Decentralised minimum-time average consensus in digraphs

Themistoklis Charalambous; Ye Yuan; Tao Yang; Wei Pan; Christoforos N. Hadjicostis; Michael Johansson

doi:10.1109/CDC.2013.6760277

Decentralised minimum-time average consensus in digraphs

Themistoklis Charalambous, Ye Yuan, Tao Yang, Wei Pan, Christoforos N. Hadjicostis, Michael Johansson

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Scientific › peer-review

10 Citations (Scopus)

Abstract

Distributed algorithms for average consensus in directed graphs are typically asymptotic in the literature. In this work, we propose a protocol to distributively reach average consensus in a finite number of steps on interconnection topologies that form strongly connected directed graphs (digraphs). The average consensus value can be computed, based exclusively on local observations at each component, by running a protocol that requires each component to observe and store its own value over a finite and minimal number of steps, and to have knowledge of the number of its out-going links (i.e., the number of components to which it sends information). The proposed algorithm is demonstrated via illustrative examples.

Original language	English
Title of host publication	2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013
Publisher	IEEE
Pages	2617-2622
Number of pages	6
ISBN (Print)	9781467357173
DOIs	https://doi.org/10.1109/CDC.2013.6760277
Publication status	Published - 2013
MoE publication type	A4 Article in a conference publication
Event	IEEE Conference on Decision and Control - Florence, Italy Duration: 10 Dec 2013 → 13 Dec 2013 Conference number: 52

Conference

Conference	IEEE Conference on Decision and Control
Abbreviated title	CDC
Country/Territory	Italy
City	Florence
Period	10/12/2013 → 13/12/2013

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title = "Decentralised minimum-time average consensus in digraphs",

abstract = "Distributed algorithms for average consensus in directed graphs are typically asymptotic in the literature. In this work, we propose a protocol to distributively reach average consensus in a finite number of steps on interconnection topologies that form strongly connected directed graphs (digraphs). The average consensus value can be computed, based exclusively on local observations at each component, by running a protocol that requires each component to observe and store its own value over a finite and minimal number of steps, and to have knowledge of the number of its out-going links (i.e., the number of components to which it sends information). The proposed algorithm is demonstrated via illustrative examples.",

author = "Themistoklis Charalambous and Ye Yuan and Tao Yang and Wei Pan and Hadjicostis, {Christoforos N.} and Michael Johansson",

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note = "IEEE Conference on Decision and Control, CDC ; Conference date: 10-12-2013 Through 13-12-2013",

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AU - Charalambous, Themistoklis

AU - Yuan, Ye

AU - Yang, Tao

AU - Pan, Wei

AU - Hadjicostis, Christoforos N.

AU - Johansson, Michael

N1 - Conference code: 52

PY - 2013

Y1 - 2013

N2 - Distributed algorithms for average consensus in directed graphs are typically asymptotic in the literature. In this work, we propose a protocol to distributively reach average consensus in a finite number of steps on interconnection topologies that form strongly connected directed graphs (digraphs). The average consensus value can be computed, based exclusively on local observations at each component, by running a protocol that requires each component to observe and store its own value over a finite and minimal number of steps, and to have knowledge of the number of its out-going links (i.e., the number of components to which it sends information). The proposed algorithm is demonstrated via illustrative examples.

AB - Distributed algorithms for average consensus in directed graphs are typically asymptotic in the literature. In this work, we propose a protocol to distributively reach average consensus in a finite number of steps on interconnection topologies that form strongly connected directed graphs (digraphs). The average consensus value can be computed, based exclusively on local observations at each component, by running a protocol that requires each component to observe and store its own value over a finite and minimal number of steps, and to have knowledge of the number of its out-going links (i.e., the number of components to which it sends information). The proposed algorithm is demonstrated via illustrative examples.

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U2 - 10.1109/CDC.2013.6760277

DO - 10.1109/CDC.2013.6760277

M3 - Conference contribution

AN - SCOPUS:84902324372

SN - 9781467357173

SP - 2617

EP - 2622

BT - 2013 IEEE 52nd Annual Conference on Decision and Control, CDC 2013

PB - IEEE

T2 - IEEE Conference on Decision and Control

Y2 - 10 December 2013 through 13 December 2013

ER -

Decentralised minimum-time average consensus in digraphs

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