant challenges in communication, including interference, collisions, and energy inefficiency. In changing underwater environment to make routing possible among nodes or/and base station (BS) an adaptive receiver-initiated deep adaptive with power control and collision avoidance MAC (DAWPC-MAC) protocol is proposed to address the challenges of interference, collisions, and energy inefficiency. The proposed framework is based on Deep Q-Learning (DQN) to optimize network performance by enhancing collision avoidance in a varying sensor locations, conserving energy in changing path loss with respect to time and depth and reducing number of relaying nodes to make communication reliable and ensuring synchronization. The dynamic and unpredictable underwater environment, shaped by variations in environmental parameters such as temperature (T) with respect to latitude, longitude, and depth, is carefully considered in the design of the proposed MAC protocol. Sensor nodes are enabled to adaptively schedule wake-up times and efficiently control transmission power to communicate with other sensor nodes and/or courier node plays vital role in routing for data collection and forwarding. DAWPC-MAC ensures energy-efficient and reliable time-sensitive data transmission, improving the packet delivery rati (PDR) by 14%, throughput by over 70%, and utility by more than 60% compared to existing methods like TDTSPC-MAC, DC-MAC, and ALOHA MAC. These enhancements significantly contribute to network longevity and operational efficiency in time-critical underwater applications. | |
| 653 | |a Parameters | ||
| 653 | |a Adaptability | ||
| 653 | |a Protocol | ||
| 653 | |a Traffic | ||
| 653 | |a Communication | ||
| 653 | |a Power control | ||
| 653 | |a Collision avoidance | ||
| 653 | |a Bandwidths | ||
| 653 | |a Synchronization | ||
| 653 | |a Energy efficiency | ||
| 653 | |a Optimization | ||
| 653 | |a Wireless sensor networks | ||
| 653 | |a Nodes | ||
| 653 | |a Synchronism | ||
| 653 | |a Packet transmission | ||
| 653 | |a Data transmission | ||
| 653 | |a Transmitters | ||
| 653 | |a Energy conservation | ||
| 653 | |a Energy consumption | ||
| 653 | |a Data collection | ||
| 653 | |a Propagation | ||
| 653 | |a Learning | ||
| 653 | |a Sensors | ||
| 653 | |a Neural networks | ||
| 653 | |a Decision making | ||
| 653 | |a Energy | ||
| 653 | |a Design | ||
| 653 | |a Literature reviews | ||
| 653 | |a Acoustics | ||
| 653 | |a Collisions | ||
| 653 | |a Underwater | ||
| 653 | |a Resource management | ||
| 653 | |a Environmental | ||
| 700 | 1 | |a Qiao Gang |u National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China; <email>wazirrahman@hrbeu.edu.cn</email> (W.U.R.); <email>qiaogang@hrbeu.edu.cn</email> (Q.G.); <email>wasiqali@hrbeu.edu.cn</email> (W.A.); <email>adil@hrbeu.edu.cn</email> (M.A.); Key Laboratory of Marine Information Acquisition and Security, Harbin Engineering University, Ministry of Industry and Information Technology, Harbin 150001, China; College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China | |
| 700 | 1 | |a Zhou, Feng |u National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China; <email>wazirrahman@hrbeu.edu.cn</email> (W.U.R.); <email>qiaogang@hrbeu.edu.cn</email> (Q.G.); <email>wasiqali@hrbeu.edu.cn</email> (W.A.); <email>adil@hrbeu.edu.cn</email> (M.A.); Key Laboratory of Marine Information Acquisition and Security, Harbin Engineering University, Ministry of Industry and Information Technology, Harbin 150001, China; College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China | |
| 700 | 1 | |a Tahir, Muhammad |u Department of Engineering and Computer Science, NUML Faisalabad Campus, Faisalabad 38000, Pakistan; <email>engr.tahir1987@gmail.com</email> | |
| 700 | 1 | |a Wasiq Ali |u National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China; <email>wazirrahman@hrbeu.edu.cn</email> (W.U.R.); <email>qiaogang@hrbeu.edu.cn</email> (Q.G.); <email>wasiqali@hrbeu.edu.cn</email> (W.A.); <email>adil@hrbeu.edu.cn</email> (M.A.); Key Laboratory of Marine Information Acquisition and Security, Harbin Engineering University, Ministry of Industry and Information Technology, Harbin 150001, China; College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China | |
| 700 | 1 | |a Muhammad Adil |u National Key Laboratory of Underwater Acoustic Technology, Harbin Engineering University, Harbin 150001, China; <email>wazirrahman@hrbeu.edu.cn</email> (W.U.R.); <email>qiaogang@hrbeu.edu.cn</email> (Q.G.); <email>wasiqali@hrbeu.edu.cn</email> (W.A.); <email>adil@hrbeu.edu.cn</email> (M.A.); Key Laboratory of Marine Information Acquisition and Security, Harbin Engineering University, Ministry of Industry and Information Technology, Harbin 150001, China; College of Underwater Acoustic Engineering, Harbin Engineering University, Harbin 150001, China | |
| 700 | 1 | |a Muhammad Ilyas Khattak |u School of Control Science and Engineering, Shandong University, Jinan 250100, China; <email>ilyas@mail.sdu.edu.cn</email> | |
| 773 | 0 | |t Journal of Marine Science and Engineering |g vol. 13, no. 3 (2025), p. 616 | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
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