Optimal scheduling strategy of AUV based on importance and age of information

In this paper, we consider a underwater wireless sensor network, which is composed of an autonomous underwater vehicle (AUV) and the underwater data collection stations. Constrained by limited resources, at each decision epoch the AUV selects one underwater data collection station to update the data and then uploads it to the surface base station. Different from other underwater communication models, we consider the influence of underwater environment on the AUV and develop an AUV model with random lifetime, meanwhile, we further propose that the information arrives randomly with different importance levels. The system model is formulated into a discounted Markov decision process with infinite horizon. Taking the age of information and the importance of information as the performance metrics, the optimal scheduling strategy of the AUV is developed, and the threshold structure characteristics of the optimal strategy are proved. Finally, the numerical examples are given to illustrate the theoretical results, and the impacts of system parameters on the optimal strategy and the value function are also investigated.