Ultra-Low Latency Architectures for Secure Real-Time Payment Processing: Achieving Sub-50ms End-to-End Throughput
Keywords:
Ultra-Low, Payment, Throughput, Architecture, Latency, Security, Processing, Sub-50msAbstract
This article discusses advanced architectures to realize low latency in the order of micro-second in secure real-time payment processing systems. As the financial services industry requires increasing throughput of sub-50ms transactions, the traditional blockchain and cloud approaches are insufficient. We consider state-of-the-art frameworks Teechan, FastPay, SecurePay and edge/serverless-based infrastructures and compare their latency, throughput, scalability and security. An experimental analysis allows us to show how architectural optimizations and hybrid technologies can be used to bring about performance breakthroughs that do not affect data integrity or regulatory compliance. Our results provide a complete reference line and indicate the future work on real-time financial systems, which can be used in the construction of the next-generation payment systems with unprecedented responsiveness and reliability.
Downloads
References
Lind, J., Eyal, I., Pietzuch, P., & Sirer, E. G. (2016). Teechan: Payment channels using trusted execution environments. arXiv (Cornell University). https://doi.org/10.48550/arxiv.1612.07766
Baudet, M., Danezis, G., & Sonnino, A. (2020). FastPay: High-Performance Byzantine fault tolerant settlement. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2003.11506
Androulaki, E., Barger, A., Bortnikov, V., Cachin, C., Christidis, K., De Caro, A., ... & Yellick, J. (2018, April). Hyperledger fabric: a distributed operating system for permissioned blockchains. In Proceedings of the thirteenth EuroSys conference (pp. 1-15). https://doi.org/10.48550/arXiv.1801.10228
Carcillo, F., Dal Pozzolo, A., Le Borgne, Y. A., Caelen, O., Mazzer, Y., & Bontempi, G. (2018). Scarff: a scalable framework for streaming credit card fraud detection with spark. Information fusion, 41, 182-194. https://doi.org/10.48550/arXiv.1709.08920
Wen, J., Chen, Z., Li, D., Chen, J., Liu, Y., Wang, H., Jin, X., & Liu, X. (2022). FAASLIGHT: General Application-Level Cold-Start Latency Optimization for Function-as-a-Service in Serverless Computing. arXiv (Cornell University). https://doi.org/10.48550/arxiv.2207.08175
Chen, K., Zhang, T., Gitlin, R. D., & Fettweis, G. (2018). Ultra-Low latency mobile networking. IEEE Network, 33(2), 181–187. https://doi.org/10.1109/mnet.2018.1800011
Tian, X., Han, R., Wang, L., Lu, G., & Zhan, J. (2015). Latency critical big data computing in finance. The Journal of Finance and Data Science, 1(1), 33–41. https://doi.org/10.1016/j.jfds.2015.07.002
Kondoro, A., Dhaou, I., Tenhunen, H., & Mvungi, N. (2021). A low latency secure communication architecture for microgrid control. Energies, 14(19), 6262. https://doi.org/10.3390/en14196262
Vladyko, A., Elagin, V., Spirkina, A., Muthanna, A., & Ateya, A. (2022). Distributed Edge Computing with Blockchain Technology to Enable Ultra-Reliable Low-Latency V2X Communications. Electronics, 11(2), 173. https://doi.org/10.3390/electronics11020173
Ali-Eldin, A., Wang, B., & Shenoy, P. (2021). The Hidden cost of the Edge: A Performance Comparison of Edge and Cloud Latencies. arXiv (Cornell University).
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
All papers should be submitted electronically. All submitted manuscripts must be original work that is not under submission at another journal or under consideration for publication in another form, such as a monograph or chapter of a book. Authors of submitted papers are obligated not to submit their paper for publication elsewhere until an editorial decision is rendered on their submission. Further, authors of accepted papers are prohibited from publishing the results in other publications that appear before the paper is published in the Journal unless they receive approval for doing so from the Editor-In-Chief.
IJISAE open access articles are licensed under a Creative Commons Attribution-ShareAlike 4.0 International License. This license lets the audience to give appropriate credit, provide a link to the license, and indicate if changes were made and if they remix, transform, or build upon the material, they must distribute contributions under the same license as the original.
