Joint optimization for latency minimization in UAV-assisted MEC networks

Combining unmanned aerial vehicles (UAVs) with multi-access edge computing (MEC) networks has been deemed as a potential approach for delay-sensitive applications. In this paper, we propose a UAV-assisted MEC network architecture and jointly optimize the UAVs' position, task offloading, bandwidth allocation, and computing resource allocation to minimize the time consumption of each terminal devices cluster. To solve this problem, we design a joint optimization algorithm based on the particle swarm optimization (PSO) and bisection searching (BSS) approach. The results of the simulation reveal that the devised algorithm can significantly reduce time consumption and guarantee the fairness of the whole network.