AoI-Inspired Collaborative Information Collection for AUV-Assisted Internet of Underwater Things

In order to better explore the ocean, autonomous underwater vehicles (AUVs) have been widely applied to facilitate the information collection. However, considering the extremely large-scale deployment of sensor nodes in the Internet of Underwater Things (IoUT), a homogeneous AUV-enabled information collection system cannot support timely and reliable information collection considering the time-varying underwater environment as well as AUV's energy and mobility constraints. In this article, we propose a multi-AUV-assisted heterogeneous underwater information collection scheme for the sake of optimizing the peak Age of Information (AoI). Moreover, the limited service M/G/1 vacation queueing model is utilized to model the process of information exchange, where the optimal upper limit of the number of AUVs served in the queueing system as well the steady-state distribution of the queue length are derived. A low-complexity adaptive algorithm for adjusting the upper limit of the queuing length is also proposed. Finally, simulation results validate the effectiveness of our proposed scheme and algorithm, which outperform traditional methods in terms of the peak AoI.