Distributed time synchronization algorithm based on sequential belief propagation in wireless sensor networks

Abstract

In the context of the non-Gaussian delay model, the fully distributed time synchronization approach based on Gaussian belief propagation will lead to the decline of synchronization accuracy. This paper proposes a distributed time synchronization algorithm based on sequential belief propagation (SBP-DTS), which assumes that the network delay is unknown. SBP-DTS first establishes a factor graph (FG) model for the time synchronization problem of wireless sensor networks (WSNs), and then uses sequential belief propagation (BP) algorithms to estimate node clock parameters under an unknown random delay model. At the same time, in order to reduce the amount of data exchanged between nodes during the execution of sequential belief propagation algorithm, the weighted expectation–maximization (EM) algorithm is used to reduce the number of Gaussian mixture components in the message. At last, the performance of SBP-DTS is evaluated under asymmetric Gaussian and exponential delay models.