Replica Aware Job Scheduling in Grid Environments

We proposes a heuristic algorithm that explores the advantage of file sharing and replication while executing independent jobs in a grid environment. The proposed scheduling algorithm not only consider execution time load balancing, but also consider the location of data and replica these jobs require. The simulation results indicate that the proposed algorithm is more scalable than a random heuristic algorithm. In addition, in most cases the relative performance of our heuristic algorithm is within 50% of a conservative theoretical lower bound. The simulation results also indicate that the heuristic performs well in our synthesis environment, as well as in real grid system like Taiwan Unigrid.