  With the development of smart vehicles, computing-intensive tasks are widely
and rapidly generated. To alleviate the burden of on-board CPU, connected
vehicles can offload tasks to or make request from nearby edge server thanks to
the emerging Mobile Edge Computing (MEC). However, such approach may sharply
increase the workload of an edge server, and cause network congestion,
especially in rural and mountain areas where there are few edge servers. To
this end, a UAV-assisted MEC system is proposed in this paper, and joint
optimization algorithm of the deployment and resource allocation of UAVs
(JOAoDR) is proposed to decide the location and balance the resource and
rewards of the UAVs. We solve a long-term profit maximization problem in terms
of the operator. Numerical results demonstrated that our algorithm outperforms
other benchmarks algorithm, and validated our solution.
