IBFT: An Impartial Byzantine Fault Tolerance Consensus Protocol for Blockchain
Consensus protocol is the core component of blockchain, which solves the problem of data consistency among nodes in decentralized networks. Practical Byzantine Fault Tolerance (PBFT) consensus protocol has been applied in many scenarios which can tolerate a certain number of malicious nodes. However, it also exposes some shortages. In particular, PBFT uses a simple and predictable way to elect the primary node, which may incur the risk of Byzantine node being elected as primary node. Besides, the communication complexity of $O(N^2)$ hinders the application of PBFT in large scale networks. To address the above problems, we propose an Impartial Byzantine Fault Tolerance (IBFT) consensus protocol for consortium blockchains in this paper. First, to decrease the probability of Byzantine nodes becoming primary node, a temporary committee is introduced to select the highly credible nodes as candidates for primary node. The theory of planned behavior is exploited as the theoretical basis for credibility evaluation. Then, to ensure that the candidate is unpredictable when view changes, a randomized primary election strategy based on ECC signatures and historical block hash is designed. Third, a threshold signature scheme is devised to implement the 1-to-N mode of aggregate-verify during the prepare and commit stages, thus to simplify the communication complexity from $O(N^2)$ to $O(N)$. The simulation results show that IBFT is superior to PBFT in reliability and throughput is improved by 54.25% while balancing fault tolerance, node democracy and node motivation.
Sat 27 JulDisplayed time zone: Beijing, Chongqing, Hong Kong, Urumqi change
11:00 - 12:15 | Session 4 - Network & ConsensusResearch Track at The ballroom B Chair(s): Yury Yanovich Skolkovo Institute of Science and Technology; Faculty of Computer Science, HSE University | ||
11:00 15mPaper | IBFT: An Impartial Byzantine Fault Tolerance Consensus Protocol for Blockchain Research Track Yangpu Zeng Zhejiang Normal University, Feilong Lin Zhejiang Normal University, Lei Tian Zhejiang Normal University, Jiahao Gan Zhejiang Normal University, Zhongyu Chen Zhejiang Normal University | ||
11:15 15mPaper | Fault Tolerance Testing and Tuning for Consortium Blockchain Research Track Taiwu Pang East China Normal University, Zheming Ye East China Normal University, Zhao Zhang East China Normal University, Cheqing Jin East China Normal University | ||
11:30 15mPaper | ATBFT-Automatically switch consensus protocol Research Track Yuxuan Lu School of Software, Shandong University, Jinan 250101, PR China, Chang Liu School of Computing Science, Newcastle University, Newcastle NE1 7RU, PR United Kingdom, Lanju Kong Shangdong University, Xiangyu Niu School of Software, Shandong University, Jinan 250101, PR China | ||
11:45 15mPaper | An Efficient Bitcoin Network Topology Discovery Algorithm for Dynamic Display Research Track Zening Zhao Tianjin University of Technology, Jinsong Wang Tianjin University of Technology, Miao Yang Tianjin University of Technology, Haitao Wang Tianjin University of Technology | ||
12:00 15mPaper | Meta Reinforcement Learning Based Dynamic Tuning for Blockchain Systems in Diverse Network Environments Research Track Yue Pei Beihang University, Mengxiao Zhu North China University of Technology, Chen Zhu Beihang University, weihusong Beihang University, Yi Sun Chinese Academy of Sciences, Lei Li Zhongguancun Laboratory, Haogang Zhu Beihang University |