HAO-AVP: An Entropy-Gini Reinforcement Learning Assisted Hierarchical Void Repair Protocol for Underwater Wireless Sensor Networks

. 2026 Jan 20;26(2):684. doi: 10.3390/s26020684

Algorithm 2: Void Prediction and Identification

Input: Neighbors

N_{i}

, Energy History H_{E}

1: // --- Proactive Prediction (Background Process) ---

Update Markov Transition Matrix based on H_{E}

Calculate Probability P_{d a n g e r}

of neighbors entering “Endangered State”

IF J o i n t_{P r o b a b i l i t y} (P_{d a n g e r}) > T h r e s h o l d_{w a r n i n g}

THEN

5: Trigger Void Alert and update Neighbor List

6: END IF

7: // --- Real-time Identification (Forwarding Process) ---

8: IF no neighbor provides progress to Sink THEN

Broadcast V O I D_{D I S C O V E R Y}

(TTL)

10:

Receive H o p_{C o u n t}

feedback from neighbors

11: IF valid path exists THEN Update Routing Table

12: ELSE Trigger Hierarchical Repair (Algorithm 3)

13: END IF