Research on the improved PBFT consensus algorithm based on credit mechanism

Weixing Wang; Guangxia Xu; Liuqin Ye; Chuang Ma

doi:10.1117/12.3011605

8 November 2023 Research on the improved PBFT consensus algorithm based on credit mechanism

Weixing Wang, Guangxia Xu, Liuqin Ye, Chuang Ma

Proceedings Volume 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023); 1292322 (2023) https://doi.org/10.1117/12.3011605
Event: 3rd International Conference on Artificial Intelligence, Virtual Reality and Visualization (AIVRV 2023), 2023, Chongqing, China

Abstract

The PBFT consensus algorithm commonly used in the consortium chain has the disadvantages of three-stage consensus process, resulting in high communication costs. This paper proposes an enhanced PBFT algorithm that utilizes a credit mechanism to select master nodes that can improve system availability. The three-stage consensus process of PBFT is optimized, and the master node collects the confirmation messages broadcast by the whole network during the confirmation stage, effectively reducing communication overhead. At the same time, the block height synchronization mechanism is used to ensure the high consistency of consensus node blocks, restore the block height of failed nodes, and achieve fast consensus. Empirical results show that the improved P-PBFT consensus algorithm effectively reduces resource consumption and latency.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Weixing Wang, Guangxia Xu, Liuqin Ye, and Chuang Ma "Research on the improved PBFT consensus algorithm based on credit mechanism", Proc. SPIE 12923, Third International Conference on Artificial Intelligence, Virtual Reality, and Visualization (AIVRV 2023), 1292322 (8 November 2023); https://doi.org/10.1117/12.3011605

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available