Distributed Synchronization on Weakly Connected Networks

Distributed synchronization for wireless networks is based on the mutual exchange of the same chirp-signature by nodes. Collisions of these signatures drive the system toward time and (carrier) frequency synchronization using distributed consensus algorithms. This letter investigates the convergence...

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Vydáno v:IEEE Communications Letters Ročník 21; číslo 7; s. 1577 - 1580
Hlavní autoři: Denic, Stojan, Georgiou, Orestis, Spagnolini, Umberto
Médium: Journal Article
Jazyk:angličtina
japonština
Vydáno: New York IEEE 01.07.2017
Institute of Electrical and Electronics Engineers (IEEE)
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Algebraic connectivity
Algebraic connectivity; consensus methods; distributed inference; distributed synchronization; laplacian spectrum; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering
Asymptotic properties
Bridges
Chirp
Clusters
Collisions
consensus methods
Convergence
Distortion
distributed inference
distributed synchronization
Eigenvalues and eigenfunctions
Frequency synchronization
Laplace equations
laplacian spectrum
Links
Mean square values
Signatures
Symmetric matrices
Synchronization
Time synchronization
Topology optimization
Wireless networks
ISSN:1089-7798, 1558-2558
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Abstract Distributed synchronization for wireless networks is based on the mutual exchange of the same chirp-signature by nodes. Collisions of these signatures drive the system toward time and (carrier) frequency synchronization using distributed consensus algorithms. This letter investigates the convergence and the asymptotic distortion properties on noisy networks when neighboring clusters of nodes are weakly connected to each other only through a subset of nodes and bridging links. These heavily connected clusters act as macroagents, and the consensus properties of the ensemble depend on the number of bridge links between them. The convergence rate and mean square synchronization deviation are derived as functions of the number of bridge links for different examples of weakly connected noisy networks via the analytic calculation of Laplacian spectra. Our approach facilitates the study of network topology optimization for distributed synchronization.
AbstractList Distributed synchronization for wireless networks is based on the mutual exchange of the same chirp-signature by nodes. Collisions of these signatures drive the system toward time and (carrier) frequency synchronization using distributed consensus algorithms. This letter investigates the convergence and the asymptotic distortion properties on noisy networks when neighboring clusters of nodes are weakly connected to each other only through a subset of nodes and bridging links. These heavily connected clusters act as macroagents, and the consensus properties of the ensemble depend on the number of bridge links between them. The convergence rate and mean square synchronization deviation are derived as functions of the number of bridge links for different examples of weakly connected noisy networks via the analytic calculation of Laplacian spectra. Our approach facilitates the study of network topology optimization for distributed synchronization.
Author Georgiou, Orestis
Spagnolini, Umberto
Denic, Stojan
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SubjectTerms Algebraic connectivity
Algebraic connectivity; consensus methods; distributed inference; distributed synchronization; laplacian spectrum; Modeling and Simulation; Computer Science Applications1707 Computer Vision and Pattern Recognition; Electrical and Electronic Engineering
Asymptotic properties
Bridges
Chirp
Clusters
Collisions
consensus methods
Convergence
Distortion
distributed inference
distributed synchronization
Eigenvalues and eigenfunctions
Frequency synchronization
Laplace equations
laplacian spectrum
Links
Mean square values
Signatures
Symmetric matrices
Synchronization
Time synchronization
Topology optimization
Wireless networks
Title Distributed Synchronization on Weakly Connected Networks
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Volume 21
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