Revisiting the Schedule Graph Generation for the Exact and Sustainable Analysis of Non-preemptive Scheduling
Marek Vlk, Marek Jaros, Zdenek Hanzalek

TL;DR
This paper improves schedule graph generation methods for non-preemptive task scheduling, making analysis more accurate and efficient by reformulating policies and eligibility rules, applicable to tasks with jitter and execution variation.
Contribution
It introduces a new schedulability analysis with refined job-eligibility rules that is both exact and more efficient for non-work-conserving policies.
Findings
Analysis is substantially faster than previous methods.
The new approach is exact and applicable to both work-conserving and non-work-conserving policies.
Reformulating policies avoids negative results in schedulability analysis.
Abstract
This paper addresses the problem of scheduling non-preemptive tasks with release jitter and execution time variation on a uniprocessor. We show that the schedulability analysis based on schedule graph generation, proposed by Nasri and Brandenburg [RTSS 2017], produces negative results when it could be easily avoided by slightly reformalizing the notion of non-work-conserving policies. In this work, we develop a schedulability analysis that constructs the schedule graph using new job-eligibility rules and is exact and sustainable for both work-conserving and enhanced formalization of non-work-conserving policies. Besides, the experimental evaluation shows that our schedulability analysis is substantially faster.
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Taxonomy
TopicsScheduling and Optimization Algorithms
