Timing analysis of asynchronized distributed cause-effect chains

Mario Gunzel; Kuan Hsun Chen; Niklas Ueter; Georg von der Brüggen; Marco Durr; Jian Jia Chen

doi:10.1109/RTAS52030.2021.00012

Timing analysis of asynchronized distributed cause-effect chains

Mario Gunzel, Kuan Hsun Chen, Niklas Ueter, Georg von der Brüggen, Marco Durr, Jian Jia Chen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

41 Citations (Scopus)

Abstract

Real-time systems require the formal guarantee of timing-constraints, not only for the individual tasks but also for the data-propagation paths. A cause-effect chain describes the data flow among multiple tasks, e.g., from sensors to actuators, independent from the priority order of the tasks. In this paper, we provide an end-to-end timing-analysis for cause-effect chains on asynchronized distributed systems with periodic task activations, considering the maximum reaction time (duration of data processing) and the maximum data age (ivorst-case data freshness). On one local electronic control unit (ECU), we present how to compute the exact local (ivorst-case) end-to-end latencies when the execution time of the periodic tasks is fixed. We further extend our analysis to globally asynchronized systems by combining the local results. Throughout synthesized data based on an automotive benchmark as well as on randomized parameters, we show that our analytical results improve the state-of-the-art for periodic task activations.

Original language	English
Title of host publication	2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021
Place of Publication	Piscataway, NJ
Publisher	IEEE
Pages	40-52
Number of pages	13
ISBN (Electronic)	978-1-6654-0386-3
ISBN (Print)	978-1-6654-4739-3
DOIs	https://doi.org/10.1109/RTAS52030.2021.00012
Publication status	Published - May 2021
Externally published	Yes
Event	27th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2021 - Virtual, Online Duration: 18 May 2021 → 21 May 2021 Conference number: 27

Publication series

Name	Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS
Publisher	IEEE
Volume	2021
ISSN (Print)	1545-3421
ISSN (Electronic)	2642-7346

Conference

Conference	27th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2021
Abbreviated title	RTAS 2021
City	Virtual, Online
Period	18/05/21 → 21/05/21

Keywords

Cause-effect Chains
Distributed Systems
Embedded Control Systems
End-to-end Timing Analysis
Real-Time Systems

Access to Document

10.1109/RTAS52030.2021.00012

Cite this

Gunzel, M., Chen, K. H., Ueter, N., von der Brüggen, G., Durr, M., & Chen, J. J. (2021). Timing analysis of asynchronized distributed cause-effect chains. In 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021 (pp. 40-52). Article 9470490 (Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS; Vol. 2021). IEEE. https://doi.org/10.1109/RTAS52030.2021.00012

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title = "Timing analysis of asynchronized distributed cause-effect chains",

abstract = "Real-time systems require the formal guarantee of timing-constraints, not only for the individual tasks but also for the data-propagation paths. A cause-effect chain describes the data flow among multiple tasks, e.g., from sensors to actuators, independent from the priority order of the tasks. In this paper, we provide an end-to-end timing-analysis for cause-effect chains on asynchronized distributed systems with periodic task activations, considering the maximum reaction time (duration of data processing) and the maximum data age (ivorst-case data freshness). On one local electronic control unit (ECU), we present how to compute the exact local (ivorst-case) end-to-end latencies when the execution time of the periodic tasks is fixed. We further extend our analysis to globally asynchronized systems by combining the local results. Throughout synthesized data based on an automotive benchmark as well as on randomized parameters, we show that our analytical results improve the state-of-the-art for periodic task activations.",

keywords = "Cause-effect Chains, Distributed Systems, Embedded Control Systems, End-to-end Timing Analysis, Real-Time Systems",

author = "Mario Gunzel and Chen, {Kuan Hsun} and Niklas Ueter and {von der Br{\"u}ggen}, Georg and Marco Durr and Chen, {Jian Jia}",

note = "Funding Information: ACKNOWLEDGMENT This work has been supported by European Research Council (ERC) Consolidator Award 2019, as part of PropRT (Number 865170), and by Deutsche Forschungsgemeinschaft (DFG), as part of Sus-Aware (Project no. 398602212) Publisher Copyright: {\textcopyright} 2021 IEEE.; 27th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2021, RTAS 2021 ; Conference date: 18-05-2021 Through 21-05-2021",

year = "2021",

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doi = "10.1109/RTAS52030.2021.00012",

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isbn = "978-1-6654-4739-3",

series = "Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS",

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Gunzel, M, Chen, KH, Ueter, N, von der Brüggen, G, Durr, M & Chen, JJ 2021, Timing analysis of asynchronized distributed cause-effect chains. in 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021., 9470490, Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS, vol. 2021, IEEE, Piscataway, NJ, pp. 40-52, 27th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2021, Virtual, Online, 18/05/21. https://doi.org/10.1109/RTAS52030.2021.00012

Timing analysis of asynchronized distributed cause-effect chains. / Gunzel, Mario; Chen, Kuan Hsun; Ueter, Niklas et al.
2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021. Piscataway, NJ: IEEE, 2021. p. 40-52 9470490 (Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS; Vol. 2021).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

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AU - Gunzel, Mario

AU - Chen, Kuan Hsun

AU - Ueter, Niklas

AU - von der Brüggen, Georg

AU - Durr, Marco

AU - Chen, Jian Jia

N1 - Conference code: 27

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N2 - Real-time systems require the formal guarantee of timing-constraints, not only for the individual tasks but also for the data-propagation paths. A cause-effect chain describes the data flow among multiple tasks, e.g., from sensors to actuators, independent from the priority order of the tasks. In this paper, we provide an end-to-end timing-analysis for cause-effect chains on asynchronized distributed systems with periodic task activations, considering the maximum reaction time (duration of data processing) and the maximum data age (ivorst-case data freshness). On one local electronic control unit (ECU), we present how to compute the exact local (ivorst-case) end-to-end latencies when the execution time of the periodic tasks is fixed. We further extend our analysis to globally asynchronized systems by combining the local results. Throughout synthesized data based on an automotive benchmark as well as on randomized parameters, we show that our analytical results improve the state-of-the-art for periodic task activations.

AB - Real-time systems require the formal guarantee of timing-constraints, not only for the individual tasks but also for the data-propagation paths. A cause-effect chain describes the data flow among multiple tasks, e.g., from sensors to actuators, independent from the priority order of the tasks. In this paper, we provide an end-to-end timing-analysis for cause-effect chains on asynchronized distributed systems with periodic task activations, considering the maximum reaction time (duration of data processing) and the maximum data age (ivorst-case data freshness). On one local electronic control unit (ECU), we present how to compute the exact local (ivorst-case) end-to-end latencies when the execution time of the periodic tasks is fixed. We further extend our analysis to globally asynchronized systems by combining the local results. Throughout synthesized data based on an automotive benchmark as well as on randomized parameters, we show that our analytical results improve the state-of-the-art for periodic task activations.

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KW - Embedded Control Systems

KW - End-to-end Timing Analysis

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BT - 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021

PB - IEEE

CY - Piscataway, NJ

T2 - 27th IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS 2021

Y2 - 18 May 2021 through 21 May 2021

ER -

Gunzel M, Chen KH, Ueter N, von der Brüggen G, Durr M, Chen JJ. Timing analysis of asynchronized distributed cause-effect chains. In 2021 IEEE 27th Real-Time and Embedded Technology and Applications Symposium, RTAS 2021. Piscataway, NJ: IEEE. 2021. p. 40-52. 9470490. (Proceedings of the IEEE Real-Time and Embedded Technology and Applications Symposium, RTAS). doi: 10.1109/RTAS52030.2021.00012

Timing analysis of asynchronized distributed cause-effect chains

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Keywords

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