Joint Task Assignment and Computation Cooperation in Multi-UAV Data Processing System

The rapid advancement of unmanned aerial vehicles (UAVs) and mobile edge computing (MEC) has spurred growing interest in multi-UAV cooperative systems across various applications. However, effectively coordinating multiple UAVs for target point (TP) data processing, task offloading, and path planning remains challenging, particularly when aiming to minimize task completion time. To address these challenges, we propose a joint task assignment and resource allocation optimization (TARO) approach for efficient TP access in multi-UAV MEC systems. Specifically, we formulate an optimization problem that minimizes the task completion time while balancing task assignment through path planning, task offloading and bandwidth allocation. Given the mixed-integer nonlinear programming (MINLP) nature of the problem, we develop an efficient optimization algorithm by decomposing it into three subproblems. We propose an iterative algorithm to solve the challenging problem effectively. Simulation results demonstrate that the proposed TARO approach significantly reduces task completion time compared to traditional benchmarks.