Building Resilient Systems with Fault Tolerance and Recovery Mechanisms

Authors

  • Professor Julian Thorne

Abstract

Building resilient systems is a critical aspect of modern software engineering, particularly in the context of distributed applications where failures are inevitable. This paper presents a comprehensive overview of fault tolerance and recovery mechanisms, focusing on techniques such as redundancy, replication, consensus algorithms, and graceful degradation. The paper discusses how these strategies can be applied to improve the reliability and availability of software systems, ensuring minimal downtime and consistent performance under failure conditions. It also covers techniques such as automatic failover, retry logic, and monitoring for detecting and recovering from faults. Through case studies of enterprise-level systems, the research highlights the practical implementation of these techniques and their effectiveness in real-world applications.

References

Cardozo, K., Nehmer, L., Esmat, Z. A. R. E., Afsari, M., Jain, J., Parpelli, V., ... & Shahid, T. (2024). U.S. Patent No. 11,893,819. Washington, DC: U.S. Patent and Trademark Office.

Gupta, M., & Jain, J. (2024). Optimizing E-commerce Dynamic Pricing Using Aggregated Market Data and Cloud-Based Analytics. International Journal of Global Innovations and Solutions (IJGIS).

Jain, J., & Gupta, M. (2024). Enhancing Software Engineering Practices for AI-Driven Fintech Applications. International Journal of Global Innovations and Solutions (IJGIS).

Jain, J. (2024). AI-Driven Optical Character Recognition for Fraud Detection in FinTech Income Verification Systems.

Fiore, U., De Santis, A., Perla, F., Zanetti, P., & Palmieri, F. (2019). Using generative adversarial networks for improving classification effectiveness in credit card fraud detection. Information Sciences, 479, 448–455.

Jurgovsky, J., Granitzer, M., Ziegler, K., Calabretto, S., Portier, P. E., He-Guelton, L., & Caelen, O. (2018). Sequence classification for credit-card fraud detection. Expert Systems with Applications, 100, 234–245.

Chen, C., & Chen, M. (2020). A hybrid deep learning model for detecting financial fraud. In Proceedings of the IEEE Symposium on Computers and Communications (pp. 345–350).

Whitrow, C., Hand, D. J., Juszczak, P., Weston, D., & Adams, N. M. (2009). Transaction aggregation as a strategy for credit card fraud detection. Data Mining and Knowledge Discovery, 18(1), 30–55.

Van Vlasselaer, V., Eliassi-Rad, T., Akoglu, L., Snoeck, M., & Baesens, B. (2017). GOTCHA! Network-based fraud detection for social security fraud. Management Science, 63(9), 3090–3110.

Pozzolo, A. D., Boracchi, G., Caelen, O., Alippi, C., & Bontempi, G. (2018). Credit card fraud detection: A realistic modeling and a novel learning strategy. IEEE Transactions on Neural Networks and Learning Systems, 29(8), 3784–3797.

Carcillo, F., Dal Pozzolo, A., Le Borgne, Y. A., Caelen, O., Mazzer, Y., & Bontempi, G. (2019). Scarff: A scalable framework for streaming credit card fraud detection with Spark. Information Fusion, 41, 182–194.

Roy, A., Sun, J., Mahoney, W., Alshboul, R., & Prabakar, N. (2018). Deep learning detecting fraud in credit card transactions. In Proceedings of the IEEE International Conference on Big Data (pp. 1846–1855).

Cardozo, Kenneth, Landon Nehmer, Z. A. R. E. Esmat, Mani Afsari, Jitender Jain, Venkateshwar Parpelli, Bhuvaneswari Balasubramanian, Bijun Du, Daniel Nizinski, and Tausif Shahid. "Systems and methods for extracting and processing data using optical character recognition in real-time environments." U.S. Patent Application 18/429,247, filed May 23, 2024.

Jain, J. Leveraging Advanced AI and Cloud Computing for Scalable Innovations in Fintech Systems, 2022.

Jain, J., Khunger, A., Agarwal, G., Tanikonda, A., & Modake, R. (2021). Optimizing Payment Gateways in Fintech Using AI-Augmented OCR and Intelligent Workflow. Authorea Preprints.

Jain, J., Modake, R., Khunger, A., & dnyandev Jagdale, A. CLOUD-NATIVE SECURITY FRAMEWORK: USING MACHINE LEARNING TO IMPLEMENT SELECTIVE MFA IN MODERN BANKING PLATFORMS , 2019.

Published

2025-01-14

How to Cite

Thorne, P. J. (2025). Building Resilient Systems with Fault Tolerance and Recovery Mechanisms. Indonasian Journal of Advanced Research & Technology , 7(7). Retrieved from https://scholarlyarticle.vncinstitute.com/index.php/IJART/article/view/52

Issue

Section

Articles