File Replication Method Based on Demand Forecasting of File Download in P2P Networks

AbstrAct: In peer-to-peer (P2P) networks that support file-sharing services, the level of access demand can vary widely between different files. Since fewer nodes store files for which there is a lower demand, these files are more likely to be lost from the P2P networks if users leave the network or delete the files. File loss can cause users to seek alternatives to P2P services, and lead to degradation in service quality. We propose and evaluate a replication method based on demand forecasting that aims to prevent the loss of low-demand files. In this method, the number of file replicas to be placed is determined based on the forecast demand for the file, so that the loss of low-demand files is likely prevented by placing replicas at nodes that frequently use P2P services. Based on simulation results, we compared our proposed method with basic replication methods in terms of the number of files and the amount of storage used. Our experimental results show that the proposed method prevents file loss by preserving low-demand files over extended periods of time. We also confirmed that the node storage resources consumed by this method are efficiently used.