Improving Trust in a (Trans)National Invoicing System: The Performance of Crash vs. Byzantine Fault Tolerance at Scale
Source abstract
Abstract
Crash fault tolerance describes the capability of a distributed system to maintain its proper function despite the occurrence of crashes or failures in one or more of its components. When a distributed system possesses crash fault tolerance, it can be further fortified to achieve Byzantine fault tolerance. Byzantine fault tolerance empowers a distributed system to establish consensus among participants, even when faced with faulty or malicious behavior. Consensus plays a critical role in various tasks, including determining the accurate value of a shared variable, electing a leader, or validating the integrity of a business transaction. Compared to crash fault tolerance, Byzantine fault tolerance instills greater trust because it enables consensus even in the presence of malicious entities. This paper focuses on the performance evaluation of two blockchain solutions that exhibit Byzantine fault tolerance, in contrast to a blockchain solution that demonstrates crash fault tolerance. Specifically, the paper investigates the additional performance requirements associated with the enhanced trust resulting from Byzantine fault tolerance in e-business trading on both national and transnational scales. We analyze the resources needed to operate a business-to-business/business-to-government (B2B/B2G) compliance framework in two distinct geographic scenarios. The first examines the national scale, using Denmark as an example, which is the eleventh largest European country by GDP. The second scenario considers the scale of the European Union (EU) with its 27 member states (plus the United Kingdom).
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Blockchain Technology Applications and Security · Distributed systems and fault tolerance · Cloud Computing and Resource Management
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Digitalization, Copenhagen Business School, 2000 Copenhagen, Denmark
School of Information Technology, Deakin University, Geelong, VIC 3220, Australia
Aztec Labs, 161 Rosebery Avenue, London EC1R 4QX, UK
ZTLment, Linnésgade 20A, 2.sal, 1361 Copenhagen, Denmark
References (49)
Show source-provided references
1. Diedrich, H. (2016). Ethereum: Blockchains, Digital Assets, Smart Contracts, Decentralized Autonomous Organizations, Wildfire Publishing.
2. China takes blockchain national: The state-sponsored platform will launch in 100 cities10.1109/MSPEC.2020.9055903 ↗
3. The Byzantine generals problem
4. consensys.net (2023, May 22). A Permissioned Implementation of Ethereum Supporting Data Privacy. Available online: https://github.com/ConsenSys/quorum.
5. Buchman, E. (2023, May 22). Tendermint: Byzantine Fault Tolerance in the Age of Blockchains. Available online: http://atrium.lib.uoguelph.ca/xmlui/bitstream/handle/10214/9769/Buchman_Ethan_201606_MAsc.pdf.
6. Vukolić, M. (2017). Proceedings of the ACM Workshop on Blockchain, Cryptocurrencies and Contracts, Co-Located with ASIA CCS 2017, Association for Computing Machinery.
7. Kreps, J., Narkhede, N., and Rao, J. (2011, January 12–16). Kafka: A Distributed Messaging System for Log Processing. Proceedings of the NetDB, Association for Computing Machinery, Athens, Greece.
8. Deloitte (2023, April 16). Analyse Af Erhvervsøkonomiske Konsekvenser Af Udvalgte E-Handelsinitiativer. Available online: https://www2.deloitte.com/dk/da/pages/finance/articles/deloitte-economics.html.
9. (2023, May 22). Danmarks Nationalbank. Available online: https://www.nationalbanken.dk/da/bankogbetalinger/betalingsraad/Documents/BR_Rapport_om_virksomhedsbetalinger_2015.pdf.
10. Baily, P. (1987). Purchasing and Supply Management, Springer.10.1007/978-1-4899-6902-6 ↗
11. Danish Business Authority (2023, April 16). Submission of Annual Report. Available online: https://indberet.virk.dk/myndigheder/stat/ERST/Regnskab_20.pdf.
12. OpenPEPPOL (2023, April 16). PEPPOL Invoice Example. Available online: https://raw.githubusercontent.com/OpenPEPPOL/peppol-bis-invoice-3/master/rules/examples/base-example.xml.
13. de Best, R. (2023, May 22). Available online: https://www.statista.com/statistics/647523/worldwide-bitcoin-blockchain-size/.
14. Zhuang, Y., Tredger, S., Matthews, C., McGeer, R., and Coady, Y. (2012, January 12–14). Distributed Systems in the Wild: The Theoretical Foundations and Experimental Perspectives. Proceedings of the 2012 Seventh International Conference on P2P, Parallel, Grid, Cloud and Internet Computing, Victoria, BC, Canada.10.1109/3PGCIC.2012.32 ↗
15. Spasovski, J., and Eklund, P. (2017, January 7–10). Proof of Stake Blockchain: Performance and Scalability for Groupware Communications. Proceedings of the 9th International Conference on Management of Digital EcoSystems, Bangkok Thailand.10.1145/3167020.3167058 ↗
16. Hao, Y., Li, Y., Dong, X., Fang, L., and Chen, P. (2018, January 26–30). Performance analysis of consensus algorithm in private blockchain. Proceedings of the 2018 IEEE Intelligent Vehicles Symposium (IV), Changshu, China.10.1109/IVS.2018.8500557 ↗
17. Wang, Z., Dong, X., Li, Y., Fang, L., and Chen, P. (2018, January 22–24). Iot security model and performance evaluation: A blockchain approach. Proceedings of the 2018 International Conference on Network Infrastructure and Digital Content (IC-NIDC), Guiyang, China.10.1109/ICNIDC.2018.8525716 ↗
18. Pongnumkul, S., Siripanpornchana, C., and Thajchayapong, S. (August, January 31). Performance analysis of private blockchain platforms in varying workloads. Proceedings of the 2017 26th International Conference on Computer Communication and Networks (ICCCN), Vancouver, BC, Canada.10.1109/ICCCN.2017.8038517 ↗
19. Dinh, T., Wang, J., Chen, G., Liu, R., Ooi, B., and Tan, K. (2017). BLOCKBENCH: A Framework for Analyzing Private Blockchains. arXiv.10.1145/3035918.3064033 ↗
20. Kruger, A. (2023, May 22). Chainhammer. Available online: https://github.com/drandreaskrueger/chainhammer.
21. Blockchain-based event processing in supply chains—A case study at IKEA10.1016/j.rcim.2020.101971 ↗
22. Cachin, C., and Vukolic, M. (2017). Blockchain Consensus Protocols in the Wild. CoRR.
23. Beck, R., and Eklund, P. (2019, January 12–14). Factors that Impact Blockchain Scalability. Proceedings of the 11th International Conference on Management of Digital EcoSystems (MEDES 2019), Limassol, Cyprus.
24. Ongaro, D., and Ousterhout, J. (2014, January 19–20). In Search of an Understandable Consensus Algorithm. Proceedings of the 2014 USENIX Annual Technical Conference (USENIX ATC 14), Philadelphia, PA, USA.
25. Moniz, H. (2020). The Istanbul BFT Consensus Algorithm. arXiv.
26. Buterin, V. (2023, June 06). The Etheruem Whitepaper. Available online: https://ethereum.org/669c9e2e2027310b6b3cdce6e1c52962/Ethereum_Whitepaper_-_Buterin_2014.pdf.
27. Baliga, A., Subhod, I., Kamat, P., and Chatterjee, S. (2018). Performance Evaluation of the Quorum Blockchain Platform. arXiv.
28. Castro, M., and Liskov, B. (1999, January 22–25). Practical Byzantine fault tolerance. Proceedings of the OSDI, New Orleans, LA, USA.
29. Hyperledger (2023, May 22). Introduction to Hyperledger Fabric. Available online: https://hyperledger-fabric.readthedocs.io/en/release-2.2/whatis.html.
30. Kafka, A. (2023, May 22). Apache Kafka Documentation. Available online: https://kafka.apache.org/.
31. Modern Messaging for Distributed Sytems10.1088/1742-6596/608/1/012038 ↗
32. Microsoft (2023, April 16). Azure Locations. Available online: https://azure.microsoft.com/en-us/global-infrastructure/locations/.
33. Campean, D. (2023, April 16). How to Build a Distributed Load Testing Infrastructure with AWS, Docker, and JMeter. Available online: https://dragoscampean.medium.com/how-to-build-a-distributed-load-testing-infrastructure-with-aws-docker-and-jmeter-accf3c2aa3a3.
34. (2023, May 22). Microsoft. Available online: https://learn.microsoft.com/en-us/answers/questions/31361/how-can-i-use-ethereum-through-azure.
35. (2023, May 22). Available online: https://github.com/tendermint/tendermint/blob/master/docs/nodes/running-in-production.md.
36. Thakkar, P., Nathan, S., and Viswanathan, B. (2018, January 25–28). Performance benchmarking and optimizing Hyperledger Fabric blockchain platform. Proceedings of the 26th IEEE International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, Milwaukee, WI, USA.10.1109/MASCOTS.2018.00034 ↗
37. FastFabric: Scaling hyperledger fabric to 20,000 transactions per second10.1002/nem.2099 ↗
38. Sukhwani, H., Martínez, J.M., Chang, X., Trivedi, K.S., and Rindos, A. (2017, January 26–29). Performance modeling of PBFT consensus process for permissioned blockchain network (Hyperledger Fabric). Proceedings of the IEEE Symposium on Reliable Distributed Systems, Hong Kong, China.10.1109/SRDS.2017.36 ↗
39. Sukhwani, H., Wang, N., Trivedi, K.S., and Rindos, A. (2018, January 1–3). Performance modeling of hyperledger fabric (permissioned blockchain network). Proceedings of the NCA 2018—2018 IEEE 17th International Symposium on Network Computing and Applications, Cambridge, MA, USA.10.1109/NCA.2018.8548070 ↗
40. Kuzlu, M., Pipattanasomporn, M., Gurses, L., and Rahman, S. (2019, January 14–17). Performance analysis of a hyperledger fabric blockchain framework: Throughput, latency and scalability. Proceedings of the 2019 2nd IEEE International Conference on Blockchain, Blockchain 2019, Atlanta, GA, USA.10.1109/Blockchain.2019.00003 ↗
41. (2023, May 22). GitHub [Source Code]. Available online: https://github.com/hyperledger/caliper-benchmarks/.
42. Blockchain Performance Analysis for Supporting Cross-Border E-Government Services10.1109/TEM.2020.2979325 ↗
43. Kreps, J. (2023, May 22). Benchmarking Apache Kafka: 2 Million Writes Per Second (On Three Cheap Machines). Available online: https://engineering.linkedin.com/kafka/benchmarking-apache-kafka-2-million-writes-second-three-cheap-machines.
44. (2023, May 22). GitHub [Source Code]. Available online: https://github.com/tendermint/tendermint/issues/1835#issuecomment-402054099.
45. (2023, May 22). GitHub [Source Code]. Available online: https://hyperledger.github.io/caliper-benchmarks/fabric/performance/2.1.0/goContract/nodeSDK/submit/create-asset/.
46. Le Noac’h, P., Costan, A., and Bougé, L. (2017, January 11–14). A performance evaluation of Apache Kafka in support of big data streaming applications. Proceedings of the 2017 IEEE International Conference on Big Data, Big Data 2017, Boston, MA, USA.10.1109/BigData.2017.8258548 ↗
47. A Distributed Message Delivery Infrastructure for Connected Vehicle Technology Applications10.1109/TITS.2017.2701799 ↗
48. Nguyen, D., Luckow, A., Duffy, E., Kennedy, K., and Apon, A. (2018, January 1–4). Evaluation of highly available cloud streaming systems for performance and price. Proceedings of the 18th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, Washington, DC, USA.10.1109/CCGRID.2018.00056 ↗
49. IBM (2023, May 22). Available online: https://www.ibm.com/blogs/blockchain/2019/04/does-hyperledger-fabric-perform-at-scale/.