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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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
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Abstract	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.
AbstractList	Abstract 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. 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.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. 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.
ArticleNumber	24957
Author	Li, Ming Luo, Haibo Xu, Furong Zhang, Jianshan Deng, Fukang
Author_xml	– sequence: 1 givenname: Fukang surname: Deng fullname: Deng, Fukang organization: School of Computer and Big Data, Minjiang University, College of Computer and Data Science, Fuzhou University – sequence: 2 givenname: Haibo surname: Luo fullname: Luo, Haibo organization: School of Computer and Big Data, Minjiang University – sequence: 3 givenname: Furong surname: Xu fullname: Xu, Furong organization: Fujian Institute of Education – sequence: 4 givenname: Ming surname: Li fullname: Li, Ming email: zxlmhh2021@163.com organization: School of Computer and Big Data, Minjiang University – sequence: 5 givenname: Jianshan surname: Zhang fullname: Zhang, Jianshan email: jszhang@mju.edu.cn organization: School of Computer and Big Data, Minjiang University
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Snippet	With the rapid development of the marine economy, the conflict between the limited capacity of existing network infrastructure and the growing demand for... Abstract With the rapid development of the marine economy, the conflict between the limited capacity of existing network infrastructure and the growing demand...
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StartPage	24957
SubjectTerms	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
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Title	Energy-efficient data collection optimization for dual-UAV-assisted relay marine networks
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