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Article: Ultrafast consensus via predictive mechanisms
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TitleUltrafast consensus via predictive mechanisms
 
AuthorsZhang, HT3 4
Zhiqiang Chen, M5 4
Zhou, T1 2
Stan, GB4
 
Issue Date2008
 
PublisherInstitute of Physics Publishing Ltd.. The Journal's web site is located at http://iopscience.iop.org/0295-5075
 
CitationEpl, 2008, v. 83 n. 4 [How to Cite?]
DOI: http://dx.doi.org/10.1209/0295-5075/83/40003
 
AbstractAn important natural phenomenon surfaces that ultrafast consensus can be achieved by introducing predictive mechanisms. By predicting the dynamics of a network several steps ahead and using this information in the consensus protocol, it is shown that, without changing the topology of the network, drastic improvements can be achieved in terms of the speed of convergence towards consensus and of the feasible range of sampling periods, compared with the routine consensus protocol. In natural science, this study provides an evidence for the idea that some predictive mechanisms exist in widely-spread biological swarms, flocks, and schools. From the industrial engineering point of view, inclusion of an efficient predictive mechanism allows for a significant increase in the consensus speed and a reduction of the required communication energy. © 2008 Europhysics Letters Association.
 
ISSN0295-5075
2013 Impact Factor: 2.269
 
DOIhttp://dx.doi.org/10.1209/0295-5075/83/40003
 
ISI Accession Number IDWOS:000259025900003
Funding AgencyGrant Number
NNSFC60704041
10635040
EPSRCEP/E02761X/1
Funding Information:

Thanks are due to Prof. Guanrong Chen ( City University of Hong Kong) and Prof. Jan Maciejowski (Cambridge University), who offered many valuable suggestions, and the reviewers for improving the quality of this paper. H-TZ acknowledges the support of NNSFC under grant No. 60704041. TZ acknowledges the support of NNSFC under grant No. 10635040. G-BS acknowledges the support of the EPSRC under grant No. EP/E02761X/1.

 
ReferencesReferences in Scopus
 
DC FieldValue
dc.contributor.authorZhang, HT
 
dc.contributor.authorZhiqiang Chen, M
 
dc.contributor.authorZhou, T
 
dc.contributor.authorStan, GB
 
dc.date.accessioned2012-08-08T08:45:21Z
 
dc.date.available2012-08-08T08:45:21Z
 
dc.date.issued2008
 
dc.description.abstractAn important natural phenomenon surfaces that ultrafast consensus can be achieved by introducing predictive mechanisms. By predicting the dynamics of a network several steps ahead and using this information in the consensus protocol, it is shown that, without changing the topology of the network, drastic improvements can be achieved in terms of the speed of convergence towards consensus and of the feasible range of sampling periods, compared with the routine consensus protocol. In natural science, this study provides an evidence for the idea that some predictive mechanisms exist in widely-spread biological swarms, flocks, and schools. From the industrial engineering point of view, inclusion of an efficient predictive mechanism allows for a significant increase in the consensus speed and a reduction of the required communication energy. © 2008 Europhysics Letters Association.
 
dc.description.naturelink_to_subscribed_fulltext
 
dc.identifier.citationEpl, 2008, v. 83 n. 4 [How to Cite?]
DOI: http://dx.doi.org/10.1209/0295-5075/83/40003
 
dc.identifier.doihttp://dx.doi.org/10.1209/0295-5075/83/40003
 
dc.identifier.eissn1286-4854
 
dc.identifier.isiWOS:000259025900003
Funding AgencyGrant Number
NNSFC60704041
10635040
EPSRCEP/E02761X/1
Funding Information:

Thanks are due to Prof. Guanrong Chen ( City University of Hong Kong) and Prof. Jan Maciejowski (Cambridge University), who offered many valuable suggestions, and the reviewers for improving the quality of this paper. H-TZ acknowledges the support of NNSFC under grant No. 60704041. TZ acknowledges the support of NNSFC under grant No. 10635040. G-BS acknowledges the support of the EPSRC under grant No. EP/E02761X/1.

 
dc.identifier.issn0295-5075
2013 Impact Factor: 2.269
 
dc.identifier.issue4
 
dc.identifier.scopuseid_2-s2.0-79051469236
 
dc.identifier.urihttp://hdl.handle.net/10722/157104
 
dc.identifier.volume83
 
dc.languageeng
 
dc.publisherInstitute of Physics Publishing Ltd.. The Journal's web site is located at http://iopscience.iop.org/0295-5075
 
dc.publisher.placeUnited Kingdom
 
dc.relation.ispartofEPL
 
dc.relation.referencesReferences in Scopus
 
dc.titleUltrafast consensus via predictive mechanisms
 
dc.typeArticle
 
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Author Affiliations
  1. University of Science and Technology of China
  2. Universite de Fribourg
  3. Huazhong University of Science and Technology
  4. University of Cambridge
  5. University of Leicester