File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Ultrafast consensus via predictive mechanisms

TitleUltrafast consensus via predictive mechanisms
Authors
Issue Date2008
PublisherInstitute of Physics Publishing Ltd.. The Journal's web site is located at http://iopscience.iop.org/0295-5075
Citation
Epl, 2008, v. 83 n. 4 How to Cite?
Abstract
An 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.
Persistent Identifierhttp://hdl.handle.net/10722/157104
ISSN
2013 Impact Factor: 2.269
ISI Accession Number ID
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.

References

 

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
DC FieldValueLanguage
dc.contributor.authorZhang, HTen_US
dc.contributor.authorZhiqiang Chen, Men_US
dc.contributor.authorZhou, Ten_US
dc.contributor.authorStan, GBen_US
dc.date.accessioned2012-08-08T08:45:21Z-
dc.date.available2012-08-08T08:45:21Z-
dc.date.issued2008en_US
dc.identifier.citationEpl, 2008, v. 83 n. 4en_US
dc.identifier.issn0295-5075en_US
dc.identifier.urihttp://hdl.handle.net/10722/157104-
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.en_US
dc.languageengen_US
dc.publisherInstitute of Physics Publishing Ltd.. The Journal's web site is located at http://iopscience.iop.org/0295-5075en_US
dc.relation.ispartofEPLen_US
dc.titleUltrafast consensus via predictive mechanismsen_US
dc.typeArticleen_US
dc.identifier.emailZhiqiang Chen, M:mzqchen@hku.hken_US
dc.identifier.authorityZhiqiang Chen, M=rp01317en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1209/0295-5075/83/40003en_US
dc.identifier.scopuseid_2-s2.0-79051469236en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-79051469236&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume83en_US
dc.identifier.issue4en_US
dc.identifier.eissn1286-4854-
dc.identifier.isiWOS:000259025900003-
dc.publisher.placeUnited Kingdomen_US
dc.identifier.scopusauthoridZhang, HT=7409192616en_US
dc.identifier.scopusauthoridZhiqiang Chen, M=35085827300en_US
dc.identifier.scopusauthoridZhou, T=8575473800en_US
dc.identifier.scopusauthoridStan, GB=16053936800en_US

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats