Improving files availability for BitTorrent using a diffusion model
This addresses file availability issues for BitTorrent users, representing an incremental improvement to existing P2P mechanisms.
The paper tackles the problem of ensuring continuous file availability in BitTorrent by proposing a combined mathematical diffusion model and neural network approach to forecast torrent availability and prioritize fragment copying, achieving improved availability metrics.
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.