Capacity Augmentation Bound of Federated Scheduling for Parallel DAG Tasks

Abstract

We present a novel federated scheduling approach for parallel real-time tasks under a general directed acyclic graph (DAG) model. We provide a capacity augmentation bound of 2 for hard real-time scheduling; here we use the worst-case execution time and critical-path length of tasks to determine schedulability. This is the best known capacity augmentation bound for parallel tasks. By constructing example task sets, we further show that the lower bound on capacity augmentation of federated scheduling is also 2 for any m > 2. Hence, the gap is closed and bound 2 is a strict bound for federated scheduling. The federated scheduling algorithm is also a schedulability test that often admits task sets with utilization much greater than 50%m. Type of Report: Other Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Capacity Augmentation Bound of Federated Scheduling for Parallel DAG Tasks Jing Li, Abusayeed Saifullah, Kunal Agrawal, Christopher Gill, and Chenyang Lu Department of Computer Science and Engineering Washington University in St. Louis {li.jing, saifullah}@go.wustl.edu, {kunal, cdgill, lu}@cse.wustl.edu