Parallel Path Progression DAG Scheduling

TL;DR

This paper introduces a novel scheduling approach for DAG-based parallel tasks in real-time systems, significantly improving response time analysis and resource efficiency for highly parallel structures.

Contribution

It proposes a new path parallel progression scheduling property with only two subtask priorities, enhancing response time analysis and scheduling of DAG tasks.

Findings

Improved response time bounds for DAG tasks.

Enhanced scheduling efficiency for highly parallel structures.

Better resource utilization in real-time systems.

Abstract

To satisfy the increasing performance needs of modern cyber-physical systems, multiprocessor architectures are increasingly utilized. To efficiently exploit their potential parallelism in hard real-time systems, appropriate task models and scheduling algorithms that allow providing timing guarantees are required. Such scheduling algorithms and the corresponding worst-case response time analyses usually suffer from resource over-provisioning due to pessimistic analyses based on worst-case assumptions. Hence, scheduling algorithms and analysis with high resource efficiency are required. A prominent parallel task model is the directed-acyclic-graph (DAG) task model, where precedence constrained subjobs express parallelism. This paper studies the real-time scheduling problem of sporadic arbitrary-deadline DAG tasks. We propose a path parallel progression scheduling property with only two distinct subtask priorities, which allows to track the execution of a collection of paths simultaneously. This novel approach significantly improves the state-of-the-art response time analyses for parallel DAG tasks for highly parallel DAG structures. Two hierarchical scheduling algorithms are designed based on this property, extending the parallel path progression properties and improving the response time analysis for sporadic arbitrary-deadline DAG task sets.