Distributed clock skew and offset estimation from relative measurements in mobile networks with Markovian switching topology

Liao, Chenda; Barooah, Prabir

doi:10.1016/j.automatica.2013.07.015

Cited by 31 publications

(30 citation statements)

References 25 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is in contrast to approaches where statistical models of disturbances are assumed [13,24,25], or to approaches that are focused on averaging initial samples [2,9,[26][27][28], or to methods where the estimation variables are static parameters [12,18,[29][30][31], or to those where only local measurements are diffused over the network [32]. Compared to [2,7,9,13,26,28], we do not use the consensus algorithms in the estimator, and compared to [9], we do not use the Laplacian matrix associated to the communication graph to design the estimator.…”

Section: Introductionmentioning

confidence: 90%

Model based peer-to-peer estimator over wireless sensor networks with lossy channels

Fischione

Speranzon³

2015

Automatica

View full text Add to dashboard Cite

In this paper, the design methods and fundamental performance analysis of an adaptive peer-to-peer estimator are established for networks exhibiting message losses. Based on a signal state model, estimates are locally computed at each node of the network by adaptively filtering neighboring nodes' estimates and measurements communicated over lossy channels. The computation is based on a distributed optimization approach that guarantees the stability of the estimator while minimizing the estimation error variance. The fundamental performance limitations of the estimator are established based on the variance of the estimation error in relation to the message loss process. Numerical simulations validate the theoretical analysis and illustrate the performance with respect to other estimators.

show abstract

Section: Introductionmentioning

confidence: 90%

Model based peer-to-peer estimator over wireless sensor networks with lossy channels

Fischione

Speranzon³

2015

Automatica

View full text Add to dashboard Cite

show abstract

“…In Carli, Chiuso, Schenato, and Zampieri (2011), the authors introduce a protocol to synchronize a network of controlled discrete-time double integrators which are nonidentical, with unknown model parameters and subject to additive measurement and process noise. In Liao and Barooah (2013), by assuming the dynamic nature of the network to be modeled as a Markov chain, the authors propose a distributed algorithm for the estimation of scalar parameters from noisy relative measurements. In particular, they prove that the estimates are mean square convergent under fairly weak assumptions.…”

Section: Related Workmentioning

confidence: 99%

Clock synchronization protocol for wireless sensor networks with bounded communication delays

2015

View full text Add to dashboard Cite

“…We model the switching of the network topologies as a Markov chain; the reasonableness of this model for mobile networks has been established in [11]. We model the switching of the network topologies as a Markov chain; the reasonableness of this model for mobile networks has been established in [11].…”

Section: Markovian Topology Switchingmentioning

confidence: 99%

“…Recalling that L bi and D i correspond to  i ∈ G, we can use the same formula as that in (11) to defineL b andD. This means every graph in the state space of the chain occurs infinitely often.…”

Section: Markovian Topology Switchingmentioning

confidence: 99%

“…They typically perform synchronization by estimating skews and/or offsets and then computing the global time from them. The algorithm in [11] is called JaT algorithm (Jacobi-type) due to its similarity to the Jacobi algorithm first proposed in [8]. In these algorithms, estimates of a log-skews (and offsets) are obtained from noisy measurements of the difference of log-skews (and offsets) between pairs of neighbors.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

An Algorithm for Accurate Distributed Time Synchronization in Mobile Wireless Sensor Networks from Noisy Difference Measurements

Liao¹,

Barooah

2016

Asian Journal of Control

Self Cite

View full text Add to dashboard Cite

We propose a distributed algorithm for time synchronization in mobile wireless sensor networks. The problem of time synchronization is formulated as nodes estimating their skews and offsets from noisy difference measurements of offsets and logarithm of skews; the measurements acquired by time-stamped message exchanges between neighbors. The algorithm ensures that the estimation error is mean square convergent (variance converging to 0) under certain conditions. A sequence of scheduled update instants is used to meet the requirement of decreasing time-varying gains that need to be synchronized across nodes with unsynchronized clocks. Moreover, a modification on the algorithm is also presented to improve the initial convergence speed. Simulations indicate that highly accurate global time estimates can be achieved with the proposed algorithm for long time durations, while the errors in competing algorithms increase over time.where the scalar parameters u , u are called its skew (the relative speed of the clock with respect to t) and offset Manuscript

show abstract

Distributed clock skew and offset estimation from relative measurements in mobile networks with Markovian switching topology

Cited by 31 publications

References 25 publications

Model based peer-to-peer estimator over wireless sensor networks with lossy channels

Model based peer-to-peer estimator over wireless sensor networks with lossy channels

Clock synchronization protocol for wireless sensor networks with bounded communication delays

An Algorithm for Accurate Distributed Time Synchronization in Mobile Wireless Sensor Networks from Noisy Difference Measurements

Contact Info

Product

Resources

About