SAGkit: A Python SAG Toolkit for Response Time Analysis of Hybrid-Triggered Jobs

TL;DR

SAGkit is a Python toolkit that provides exact and efficient response-time analysis for hybrid-triggered jobs in distributed control systems, addressing the limitations of traditional methods in handling complex timing scenarios.

Contribution

The paper introduces SAGkit, a novel Python toolkit implementing the SAG framework for exact RTA of hybrid-triggered jobs, enabling analysis of complex distributed systems with minimal overhead.

Findings

Achieves exact RTA with acceptable runtime

Handles non-preemptive systems with jitter and variations

Open-access toolkit for research and development

Abstract

For distributed control systems, modern latency-critical applications are increasingly demanding real-time guarantees and robustness. Response-time analysis (RTA) is useful for this purpose, as it helps analyze and guarantee timing bounds. However, conventional RTA methods struggle with the state-space explosion problem, especially in non-preemptive systems with release jitter and execution time variations. In this paper, we introduce SAGkit, a Python toolkit that implements the schedule-abstraction graph (SAG) framework. SAGkit novelly enables exact and sustainable RTA of hybrid-triggered jobs by allowing job absence on the SAG basis. Our experiments demonstrate that SAGkit achieves exactness with acceptable runtime and memory overhead. This lightweight toolkit empowers researchers to analyze complex distributed control systems and is open-access for further development.