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An Adaptive Priority-Based Heuristic Approach for Scheduling DAG Applications with Uncertainties

机译:基于自适应优先级的启发式调度不确定DAG应用

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摘要

In the context of large-scale distributed computing environments, among various DAG scheduling heuristics aiming at coping with severe uncertainties during task execution, those ones that try to maximize the parallelism of ready tasks seems to be promising. However, most of such heuristics consider only the DAG structure when making scheduling decision. When the information about task execution time (even though might be inaccurate) is given, it might be interesting to investigate whether this information should be taken into account during scheduling, and if yes, how to. This paper presents an adaptive priority-based heuristic, which properly considers the task execution time estimate and the DAG structure attributes in the task prioritization. The evaluation result shows the proposed approach obtains better scheduling performance than existing solutions.
机译:在大规模分布式计算环境的背景下,在旨在应对任务执行过程中的严重不确定性的各种DAG调度启发式方法中,那些试图使就绪任务的并行性最大化的方法似乎很有希望。但是,大多数此类试探法在制定调度决策时仅考虑DAG结构。当给出有关任务执行时间的信息(即使可能不准确)时,调查在计划期间是否应考虑此信息可能是有趣的,如果是,则应该如何考虑。本文提出了一种基于自适应优先级的启发式方法,该方法在任务优先级排序中适当考虑了任务执行时间估计和DAG结构属性。评估结果表明,该方法具有比现有解决方案更好的调度性能。

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