Autoregressive Integrated Model for Time Synchronization in Wireless Sensor Networks

Wasif Masood, J. F. Schmidt
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引用次数: 3

Abstract

Time synchronization is challenging in wireless sensor networks due to the use of low-precision oscillators and the limited computational capacity of resources limited sensor nodes. While several schemes exist, the performance analysis of a majority of them is based on simulations and fail to capture key features of real world deployments. This paper explores the use of autoregressive integrated moving average models to provide a general clock model for sensor nodes with low precision oscillators and limited computational power. Based on measurements with off-the-shelf sensor devices Z1, an autoregressive integrated model for time synchronization is proposed. We derive a synchronization scheme (ARI-Sync) based on this model and compare it against the well known Flooding Time Synchronization Protocol (FTSP) observing significantly improved accuracy, roughly doubling the resynchronization period of Z1 nodes for a typical wireless sensor network application.
无线传感器网络时间同步的自回归集成模型
由于使用低精度振荡器和有限的资源有限的传感器节点的有限计算能力,无线传感器网络中的时间同步是一个挑战。虽然存在几种方案,但大多数方案的性能分析都是基于模拟的,无法捕捉到真实世界部署的关键特征。本文探索使用自回归积分移动平均模型为具有低精度振荡器和有限计算能力的传感器节点提供通用时钟模型。基于现有传感器器件Z1的测量,提出了一种时间同步的自回归集成模型。我们基于该模型推导了一种同步方案(ARI-Sync),并将其与众所周知的泛洪时间同步协议(FTSP)进行了比较,观察到精度显着提高,对于典型的无线传感器网络应用,Z1节点的重新同步周期大约增加了一倍。
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