Large Scale Data Management in Grid Systems: a Survey

Abstract

Today the grid computing, intended initially for the intensive computing, open towards the management of voluminous, heterogeneous, and distributed data on a large-scale environment. The grid data management raises new problems and presents real challenges: resource discovery, efficiency of access, autonomic management, security, and benchmarking. This importance comes out of characteristics offered by grid systems: autonomy, heterogeneity and dynamicity of nodes. Firstly, we recall the fundamental problems of the large scale data management in grid systems and characteristics of these systems. Then, we describe in a highlight way proposed approaches (Web services, P2P techniques, Agent-based approach) for resource discovery. The remainder of the paper is devoted to point out the contributions of mobile agents for some problems of large scale data management, in particularly: dynamic query optimization, task placement, and embedded cost model. We show how mobile agents can help for decentralized control, and scaling.