Optimization Scheme of Consensus Mechanism Based on Practical Byzantine Fault Tolerance Algorithm

Gao, Zhipeng; Yang, Lulin

doi:10.1007/978-981-15-3278-8_12

Cited by 6 publications

(4 citation statements)

References 6 publications

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“… The acknowledgment will be forwarded to the remaining sub-nodes by each node. It can assume the number of nodes in the blockchain is N. When one of the nodes received more than acknowledge, it will start processing the request and send feedback to the client [10].  The blockchain system will record the block after the verification.…”

Section: Practical Byzantine Fault Tolerantmentioning

confidence: 99%

Analysis of the current application of blockchain in social media

Yang

2023

Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022)

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Since the appearance of bitcoin, blockchain technology has been widely treated as an opportunity for businesses and the technology revolution. Until now, blockchain technology has been applied to several fields such as energy system evolution, Cryptocurrency, and social media. In this paper, the author mainly explored the current application of blockchain technology in social media, the algorithm behind blockchain technology, and the existing problem in blockchain technology. For the application in social media, this paper explores fake news detection, user trust framework, and decentralized online social network. For the algorithm behind blockchain technology, the Raft algorithm and Practical Byzantine Fault Tolerant algorithm are discussed in this paper. Moreover, one of the innovative consensus algorithms will be explained in the subsection. The following topics will be discussed in the existing problems section: Internet of Things issues, delayed confirmation, and information security. Finally, the author concluded that the current application of blockchain in social media is still developing, and more possibilities for blockchain application in social media will be found with further development.

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Section: Practical Byzantine Fault Tolerantmentioning

confidence: 99%

Analysis of the current application of blockchain in social media

Yang

2023

Third International Symposium on Computer Engineering and Intelligent Communications (ISCEIC 2022)

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“… Pratic Byzantic Fault Torent (PBFT) [13, 14] was first applied in the distributed field to solve the consistency problem. The PBFT consensus mechanism requires that the number of all nodes be at least 3 f + 1 ( f is the number of fault nodes or evil nodes).…”

Section: Related Workmentioning

confidence: 99%

Traceability model based on improved witness mechanism

2022

CAAI Trans on Intel Tech

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Traceability system is one of the popular applications of graphic blockchains. However, there are centralisation problems and a long time for final consistency confirmation in the graphic blockchain. In addition, the blockchain system in the traceability application scenario has the problem of insufficient supervision. Therefore, a witness‐based graphic blockchain consensus mechanism is proposed. In the consensus mechanism, a verifiable random function is used to screen the publishers of the unit; an SM2 threshold signature is used to sign the unit information to improve the non‐repudiation of the traceability information uploaders to the unit information under the supervision of the witness. The improved consistency algorithm cancels the process of finding a stable main chain and makes relatively many nodes to participate in the consensus process. The experimental results show that the graphic blockchain using the improved witness mechanism can reduce the degree of centralisation, shorten the time for new units to reach consensus, and greatly ensure the security and scalability of the blockchain system.

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“…The PBFT algorithm was proposed in 1999 as an algorithm specifically designed to solve the Byzantine general problem (Gao, Z., & Yang, L., 2020;Yu, G., et al, 2020). The algorithm aims to solve the problem of ensuring the consistency and correctness of the final decision in the presence of malicious nodes throughout the network.…”

Section: Pbft Consistency Protocolmentioning

confidence: 99%

Improvement of the PBFT Algorithm Based on Grouping and Reputation Value Voting

Liu

et al. 2022

International Journal of Digital Crime and Forensics

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An improved practical Byzantine fault tolerance (Practical Byzantine Fault Tolerant consensus algorithm based on reputation, RPBFT) algorithm based on grouping and reputation value voting is proposed for the problems of high communication complexity, poor scalability, and random selection of master nodes of the practical Byzantine fault tolerance (PBFT) consensus algorithm of the consortium chain. First, the consistency process is optimized to take the response speed of nodes to each group leader as the basis of grouping, and the intragroup consensus is performed. The group leader then takes the result of intragroup consensus and participates in extra-group consensus to reduce the frequency and time of internode communication. Second, the reputation model and voting mechanism are proposed, and the group leader is generated by node reputation value voting, which enhances the initiative and reliability of trusted nodes and reduces the abnormal nodes as group leader. Finally, a simulation and performance testing system based on this improved scheme is built to prove the effectiveness as well as the usability of the scheme through simulation experiments. The experimental results show that when the number of network nodes is 36, the throughput of the RPBFT algorithm is six times that of PBFT. Therefore, the consensus delay is reduced by 91.7%, and the communication overhead is reduced by 37.8%.

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Optimization Scheme of Consensus Mechanism Based on Practical Byzantine Fault Tolerance Algorithm

Cited by 6 publications

References 6 publications

Analysis of the current application of blockchain in social media

Analysis of the current application of blockchain in social media

Traceability model based on improved witness mechanism

Improvement of the PBFT Algorithm Based on Grouping and Reputation Value Voting

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