DAG-Fluid: A Real-Time Scheduling Algorithm for DAGs
Fei Guan, Jiaqing Qiao, Yu Han
Abstract
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 - 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.