Open Access

ARTICLE

Research on Time Synchronization Method Under Arbitrary Network Delay in Wireless Sensor Networks

Bing Hu¹, Feng Xiang², Fan Wu³, Jian Liu⁴, Zhe Sun¹, Zhixin Sun^1,*

1 Key Laboratory of Broadband Wireless Communication and Sensor Network Technology, Nanjing University of Posts and Telecommunications, Nanjing, 210003, China.
2 YuanTong Express Co. LTD, Shanghai, 201705, China.
3 Department of Computer Science, Tuskegee University, Tuskegee, AL, 36088, USA.
4 College of Information Engineering, Nanjing University of Finance and Economics, Nanjing, 210023, China.
* Corresponding Author: Zhixin Sun. Email: sunzx@njupt.edu.cn.

Computers, Materials & Continua 2019, 61(3), 1323-1344. https://doi.org/10.32604/cmc.2019.06414

Abstract

To cope with the arbitrariness of the network delays, a novel method, referred to as the composite particle filter approach based on variational Bayesian (VB-CPF), is proposed herein to estimate the clock skew and clock offset in wireless sensor networks. VB-CPF is an improvement of the Gaussian mixture kalman particle filter (GMKPF) algorithm. In GMKPF, Expectation-Maximization (EM) algorithm needs to determine the number of mixture components in advance, and it is easy to generate overfitting and underfitting. Variational Bayesian EM (VB-EM) algorithm is introduced in this paper to determine the number of mixture components adaptively according to the observations. Moreover, to solve the problem of data packet loss caused by unreliable links, we propose a robust time synchronization (RTS) method in this paper. RTS establishes an autoregressive model for clock skew, and calculates the clock parameters based on the established autoregressive model in case of packet loss. The final simulation results illustrate that VB-CPF yields much more accurate results relative to GMKPF when the network delays are modeled in terms of an asymmetric Gaussian distribution. Moreover, RTS shows good robustness to the continuous and random dropout of time messages.

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