An UAV and EV based mobile edge computing system for total delay minimization

Abstract

In this paper, we studied a collaborative mobile edge computing(MEC) system based on unmanned aerial vehicle(UAV) and electric vehicle(EV), in which the EV moves to the target area carrying the UAV to provide computing and offloading services to the user equipment(UE). We aimed at minimizing all the UE tasks delay by optimizing the task offloading ratio, the UAV hovering position, and the computing resource allocation of EV and UAV, respectively. The problem was formulated as a Nonlinear Programming(NLP) problem, and we decomposed it into EV related subproblem and UAV related subproblem by the Block-Coordinate Descent(BCD) method. For EV related subproblem, we obtained the optimal offloading ratio by making the computing time on the UAV equal to its offloading time, and proved the method is feasible. For the UAV related subproblem, we introduced the non-orthogonal multiple access(NOMA) and successive interference cancellation(SIC) techniques to improve the communication efficiency, and we obtained the optimal hovering position by using the successive convex approximation(SCA) technique twice to transfer this subproblem into a convex problem. Finally, an overall iterative algorithm was proposed. To verify the effectiveness of our algorithm, we compared our scheme with ‘PSO’, ‘GT’, ‘MC’ and benchmark algorithm.