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An Optimized Byzantine Fault Tolerance Algorithm for Consortium Blockchain

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Abstract

According to different application scenarios of blockchain system, it is generally divided into public chain, private chain and consortium chain. Consortium chain is a typical multi-center blockchain, because it has better landing, it is supported by more and more enterprises and governments. This paper analyzes the advantages and problems of Practical Byzantine Fault Tolerance (PBFT) algorithm for the application scenarios of the consortium chain. In order to be more suitable for consortium chains, this paper proposes a new optimized consensus algorithm based on PBFT. Aiming at the shortcomings of PBFT, such as the inability to dynamically join nodes, low multi-node consensus efficiency, and primary master node selection, our optimized algorithm has designed a hierarchical structure to increase scalability and improve consensus efficiency. The simulation results show that compared with PBFT and RAFT, our new consensus algorithm increases the data throughput while supporting more nodes, and effectively reducing the consensus delay and the number of communication times between nodes.

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References

  1. Nakamoto S (2008) Bitcoin: A peer-to-peer electronic cash system

  2. Peck ME (2017) Blockchain world-Do you need a blockchain? This chart will tell you if the technology can solve your problem. IEEE Spectrum 54(10):38–60

    Article  Google Scholar 

  3. Zheng Z, Xie S, Dai H, Chen X, Wang H (2017) An overview of blockchain technology: Architecture, consensus, and future trends. In: 2017 IEEE international congress on big data (BigData congress). IEEE, pp 557–564

  4. Yang S, Deng B, Wang J, Li H, Lu M, Che Y, Wei X, Loparo KA (2019) Scalable digital neuromorphic architecture for large-scale biophysically meaningful neural network with multi-compartment neurons. IEEE Trans Neural Netw Learn Sys 31(1):148–162

    Article  Google Scholar 

  5. Yang S, Wang J, Deng B, Liu C, Li H, Fietkiewicz C, Loparo KA (2018) Real-time neuromorphic system for large-scale conductance-based spiking neural networks. IEEE Trans Cybern 49(7):2490–2503

    Article  Google Scholar 

  6. Morabito V (2017) Business innovation through blockchain. Springer International Publishing, Cham

    Book  Google Scholar 

  7. Buterin V (2014) A next-generation smart contract and decentralized application platform. White Paper 3(37)

  8. Crosby M, Pattanayak P, Verma S, Kalyanaraman V (2016) Blockchain technology: Beyond bitcoin. Applied Innovation 2(6-10):71

    Google Scholar 

  9. Mohan C (2019) State of public and private blockchains: Myths and reality. In: Proceedings of the 2019 international conference on management of data, pp 404–411

  10. Guo Y, Liang C (2016) Blockchain application and outlook in the banking industry. Financial Innovation 2(1):24

    Article  Google Scholar 

  11. Gramoli V (2020) From blockchain consensus back to byzantine consensus. Future Gener Comput Syst 107:760–769

    Article  Google Scholar 

  12. Xiao Y, Zhang N, Lou W, Hou YT (2020) A survey of distributed consensus protocols for blockchain networks. IEEE Commun Surv Tutor 22(2):1432–1465

    Article  Google Scholar 

  13. Pahlajani S, Kshirsagar A, Pachghare V (2019) Survey on private blockchain consensus algorithms. In: 2019 1st International conference on innovations in information and communication technology (ICIICT). IEEE, pp 1–6

  14. Jakobsson M, Juels A (1999) Proofs of work and bread pudding protocols. In: Secure information networks. Springer, Boston, pp 258–272

  15. King S, Nadal S (2012) Ppcoin: Peer-to-peer crypto-currency with proof-of-stake. Self-published paper, August, 19, 1

  16. Larimer D (2017) Delegated proof-of-stake consensus. bitshares.org. https://bitshares.org/technology/delegating-proof-of-stake-consensushttps://bitshares.org/technology/delegating-proof-of-stake-consensus. Accessed March 28th, 2017

  17. Sankar LS, Sindhu M, Sethumadhavan M (2017) Survey of consensus protocols on blockchain applications. In: 2017 4th international conference on advanced computing and communication systems (ICACCS). IEEE, pp 1–5

  18. Mingxiao D, Xiaofeng M, Zhe Z, Xiangwei W, Qijun C (2017) A review on consensus algorithm of blockchain. In: 2017 IEEE International Conference on Systems, Man, and Cybernetics (SMC). IEEE, pp 2567–2572

  19. Huang D, Ma X, Zhang S (2019) Performance analysis of the raft consensus algorithm for private blockchains. IEEE Trans Sys Man Cybern Sys 50(1):172–181

    Article  Google Scholar 

  20. Castro M, Liskov B (2002) Practical Byzantine fault tolerance and proactive recovery. ACM Trans Comput Sys (TOCS) 20(4):398–461

    Article  Google Scholar 

  21. Khosravi A, Kavian YS (2016) Broadcast gossip ratio consensus: Asynchronous distributed averaging in strongly connected networks. IEEE Trans Signal Process 65(1):119–129

    Article  MathSciNet  Google Scholar 

  22. Sukhwani H, Martínez JM, Chang X, Trivedi KS, Rindos A (2017) Performance modeling of PBFT consensus process for permissioned blockchain network (hyperledger fabric). In: 2017 IEEE 36th Symposium on Reliable Distributed Systems (SRDS). IEEE, pp 253–255

  23. Zhang L, Li Q (2018) Research on consensus efficiency based on practical byzantine fault tolerance. In: 2018 10th International conference on modelling, identification and control (ICMIC). IEEE, pp 1–6

  24. Wang S (2019) Performance evaluation of hyperledger fabric with malicious behavior. In: International conference on blockchain. Springer, Cham, pp 211–219

  25. Wang X, WeiLi J, Chai J (2018) The research on the incentive method of consortium blockchain based on practical byzantine fault tolerant. In: 2018 11th international symposium on computational intelligence and design (ISCID), vol 2. IEEE, pp 154–156

  26. He L, Hou Z (2019) An improvement of consensus fault tolerant algorithm applied to alliance chain. In: 2019 IEEE 9th international conference on electronics information and emergency communication (ICEIEC). IEEE, pp 1–4

  27. Wang H, Guo K (2019) Byzantine fault tolerant algorithm based on vote. In: 2019 international conference on cyber-enabled distributed computing and knowledge discovery (CyberC). IEEE, pp 190–196

  28. Zhu S, Zhang Z, Chen L, Chen H, Wang Y (2020) A PBFT consensus scheme with reputation value voting based on dynamic clustering. In: International conference on security and privacy in digital economy. Springer, Singapore, pp 336–354

  29. Miller A, Xia Y, Croman K, Shi E, Song D (2016) The honey badger of BFT protocols. In: Proceedings of the 2016 ACM SIGSAC conference on computer and communications security, pp 31–42

  30. Gueta GG, Abraham I, Grossman S, Malkhi D, Pinkas B, Reiter M, Seredinschi D, Tamir O, Tomescu A (2018) Sbft: a scalable decentralized trust infrastructure for blockchains (1804)

  31. Li Y, Wang Z, Fan J, Zheng Y, Luo Y, Deng C, Ding J (2019) An extensible consensus algorithm based on PBFT. In: 2019 international conference on cyber-enabled distributed computing and knowledge discovery (CyberC). IEEE, pp 17–23

  32. Zhang J, Rong Y, Cao J, Rong C, Bian J, Wu W (2019) DBFT: A byzantine fault tolerant protocol with graceful performance degradation. In: 2019 38th symposium on reliable distributed systems (SRDS). IEEE, pp 123–12309

  33. Jalalzai MM, Busch C (2018) Window based BFT blockchain consensus. In: 2018 IEEE international conference on Internet of Things (iThings) and IEEE green computing and communications (GreenCom) and IEEE Cyber, physical and social computing (CPSCom) and IEEE Smart Data (SmartData). IEEE, pp 971–979

  34. Gao S, Yu T, Zhu J, Cai W (2019) T-PBFT: An EigenTrust-based practical Byzantine fault tolerance consensus algorithm. China Commun 16(12):111–123

    Article  Google Scholar 

  35. Lao L, Dai X, Xiao B, Guo S (2020) G-PBFT: a location-based and scalable consensus protocol for IOT-Blockchain applications. In: 2020 IEEE International parallel and distributed processing symposium (IPDPS). IEEE, pp 664–673

  36. Okusanya O (2019) Consensus in Distributed Systems: RAFT vs CRDTs. https://repository.stcloudstate.edu/csitetds/29

Download references

Funding

This work was supported in part by the National Natural Science Foundation of China (NSFC) under Grant No. 61902203, Key Research and Development Plan - Major Scientific and Technological Innovation Projects of ShanDong Province (2019JZZY020101).

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Prof. Zhihan Lv conceived the work and suggested the outline of the paper. Mr.Yuxi Li and Mr. Liang Qiao carried out investigations and wrote the paper.

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Correspondence to Zhihan Lv.

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The authors declare no competing interests.

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Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Yuxi Li and Liang Qiao contributes equally to this work, both are the first authors.

This article is part of the Topical Collection: Special Issue on Blockchain for Peer-to-Peer Computing

Guest Editors: Keping Yu, Chunming Rong, Yang Cao, and Wenjuan Li

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Li, Y., Qiao, L. & Lv, Z. An Optimized Byzantine Fault Tolerance Algorithm for Consortium Blockchain. Peer-to-Peer Netw. Appl. 14, 2826–2839 (2021). https://doi.org/10.1007/s12083-021-01103-8

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  • DOI: https://doi.org/10.1007/s12083-021-01103-8

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