End-to-end timing analysis of sporadic cause-effect chains in distributed systems

Marco Dürr, Georg Von Der Brüggen, Kuan Hsun Chen, Jian Jia Chen

Research output: Contribution to journalConference articleAcademicpeer-review

4 Citations (Scopus)

Abstract

A cause-effect chain is used to define the logical order of data dependent tasks, which is independent from the execution order of the jobs of the (periodic/sporadic) tasks. Analyzing the worst-case End-to-End timing behavior, associated to a cause-effect chain, is an important problem in embedded control systems. For example, the detailed timing properties of modern automotive systems are specified in the AUTOSAR Timing Extensions. In this paper, we present a formal End-to-End timing analysis for distributed systems. We consider the two most important End-to-End timing semantics, i.e., the button-to-action delay (termed as the maximum reaction time) and the worst-case data freshness (termed as the maximum data age). Our contribution is significant due to the consideration of the sporadic behavior of job activations, whilst the results in the literature have been mostly limited to periodic activations. The proof strategy shows the (previously unexplored) connection between the reaction time (data age, respectively) and immediate forward (backward, respectively) job chains. Our analytical results dominate the state of the art for sporadic task activations in distributed systems and the evaluations show a clear improvement for synthesized task systems as well as for a real world automotive benchmark setting.

Original languageEnglish
Article numbera58
JournalACM transactions on embedded computing systems
Volume18
Issue number5s
DOIs
Publication statusPublished - Oct 2019
Externally publishedYes
EventInternational Conference on Compilers, Architectures, and Synthesis for Embedded Systems, CASES 2019 - New York, United States
Duration: 13 Oct 201918 Oct 2019

Keywords

  • Distributed systems
  • Embedded control systems
  • End-to-End timing analysis
  • Sporadic cause-effect chains

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