Energy-efficient data collection optimization for dual-UAV-assisted relay marine networks

With the rapid development of the marine economy, the conflict between the limited capacity of existing network infrastructure and the growing demand for marine data collection has become increasingly prominent. Due to their high mobility and ease of deployment, unmanned aerial vehicles (UAVs) are p...

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Bibliographic Details
Published in:Scientific reports Vol. 15; no. 1; pp. 24957 - 17
Main Authors: Deng, Fukang, Luo, Haibo, Xu, Furong, Li, Ming, Zhang, Jianshan
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 10.07.2025
Nature Publishing Group
Nature Portfolio
Subjects:
639/705
639/705/1042
639/705/117
Algorithms
Climate change
Collaboration
Communications networks
Data collection
Data Offloading
Data processing
Digital Age
Efficiency
Energy consumption
Energy efficiency
Energy-Efficient
Humanities and Social Sciences
Marine Network
multidisciplinary
Nonlinear programming
Optimization
Performance evaluation
Resource Allocation
Science
Science (multidisciplinary)
UAV Trajectory
Unmanned aerial vehicles
Wireless communications
Marine Network
UAV Trajectory
Resource Allocation
Data Offloading
Energy-Efficient
ISSN:2045-2322, 2045-2322
Online Access:Get full text
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Summary:With the rapid development of the marine economy, the conflict between the limited capacity of existing network infrastructure and the growing demand for marine data collection has become increasingly prominent. Due to their high mobility and ease of deployment, unmanned aerial vehicles (UAVs) are playing an increasingly important role in marine data collection and transmission. This paper investigates the marine data collection problem with dual-UAV-assisted relay. Specifically, it aims to minimize the total system energy consumption while satisfying constraints such as quality of service and service coverage, through joint optimization of access relationship, UAV trajectory, data offloading, and communication resource allocation. To address this non-convex mixed-integer nonlinear programming problem, a joint optimization algorithm is proposed. The algorithm first employs a greedy algorithm-based approach to solve the access relationship optimization sub-problem, then applies a successive convex approximation (SCA)-based approach to solve the UAV trajectory and communication resource allocation sub-problems, and finally iteratively solves these sub-problems to obtain a near-optimal solution to the original problem. Simulation results demonstrate that, compared with several benchmark algorithms, the proposed joint optimization algorithm significantly reduces the total system energy consumption while ensuring the successful completion of all data collection.
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ISSN:2045-2322
2045-2322
DOI:10.1038/s41598-025-10766-9