Community-driven data grids

Beyond already existing huge data volumes, e-science communities face major challenges in managing the anticipated data deluge of forthcoming projects. Community-driven data grids target at domain-specific federations and provide a distributed, collaborative data management by employing dominant data characteristics (e. g., data skew) and query patterns to optimize the overall throughput. By combining well-established techniques for data partitioning and replication with Peer-to-Peer (P2P) technologies we can address several challenging problems: data load balancing, handling of query hot spots, and the adaption to short-term burst as well as long-term load redistributions.

• Type: Journal
• Year: 2008
• Where: PVLDB
• Authors: Tobias Scholl, Alfons Kemper
• Keywords: Collaborative Data Management, Dominant Data Characteristics, Huge Data Volumes, PVLDB 2008