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AdaSynch: A General Adaptive Clock Synchronization Scheme Based on Kalman Filter for WSNs

机译:AdaSynch:一种基于卡尔曼滤波器的WSN通用自适应时钟同步方案

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Efficient and accurate clock synchronization is a challenge for wireless sensor networks (WSNs). Unlike previous works on clock synchronization in WSNs that consider communication delay as the main cause of clock inaccuracy, we propose a new adaptive synchronization scheme, AdaSynch, which considers the principium of the clock. We aim to overcome the challenges posed by WSNs’ resource constraints such as limited energy and bandwidth, low precision oscillators and random factors. By implementing some experiments on TelosB platform, we find that the clock system switches between multiple clock models. Motivated by experiment results, we establish a general clock model which describes the clock offset in terms of the oscillators. We then design two kinds of basic Kalman filter models to achieve clock synchronization. In order to execute Kalman filtering, we propose a recursion method based on the Expectation-Maximization (EM) algorithm to access the parameters of the Kalman filter model adaptively. To describe alternation in the clock model, we propose a Multimodel Kalman filter, and put forward an adaptive method based on hypothesis testing to describe these complexities in the clock model. We demonstrate the performance gains of our scheme through experiments using different Kalman filter models based on experiment data.
机译:对于无线传感器网络(WSN)而言,高效,准确的时钟同步是一项挑战。与先前将通信延迟视为时钟不准确的主要原因的WSN中的时钟同步工作不同,我们提出了一种新的自适应同步方案AdaSynch,它考虑了时钟的原理。我们旨在克服无线传感器网络的资源限制所带来的挑战,例如有限的能量和带宽,低精度的振荡器和随机因素。通过在TelosB平台上进行一些实验,我们发现时钟系统在多个时钟模型之间切换。根据实验结果,我们建立了一个通用的时钟模型,该模型描述了振荡器的时钟偏移。然后,我们设计两种基本的卡尔曼滤波器模型来实现时钟同步。为了执行卡尔曼滤波,我们提出了一种基于期望最大化(EM)算法的递归方法,以自适应地访问卡尔曼滤波模型的参数。为了描述时钟模型中的交替,我们提出了一种多模型卡尔曼滤波器,并提出了一种基于假设检验的自适应方法来描述时钟模型中的这些复杂性。我们通过使用基于实验数据的不同卡尔曼滤波器模型进行实验,证明了该方案的性能提升。

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