
Initially developed for the scientific community, Grid computing is now gaining much interest in important areas such as enterprise information systems. This makes data management critical since the techniques must scale up while addressing the autonomy, dynamicity and heterogeneity of the data sources. In this paper, we discuss the main open problems and new issues related to Grid data management. We first recall the main principles behind data management in distributed systems and the basic techniques. Then we make precise the requirements for Grid data management. Finally, we introduce the main techniques needed to address these requirements. This implies revisiting distributed database techniques in major ways, in particular, using P2P techniques.
[INFO.INFO-DC]Computer Science [cs]/Distributed, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], and Cluster Computing [cs.DC], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], ACM: E.: Data, peer-to-peer, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.5: Heterogeneous Databases, Parallel, Grid computing data management, distributed data management
[INFO.INFO-DC]Computer Science [cs]/Distributed, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], and Cluster Computing [cs.DC], [INFO.INFO-DC] Computer Science [cs]/Distributed, Parallel, and Cluster Computing [cs.DC], [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], ACM: E.: Data, peer-to-peer, ACM: H.: Information Systems/H.2: DATABASE MANAGEMENT/H.2.5: Heterogeneous Databases, Parallel, Grid computing data management, distributed data management
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