The Evolution and Optimization Strategies of a PBFT Consensus Algorithm for Consortium Blockchains DOI Creative Commons

Fan Yuan,

Xia Huang,

Long Tai Zheng

et al.

Information, Journal Year: 2025, Volume and Issue: 16(4), P. 268 - 268

Published: March 27, 2025

With the rapid development of blockchain technology, consensus algorithms have become a significant research focus. Practical Byzantine Fault Tolerance (PBFT), as widely used mechanism in consortium blockchains, has undergone numerous enhancements recent years. However, existing review studies primarily emphasize broad comparisons different and lack an in-depth exploration PBFT optimization strategies. The such makes it challenging for researchers practitioners to identify most effective optimizations specific application scenarios. In this paper, we improvement schemes from three key directions: communication complexity optimization, dynamic node management, incentive integration. Specifically, explore hierarchical networking, adaptive selection, multi-leader view switching, hybrid model incorporating staking penalty mechanisms. Finally, paper presents comparative analysis these strategies, evaluates their applicability across various scenarios, offers insights into future directions algorithm design.

Language: Английский

The Evolution and Optimization Strategies of a PBFT Consensus Algorithm for Consortium Blockchains DOI Creative Commons

Fan Yuan,

Xia Huang,

Long Tai Zheng

et al.

Information, Journal Year: 2025, Volume and Issue: 16(4), P. 268 - 268

Published: March 27, 2025

With the rapid development of blockchain technology, consensus algorithms have become a significant research focus. Practical Byzantine Fault Tolerance (PBFT), as widely used mechanism in consortium blockchains, has undergone numerous enhancements recent years. However, existing review studies primarily emphasize broad comparisons different and lack an in-depth exploration PBFT optimization strategies. The such makes it challenging for researchers practitioners to identify most effective optimizations specific application scenarios. In this paper, we improvement schemes from three key directions: communication complexity optimization, dynamic node management, incentive integration. Specifically, explore hierarchical networking, adaptive selection, multi-leader view switching, hybrid model incorporating staking penalty mechanisms. Finally, paper presents comparative analysis these strategies, evaluates their applicability across various scenarios, offers insights into future directions algorithm design.

Language: Английский

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