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

机译:基于无线传感器网络中顺序信仰传播的分布式时间同步算法

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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.
机译:在非高斯延迟模型的背景下,基于高斯信念传播的完全分布时间同步方法将导致同步精度的下降。 本文提出了一种基于顺序信念传播(SBP-DTS)的分布式时间同步算法,其假设网络延迟未知。 SBP-DTS首先为无线传感器网络(WSN)的时间同步问题建立一个因子图(FG)模型,然后使用顺序信念传播(BP)算法来估计未知随机延迟模型下的节点时钟参数。 同时,为了减少节点之间交换的数据量,在执行顺序信念传播算法期间,加权期望 - 最大化(EM)算法用于减少消息中的高斯混合组件的数量。 最后,在非对称高斯和指数延迟模型下评估SBP-DTS的性能。

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