Evaluating Global Optimisation for Data Grids using Replica Location Services

As efforts to develop grid computing solutions gather pace, considerable attention has been directed at defining and addressing technical requirements associated with computational grids. However less focus has been given to the increasingly important challenge of achieving ready data availability over dispersed environments. Previous studies on data availability have explored replication strategies for data grids, with some incorporating both replication and processor scheduling schemes. These endeavours have however largely resulted in performance improvement at local sites without addressing global optimisation for the data grid networks, which typically consist of scattered nodes that participate in joint experiments. This paper sets out to study through the OPNET simulation environment, the impact on data grid performance, of employing replica location service (RLS)-based schemes. The RLS is designed as an enabling tool for achieving global efficiency in the data replication decisions by locating replicated datasets at most suitable places in distributed grid environments. The results from our simulations show that using RLS-based schemes to obtain data from neighbouring sites improves the performance of the data grid network