Chord: A scalable peer-to-peer lookup service for internet applications
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
A scalable content-addressable network
Proceedings of the 2001 conference on Applications, technologies, architectures, and protocols for computer communications
The D0 Experiment Data Grid - SAM
GRID '01 Proceedings of the Second International Workshop on Grid Computing
Locating Data in (Small-World?) Peer-to-Peer Scientific Collaborations
IPTPS '01 Revised Papers from the First International Workshop on Peer-to-Peer Systems
Condor-G: A Computation Management Agent for Multi-Institutional Grids
HPDC '01 Proceedings of the 10th IEEE International Symposium on High Performance Distributed Computing
Enhanced Dynamic Hierarchical Replication and Weighted Scheduling Strategy in Data Grid
Journal of Parallel and Distributed Computing
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In modern scientific computing communities, scientists are involved in managing massive amounts of very large data collections in a geographically distributed environment. Research in the area of grid computing has given us various ideas and solutions to address these requirements. Data grid mostly deals with large computational problems and provides geographically distributed resources for large-scale data-intensive applications that generate large data sets. Peer-to-peer (P2P) networks have also become a major research topic over the last few years. In a distributed P2P system, a discovery algorithm is required to locate specific information, applications, or users within the system. In this research work, we present our scientific data grid as a large P2P-based distributed system model. By using this model, we study various discovery algorithms for locating data sets in a data grid system. The algorithms we studied are based on the P2P architecture. We investigate these algorithms using our Grid Simulator developed using PARSEC. In this paper, we illustrate our scientific data grid model and our Grid Simulator. We then analyze the performance of the discovery algorithms relative to their average number of hop, success rates and bandwidth consumption.