A three-step underwater sensor network time synchronization protocol based on only the receiver

[ Instrument network instrument research and development ] One of the important prerequisites for realizing data fusion, energy management, transmission scheduling and other functions in the underwater sensor network is that all network nodes share the same time reference. Therefore, time synchronization technology is very important for underwater sensor networks.

Energy consumption and synchronization accuracy are two important factors to be considered when designing a time synchronization protocol. In response, Yan Shefeng’s team, a researcher at the Key Laboratory of Underwater Vehicle Information Technology, Institute of Acoustics, Chinese Academy of Sciences, proposed a three-step underwater sensor network time synchronization protocol based on only the receiving end, which uses silent nodes in the network to pair two active nodes. The time information exchange process between the monitoring, so as to achieve time synchronization with the active node. Related research results are published online in IEEE Internet of Things Journal.

Researchers combine this time synchronization protocol with support vector machine technology to estimate the clock frequency offset of the active node; calculate the maximum likelihood estimation (Maximum Likelihood Estimation, MLE) of the clock frequency offset of the silent node, designed The algorithm avoids the use of convex optimization toolbox and saves the amount of calculation; calculates the minimum variance unbiased estimate of the clock deviation of all nodes, and completes the time synchronization of the underwater sensor network.

Research shows that this time synchronization protocol, which takes into account both energy consumption and synchronization accuracy, reduces the number of time information exchanges in the network, has lower energy consumption and is faster than other existing protocols (such as LDA, JMLE and GMLLE). The synchronization accuracy is high, suitable for underwater sensor networks, and has good application prospects.

The research work was funded by the National Natural Science Foundation of China.