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Distributed Sequential Consensus in Networks: Analysis of Partially Connected Blockchains with Uncertainty

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dc.contributor.author Kushch, Sergii
dc.contributor.author Corchado, Juan Manuel
dc.contributor.author Prieto Castrillo, Francisco
dc.date.accessioned 2017-11-08T16:23:06Z
dc.date.available 2017-11-08T16:23:06Z
dc.date.issued 2017-11
dc.date.submitted 2017-09
dc.identifier.issn 1076-2787
dc.identifier.issn 1099-0526
dc.identifier.uri http://hdl.handle.net/1721.1/112142
dc.description.abstract This work presents a theoretical and numerical analysis of the conditions under which distributed sequential consensus is possible when the state of a portion of nodes in a network is perturbed. Specifically, it examines the consensus level of partially connected blockchains under failure/attack events. To this end, we developed stochastic models for both verification probability once an error is detected and network breakdown when consensus is not possible. Through a mean field approximation for network degree we derive analytical solutions for the average network consensus in the large graph size thermodynamic limit. The resulting expressions allow us to derive connectivity thresholds above which networks can tolerate an attack. en_US
dc.publisher Hindawi Publishing Corporation en_US
dc.relation.isversionof https://doi.org/10.1155/2017/4832740 en_US
dc.rights Creative Commons Attribution en_US
dc.rights.uri http://creativecommons.org/licenses/by/4.0/ en_US
dc.source Hindawi Publishing Corporation en_US
dc.title Distributed Sequential Consensus in Networks: Analysis of Partially Connected Blockchains with Uncertainty en_US
dc.type Article en_US
dc.identifier.citation Prieto-Castrillo, Francisco et al. "Distributed Sequential Consensus in Networks: Analysis of Partially Connected Blockchains with Uncertainty." Complexity 2017 (November 2017): 4832740 © 2017 Francisco Prieto-Castrillo et al en_US
dc.contributor.department Massachusetts Institute of Technology. Media Laboratory en_US
dc.contributor.mitauthor Prieto Castrillo, Francisco
dc.relation.journal Complexity en_US
dc.identifier.mitlicense PUBLISHER_CC en_US
dc.eprint.version Final published version en_US
dc.type.uri http://purl.org/eprint/type/JournalArticle en_US
eprint.status http://purl.org/eprint/status/PeerReviewed en_US
dc.date.updated 2017-11-04T07:00:13Z
dc.language.rfc3066 en
dc.rights.holder Copyright © 2017 Francisco Prieto-Castrillo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
dspace.orderedauthors Prieto-Castrillo, Francisco; Kushch, Sergii; Corchado, Juan Manuel en_US
dspace.embargo.terms N en_US


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