@article{127,
  author = {Mamoru Kobayashi, Jun Kageyama, Susumu Shibusawa, Tatsuhiro Yonekura},
  title = {File Replication Method Based on Demand Forecasting of File Download in P2P Networks},
  journal = {Journal of Digital Information Management},
  year = {2010},
  volume = {8},
  number = {4},
  doi = {},
  url = {http://www.dline.info/fpaper/jdim/v8i4/4.pdf},
  abstract = {In peer-to-peer (P2P) networks that support fi le-sharing services, the level of access demand can vary widely between different fi les. Since fewer nodes store fi les for which there is a lower demand, these fi les are more likely to be lost from the P2P networks if users leave the network or delete the fi les. 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 fi les. In this method, the number of fi le replicas to be placed is determined based on the forecast demand for the fi le, so that the loss of low-demand fi les 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 fi les and the amount of storage used. Our experimental results show that the proposed method prevents fi le loss by preserving lowdemand fi les over extended periods of time. We also confi rmed that the node storage resources consumed by this method are effi ciently used. },
}