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

Area of Science:

• Marine Engineering
• Wireless Communication Networks
• Robotics and Control Systems

Background:

• Growing marine economy demands increased marine data collection, straining existing network infrastructure.
• Unmanned aerial vehicles (UAVs) offer a flexible solution for mobile marine data collection and transmission.
• The need for energy-efficient and reliable data collection in marine environments is critical.

Purpose of the Study:

• To minimize total system energy consumption for dual-UAV-assisted marine data collection.
• To optimize UAV trajectory, data offloading, and communication resource allocation.
• To ensure quality of service and service coverage constraints are met.

Main Methods:

• Developed a joint optimization algorithm for a non-convex mixed-integer nonlinear programming problem.
• Utilized a greedy algorithm for access relationship optimization.
• Employed successive convex approximation (SCA) for UAV trajectory and resource allocation optimization.

Main Results:

• The proposed joint optimization algorithm significantly reduces total system energy consumption.
• Achieved successful completion of all data collection tasks under defined constraints.
• Demonstrated superior performance compared to benchmark algorithms in simulations.

Conclusions:

• The dual-UAV-assisted relay system effectively addresses the challenges of marine data collection.
• The proposed optimization algorithm provides an energy-efficient solution for marine data transmission.
• This approach enhances the capacity and reliability of marine network infrastructure.