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In this paper, we consider a UAV-enabled MEC platform that serves multiplemobile ground users with random movements and task arrivals. We aim to minimizethe average weighted energy consumption of all users subject to the average UAVenergy consumption and data queue stability constraints. To control the systemoperation in sequential time slots, we formulate the problem as a multi-stagestochastic optimization, and propose an online algorithm that optimizes theresource allocation and the UAV trajectory in each stage. We adopt Lyapunovoptimization to convert the multi-stage stochastic problem into per-slotdeterministic problems with much less optimizing variables. To tackle thenon-convex per-slot problem, we use the successive convex approximation (SCA)technique to jointly optimize the resource allocation and the UAV movement.Simulation results show that the proposed online algorithm can satisfy theaverage UAV energy and queue stability constraints, and significantlyoutperform the other considered benchmark methods in reducing the energyconsumption of ground users.

Dynamic Trajectory and Offloading Control of UAV-enabled MEC under User Mobility