Schedulable Job-Level Dependencies for Cause-Effect Chains via Graph Neural Networks

arXiv (Cornell University)

Abstract

Modern automotive software architectures comprise large sets of mixed-criticality functions executing on shared multi-core platforms with strict real-time and end-to-end timing requirements. Sensor-to-actuator data propagation in such systems is typically expressed via cause-effect chains with worst-case data-age budgets. Job-level dependencies (JLDs) have been introduced to provide a schedule-agnostic mechanism for bounding the data age independently of the underlying scheduler. The state-of-the-art methods for synthesizing JLDs, however, do not check whether the produced JLDs are enforceable under a concrete scheduling policy or jointly schedulable at the system level. In this paper we propose the first machine-learning-based JLD synthesis method, built around a two-level Graph Neural Network with temperature-controlled sampling that learns the structural patterns connecting cause-effect chain configurations to their JLD solutions. Since learned outputs may not be correct by construction, we embed the GNN in a novel Generate-and-Verify architecture in which a safe DP data-age checker, together with a per-chain EDF feasibility checker and a system-level demand-bound test, accept or reject each candidate. We show that the ML-based generator substantially outperforms the original greedy heuristic while achieving orders-of-magnitude lower synthesis time, demonstrating that learned structural priors can effectively replace exponential propagation-tree enumeration on this class of real-time scheduling problems.

Authors 5

1. Silviu S. Craciunas

   NXP (Germany)

   Affiliation as printed

   NXP Semiconductors , Vienna , Austria

2. Christian Hakert

   TU Dortmund University · Technical University of Denmark

   Affiliation as printed

   TU Dortmund , Germany

   Technical University of Denmark , Kongens Lyngby , Denmark

3. Jian-Jia Chen Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen , Germany

4. Zdeněk Hanzálek

   Czech Technical University in Prague

   Affiliation as printed

   Czech Technical University , Czech Republic

5. Paul Pop

   Technical University of Denmark

   Affiliation as printed

   Technical University of Denmark , Kongens Lyngby , Denmark