Altitude Optimization and Task Allocation of UAV-Assisted MEC Communication System.

Area of Science:

• Wireless Communication Systems
• Mobile Edge Computing (MEC)
• Maritime Communications

Background:

• Unmanned Aerial Vehicles (UAVs) offer flexible mobility in wireless networks.
• Mobile Edge Computing (MEC) enhances computing services for latency-sensitive applications.
• Maritime communication systems face challenges in providing high-quality, low-latency services.

Purpose of the Study:

• To propose a novel UAV-assisted MEC system for uplink maritime communications.
• To minimize total system latency by optimizing UAV altitude and task allocation.
• To provide flexible computing assistance to maritime users via UAV-equipped MEC servers.

Main Methods:

• Formulation of an optimization problem to minimize system latency.
• Design of the optimal flying altitude for the UAV.
• Determination of the optimal task allocation ratio between UAV and onshore base station.
• Derivation of semi closed-form and closed-form expressions for optimization variables.

Main Results:

• A novel UAV-assisted MEC uplink maritime communication system was developed.
• Optimal UAV altitude and task allocation strategies were derived.
• The proposed system effectively minimizes latency for maritime users.
• Simulation results validated the theoretical analyses.

Conclusions:

• The UAV-assisted MEC system offers a promising solution for low-latency maritime communications.
• Optimizing UAV altitude and task allocation is crucial for performance enhancement.
• The developed analytical framework provides valuable insights for system design and deployment.