research-article

A framework for Model-Driven Engineering of resilient software-controlled systems

Authors:

Samuele Sampietro,

Enrico VicarioAuthors Info & Claims

Computing, Volume 103, Issue 4

Pages 589 - 612

https://doi.org/10.1007/s00607-020-00841-6

Published: 01 April 2021 Publication History

Abstract

Emergent paradigms of Industry 4.0 and Industrial Internet of Things expect cyber-physical systems to reliably provide services overcoming disruptions in operative conditions and adapting to changes in architectural and functional requirements. In this paper, we describe a hardware/software framework supporting operation and maintenance of software-controlled systems enhancing resilience by promoting a Model-Driven Engineering (MDE) process to automatically derive structural configurations and failure models from reliability artifacts. Specifically, a reflective architecture developed around digital twins enables representation and control of system Configuration Items properly derived from SysML Block Definition Diagrams, providing support for variation. Besides, a plurality of distributed analytic agents for qualitative evaluation over executable failure models empowers the system with runtime self-assessment and dynamic adaptation capabilities. We describe the framework architecture outlining roles and responsibilities in a System of Systems perspective, providing salient design traits about digital twins and data analytic agents for failure propagation modeling and analysis. We discuss a prototype implementation following the MDE approach, highlighting self-recovery and self-adaptation properties on a real cyber-physical system for vehicle access control to Limited Traffic Zones.

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Cited By

Rios EIturbe ERego AFerry NTigli JLavirotte SRocher GNguyen PSong HDautov RMallouli WCavalli A(2023)The DYNABIC approach to resilience of critical infrastructuresProceedings of the 18th International Conference on Availability, Reliability and Security10.1145/3600160.3605055(1-8)Online publication date: 29-Aug-2023
https://dl.acm.org/doi/10.1145/3600160.3605055
Plazas JBimonte SSchneider Mde Vaulx CBattistoni PSebillo MCorrales J(2022)Sense, Transform & Send for the Internet of Things (STS4IoT)Data & Knowledge Engineering10.1016/j.datak.2021.101971139:COnline publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.datak.2021.101971
Becker FBibow PDalibor MGannouni AHahn VHopmann CJarke MKoren IKröger MLipp JMaibaum JMichael JRumpe BSapel PSchäfer NSchmitz GSchuh GWortmann A(2021)A Conceptual Model for Digital Shadows in Industry and Its ApplicationConceptual Modeling10.1007/978-3-030-89022-3_22(271-281)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1007/978-3-030-89022-3_22

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A framework for Model-Driven Engineering of resilient software-controlled systems

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Published In

cover image Computing

Computing Volume 103, Issue 4

Apr 2021

212 pages

ISSN:0010-485X

Issue’s Table of Contents

© The Author(s) 2020.

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 April 2021

Accepted: 17 August 2020

Received: 12 February 2020

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Cited By

Rios EIturbe ERego AFerry NTigli JLavirotte SRocher GNguyen PSong HDautov RMallouli WCavalli A(2023)The DYNABIC approach to resilience of critical infrastructuresProceedings of the 18th International Conference on Availability, Reliability and Security10.1145/3600160.3605055(1-8)Online publication date: 29-Aug-2023
https://dl.acm.org/doi/10.1145/3600160.3605055
Plazas JBimonte SSchneider Mde Vaulx CBattistoni PSebillo MCorrales J(2022)Sense, Transform & Send for the Internet of Things (STS4IoT)Data & Knowledge Engineering10.1016/j.datak.2021.101971139:COnline publication date: 1-May-2022
https://dl.acm.org/doi/10.1016/j.datak.2021.101971
Becker FBibow PDalibor MGannouni AHahn VHopmann CJarke MKoren IKröger MLipp JMaibaum JMichael JRumpe BSapel PSchäfer NSchmitz GSchuh GWortmann A(2021)A Conceptual Model for Digital Shadows in Industry and Its ApplicationConceptual Modeling10.1007/978-3-030-89022-3_22(271-281)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1007/978-3-030-89022-3_22

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