Journal
IEEE INTERNET OF THINGS JOURNAL
Volume 9, Issue 3, Pages 1775-1789Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2021.3088279
Keywords
Trajectory; Optimization; Internet of Things; Energy consumption; Task analysis; Sensors; Acoustic communication (telecommunication); Energy efficiency; Internet of Underwater Things (IoUT); Lyapunov optimization; trajectory scheduling; underwater information collection
Categories
Funding
- National Natural Science Foundation of China [62071268, 61971257]
- Young Elite Scientist Sponsorship Programs by CAST [2020QNRC001]
- Project The Verification Platform of Multi-Tier Coverage Communication Network for Oceans of Peng Cheng Laboratory [LZC0020]
- NSF [EARS-1839818, CNS-1717454, CNS-1731424, CNS-1702850]
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In this article, a heterogeneous AUV-aided information collection system is proposed to maximize the energy efficiency of IoUT nodes by optimizing AUV trajectory, resource allocation, and the Age of Information. The trajectory of AUVs with low time complexity is obtained using particle swarm optimization, and a two-stage joint optimization algorithm based on Lyapunov optimization is used to strike a balance between energy efficiency and system queue backlog.
In the face of deeply exploring and exploiting marine resources, the Internet of Underwater Things (IoUT) networks have drawn great attention considering its widely distributed low-cost and easy-deployment smart sensing nodes. However, given the hostile underwater environment, it is critical to conceive energy-efficient information collection because of limited underwater energy supply and inefficient artificial recharge methods. Characterized by high flexibility and maneuverability, autonomous underwater vehicles (AUVs) are regarded as a promising solution for information collection in the IoUT relying upon delicate AUVs' trajectory and information collection strategy design with the spirit of balancing their energy consumption and information processing capability. In this article, we propose a heterogeneous AUV-aided information collection system with the aim of maximizing the energy efficiency of IoUT nodes taking into account AUV trajectory, resource allocation, and the Age of Information (AoI). Moreover, based on the particle swarm optimization (PSO), we obtain the trajectory of AUVs with low time complexity. Additionally, a two-stage joint optimization algorithm based on the Lyapunov optimization is constructed to strike a tradeoff between energy efficiency and system queue backlog iteratively. Finally, simulation results validate the effectiveness and superiority of our proposed strategy.
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