ADRP-DQL: An adaptive distributed routing protocol for underwater acoustic sensor networks using deep Q-learning

IF 4.4 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS Ad Hoc Networks Pub Date : 2024-10-28 DOI:10.1016/j.adhoc.2024.103692
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Abstract

Underwater Wireless Sensor Networks (UWSNs) face unique constraints due to their unstructured and dynamic underwater environment. Data gathering from these networks is crucial as energy resources are limited. In this regard, efficient routing protocols are needed to optimize energy consumption, increase the network lifetime, and enhance data delivery in these networks. In this work, we develop an Adaptive Distributed Routing Protocol for UWSNs using Deep Q-Learning (ADRP-DQL). This protocol employs the ability of reinforcement learning to dynamically learn the best routing decisions based on the network’s state and action-value estimates. It allows nodes to make intelligent routing decisions, considering residual energy, depth and node degree. A Deep Q-Network (DQN) is employed as the function approximator to estimate action values and choose the optimal routing decisions. The DQN is trained using off-policy and on-policy strategies and the neural network model. Simulation results demonstrate that ADRP-DQL performs well regarding energy efficiency (EE), data delivery ratio, and network lifetime. The results highlight the proposed protocol’s effectiveness and adaptability to UWSNs. The ADRP-DQL protocol contributes to intelligent routing for UWSNs, offering a promising approach to enhance performance and optimize energy utilization in these demanding environments.
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ADRP-DQL:使用深度 Q 学习的水下声学传感器网络自适应分布式路由协议
水下无线传感器网络(UWSN)因其非结构化和动态的水下环境而面临独特的限制。由于能源资源有限,从这些网络收集数据至关重要。在这方面,需要高效的路由协议来优化能源消耗、延长网络寿命并加强这些网络的数据传输。在这项工作中,我们开发了一种使用深度 Q 学习的 UWSN 自适应分布式路由协议(ADRP-DQL)。该协议利用强化学习的能力,根据网络状态和行动值估计动态学习最佳路由决策。它允许节点在考虑剩余能量、深度和节点度的情况下做出智能路由决策。深度 Q 网络(DQN)被用作函数近似器,用于估计行动值和选择最佳路由决策。DQN 使用非策略和策略策略以及神经网络模型进行训练。仿真结果表明,ADRP-DQL 在能效(EE)、数据交付率和网络寿命方面表现良好。这些结果凸显了所提协议的有效性和对 UWSN 的适应性。ADRP-DQL 协议为 UWSN 的智能路由做出了贡献,为在这些要求苛刻的环境中提高性能和优化能源利用提供了一种有前途的方法。
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来源期刊
Ad Hoc Networks
Ad Hoc Networks 工程技术-电信学
CiteScore
10.20
自引率
4.20%
发文量
131
审稿时长
4.8 months
期刊介绍: The Ad Hoc Networks is an international and archival journal providing a publication vehicle for complete coverage of all topics of interest to those involved in ad hoc and sensor networking areas. The Ad Hoc Networks considers original, high quality and unpublished contributions addressing all aspects of ad hoc and sensor networks. Specific areas of interest include, but are not limited to: Mobile and Wireless Ad Hoc Networks Sensor Networks Wireless Local and Personal Area Networks Home Networks Ad Hoc Networks of Autonomous Intelligent Systems Novel Architectures for Ad Hoc and Sensor Networks Self-organizing Network Architectures and Protocols Transport Layer Protocols Routing protocols (unicast, multicast, geocast, etc.) Media Access Control Techniques Error Control Schemes Power-Aware, Low-Power and Energy-Efficient Designs Synchronization and Scheduling Issues Mobility Management Mobility-Tolerant Communication Protocols Location Tracking and Location-based Services Resource and Information Management Security and Fault-Tolerance Issues Hardware and Software Platforms, Systems, and Testbeds Experimental and Prototype Results Quality-of-Service Issues Cross-Layer Interactions Scalability Issues Performance Analysis and Simulation of Protocols.
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