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Creating consensus group using online learning based reputation in blockchain networks

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dc.contributor.author Buğday, Ahmet
dc.contributor.author Özsoy, Adnan
dc.contributor.author Öztaner, Serdar Murat
dc.contributor.author Sever, Hayri
dc.date.accessioned 2020-01-31T11:54:09Z
dc.date.available 2020-01-31T11:54:09Z
dc.date.issued 2019-10
dc.identifier.citation Bugday, Ahmet...et al. (2019). "Creating consensus group using online learning based reputation in blockchain networks", Pervasive and Mobile Computing, Vol. 59. tr_TR
dc.identifier.issn 1574-1192
dc.identifier.uri http://hdl.handle.net/20.500.12416/2395
dc.description.abstract One of the biggest challenges to blockchain technology is the scalability problem. The choice of consensus algorithm is critical to the practical solution of the scalability problem. To increase scalability, Byzantine Fault Tolerance (BFT) based methods have been most widely applied. This study proposes a new model instead of Proof of Work (PoW) for forming the consensus group that allows the use of BFT based methods in the public blockchain network. The proposed model uses the adaptive hedge method, which is a decision-theoretic online learning algorithm (Qi et al., 2016). The reputation value is calculated for the nodes that want to participate in the consensus committee, and nodes with high reputation values are selected for the consensus committee to reduce the chances of the nodes in the consensus committee being harmful. Since the study focuses on the formation of the consensus group, a simulated blockchain network is used to test the proposed model more effectively. Test results indicate that the proposed model, which is a new approach in the literature making use of machine learning for the construction of consensus committee, successfully selects the node with the higher reputation for the consensus group. (C) 2019 Elsevier B.V. All rights reserved. tr_TR
dc.language.iso eng tr_TR
dc.publisher Elsevier tr_TR
dc.relation.isversionof 10.1016/j.pmcj.2019.101056 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Consensus Committee tr_TR
dc.subject The Blockchain tr_TR
dc.subject BFT tr_TR
dc.subject PBFT tr_TR
dc.subject Hedged Learning tr_TR
dc.title Creating consensus group using online learning based reputation in blockchain networks tr_TR
dc.type article tr_TR
dc.relation.journal Pervasive and Mobile Computing tr_TR
dc.contributor.authorID 11916 tr_TR
dc.identifier.volume 59 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Yazılım Mühendisliği Bölümü tr_TR


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