Consensus Clock Synchronization for Wireless Sensor Networks

Maggs, Michael Kevin; O'Keefe, S.G.; Thiel, David V.

doi:10.1109/jsen.2011.2182045

Cited by 165 publications

(116 citation statements)

References 17 publications

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“…These protocols include: RBS [5], TPSN [6], FTSP [7], Firefly synchronization method [8,14], TSMP [13] and DCTS [10,15].…”

Section: Related Workmentioning

confidence: 99%

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A Novel Two-way Time Synchronization Protocol for Fusion Application

Pang

Wu³

et al. 2016

IJFGCN

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“…These protocols include: RBS [5], TPSN [6], FTSP [7], Firefly synchronization method [8,14], TSMP [13] and DCTS [10,15].…”

Section: Related Workmentioning

confidence: 99%

“…DCTS refers to some distributed consensus time synchronization algorithms [10,15]. In DCTS, nodes periodically broadcast their own local time to make neighbors synchronized.…”

Section: Related Workmentioning

confidence: 99%

A Novel Two-way Time Synchronization Protocol for Fusion Application

Pang

Wu³

et al. 2016

IJFGCN

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“…Thus, the likelihood function can be obtained from Equation (53), and it is denoted by p(A i,j , A j,i |β i , β j ).…”

Section: Belief-based Synchronization Algorithmsmentioning

confidence: 99%

“…However, the message delays are not considered in these algorithms, and their performance degenerates significantly when message delays exist [46]. Other consensus-based distributed synchronization algorithms, such as [52,53], typically suffer from slow convergence speed and require a high number of data packages [22]. To overcome this issue, Berger et al [54] recently presented a fully-distributed low-complexity consensus-based synchronization algorithm for embedded WSNs.…”

Section: Consensus-based Synchronization Algorithmsmentioning

confidence: 99%

An Overview of a Class of Clock Synchronization Algorithms for Wireless Sensor Networks: A Statistical Signal Processing Perspective

Jeske

Serpedin

2015

Algorithms

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Recently, wireless sensor networks (WSNs) have drawn great interest due to their outstanding monitoring and management potential in medical, environmental and industrial applications. Most of the applications that employ WSNs demand all of the sensor nodes to run on a common time scale, a requirement that highlights the importance of clock synchronization. The clock synchronization problem in WSNs is inherently related to parameter estimation. The accuracy of clock synchronization algorithms depends essentially on the statistical properties of the parameter estimation algorithms. Recently, studies dedicated to the estimation of synchronization parameters, such as clock offset and skew, have begun to emerge in the literature. The aim of this article is to provide an overview of the state-of-the-art clock synchronization algorithms for WSNs from a statistical signal processing point of view. This article focuses on describing the key features of the class of clock synchronization algorithms that exploit the traditional two-way message (signal) exchange mechanism. Upon introducing the two-way message exchange mechanism, the main clock offset estimation algorithms for pairwise synchronization of sensor nodes are first reviewed, and their performance is compared. The class of fully-distributed clock offset estimation algorithms for network-wide synchronization is then surveyed. The paper concludes with a list of open research problems pertaining to clock synchronization of WSNs.

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“…This background is required to understand network synchronization and localization algorithms, as well as fundamental performance bounds [63]. In Chapter 5, we revisit the synchronization (and ranging) [33, 45,52,57,82,85,110,117,134,142] and localization [11,98,107,115,135] problem, dealing specifically with separate approaches, whereby localization is based on distance measurements and distance differences, obtained after synchronization is completed. Practical implementations and the combination of recently proposed methods from both fields are analyzed.…”

Section: Introductionmentioning

confidence: 99%