ADMM for consensus on colored networks

João F. C. Mota; João M. F. Xavier; Pedro M. Q. Aguiar; Markus Püschel

doi:10.1109/CDC.2012.6426225

ADMM for consensus on colored networks

João F. C. Mota^*, João M. F. Xavier, Pedro M. Q. Aguiar, Markus Püschel

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

6 Citations (Scopus)

Abstract

We propose a novel distributed algorithm for one of the most fundamental problems in networks: the average consensus. We view the average consensus as an optimization problem, which allows us to use recent techniques and results from the optimization area. Based on the assumption that a coloring scheme of the network is available, we derive a decentralized, asynchronous, and communication-efficient algorithm that is based on the Alternating Direction Method of Multipliers (ADMM). Our simulations with other state-of-the-art consensus algorithms show that the proposed algorithm is the one exhibiting the most stable performance across several network models.

Original language	English
Title of host publication	2012 IEEE 51st Annual Conference on Decision and Control
Pages	5116-5121
Number of pages	6
ISBN (Electronic)	978-1-4673-2066-5
DOIs	https://doi.org/10.1109/CDC.2012.6426225
Publication status	Published - 2012

ASJC Scopus subject areas

Control and Systems Engineering
Modelling and Simulation
Control and Optimization

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10.1109/CDC.2012.6426225

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title = "ADMM for consensus on colored networks",

abstract = "We propose a novel distributed algorithm for one of the most fundamental problems in networks: the average consensus. We view the average consensus as an optimization problem, which allows us to use recent techniques and results from the optimization area. Based on the assumption that a coloring scheme of the network is available, we derive a decentralized, asynchronous, and communication-efficient algorithm that is based on the Alternating Direction Method of Multipliers (ADMM). Our simulations with other state-of-the-art consensus algorithms show that the proposed algorithm is the one exhibiting the most stable performance across several network models.",

author = "Mota, {Jo{\~a}o F. C.} and Xavier, {Jo{\~a}o M. F.} and Aguiar, {Pedro M. Q.} and Markus P{\"u}schel",

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AU - Mota, João F. C.

AU - Xavier, João M. F.

AU - Aguiar, Pedro M. Q.

AU - Püschel, Markus

PY - 2012

Y1 - 2012

N2 - We propose a novel distributed algorithm for one of the most fundamental problems in networks: the average consensus. We view the average consensus as an optimization problem, which allows us to use recent techniques and results from the optimization area. Based on the assumption that a coloring scheme of the network is available, we derive a decentralized, asynchronous, and communication-efficient algorithm that is based on the Alternating Direction Method of Multipliers (ADMM). Our simulations with other state-of-the-art consensus algorithms show that the proposed algorithm is the one exhibiting the most stable performance across several network models.

AB - We propose a novel distributed algorithm for one of the most fundamental problems in networks: the average consensus. We view the average consensus as an optimization problem, which allows us to use recent techniques and results from the optimization area. Based on the assumption that a coloring scheme of the network is available, we derive a decentralized, asynchronous, and communication-efficient algorithm that is based on the Alternating Direction Method of Multipliers (ADMM). Our simulations with other state-of-the-art consensus algorithms show that the proposed algorithm is the one exhibiting the most stable performance across several network models.

UR - http://www.scopus.com/inward/record.url?scp=84874235676&partnerID=8YFLogxK

U2 - 10.1109/CDC.2012.6426225

DO - 10.1109/CDC.2012.6426225

M3 - Conference contribution

AN - SCOPUS:84874235676

SN - 978-1-4673-2065-8

SP - 5116

EP - 5121

BT - 2012 IEEE 51st Annual Conference on Decision and Control

ER -

ADMM for consensus on colored networks

Abstract

ASJC Scopus subject areas

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