| Summary: | Optimizing the scheduling algorithm is a key problem to improving the service efficiency of urban heterogeneous computing platforms. In this paper, we propose a novel list-based scheduling algorithm called Modified Predict Earliest Finish Time (MPEFT) for heterogeneous computing systems with the aim to minimize the total execution time. The algorithm consists of two stages: task prioritization and processor selection. In the task prioritization phase, the priority of tasks is calculated by time cost of all paths from a task to the exit task. Compared with the prior works, more accurate task priorities are obtained by considering not only the critical path but also the non-critical ones. In the processor selection phase, the processor is allocated for a task according to whether the computing resources are sufficient to its successive tasks. The experiments on randomly generated workflows and the workflows from practical applications show that the MPEFT outperforms other existing list scheduling algorithms.
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