Simulation of dynamic data replication strategies in Data Grids

Publisher Website
Google Scholar
Abstract
Data Grids provide geographically distributed resources for large-scale data-intensive applications that generate large data sets. However, ensuring efficient access to such huge and widely distributed data is hindered by the high latencies of the Internet. We address these challenges by employing intelligent replication and caching of objects at strategic locations. Inour approach, replication decisions are based on a cost-driven model that computes data access gains and replica creation and maintenance costs. These measures are in turn based on factors such as runtime accumulated read/write statistics, network latency, bandwidth, and replica size. To support large numbers of users who continuously change their data and processing needs, we introduce scalable replica distribution topologies that adapt replica placement to meet these needs. To evaluate the performance of our approach, we developed a Data Grid simulator, called the GridNet. Simulation results demonstrate that replication improves the data access time in Data Grids, and that the gain increases with the size of thedatasets involved.

This publication has 8 references indexed in Scilit: