Resource allocation for multi‐UAV‐assisted mobile edge computing to minimize weighted energy consumption

This paper studies a multi-unmanned aerial vehicle (UAV) assisted mobile edge computing (MEC) system, where multiple UAVs equipped with MEC server are deployed to provide offloading services for ground users limited local resources. Specifically, each user divides its tasks into two parts: one part is offloaded the associated UAV calculation, and remaining calculated locally. It aimed minimize weighted energy consumption of all by jointly optimizing trajectory, scheduling, central processing unit (CPU) calculation frequency allocation, time allocation. However, formulated problem mixed integer non-convex problem, which challenging obtain an optimal solution. In order effectively solve this, efficient two-stage iterative algorithm based on alternative optimization proposed decomposing original sub-problems suboptimal The simulation results show that scheme superior other benchmark schemes in reducing system consumption.