Data Management in Grid and Peer-to-Peer Systems: First International Conference, Globe 2008, Turin, Italy, September 3, 2008, Proceedings
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.
1110832682
Data Management in Grid and Peer-to-Peer Systems: First International Conference, Globe 2008, Turin, Italy, September 3, 2008, Proceedings
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.
54.99 In Stock
Data Management in Grid and Peer-to-Peer Systems: First International Conference, Globe 2008, Turin, Italy, September 3, 2008, Proceedings

Data Management in Grid and Peer-to-Peer Systems: First International Conference, Globe 2008, Turin, Italy, September 3, 2008, Proceedings

by Abdelkader Hameurlain (Editor)
Data Management in Grid and Peer-to-Peer Systems: First International Conference, Globe 2008, Turin, Italy, September 3, 2008, Proceedings

Data Management in Grid and Peer-to-Peer Systems: First International Conference, Globe 2008, Turin, Italy, September 3, 2008, Proceedings

by Abdelkader Hameurlain (Editor)

Paperback(2008)

$54.99 
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Overview

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.

Product Details

ISBN-13: 9783540851752
Publisher: Springer Berlin Heidelberg
Publication date: 09/25/2008
Series: Lecture Notes in Computer Science , #5187
Edition description: 2008
Pages: 121
Product dimensions: 6.00(w) x 9.40(h) x 0.40(d)

Table of Contents

P2P Storage Systems and Caching.- A File Transfer Service with Client/Server, P2P and Wide Area Storage Prools.- A Study of Reconstruction Process Load in P2P Storage Systems.- Subrange Caching: Handling Popular Range Queries in DHTs.- Context-Aware Cache Management in Grid Middleware.- P2P Data Integration Systems.- Query Propagation in a P2P Data Integration System in the Presence of Schema Constraints.- Dynamic Source Selection in Large Scale Mediation Systems.- Information Sharing Agents in a Peer Data Exchange System.- Querying in Grid and P2P Systems.- Correlated Query Process and P2P Execution.- Multi-set DHT for Range Queries on Dynamic Data for Grid Information Service.- Experimenting the Query Performance of a Grid-Based Sensor Network Data Warehouse.
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