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Conference Paper: Fast convergence for consensus in dynamic networks

TitleFast convergence for consensus in dynamic networks
Authors
KeywordsConvergence time
Dynamic network
Fast convergence
Time step
Underlying networks
Weighted averages
Issue Date2011
PublisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/
Citation
The 38th International Colloquium on Automata, Languages and Programming (ICALP 2011), Zurich, Switzerland, 4-8 July 2011. In Lecture Notes in Computer Science, 2011, v. 6756 pt. 2, p. 514-525 How to Cite?
Abstract
We study the convergence time required to achieve consensus in dynamic networks. In each time step, a node's value is updated to some weighted average of its neighbors' and its old values. We study the case when the underlying network is dynamic, and investigate different averaging models. Both our analysis and experiments show that dynamic networks exhibit fast convergence behavior, even under very mild connectivity assumptions. © 2011 Springer-Verlag.
DescriptionLNCS v. 3756 entitled: Automata, languages and programming : 38th international colloquium, ICALP 2011 ... proceedings
Persistent Identifierhttp://hdl.handle.net/10722/152001
ISBN
ISSN
2013 SCImago Journal Rankings: 0.310
References

 

Author Affiliations
  1. The University of Hong Kong
DC FieldValueLanguage
dc.contributor.authorChan, HTHen_US
dc.contributor.authorNing, Len_US
dc.date.accessioned2012-06-26T06:32:18Z-
dc.date.available2012-06-26T06:32:18Z-
dc.date.issued2011en_US
dc.identifier.citationThe 38th International Colloquium on Automata, Languages and Programming (ICALP 2011), Zurich, Switzerland, 4-8 July 2011. In Lecture Notes in Computer Science, 2011, v. 6756 pt. 2, p. 514-525en_US
dc.identifier.isbn978-364222011-1-
dc.identifier.issn0302-9743en_US
dc.identifier.urihttp://hdl.handle.net/10722/152001-
dc.descriptionLNCS v. 3756 entitled: Automata, languages and programming : 38th international colloquium, ICALP 2011 ... proceedings-
dc.description.abstractWe study the convergence time required to achieve consensus in dynamic networks. In each time step, a node's value is updated to some weighted average of its neighbors' and its old values. We study the case when the underlying network is dynamic, and investigate different averaging models. Both our analysis and experiments show that dynamic networks exhibit fast convergence behavior, even under very mild connectivity assumptions. © 2011 Springer-Verlag.en_US
dc.languageengen_US
dc.publisherSpringer Verlag. The Journal's web site is located at http://springerlink.com/content/105633/en_US
dc.relation.ispartofLecture Notes in Computer Scienceen_US
dc.rightsThe original publication is available at www.springerlink.com-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.subjectConvergence time-
dc.subjectDynamic network-
dc.subjectFast convergence-
dc.subjectTime step-
dc.subjectUnderlying networks-
dc.subjectWeighted averages-
dc.titleFast convergence for consensus in dynamic networksen_US
dc.typeConference_Paperen_US
dc.identifier.emailChan, HTH: hubert@cs.hku.hken_US
dc.identifier.authorityChan, HTH=rp01312en_US
dc.description.naturepostprinten_US
dc.identifier.doi10.1007/978-3-642-22012-8_41en_US
dc.identifier.scopuseid_2-s2.0-79959927794en_US
dc.identifier.hkuros188721-
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79959927794&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume6756en_US
dc.identifier.issuept. 2en_US
dc.identifier.spage514en_US
dc.identifier.epage525en_US
dc.publisher.placeGermanyen_US
dc.identifier.scopusauthoridNing, L=43761273000en_US
dc.identifier.scopusauthoridChan, THH=12645073600en_US
dc.customcontrol.immutablesml 131205-

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