A framework for Model-Driven Engineering of resilient software-controlled systems
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A framework for Model-Driven Engineering of resilient software-controlled systems Jacopo Parri1
· Fulvio Patara1
· Samuele Sampietro1
· Enrico Vicario1
Received: 12 February 2020 / Accepted: 17 August 2020 © The Author(s) 2020
Abstract Emergent paradigms of Industry 4.0 and Industrial Internet of Things expect cyberphysical 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. Keywords Resilience · Software-controlled system of systems · Model-Driven Engineering · Reflection architectural pattern · Digital twins · Fault trees
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Fulvio Patara [email protected] https://stlab.dinfo.unifi.it/patara/ Jacopo Parri [email protected] Samuele Sampietro [email protected] Enrico Vicario [email protected] https://stlab.dinfo.unifi.it/vicario/
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Department of Information Engineering, University of Florence, Florence, Italy
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J. Parri et al.
Mathematics Subject Classification 68M15 · 68T05 · 68T42
1 Introduction 1.1 Motivation In the agenda of Industry 4.0 (I4.0), resilience of cyber-physical systems is expected to be supported by monitoring and control capabilities provided by software components exposing an agile interface for integration and processing of data carrying information at different levels of granularity, according to various pillars, notably Industrial Internet of Things (IIoT), big data and analytics, simulation, horizontal and vertical integration, and cloud computing [42,46]. This gives raise to a class of software-controlled systems that can afford functional, structural, and behavioural complexity while still maintaining commitment for high levels of reliability [1,34,45]. Effective exploitation of this potential largely depends on architectural choices that shape integration between physical, hardware, software, and human operators
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