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Performance analysis of Hyperledger Fabric platform: A hierarchical model approach

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Abstract

The widespread application of the Hyperledger Fabric platform and the timeliness requirement of transactions on the platform necessitate the effective performance evaluation of transaction processing. The existing evaluation researches on Hyperledger Fabric ignored transaction endorsement failure (due to transaction endorsing duration timeout) and/or ignored block timeout. This paper considers these two timeout constraints and develops a hierarchical model for Hyperledger Fabric v1.4 transaction process from the time when transactions are submitted by clients until the completion of validating/committing transactions as a block. Formulas for calculating performance measures, including platform throughput, transaction rejection probability and mean transaction response delay, are derived. Extensive numerical analysis and simulations are carried out to verify the approximate accuracy of the model and formulas. Moreover, numerical analysis is applied to illustrate the impact of various parameters on performance measures.

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References

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

  2. Dinh TTA, Liu R, Zhang M, Chen G, Ooi BC, Wang J (2018) Untangling blockchain: A data processing view of blockchain systems. IEEE Trans Knowl Data Eng 30(7):1366–1385

    Article  Google Scholar 

  3. Yin W, Wen Q, Li W, Zhang H, Jin Z (2018) An anti-quantum transaction authentication approach in blockchain. IEEE Access 6:5393–5401

    Article  Google Scholar 

  4. Kosba AE, Miller A, Shi E, Wen Z (2016) charalampos papamanthou: Hawk: The blockchain model of cryptography and privacy-preserving smart contracts. IEEE Symposium on Security and Privacy:839–858

  5. Yuan Y, Wang F-Y (2018) Blockchain and cryptocurrencies: Model, techniques, and applications. IEEE Trans Systems, Man, and Cybernetics: Systems 48(9):1421–1428

    Article  Google Scholar 

  6. Zheng P, Zheng Z, Luo X, Chen X, Liu X (2018) A detailed and real-time performance monitoring framework for blockchain systems. ICSE (SEIP):134–143

  7. Yuan Y, Wang F-Y (2016) Towards blockchain-based intelligent transportation systems. ITSC:2663–2668

  8. Beinke JH, Nguyen D, Teuteberg F (2018) Towards a business model taxonomy of startups in the finance sector using blockchain icis

  9. Jiang T, Fang H, Fang H (2019) Blockchain-based internet of vehicles: Distributed network architecture and performance analysis. IEEE IoT Journal 6(3):4640–4649

    Google Scholar 

  10. Hyperledger Fabric, https://www.hyperledger.org/

  11. Thakkar P, Nathan S, Viswanathan B (2018) Performance benchmarking and optimizing hyperledger fabric blockchain platform. MASCOTS:264–276

  12. Sousa J, Bessani A, Vukolic M (2018) A byzantine fault-tolerant ordering service for the hyperledger fabric blockchain platform. DSN:51–58

  13. Androulaki E, Barger A, Bortnikov V, Cachin C, Christidis K, De Caro A, Enyeart D, Ferris C, Laventman G, Manevich Y, Muralidharan S, Murthy C, Nguyen B, Sethi M, Singh G, Smith K, Sorniotti A, Stathakopoulou C, Vukolic M, Cocco SW, Yellick J (2018) Hyperledger fabric: a distributed operating system for permissioned blockchains. EuroSys: 30:1-30:15

  14. SecureKey, https://securekey.com/

  15. Global Trade Review, https://www.gtreview.com/news/europe/seven-banks-to-go-live-with-hyperledger-blockchain-trade-finance-platform-in-2017/ https://www.gtreview.com/news/europe/seven-banks-to-go-live-with-hyperledger-blockchain-trade-finance-platform-in-2017/

  16. Yu B, Wright J, Nepal S, Zhu L, Liu JK, Ranjan R (2018) IoTChain: Establishing trust in the internet of things ecosystem using blockchain. IEEE Cloud Computing 5(4):12–23

    Article  Google Scholar 

  17. Xu L, Chen L, Gao Z, Xu S, Shi W (2018) Efficient public blockchain client for lightweight users. ICST Trans Security Safety 4(13):e5

    Article  Google Scholar 

  18. Dinh TTA, Wang J, Chen G, Liu R, Ooi BC, Tan K-L (2017) BLOCKBENCH: A framework for analyzing private blockchains. SIGMOD Conference: 1085–1100

  19. Gorenflo C, Lee S, Golab L, Keshav S (2019) Fastfabric: Scaling hyperledger fabric to 20, 000 transactions per second. IEEE ICBC:455–463

  20. Ahmad A, Saad M, Bassiouni M, Mohaisen A (2018) Towards blockchain-driven, secure and transparent audit logs. MobiQuitous:443–448

  21. Hao Y, Li Y, Dong X, Fang L, Chen P (2018) Performance analysis of consensus algorithm in private blockchain. Intelligent Vehicles Symposium:280–285

  22. Liu M, Yu FR, Teng Y, Leung VCM, Song M (2019) Performance optimization for blockchain-enabled industrial internet of things (IIot) systems: a deep reinforcement learning approach. IEEE Trans Industrial Informatics 15(6):3559–3570

    Article  Google Scholar 

  23. Pongnumkul S, Siripanpornchana C, Thajchayapong S (2017) Performance analysis of private blockchain platforms in varying workloads. ICCCN:1–6

  24. Nasir Q, Qasse IA, Talib MA, Nassif AB (2018) Performance analysis of hyperledger fabric platforms. Sec Commun Netw 2018:3976093:1-3976093:14

    Google Scholar 

  25. Yuan P, Xiong X, Lei L, Zheng K (2019) Design and implementation on hyperledger-based emission trading system. IEEE Access 7:6109–6116

    Article  Google Scholar 

  26. Sukhwani H, Martínez JM, Chang X, Trivedi KS, Rindos A (2017) Performance modeling of PBFT consensus process for permissioned blockchain network (Hyperledger Fabric): SRDS: 253–255

  27. Sukhwani H, Wang N, Trivedi KS, Rindos A (2018) Performance modeling of Hyperledger Fabric (permissioned blockchain network). NCA: 1–8

  28. Li Q-L, Ma J-Y, Chang Y-X (2018) Blockchain queueing theory. International Conference on Computational Social Networks: 25–40

  29. Papadis N, Borst SC, Walid A, Grissa M, Tassiulas L (2018) Stochastic models and wide-area network measurements for blockchain design and analysis. INFOCOM: 2546–2554

  30. Baliga A, Solanki N, Verekar S, Pednekar A, Kamat P, Chatterjee S (2018) Performance characterization of hyperledger fabric. CVCBT: 65–74

  31. Chang X, Xia R, Muppala JK, Trivedi KS, Liu J (2018) Effective modeling approach for iaas data center performance analysis under heterogeneous workload. IEEE Trans Cloud Computing 6(4):991–1003

    Article  Google Scholar 

  32. Maplesoft, Inc., Maple 18, http://www.maplesoft.com/products/maple

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Acknowledgements

The research of Lili Jiang is supported in part by the Fundamental Research Funds for the Central Universities 2019YJS042. The research of Xiaolin Chang is supported in part by NSF U1836105 of China and the Fundamental Research Funds for the Central Universities of China under Grants 2018JBZ103. The research of Jelena Mišić and Vojislav B. Mišić is supported in part by the National Science and Engineering Research Council of Canada (NSERC) through Discovery Grants.

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Authors and Affiliations

  1. Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, Beijing, People’s Republic of China

    Lili Jiang, Xiaolin Chang & Yuhang Liu

  2. Ryerson University, Toronto, ON, M5B 2K3, Canada

    Jelena Mišić & Vojislav B. Mišić

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  1. Lili Jiang
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  2. Xiaolin Chang
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  3. Yuhang Liu
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Correspondence to Xiaolin Chang.

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Jiang, L., Chang, X., Liu, Y. et al. Performance analysis of Hyperledger Fabric platform: A hierarchical model approach. Peer-to-Peer Netw. Appl. 13, 1014–1025 (2020). https://doi.org/10.1007/s12083-019-00850-z

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