Resource Allocation and Trajectory Optimization of the U-MEC System Based on Contractual Relationship Under the Incentive of Revenue

The Unmanned Aerial Vehicles (UAVs)-enabled Mobile Edge Computing (U-MEC) system, which is a hot research point, has been reckoned as an effective way to deal with the digital big bang. Considering the relationship between users and the U A V, this paper proposes a U - MEC application scenario based on a contractual relationship and a revenue scheme to enhance the efficiency of energy utilization and incentive the UAV to serve for the noncontracted users. We jointly optimize the UAV's service user set, communication resources and trajectory under the constraints of the energy and different types of user demands to maximize the UAV's revenue. This is a mixed integer nonlinear programming (MINLP) challenge, which is rather laborious to get the standard answer with the expansion of user set size. Considering the complexity and feasibility of the algorithm, we adopt a solution based on the Successive Convex Approximation (SCA) technology to tackle. Finally, the simulation results verify that by adopting the SCA algorithm, the UAV can gain greater revenue than the benchmark algorithms.