Abstract
The transfer of large input data files in P2P computing Grids often leads to delays in Task completion times. Existing research related to this topic has been focused on the spatial grouping of Tasks, i.e. reuse of available data through data caching and data-aware scheduling. However, it tends to decrease the level of parallelism of Task execution. In this paper, this issue is addressed by integrating the BitTorrent P2P file sharing protocol, a novel Task selection scheduling algorithm, an existing online, data-aware Resource selection algorithm (similar to Storage Affinity), and caching support. These algorithms have been implemented in the Lightweight Bartering Grid middleware. The Java implementation relies exclusively on Free and Open Source data transfer software (Azureus, Apache FTP server, edtFTPj). The proposed data transfer architecture does not need Predictive Communications Ordering or an explicit deployment of an overlay network. It is also easily deployable. Our main contribution is the joint use of P2P computing and P2P file sharing technologies, enabling a highly scalable and adaptive data transfer architecture to support P2P computing.