Underwater Network Time Synchronization Method Based on Probabilistic Graphical Models

Abstract

In underwater clustering and benchmark networks, nodes need to reduce the rate and energy consumption of acoustic communication while ensuring synchronization accuracy. In large-scale networks, the improvement in the efficiency of existing network time synchronization often relies on the optimization of topological structures, and the improvement in efficiency within local areas is limited. This paper proposes a method to synchronize underwater time using the probability graph model. The method utilizes the positional and motion status information of sensor networks to construct a factor graph model for distributed network synchronization. By simplifying the marginal probability density function of the system clock difference, it can quickly calculate the clock difference parameters of nodes, thereby effectively improve the synchronization efficiency. The experimental results show that the method can complete global time synchronization within a cycle while achieving a clock difference correction accuracy higher than seconds, which significantly optimized the synchronization cycle and efficiency, and reduced the energy consumption of the acoustic communication.

Keywords

• underwater network time synchronization
• factor graph model
• distributed networking