Primary node election based on probabilistic linguistic term set with confidence interval in the PBFT consensus mechanism for blockchain

This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance (PBFT) consensus mechanism to effectively enhance the efficiency of reaching consensus. Specifically, a novel concept of the probabilistic linguistic term...

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Published inComplex & intelligent systems Vol. 9; no. 2; pp. 1507 - 1524
Main Authors Xie, Mingyue, Liu, Jun, Chen, Shuyu, Xu, Guangxia, Lin, Mingwei
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 01.04.2023
Springer Nature B.V
Springer
Subjects
Approximation
Attitudes
Blockchain
Complexity
Computational Intelligence
Confidence intervals
Cryptography
Data Structures and Information Theory
Decision making
Efficiency
Elections
Energy consumption
Engineering
Fault tolerance
Fuzzy sets
Intelligent systems
Linguistics
Nodes
Original Article
PBFT consensus mechanism
Primaries & caucuses
Primary node
Probabilistic linguistic term set
Semantics
Software engineering
Statistical analysis
TOPSIS
Voting
Probabilistic linguistic term set
PBFT consensus mechanism
TOPSIS
Blockchain
Primary node
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Abstract This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance (PBFT) consensus mechanism to effectively enhance the efficiency of reaching consensus. Specifically, a novel concept of the probabilistic linguistic term set with a confidence interval (PLTS-CI) is presented to express the uncertain complex voting information of nodes during primary node election. Then, a novel score function based on the exponential semantic value and confidence approximation value for the PLTS-CI, called Score-ESCA, is used to solve the problems of comparing different nodes with various voting attitudes. This method helps select the node with the highest score by utilizing complex decision attitudes, making it an accurate primary node election solution. Furthermore, the feasibility of our proposed method is proved by both theoretical analysis and experimental evaluations.
AbstractList This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance (PBFT) consensus mechanism to effectively enhance the efficiency of reaching consensus. Specifically, a novel concept of the probabilistic linguistic term set with a confidence interval (PLTS-CI) is presented to express the uncertain complex voting information of nodes during primary node election. Then, a novel score function based on the exponential semantic value and confidence approximation value for the PLTS-CI, called Score-ESCA, is used to solve the problems of comparing different nodes with various voting attitudes. This method helps select the node with the highest score by utilizing complex decision attitudes, making it an accurate primary node election solution. Furthermore, the feasibility of our proposed method is proved by both theoretical analysis and experimental evaluations.
Abstract This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance (PBFT) consensus mechanism to effectively enhance the efficiency of reaching consensus. Specifically, a novel concept of the probabilistic linguistic term set with a confidence interval (PLTS-CI) is presented to express the uncertain complex voting information of nodes during primary node election. Then, a novel score function based on the exponential semantic value and confidence approximation value for the PLTS-CI, called Score-ESCA, is used to solve the problems of comparing different nodes with various voting attitudes. This method helps select the node with the highest score by utilizing complex decision attitudes, making it an accurate primary node election solution. Furthermore, the feasibility of our proposed method is proved by both theoretical analysis and experimental evaluations.
Author Xu, Guangxia
Chen, Shuyu
Lin, Mingwei
Liu, Jun
Xie, Mingyue
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  organization: College of Computer and Cyber Security, Fujian Normal University
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Issue 2
Keywords Probabilistic linguistic term set
PBFT consensus mechanism
TOPSIS
Blockchain
Primary node
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Snippet This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance (PBFT)...
Abstract This study proposes a primary node election method based on probabilistic linguistic term set (PLTS) for the practical Byzantine fault tolerance...
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SubjectTerms Approximation
Attitudes
Blockchain
Complexity
Computational Intelligence
Confidence intervals
Cryptography
Data Structures and Information Theory
Decision making
Efficiency
Elections
Energy consumption
Engineering
Fault tolerance
Fuzzy sets
Intelligent systems
Linguistics
Nodes
Original Article
PBFT consensus mechanism
Primaries & caucuses
Primary node
Probabilistic linguistic term set
Semantics
Software engineering
Statistical analysis
TOPSIS
Voting
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Title Primary node election based on probabilistic linguistic term set with confidence interval in the PBFT consensus mechanism for blockchain
URI https://link.springer.com/article/10.1007/s40747-022-00857-9
https://www.proquest.com/docview/2802663735
https://doaj.org/article/422a91fd24c841caba61775631b6055f
Volume 9
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