• Shaikh Areeb Rasheed
• Suvarna D. Pingle

This paper presents the implementation of a lightweight predictive prefetching model designed to improve file retrieval performance in the InterPlanetary File System (IPFS). The system integrates a React.js web interface with MetaMask for decentralized authentication and uses the Pinata API to store and retrieve files from IPFS. A client-side prediction algorithm calculates a popularity score based on file access count and file age, enabling the system to identify and highlight files that the user is most likely to request next. The prediction logic runs entirely on the browser using local storage, ensuring low computational overhead and preserving the decentralized nature of IPFS. The implemented system includes modules for file upload, metadata management, access tracking, and trending file generation. Experimental evaluation demonstrates that the proposed approach improves the user’s ability to locate frequently accessed content while reducing retrieval effort. The results confirm that simple browser-based predictive techniques can significantly enhance the practical usability of decentralized storage platforms.

IPFS, Predictive Prefetching, Decentralized Storage, MetaMask, Pinata API, File Retrieval Optimization, Content Addressing.

"Implementation Of Enhancing File Retrieval Efficiency In Ipfs Using The Predictive Prefetching File Optimization Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 12, page no.a136-a142, December-2025, Available :http://www.jetir.org/papers/JETIR2512018.pdf

"Implementation Of Enhancing File Retrieval Efficiency In Ipfs Using The Predictive Prefetching File Optimization Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 12, page no. ppa136-a142, December-2025, Available at : http://www.jetir.org/papers/JETIR2512018.pdf