Combining Data Replication Algorithms and Job Scheduling Heuristics in the Data Grid

Ming Tang, Bu-Sung Lee, Xueyan Tang, Chai Kiat Yeo

Abstract: In the Data Grid environment, the primary goal of data replication is to shorten the data access time that is experienced by the job and reduce the job turnaround time as a consequence. After introducing a Data Grid architecture that supports efficient data access for the Grid job, two dynamic data replication algorithms are put forward. Combined with different Grid scheduling heuristics, the performances of the data replication algorithms are evaluated with various simulations. The simulation results demonstrate that the dynamic replication algorithms can reduce the job turnaround time remarkably. Especially the combination of Shortest Turnaround Time (STT) scheduling heuristic and Centralized Dynamic Replication (CDR) algorithm exhibits prominent performance in diverse conditions of workload and system environment.