Consensus-Based Time Synchronization Using Bayesian Estimation in Wireless Sensor Networks Under Communication Delays

Abstract

Time synchronization is crucial for various applications in wireless sensor networks. Consensus-based time synchronization is an essential distributed strategy for its high precision, robustness, and scalability. In practical networks, however, communication delays are not ignorable and make time messages received inaccurate, which is the fundamental limitation for time synchronization. It was pointed out that if a consensus-based time synchronization algorithm does not consider the influence of delays, it may be divergent under the scenario with delays. Making use of the knowledge of statistical signal processing to develop an efficient relative skew estimator is a viable method to restrain communication delays. In this article, we propose a relative skew estimator based on Bayesian estimation theory to counteract the impact of time delays, which improves the estimation accuracy while reducing the memory requirement. By applying the presented estimator to average consensus protocol, precise network-wide synchronization is achieved in the presence of delays. In addition, the proof of convergence of the proposed scheme is given by theoretical analysis. Simulation results demonstrate the effectiveness of the proposed scheme and show that our algorithm outperforms other similar algorithms in terms of synchronization accuracy under random delays.