A Study of Predictive Caching Using Local Storage and Machine Learning in Web Applications

• Author(s): Ayush Wange; Dr. Netraja Mulay
• Paper ID: 1717631
• Page: 1535-1538
• Published Date: 14-05-2026
• Published In: Iconic Research And Engineering Journals
• Publisher: IRE Journals
• e-ISSN: 2456-8880
• Volume/Issue: Volume 9 Issue 11 May-2026

Abstract

This study explores improving web performance using Machine Learning–based predictive caching with localStorage. Traditional caching only stores previously visited content, which limits performance for first-time users. The proposed system predicts user behavior and preloads likely content in advance. The study compares no caching, traditional caching, and ML-based caching using metrics like LCP, FCP, and TTI. Results show significant improvements, with faster load times and higher cache efficiency using predictive caching. Overall, predictive caching provides a more efficient and responsive web experience than traditional methods.

Keywords

Localstorage, Predictive Caching, Machine Learning, Web Performance, LCP, FCP, TTI, Client-Side Caching, User Behavior Prediction.

Citations

IRE Journals:
Ayush Wange, Dr. Netraja Mulay "A Study of Predictive Caching Using Local Storage and Machine Learning in Web Applications" Iconic Research And Engineering Journals Volume 9 Issue 11 2026 Page 1535-1538 https://doi.org/10.64388/IREV9I11-1717631

IEEE:
Ayush Wange, Dr. Netraja Mulay "A Study of Predictive Caching Using Local Storage and Machine Learning in Web Applications" Iconic Research And Engineering Journals, 9(11) https://doi.org/10.64388/IREV9I11-1717631