Admission Control Mechanism for Offloading Tasks in UAV-Assisted Edge Computing

In light of the dynamic nature of user requirements in edge computing networks, as well as the communication congestion stemming from several users offloading tasks, this study proposes an admission control mechanism for an Unmanned Aerial Vehicle (UAV)-assisted edge computing system. The aim is to maximize service provider revenue while maintaining Quality of Service (QoS) for users. First, a server communication threshold structure is established based on factors such as user channel quality and base station communication bandwidth, mitigating excessively high transmission delays for tasks. Users without a connection to a base station can opt to offload tasks to a UAV or process them directly on their terminal devices. Second, an optimal threshold for UAV task reception is determined considering the limited resources and operating costs of UAVs. UAVs perform preprocessing operations on tasks and offload the preprocessed tasks to the base station to reduce task-processing delays. This stage is modeled as a birth and death process, with matrix geometry methods employed to derive the probability distribution of the system's stable state and the expected benefits for users. Subsequently, the optimal UAV task reception threshold is determined, optimal prices are set, and the UAV revenue is maximized under high task concurrency conditions. The simulation results demonstrate the significant advantages of the proposed solution algorithm in terms of revenue of service providers and user QoS.