Joint User Association and Deployment Optimization for Delay-Minimized UAV-Aided MEC Networks

The development of computation-intensive and delay-sensitive smart applications has put forward great challenge to the current cellular networks. To cope with this challenge, unmanned aerial vehicles (UAVs) providing additional on-demand communication and computing services has become a promising technology. This letter proposes a novel task offloading framework in UAV-aided mobile edge computing (MEC) networks. Specifically, the MEC queuing delay is considered in the formulated problem, where the average task delay is minimized via jointly optimizing user association and UAV deployment. The optimal transport theory is introduced to analyze the user association sub-problem, and the UAV deployment is optimized by the classical particle swarm optimization algorithm. Simulation results show that the delay performance is significantly improved by the proposed algorithm.