Robust Resource Scheduling for Air-Ground Cooperative Mobile Edge Computing

Abstract

Mobile edge computing (MEC) is a novel technology for enhancing the computation capacity of user equipment (UEs), by offloading the computation-intensive tasks at UEs to a base station. In the context of UAV-mounted MEC, state of the art only addresses the optimization of offloading and wireless/computing resource allocation in the presence of air-ground channels. In contrast, this paper addresses the optimization, considering both the time-varying/random terrestrial channels and the line-of-sight air-ground channels, where a robust optimization problem is formulated so as to minimize the energy consumption of the UAV and the UEs. In order to develop a resource scheduling scheme which enables energy-efficient air-ground cooperative MEC, we propose a joint iterative optimization algorithm by exploiting the weighted mean square error approach and S-procedure. Numerical results demonstrate that, compared to various baseline schemes, the proposed algorithm can effectively reduce the energy consumption in the presence of a large number of input tasks. Compared with the non-robust schemes, the proposed algorithm can reduce the energy consumption more stably.