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Data Management in Grid and Peer-to-Peer Systems

53,49 €*

Sofort verfügbar, Lieferzeit: 1-3 Tage

Produktnummer: 18ee172a2873784a77a792ae6097663260
Themengebiete: Peer cost model data integration and metadata management data storage and management data stream systems data warehousing distributed query languages distributed systems dynamic data placement issues flexible and adaptive query processing
Veröffentlichungsdatum: 18.08.2008
EAN: 9783540851752
Sprache: Englisch
Seitenzahl: 121
Produktart: Kartoniert / Broschiert
Herausgeber: Hameurlain, Abdelkader
Verlag: Springer Berlin
Untertitel: First International Conference, Globe 2008, Turin, Italy, September 3, 2008, Proceedings
Produktinformationen "Data Management in Grid and Peer-to-Peer Systems"
First International Conference on Data Management in Grid and Peer-to-Peer (P2P) Systems, Globe 2008 Data management can be achieved by different types of systems: from centralized file management systems to grid and P2P systems passing through distributed systems, par- lel systems, and data integration systems. An increase in the demand of data sharing from different sources accessible through networks has led to proposals for virtual data in- gration approach. The aim of data integration systems, based on the mediator-wrapper architecture, is to provide uniform access to multiple distributed, autonomous and h- erogeneous data sources. Heterogeneity may occur at various levels (e. g. , different ha- ware platforms, operating systems, DBMS). For more than ten years, research topics such as grid and P2P systems have been very active and their synergy has been pointed out. They are important for scale d- tributed systems and applications that require effective management of voluminous, distributed, and heterogeneous data. This importance comes out of characteristics offered by these systems (e. g. , autonomy and the dynamicity of nodes, decentralized control for scaling). Today, the grid and P2P systems intended initially for intensive computing and file sharing are open to the management of voluminous, heteroge- ous, and distributed data in a large-scale environment.

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