Open Access

ARTICLE

Linguistic Knowledge Representation in DPoS Consensus Scheme for Blockchain

Yixia Chen^1,2, Mingwei Lin^1,2,*

1 College of Computer and Cyber Security, Fujian Normal University, Fuzhou, 350117, China
2 Fujian Provincial Engineering Research Center for Public Service Big Data Mining and Application, Fujian Normal University, Fuzhou, 350117, China

* Corresponding Author: Mingwei Lin. Email:

Computers, Materials & Continua 2023, 77(1), 845-866. https://doi.org/10.32604/cmc.2023.040970

Received 06 April 2023; Accepted 19 July 2023; Issue published 31 October 2023

Abstract

The consensus scheme is an essential component in the real blockchain environment. The Delegated Proof of Stake (DPoS) is a competitive consensus scheme that can decrease energy costs, promote decentralization, and increase efficiency, respectively. However, how to study the knowledge representation of the collective voting information and then select delegates is a new open problem. To ensure the fairness and effectiveness of transactions in the blockchain, in this paper, we propose a novel fine-grained knowledge representation method, which improves the DPoS scheme based on the linguistic term set (LTS) and proportional hesitant fuzzy linguistic term set (PHFLTS). To this end, the symmetrical LTS is used in this study to express the fine-grained voting options that can be chosen to evaluate the blockchain nodes. PHFLTS is used to model the collective voting information on the voted blockchain nodes by aggregating the voting information from other blockchain nodes. To rank the blockchain nodes and then choose the delegate, a novel delegate selection algorithm is proposed based on the cumulative possibility degree. Finally, the numerical examples are used to demonstrate the implementation process of the proposed DPoS consensus algorithm and also its rationality. Moreover, the superiority of the proposed DPoS consensus algorithm is verified. The results show that the proposed DPoS consensus algorithm shows better performance than the existing DPoS consensus algorithms.

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Keywords

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