GA-Based Job Scheduling Strategies for Fault Tolerant Grid Systems

This work mainly aims at the designs of the genetic algorithm based scheduling strategies by considering four different fault tolerance techniques in the grid environment, including retry, migration, checkpoint, replication. We also take into account the risk relationship between jobs and nodes to improve the system reliability in the scheduling algorithm. According to the simulation results, we can find out that the performance of fault tolerant algorithms is better than risky algorithm whether in makespan, average turnaround time, or the job failure rate. Checkpoint algorithm has the best performance in all algorithms. On the other hand, retry algorithm is recommended for the system where the job sizes are usually smaller because of its simplicity. Finally, replicated algorithm is not suitable for the grid since it imposes too much overhead.