Using digital twins in the development of complex dependable real-time embedded systems

Xiaotian Dai; Shuai Zhao; Benjamin Michael Jean-Rene Lesage; Iain John Bate

doi:10.1007/978-3-031-19762-8

Using digital twins in the development of complex dependable real-time embedded systems

Xiaotian Dai, Shuai Zhao, Benjamin Michael Jean-Rene Lesage, Iain John Bate

Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

Modelling execution times in complex real-time embedded systems is vital for understanding and predicting tasks’ temporal behaviour, and to improve the system scheduling performance. Previous research mainly relied on worst-case execution time estimations based on formal static analyses that are often pessimistic. The models that resulted are hard to maintain and even harder to validate. In this work, the novel use of Digital Twins provides opportunities to improve this issue and beyond for dependable real-time systems. We aim to establish and contribute to three questions: (i) how to easily model execution times with an adequate level of abstraction, and how to evaluate the quality of that model; (ii) how to identify errors in the models and how to evaluate the impact of errors; and (iii) how to make decisions as to when and how to improve the models. In this paper, we proposed a Digital Twin-based adaptation framework, and demonstrated its use for modelling and refining execution time profiles. Key decisions concerning the quality of the model and its impact on performance are evaluated. Finally, some challenges and key research questions for the formal method community are proposed.

Original language	English
Title of host publication	International Symposium on Leveraging Applications of Formal Methods
Publisher	Springer
Pages	37-53
Number of pages	17
ISBN (Print)	9783031197611
DOIs	https://doi.org/10.1007/978-3-031-19762-8
Publication status	Published - 17 Oct 2022
Event	Leveraging Applications of Formal Methods, Verification and Validation. Practice: 11th International Symposium - Rhodes, Greece Duration: 22 Oct 2022 → 30 Oct 2022

Publication series

Name	Lecture Notes in Computer Science (LNCS)
Publisher	Springer
Volume	13702
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	Leveraging Applications of Formal Methods, Verification and Validation. Practice
Abbreviated title	ISoLA 2022
Country/Territory	Greece
City	Rhodes
Period	22/10/22 → 30/10/22

Bibliographical note

This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

Access to Document

10.1007/978-3-031-19762-8

ISoLA_22_DigitalTwin_ETM
This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details
Accepted author manuscript, 3.43 MB

Cite this

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title = "Using digital twins in the development of complex dependable real-time embedded systems",

abstract = "Modelling execution times in complex real-time embedded systems is vital for understanding and predicting tasks{\textquoteright} temporal behaviour, and to improve the system scheduling performance. Previous research mainly relied on worst-case execution time estimations based on formal static analyses that are often pessimistic. The models that resulted are hard to maintain and even harder to validate. In this work, the novel use of Digital Twins provides opportunities to improve this issue and beyond for dependable real-time systems. We aim to establish and contribute to three questions: (i) how to easily model execution times with an adequate level of abstraction, and how to evaluate the quality of that model; (ii) how to identify errors in the models and how to evaluate the impact of errors; and (iii) how to make decisions as to when and how to improve the models. In this paper, we proposed a Digital Twin-based adaptation framework, and demonstrated its use for modelling and refining execution time profiles. Key decisions concerning the quality of the model and its impact on performance are evaluated. Finally, some challenges and key research questions for the formal method community are proposed.",

author = "Xiaotian Dai and Shuai Zhao and Lesage, {Benjamin Michael Jean-Rene} and Bate, {Iain John}",

note = "This is an author-produced version of the published paper. Uploaded in accordance with the publisher{\textquoteright}s self-archiving policy. Further copying may not be permitted; contact the publisher for details; Leveraging Applications of Formal Methods, Verification and Validation. Practice : 11th International Symposium, ISoLA 2022 ; Conference date: 22-10-2022 Through 30-10-2022",

year = "2022",

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Dai, X , Zhao, S , Lesage, BMJ-R & Bate, IJ 2022, Using digital twins in the development of complex dependable real-time embedded systems. in International Symposium on Leveraging Applications of Formal Methods. Lecture Notes in Computer Science (LNCS), vol. 13702, Springer, pp. 37-53, Leveraging Applications of Formal Methods, Verification and Validation. Practice, Rhodes, Greece, 22/10/22. https://doi.org/10.1007/978-3-031-19762-8

Using digital twins in the development of complex dependable real-time embedded systems. / Dai, Xiaotian ; Zhao, Shuai ; Lesage, Benjamin Michael Jean-Rene et al.
International Symposium on Leveraging Applications of Formal Methods. Springer, 2022. p. 37-53 (Lecture Notes in Computer Science (LNCS); Vol. 13702).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Using digital twins in the development of complex dependable real-time embedded systems

AU - Dai, Xiaotian

AU - Zhao, Shuai

AU - Lesage, Benjamin Michael Jean-Rene

AU - Bate, Iain John

N1 - This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details

PY - 2022/10/17

Y1 - 2022/10/17

N2 - Modelling execution times in complex real-time embedded systems is vital for understanding and predicting tasks’ temporal behaviour, and to improve the system scheduling performance. Previous research mainly relied on worst-case execution time estimations based on formal static analyses that are often pessimistic. The models that resulted are hard to maintain and even harder to validate. In this work, the novel use of Digital Twins provides opportunities to improve this issue and beyond for dependable real-time systems. We aim to establish and contribute to three questions: (i) how to easily model execution times with an adequate level of abstraction, and how to evaluate the quality of that model; (ii) how to identify errors in the models and how to evaluate the impact of errors; and (iii) how to make decisions as to when and how to improve the models. In this paper, we proposed a Digital Twin-based adaptation framework, and demonstrated its use for modelling and refining execution time profiles. Key decisions concerning the quality of the model and its impact on performance are evaluated. Finally, some challenges and key research questions for the formal method community are proposed.

AB - Modelling execution times in complex real-time embedded systems is vital for understanding and predicting tasks’ temporal behaviour, and to improve the system scheduling performance. Previous research mainly relied on worst-case execution time estimations based on formal static analyses that are often pessimistic. The models that resulted are hard to maintain and even harder to validate. In this work, the novel use of Digital Twins provides opportunities to improve this issue and beyond for dependable real-time systems. We aim to establish and contribute to three questions: (i) how to easily model execution times with an adequate level of abstraction, and how to evaluate the quality of that model; (ii) how to identify errors in the models and how to evaluate the impact of errors; and (iii) how to make decisions as to when and how to improve the models. In this paper, we proposed a Digital Twin-based adaptation framework, and demonstrated its use for modelling and refining execution time profiles. Key decisions concerning the quality of the model and its impact on performance are evaluated. Finally, some challenges and key research questions for the formal method community are proposed.

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