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Volume 45 Issue 7
Jul.  2023
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LI Shuzhi, XIONG Weizhi, DENG Xiaohong, WANG Zhiqiang, LIU Hunwen. Byzantine Fault-Tolerance Consensus Algorithm Based on Perfect Binary Tree Communication[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2484-2493. doi: 10.11999/JEIT220798
Citation: LI Shuzhi, XIONG Weizhi, DENG Xiaohong, WANG Zhiqiang, LIU Hunwen. Byzantine Fault-Tolerance Consensus Algorithm Based on Perfect Binary Tree Communication[J]. Journal of Electronics & Information Technology, 2023, 45(7): 2484-2493. doi: 10.11999/JEIT220798

Byzantine Fault-Tolerance Consensus Algorithm Based on Perfect Binary Tree Communication

doi: 10.11999/JEIT220798
Funds:  The National Natural Science Foundation of China (61762046, 62166019), The Natural Science Foundation of Jiangxi Province (2020BABL202032), The Scientific Research Project of Education Department of Jiangxi Province (GJJ218506, GJJ209412)
  • Received Date: 2022-06-16
  • Rev Recd Date: 2022-12-07
  • Available Online: 2022-12-09
  • Publish Date: 2023-07-10
  • Considering the problems of a predictable primary node, high communication complexity, and lack of punishment mechanism for malicious nodes in Practical Byzantine Fault Tolerance (PBFT) algorithm, a consortium chain Byzantine Fault-Tolerant algorithm based on Perfect Binary Tree communication topology(PBT-BFT) is proposed. In PBT-BFT, a reputation evaluation model is designed to evaluate the behavior of nodes. At the same time, a Reputation-based Verifiable Random Function (R-VRF) is proposed, which makes the probability of random extraction positively correlated with the reputation value, and ensures the fairness and randomness of the lottery for nodes with different reputation values. Then, a perfect binary tree communication topology is designed to reduce the communication complexity to linear complexity, and a rotating primary node and Pipelining are proposed to improve the consensus efficiency. The experimental results show that compared with PBFT, the average throughput is increased by 121.6%, and the average delay is reduced by 73.8%, which can be well applied to the consortium chain of large-scale network nodes.
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