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Research on PBFT consensus algorithm for grouping based on feature trust
The consensus mechanism is the core of the blockchain system, which plays an important role in the performance and security of the blockchain system . The Practical Byzantine Fault Tolerance (PBFT) algorithm is a widely used consensus algorithm, but the PBFT algorithm also suffers from high consensu...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307629/ https://www.ncbi.nlm.nih.gov/pubmed/35869116 http://dx.doi.org/10.1038/s41598-022-15282-8 |
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author | Wang, Yong Zhong, Meiling Cheng, Tong |
author_facet | Wang, Yong Zhong, Meiling Cheng, Tong |
author_sort | Wang, Yong |
collection | PubMed |
description | The consensus mechanism is the core of the blockchain system, which plays an important role in the performance and security of the blockchain system . The Practical Byzantine Fault Tolerance (PBFT) algorithm is a widely used consensus algorithm, but the PBFT algorithm also suffers from high consensus latency, low throughput and performance. In this paper, we propose a grouped PBFT consensus algorithm (GPBFT) based on feature trust. First, the algorithm evaluates the trust degree of nodes in the transaction process through the EigenTrust trust model, and uses the trust degree of nodes as the basis for electing master nodes and proxy nodes. Then, the algorithm divides the nodes in the blockchain system into multiple groups, and the consensus within each independent group does not affect the other groups, which greatly reduces the communication overhead of the consensus process when the number of nodes in the system is large. Finally, we demonstrate through theoretical and experimental analysis that the GPBFT algorithm has a significant improvement in security and performance. |
format | Online Article Text |
id | pubmed-9307629 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-93076292022-07-24 Research on PBFT consensus algorithm for grouping based on feature trust Wang, Yong Zhong, Meiling Cheng, Tong Sci Rep Article The consensus mechanism is the core of the blockchain system, which plays an important role in the performance and security of the blockchain system . The Practical Byzantine Fault Tolerance (PBFT) algorithm is a widely used consensus algorithm, but the PBFT algorithm also suffers from high consensus latency, low throughput and performance. In this paper, we propose a grouped PBFT consensus algorithm (GPBFT) based on feature trust. First, the algorithm evaluates the trust degree of nodes in the transaction process through the EigenTrust trust model, and uses the trust degree of nodes as the basis for electing master nodes and proxy nodes. Then, the algorithm divides the nodes in the blockchain system into multiple groups, and the consensus within each independent group does not affect the other groups, which greatly reduces the communication overhead of the consensus process when the number of nodes in the system is large. Finally, we demonstrate through theoretical and experimental analysis that the GPBFT algorithm has a significant improvement in security and performance. Nature Publishing Group UK 2022-07-22 /pmc/articles/PMC9307629/ /pubmed/35869116 http://dx.doi.org/10.1038/s41598-022-15282-8 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Wang, Yong Zhong, Meiling Cheng, Tong Research on PBFT consensus algorithm for grouping based on feature trust |
title | Research on PBFT consensus algorithm for grouping based on feature trust |
title_full | Research on PBFT consensus algorithm for grouping based on feature trust |
title_fullStr | Research on PBFT consensus algorithm for grouping based on feature trust |
title_full_unstemmed | Research on PBFT consensus algorithm for grouping based on feature trust |
title_short | Research on PBFT consensus algorithm for grouping based on feature trust |
title_sort | research on pbft consensus algorithm for grouping based on feature trust |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9307629/ https://www.ncbi.nlm.nih.gov/pubmed/35869116 http://dx.doi.org/10.1038/s41598-022-15282-8 |
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