Autonomic Data Management System in Grid Environment

Abstract

In grid environment, a job may execute on a node that is geographically far away from its data files. These files are stored in heterogeneous storage systems located at geographically distributed virtual organizations. The current approach includes explicit data file transfers to execution nodes, which forces users to deal with different administrative policies at each site and various data access mechanisms on each storage system. This implies a lot of human interventions in order to develop dedicated programs and scripts for data transfers for job execution. We have developed a framework, called GRAVY, which enables transparent data access between distributed file systems irrespective of their heterogeneity. This feature enables highlevel schedulers integrated with GRAVY to control data placements like computational jobs (i.e., they can be queued, scheduled and monitored). In particular, GRAVY provides reliable and efficient data placement across multiple protocols and has a mechanism for transfer failure recovery without any human interaction.