LAUSR

The Space-Air-Ground Power Internet of Things (SAG-PIoT) can meet the communication needs of Power Internet of Things (PIoT) devices in localities with insufficient ground base station coverage. Considering that the battery capacity of PIoT devices is limited and difficult to be replaced, we use unmanned aerial vehicles (UAVs) to assist wireless power transmission (WPT) in the SAG-PIoT to ensure the network service quality and safe and stable operation of PIoT. In this paper, we put forward a novel WPT enabled SAG-PIoT architecture, based on which we investigate the dynamic task offloading and resource scheduling, and propose a joint online optimization algorithm for task assignment, local computing resource allocation, association control and UAV computing resource allocation to minimize the long-term time-averaged network operation cost. Since the coupling of task offloading and resource scheduling in the long-term stochastic optimization problem, it is decoupled into three subproblems to be solved separately using Lyapunov optimization. Moreover, we analyze the stability and sustainability of the proposed algorithm and reveal the tradeoff between the network stability and optimal network operation cost. Simulations show that the proposed algorithm has advantageous performances with respect of network stability, energy consumption and network operation cost compared to other benchmark algorithms.