Optimizing Execution of Component-based Applications using Group Instances
CCGRID '01 Proceedings of the 1st International Symposium on Cluster Computing and the Grid
Dynamic Matching and Scheduling of a Class of Independent Tasks onto Heterogeneous Computing Systems
HCW '99 Proceedings of the Eighth Heterogeneous Computing Workshop
Decoupling Computation and Data Scheduling in Distributed Data-Intensive Applications
HPDC '02 Proceedings of the 11th IEEE International Symposium on High Performance Distributed Computing
BOINC: A System for Public-Resource Computing and Storage
GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
The Globus Striped GridFTP Framework and Server
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
The File Mover: an efficient data transfer system for Grid applications
CCGRID '04 Proceedings of the 2004 IEEE International Symposium on Cluster Computing and the Grid
Collaborative Data Distribution with BitTorrent for Computational Desktop Grids
ISPDC '05 Proceedings of the The 4th International Symposium on Parallel and Distributed Computing
Autonomic Data Placement Strategies for Update-intensiveWeb applications
AAA-IDEA '05 Proceedings of the First International Workshop on Advanced Architectures and Algorithms for Internet Delivery and Applications
Scheduling Data-IntensiveWorkflows onto Storage-Constrained Distributed Resources
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
On the Efficiency and Cost of Introducing QoS in BitTorrent
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
Scheduling Independent Tasks Sharing Large Data Distributed with BitTorrent
GRID '05 Proceedings of the 6th IEEE/ACM International Workshop on Grid Computing
An architecture for virtual organization (VO)-based effective peering of content delivery networks
Proceedings of the second workshop on Use of P2P, GRID and agents for the development of content networks
Scheduling data-intensive bags of tasks in P2P grids with bittorrent-enabled data distribution
Proceedings of the second workshop on Use of P2P, GRID and agents for the development of content networks
Are P2P Data-Dissemination Techniques Viable in Today's Data-Intensive Scientific Collaborations?
Euro-Par '07 Proceedings of the 13th European international conference on Parallel Processing
A super-peer model for multiple job submission on a grid
Euro-Par'06 Proceedings of the CoreGRID 2006, UNICORE Summit 2006, Petascale Computational Biology and Bioinformatics conference on Parallel processing
Approximate policy iteration for closed-loop learning of visual tasks
ECML'06 Proceedings of the 17th European conference on Machine Learning
Exploiting replication and data reuse to efficiently schedule data-intensive applications on grids
JSSPP'04 Proceedings of the 10th international conference on Job Scheduling Strategies for Parallel Processing
The scalability of swarming peer-to-peer content delivery
NETWORKING'05 Proceedings of the 4th IFIP-TC6 international conference on Networking Technologies, Services, and Protocols; Performance of Computer and Communication Networks; Mobile and Wireless Communication Systems
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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.