A Cooperative Computation Offloading Strategy With On-Demand Deployment of Multi-UAVs in UAV-Aided Mobile Edge Computing

In this paper, we plan to use ground-based stations in mobile edge computing (MEC) and unmanned aerial vehicles (UAVs) to provide communication and computation offloading services in disaster areas. However, optimizing the initial number and three-dimensional position of deployed UAVs is a prerequisite for providing computing services to users. Additionally, due to the limited battery and computing power of UAVs, it is a major challenge to rationally design the UAV trajectory during the computational offloading period to ensure communication quality for mobile users and reduce the energy consumption for completing tasks. Thus, we propose a cooperative computation offloading strategy with on-demand deployment of multi-UAV in UAV-aided MEC. The strategy utilizes the predicted user trajectory for UAV deployment on the premise of the minimum path loss of users. Then, to minimize total energy consumption for completing tasks, a joint optimization problem comprising user association strategy, computing resource allocation strategy, and UAV trajectory is proposed, which is a mixed-integer nonlinear program (MINLP). Therefore, to find the suboptimal solution, we use the block coordinate descent method to solve the problem. Numerical results show that the proposed algorithm can efficiently reduce the path loss by up to 18.55% and the total energy consumption by 18.28% compared to the benchmarks.