Various scheduling algorithms have been proposed for real-time parallel tasks modeled as a Directed Acyclic Graph (DAG). The capacity augmentation bound is a quantitative metric widely used in this field to compare the algorithms. Among the existing algorithms, the lowest capacity augmentation bound for DAG tasks with implicit deadlines is 2, which has been achieved by federated scheduling. To improve the schedulability and lower the capacity augmentation bound, this paper proposes DAG-Fluid, an algorithm based on fluid scheduling. We prove that DAG-Fluid has a capacity augmentation bound of $2-\frac{1}{m+1}$ , in which $m$ is the number of processors in the system. Experiments show that DAG-Fluid performs better than the state of the art scheduling algorithms.

中文翻译：

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DAG-Fluid：DAG的实时调度算法

对于实时并行任务，已经提出了各种调度算法，这些算法被建模为有向无环图（DAG）。容量增加界限是在该领域中广泛使用的用于比较算法的定量度量。在现有算法中，具有隐式截止日期的DAG任务的最小容量扩充边界为2，这已通过联合调度实现。为了提高可调度性并降低容量扩充边界，本文提出了一种基于流体调度的DAG-Fluid算法。我们证明DAG-Fluid的容量增加范围为$ 2- \ frac {1} {m + 1} $ ，其中 $ m $是系统中的处理器数量。实验表明，DAG-Fluid的性能优于最新的调度算法。