Scheduling Linear Workflows with Dynamically Adjustable Exit Tasks on Distributed Resources

In this study, we propose and investigate a scheduling technique for linear workflow (LW) jobs with dynamically adjustable exit tasks in a distributed system. The proposed approach takes into account the probability for a LW job to permit partial computations for its exit task, under specific conditions. We investigate via simulation the case where none, half or all of the LW jobs in the workload allow partial computations, under different scenarios of load conditions and service demand variability. The simulation results provide useful insights into how the probability for a LW job to permit partial computations for its exit task, as well as the system load, affect the system performance. The results also demonstrate that partial computations, under the proposed scheduling scheme, can reduce the mean response time of the LW jobs, incurring only an insignificant degradation in their average result precision.