AoI Minimization Scheduling Using Integrated Collection-Relay in Multi-AUV Multi-Hop Underwater Networks

Underwater surveillance systems require a multi-AUV-based multi-hop underwater data collection system to deliver data from sensor nodes distributed over a wide underwater area to a buoy. In this system, the node-visit of the data collection AUV and the relay transmission to the relay AUV jointly affect the end-to-end Age of Information (AoI) from each node to the buoy. This paper proposes a discrete soft actor–critic (SAC)-based integrated scheduling policy that jointly determines the node-visit and relay transmission of the data collection AUV within a single decision-making process. The proposed method represents the end-to-end information update process from data collection to buoy update in the state design and derives a relationship showing that the accumulated node-wise max AoI increment corresponds to the Mean Peak AoI and uses this increment as the decision step reward. Computer simulation results show that the proposed method achieves a lower Mean Peak AoI and higher Delivery than conventional methods that determine node visits and relay transmissions separately, including Visit-Only SAC, Age-Greedy threshold, and Age-Gain TX. The cumulative distribution function (CDF) analysis also shows more stable performance across episodes.