AI-ENHANCED REAL-TIME DATA SYNCHRONIZATION IN DISTRIBUTED FRONT-END WEB APPLICATIONS

Authors

  • Vaibhav Vudayagiri F5 Networks Inc, USA Author

Keywords:

Artificial Intelligence, Real-time Data Synchronization, Distributed Systems, Front-end Web Applications, Machine Learning Optimization

Abstract

Real-time data synchronization is essential for enhancing user experience in collaborative and interactive web applications operating in distributed environments. This article presents novel AI-driven techniques for optimizing data synchronization and conflict resolution in distributed front-end applications. The approach combines transformer-based neural networks with adaptive conflict resolution strategies, trained on an extensive dataset of 1.2 million real-world conflict scenarios. The article demonstrates exceptional performance improvements, achieving an 89% accuracy in automated conflict resolution compared to the traditional industry average of 65%, while reducing average resolution time from 89ms to 23ms.

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Published

2024-12-03

How to Cite

Vaibhav Vudayagiri. (2024). AI-ENHANCED REAL-TIME DATA SYNCHRONIZATION IN DISTRIBUTED FRONT-END WEB APPLICATIONS. INTERNATIONAL JOURNAL OF RESEARCH IN COMPUTER APPLICATIONS AND INFORMATION TECHNOLOGY (IJRCAIT), 7(2), 1701-1709. https://ijrcait.com/index.php/home/article/view/IJRCAIT_07_02_132