Scheduling of Real-Time Tasks with Multiple Critical Sections in Multiprocessor Systems

TL;DR

This paper extends the Dependency Graph Approach for real-time multiprocessor task scheduling to handle tasks with multiple critical sections, demonstrating improved performance through novel graph construction and extensive evaluation.

Contribution

It removes the restriction of single critical sections per task and adapts job shop scheduling algorithms for dependency graph construction in multiprocessor real-time systems.

Findings

Significant performance improvements over existing methods

Effective implementation in Litmus^{RT} with manageable overheads

Extensive numerical evaluations validate the approach's advantages

Abstract

The performance of multiprocessor synchronization and locking protocols is a key factor to utilize the computation power of multiprocessor systems under real-time constraints. While multiple protocols have been developed in the past decades, their performance highly depends on the task partition and prioritization. The recently proposed Dependency Graph Approach showed its advantages and attracted a lot of interest. It is, however, restricted to task sets where each task has at most one critical section. In this paper, we remove this restriction and demonstrate how to utilize algorithms for the classical job shop scheduling problem to construct a dependency graph for tasks with multiple critical sections. To show the applicability, we discuss the implementation in Litmus^{RT} and report the overheads. Moreover, we provide extensive numerical evaluations under different configurations, which in many situations show significant improvement compared to the state-of-the-art.