Energy Consumption Minimization Scheme with Dynamic Computational Windows for UAV-Assisted Edge Computing

As unmanned aerial vehicles (UAVs) demonstrate significant potential for edge computing, their capacity to rapidly deploy computing services at user locations offers considerable advantages. However, their limited operational time poses a significant challenge for current UAV-assisted edge computing solutions. This paper addresses the optimal scheduling of UAV computing resources and introduces a computing resource scheduling scheme based on dynamic computational windows allocation (CRS-DW). Simulation results demonstrate that the CRS-DW algorithm significantly outperforms existing benchmark algorithms in performance.