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Community-Driven Data Grids

Summary: Proposes community-driven data grids as domain-specific federations for e-science, exploiting data skew and query patterns to maximize throughput. It combines partitioning, replication and P2P to balance load, handle hotspots and bursts, and preserve reproducibility via immutable, versioned datasets for PB-scale sharing. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
9818
Venue
VLDB
Year
2008
Pagerank
4.1945683e-05
Overall Rank
12,419 | 13.61%
DOI
-

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