Data replication in data grid systems is one of the important solutions that improve availability, scalability, and fault tolerance. However, this technique can also bring some involved issues such as maintaining replica consistency. Moreover, as grid environment are very dynamic some nodes can be more uploaded than the others to become eventually a bottleneck. The main idea of our work is to propose a complementary solution between replica consistency maintenance and dynamic load balancing strategy to improve access performances under a simulated grid environment
Data Grid is a geographically distributed environment that deals with data intensive application in ...
In data grid systems, data replication aims to increase availability, fault tolerance, load balancin...
Data Grid is an infrastructure that manages huge amount of data files, and provides intensive comput...
Data replication is a well-known technique used in distributed systems in order to improve fault tol...
The emergent of scientific applications which produce a huge volume of data files to be managed and ...
Data replication strategy is widely adopted for large scale data-intensive applications in distribut...
Data Grid is an infrastructure that manages huge amount of data files, and provides intensive comput...
In data grid systems, data replication aims to increase availability, fault tolerance, load balancin...
In data grid systems, data replication aims to increase availability, fault tolerance, load balancin...
Data grids are currently proposed solutions to large-scale data management problems, including effic...
Data Grid is an infrastructure that manages huge amount of data files, and provides intensive comput...
In data grid systems, data replication aims to increase availability, fault tolerance, load balancin...
International audienceIn data grid systems, data replication aims to increase availability, fault to...
Abstract--Grid computing provides virtual organizations of geographically distributed users with sof...
International audienceReplicating for performance constitutes an important issue in large-scale data...
Data Grid is a geographically distributed environment that deals with data intensive application in ...
In data grid systems, data replication aims to increase availability, fault tolerance, load balancin...
Data Grid is an infrastructure that manages huge amount of data files, and provides intensive comput...
Data replication is a well-known technique used in distributed systems in order to improve fault tol...
The emergent of scientific applications which produce a huge volume of data files to be managed and ...
Data replication strategy is widely adopted for large scale data-intensive applications in distribut...
Data Grid is an infrastructure that manages huge amount of data files, and provides intensive comput...
In data grid systems, data replication aims to increase availability, fault tolerance, load balancin...
In data grid systems, data replication aims to increase availability, fault tolerance, load balancin...
Data grids are currently proposed solutions to large-scale data management problems, including effic...
Data Grid is an infrastructure that manages huge amount of data files, and provides intensive comput...
In data grid systems, data replication aims to increase availability, fault tolerance, load balancin...
International audienceIn data grid systems, data replication aims to increase availability, fault to...
Abstract--Grid computing provides virtual organizations of geographically distributed users with sof...
International audienceReplicating for performance constitutes an important issue in large-scale data...
Data Grid is a geographically distributed environment that deals with data intensive application in ...
In data grid systems, data replication aims to increase availability, fault tolerance, load balancin...
Data Grid is an infrastructure that manages huge amount of data files, and provides intensive comput...