Joint Optimization of Resource Allocation and Multi-UAV Trajectory in Space-Air-Ground IoRT Networks

Abstract

Given suburban and rural areas with limited ground infrastructure, the Internet of Remote Things (IoRT) is considered as a promising way to provide services for smart devices that have low computing capability and wide coverage. In this paper, we present a multiple unmanned aerial vehicle (UAV) space-air- ground (SAG) IoRT computing offloading network, which provides IoRT devices powerful edge and cloud computing services. Then, the resource allocation scheme under partial computing offloading mode is studied, which jointly optimizes device scheduling, resource partitioning, bit allocation and UAV trajectory to minimize the weighted total system energy consumption with considering the constraints of UAV mobility and obstacle avoidance. To solve this non-convex problem with coupled variables, we decompose the problem into three sub-problems, then the Lagrange dual decomposition method and the successive convex optimization (SCO) technique are adopted. Simulation results demonstrate the effectiveness of the proposed algorithm in terms of saving energy.