P2P file-sharing systems have been suffering from file unavailability or poor download speed due to lack of file replicas. As a result, to download rare files, users are typically forced to pay long online waiting time (i.e., always-on strategy), which is unacceptable for most users. To get over this, several commercial P2P systems launch an offline download service, employing stable and high-capacity servers to take over the downloads. Thus users can log off and wait offline. While offline download shows a notable trend of growing popular, there has been little insight into its detailed QoS (i.e., success ratio and download time) provision and QoS characteristics. Through trace-driven simulation study, this paper quantitatively reveals the potential QoS provision of offline download, confirming that it can achieve high download success ratio (over 90%) with tolerable waiting time (less than 2 days in most cases). We further find that the retrieval of rare file is dramatically affected by any single replica's participation or leave, resulting in wildly fluctuated download time. The wild fluctuation prevents users from well perceiving the expected QoS of their offline downloads, leading to poor user experience. Motivated by this, we develop a QoS prediction method for offline download. Experiments show that the prediction achieves high accuracy and precision. Finally, we implement a prototype of offline download service, called SimpleOD, and present our experience of the QoS provision and the prediction performance in practice.
展开▼
