Minimal start time heuristics for scheduling workflows in heterogeneous computing systems

Abstract

Heterogeneous computing systems require efficient task-to-processor mapping for attaining high performance. Scheduling workflows on heterogeneous environments is shown to be NP-Complete. Several heuristics were developed to attain minimum schedule lengths. However, these algorithms employ level-wise approach of scheduling tasks. This indirectly assigns higher priority to the tasks at lower levels than those at higher levels. Further, the start time of tasks at higher levels is constrained by the completion times of tasks at lower levels. The present work proposes a novel heuristic based global scheduling algorithm namely Minimal Start Time (MST) algorithm for work- flows. The proposed approach focuses on minimizing the start times of tasks which are dependent on the tasks at lower levels to generate shorter span schedules. The primary merit of this scheme is due to the elimination of level constraints whenever there are no dependency constraints. The performance of MST algorithm is evaluated in terms of normalized makespan, speedup, efficiency and improvement of 5–20% in 80% of the cases is achieved in comparison to the earlier work.