A Priority-Based Joint UAV Deployment and Task Scheduling Method in C-RAN With Multilayer MEC

The combination of cloud radio access network (C-RAN) and mobile edge computing (MEC) has been proven to effectively enhance network transmission rates and service capabilities. However, since the ground communication facilities in the architecture are fixed, have limited coverage and are easily damaged by natural disasters, some user requests may not be processed in a timely manner. This poses a significant challenge to the flexibility and post-disaster recovery capabilities of the architecture. To this end, this article studies how to deploy uncrewed aerial vehicles (UAVs) to assist the recovery of post-disaster communication network when some ground facilities in the architecture are destroyed, and how to perform reasonable task scheduling based on user task priorities to achieve rapid and effective rescue. Moreover, this article mathematically models the problem with the goal of maximizing the success rate of user task execution. Since the established model belongs to the mixed-integer nonlinear programming (MINLP) model, which is nonconvex and NP-Hard, this article designs a priority-based algorithm for joint UAV deployment and task scheduling to obtain high-quality suboptimal solutions. The algorithm employs a two-layer optimization architecture with the characteristics of low memory usage and low time complexity. The experimental results indicate that the proposed algorithm outperforms the baseline algorithms and is more effective in handling rescue tasks under different user scales.