• Shaikh Areeb Rasheed
• Suvarna D. Pingle

The InterPlanetary File System (IPFS) has emerged as a decentralized alternative to traditional client–server storage systems, offering improved data integrity, fault tolerance, and distributed access. However, retrieving files in IPFS can be slower than expected due to network-wide lookups, variable peer availability, and limited caching. This review paper examines existing challenges related to IPFS retrieval performance and explores the potential of lightweight predictive prefetching techniques to enhance file accessibility. The study analyses how simple behavioural indicators such as access frequency and file age can be combined into a popularity-based ranking model that predicts which files a user is likely to request next. Unlike complex machine learning approaches, this method remains entirely client-side, requires no centralized computation, and aligns with the decentralized philosophy of IPFS. The paper summarizes related work, identifies gaps in existing optimization methods, and highlights why predictive prefetching offers a practical direction for improving user experience in decentralized storage systems.

IPFS, Decentralized Storage, Predictive Prefetching, File Retrieval Optimization, Content Addressing, Distributed Hash Table (DHT), Pinning Services.

"Review 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 11, page no.g335-g339, November-2025, Available :http://www.jetir.org/papers/JETIR2511689.pdf

"Review 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 11, page no. ppg335-g339, November-2025, Available at : http://www.jetir.org/papers/JETIR2511689.pdf