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Author:

Liu, Yinggang (Liu, Yinggang.) | Ning, Zhenhu (Ning, Zhenhu.) | Zhang, Jiangjiang (Zhang, Jiangjiang.) | Wang, Xiaoping (Wang, Xiaoping.)

Indexed by:

EI Scopus

Abstract:

As a blockchain consensus mechanism based on Byzantine fault tolerance, PBFT has a very important role to play in the field of consortium blockchains. However, in the context of the Internet of Things, the poor scalability of PBFT limits the application of blockchain in the face of a large number of replicas and an unstable network structure. To achieve the consistency of replicas in the Internet of Things, this article proposes a monitory Byzantine fault tolerant mechanism, a type of monitor node is added to the network model. The monitor nodes measure the behavior and judge the status of the replicas in the blockchain. The monitor node can not only guide the new node join the blockchain, but also use the trust measurement table to sense the status of the nodes, and eliminate malicious nodes or crashed nodes. To verify the effectiveness of the proposed replica elimination method, a verification simulation experiment is performed. And the experiments show that the proposed mechanism has good stability, good effectiveness and accuracy for Byzantine node elimination, and improves the security of the consensus mechanism. © 2021 IEEE.

Keyword:

Blockchain Fault tolerance Scalability Internet of things

Author Community:

  • [ 1 ] [Liu, Yinggang]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 2 ] [Ning, Zhenhu]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 3 ] [Zhang, Jiangjiang]Faculty of Information Technology, Beijing University of Technology, Beijing, China
  • [ 4 ] [Wang, Xiaoping]Faculty of Information Technology, Beijing University of Technology, Beijing, China

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Source :

Year: 2021

Page: 425-430

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 1

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 7

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