Abstract
As a result of the influence of clock drift and uncertainty delay in synchronous message transmission, the clock synchronization model based on statistical distribution cannot accurately describe clock deviation. This model also requires a large number of timestamp samples that cause a storage occupation issue for wireless sensor nodes with limited resources. The modeling method based on grey prediction has advantages of low sample demand and simple modeling process. However, the accuracy of the existing clock synchronization models needs to be improved. Based on the grey prediction theory, this paper proposes an adaptive fractional-order operator clock synchronization algorithm considering uncertainty delay. First, based on the clock model and clock offset model, the frequency offset between nodes is optimized by taking the mean on the clock frequencies. Second, a grey prediction algorithm based on a fractional-order operator is proposed by estimating the uncertainty delay in message transmission to obtain the clock offset. Finally, the order of the fractional-order accumulation is adjusted adaptively in the grey prediction model according to the collected timestamp sample values so that the estimation of the uncertainty delay is more accurate, thereby improving the accuracy of the clock offset. Compared with the first-order accumulative grey prediction clock synchronization algorithms and timing-sync protocol for sensor networks, the proposed scheme improved the synchronization accuracy by 29.18% and 44.01%, respectively, and reduced the variance of the clock offset by 48.66% and 64.89%. Thus, the proposed algorithm is characterized by improved stability.
Highlights
Clock synchronization between different nodes in wireless sensor networks (WSNs) is an important basis for coordinating network operations [1]
To improve the clock synchronization accuracy, this study estimates the uncertainty delay in clock synchronization from the perspective of statistical signal processing and proposes an adaptive fractional-order operator clock synchronization algorithm based on the grey prediction model
After frequency offset optimization, a fractional-order operator clock model based on grey prediction theory is proposed to estimate the uncertainty delay in synchronous message transmission and an accurate clock offset is obtained
Summary
Clock synchronization between different nodes in wireless sensor networks (WSNs) is an important basis for coordinating network operations [1]. Energy management, transmission scheduling, and other processes require sensor nodes to be clock synchronized [2, 3]. Clock synchronization usually relies on the way of message transmission between the nodes. The time delay is generated in the stage of message transmission between the nodes, and the delay can be usually divided into two parts: certainty delay and uncertainty delay. As the former can be directly measured, the latter is one of the key factors that affect the accuracy of synchronization. The influence of uncertainty delay on synchronization accuracy in message transmission can be reduced by establishing an accurate prediction model [5, 6]
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