Improving files availability for BitTorrent using a diffusion model

TL;DR

This paper introduces a combined mathematical and neural network approach to improve file fragment availability in BitTorrent by predicting peer behavior and optimizing fragment distribution.

Contribution

It presents a novel integration of diffusion modeling and neural networks to enhance fragment availability and counteract peer disconnections in P2P networks.

Findings

Improved fragment availability predictions

Enhanced torrent robustness against peer disconnections

Effective prioritization of file fragments for copying

Abstract

The BitTorrent mechanism effectively spreads file fragments by copying the rarest fragments first. We propose to apply a mathematical model for the diffusion of fragments on a P2P in order to take into account both the effects of peer distances and the changing availability of peers while time goes on. Moreover, we manage to provide a forecast on the availability of a torrent thanks to a neural network that models the behaviour of peers on the P2P system. The combination of the mathematical model and the neural network provides a solution for choosing file fragments that need to be copied first, in order to ensure their continuous availability, counteracting possible disconnections by some peers.