رویکردهای مدل‌سازی چندپارادایمی برای سیستم‌های سایبر-فیزیکی

Multi-Paradigm Modelling for Cyber-Physical Systems explores modeling and analysis as crucial activities in the development of Cyber-Physical Systems, which are inherently cross-disciplinary in nature and require distinct modeling techniques related to different disciplines, as well as a common background knowledge. This book will serve as a reference for anyone starting in the field of CPS who needs a solid foundation of modeling, including a comprehensive introduction to existing techniques and a clear explanation of their advantages and limitations. This book is aimed at both researchers and practitioners who are interested in various modeling paradigms across computer science and engineering. Identifies key problems and offers solution approaches as well as tools which have been developed or are necessary for modeling paradigms across cyber physical systems Explores basic theory and current research topics, related challenges, and research directions for multi-paradigm modeling Provides a complete, conceptual overview and framework of the research done by the MPM4CPS working groups and the different types of modeling paradigms developed Front Cover Multi-Paradigm Modelling Approaches for Cyber-Physical Systems Copyright Contents List of contributors 1 Introduction 1.1 Objectives 1.2 Outline of the book 1.2.1 Part 1 – Ontological framework 1.2.2 Part 2 – Methods and tools 1.2.3 Part 3 – Case studies 1.3 Acknowledgements Part 1 Ontological framework 2 An ontological foundation for multi-paradigm modelling for cyber-physical systems 2.1 Introduction 2.2 Ontology development approach 2.2.1 Modelling modes 2.2.2 Domain analysis process 2.3 Modelling languages and tools 2.3.1 Feature modelling and FeatureIDE 2.3.2 Web Ontology Language (OWL) and Protégé 2.3.3 Integrating feature modelling and OWL 2.4 Ontology architecture 2.5 Shared ontology 2.5.1 Linguistic Domain Concepts (LinguisticDC) 2.5.1.1 Languages 2.5.1.2 Syntaxes 2.5.1.3 Semantics 2.5.2 Workflow Domain Concepts (WorkflowDC) 2.5.3 Project Management Domain Concepts (ProjectManagementDC) 2.5.3.1 Stakeholders and project organisation 2.5.3.2 Resources 2.5.3.3 Project and project phases 2.5.4 Architecture Domain Concepts (ArchitectureDC) 2.5.5 Paradigm Domain Concepts (ParadigmDC) 2.6 Introduction of examples 2.6.1 Ensemble-based cyber-physical system 2.6.1.1 Overview 2.6.1.2 CPS case study 2.6.1.3 Tool chain 2.6.2 HPI cyber-physical systems lab 2.6.2.1 Overview 2.6.2.2 CPS case study 2.6.2.3 Tool chain 2.7 Conclusion References 3 A feature-based ontology for cyber-physical systems 3.1 Introduction 3.2 Metamodel of cyber-physical systems 3.3 Feature model of cyber-physical systems 3.3.1 Top-level feature diagram 3.3.2 CPS constituent elements 3.3.3 Non-functional requirements 3.3.4 Application domains 3.3.5 Disciplines 3.4 Architecture of CPS 3.5 Examples 3.5.1 Ensemble-based cyber-physical system 3.5.2 HPI cyber-physical systems lab 3.6 Conclusion References 4 An ontology for multi-paradigm modelling 4.1 Introduction 4.2 State of the art 4.2.1 Core modelling concepts 4.2.2 Multi-formalism modelling approaches 4.2.3 Model management approaches 4.2.3.1 Construction of models and modelling languages Model elements and model links Interfaces Metamodel composition 4.2.3.2 Construction of model operations Flow composition approaches Context composition approaches 4.2.3.3 Model management approaches Model integration languages Megamodels 4.3 MPM ontology 4.3.1 Core modelling notions 4.3.2 Micromodelling scale 4.3.3 Megamodelling scale 4.3.3.1 Modelling language 4.3.3.2 Megamodel 4.3.3.3 Activity performers 4.3.3.4 Formalism 4.4 Examples 4.4.1 Ensemble-based cyber-physical system 4.4.1.1 Overview 4.4.1.2 Formalism, modelling languages, models, and tools 4.4.1.3 Simulation stage 4.4.2 HPI CPSLab 4.4.2.1 Overview 4.4.2.2 Formalism, languages, models, and tools 4.4.3 Simulation stage 4.4.3.1 Model Test (MT) 4.4.3.2 Model Test – MPM ontology 4.4.3.3 Model-in-the-loop 4.4.3.4 Model-in-the-loop – MPM ontology 4.4.3.5 Rapid prototyping 4.4.3.6 Rapid prototyping – MPM ontology 4.4.3.7 Prototyping stage 4.4.3.8 Software in the Loop (SiL) 4.4.3.9 Software in the Loop (SiL) – MPM ontology 4.4.3.10 Hardware in the Loop (HiL) 4.4.3.11 Hardware in the Loop (HiL) – MPM ontology 4.5 Conclusion References 5 An integrated ontology for multi-paradigm modelling for cyber-physical systems 5.1 Introduction 5.2 State of the art 5.2.1 Viewpoints 5.2.2 Model-based development process modelling 5.2.3 Modelling paradigms 5.3 Ontology 5.3.1 Viewpoint 5.3.2 Model-based workflows 5.3.2.1 Model-based process 5.3.2.2 Activity performers 5.3.3 Modelling paradigms 5.4 Examples 5.4.1 EBCPS 5.4.1.1 Methodology 5.4.1.2 Methodology implementing process 5.4.2 HPI CPSLab 5.4.2.1 Methodology 5.4.2.2 Methodology implementing process 5.4.2.3 Simulation stage 5.4.2.4 Prototyping stage 5.4.3 Modelling paradigms 5.5 Conclusion References Part 2 Methods and tools 6 Enabling composition of cyber-physical systems with the two-hemisphere model-driven approach 6.1 Introduction 6.2 Components of cyber-physical systems 6.3 Cyber-physical systems in the context of system composition 6.4 Two-hemisphere model-driven approach 6.5 The two-hemisphere model-driven approach for solving composition problems 6.6 Conclusions Acknowledgements References 7 Multi-paradigm modelling and co-simulation in prototyping a cyber-physical production system 7.1 Introduction 7.2 Case study description 7.3 Techniques 7.3.1 The INTO-CPS technology 7.3.2 Initial models 7.3.3 Discrete-event first with VDM-RT/Overture 7.4 Methodology 7.5 Modelling of the subsystems 7.5.1 Subsystem models 7.6 Verification & validation 7.6.1 Homogeneous phase experiments 7.6.2 Analysis of the homogeneous simulation in relation to the physical system 7.6.3 Heterogeneous phase experiments 7.7 Conclusion 7.7.1 Two-phase development 7.7.2 Methodological insights Acknowledgements References 8 Agent-based cyber-physical system development with SEA_ML++ 8.1 Introduction 8.2 Background 8.3 Related work 8.4 SEA_ML++ 8.4.1 Abstract syntax 8.4.2 Graphical concrete syntax 8.4.3 Transformations 8.5 Agent-based CPS modelling and development using SEA_ML++ 8.6 Development of a multi-agent garbage collection CPS 8.6.1 System design 8.6.2 System development 8.6.3 Demonstration 8.7 Conclusion Acknowledgements References 9 CREST – a DSML for hybrid CPS modelling 9.1 Introduction 9.2 Hybrid formalisms 9.2.1 Timed and hybrid automata tools 9.2.2 Hybrid extensions of discrete formalisms 9.3 Domain-specific, hybrid modelling using CREST 9.3.1 CREST syntax 9.3.2 CREST semantics 9.3.3 Verification 9.4 Implementation 9.5 Discussion 9.6 Summary References Part 3 Case studies 10 Development of an IoT and WSN based CPS using MPM approach: a smart fire detection case study 10.1 Introduction 10.2 Requirement elicitation 10.3 System design 10.3.1 Architectural design 10.3.2 Detailed design 10.4 Modelling and simulation 10.5 Implementation 10.5.1 Hardware setup 10.5.2 Software development 10.6 Multi-paradigm development process in FTG+PM framework 10.6.1 The Formalism Transformation Graph (FTG) 10.6.2 The Process Model (PM) 10.7 Summary 10.8 Literature and further reading Acknowledgements References 11 Development of industry oriented cross-domain study programs in cyber-physical systems for Belarusian and Ukrainian universities 11.1 Introduction 11.2 Related work 11.3 Review of the labour markets of Belarus and Ukraine 11.3.1 The needs of the Belarusian labour market 11.3.2 The needs of the Ukrainian labour market 11.4 COST Action input to European curricula on CPS 11.5 Identification of industry needs 11.5.1 Method of the research on curricular in CPS 11.5.2 Analysis of survey of research institutions of Belarus 11.5.3 Analysis of survey of enterprises of Ukraine 11.5.4 Findings of survey of research institutions 11.6 Validation of COST findings for curricula on CPS in Belarusian and Ukrainian universities 11.7 Discussions and conclusions Acknowledgements References Index Back Cover "Multi-Paradigm Modelling for Cyber-Physical Systems explores modeling and analysis as crucial activities in the development of Cyber-Physical Systems, which are inherently cross-disciplinary in nature and require distinct modeling techniques related to different disciplines, as well as a common background knowledge. This book will serve as a reference for anyone starting in the field of CPS who needs a solid foundation of modeling, including a comprehensive introduction to existing techniques and a clear explanation of their advantages and limitations. This book is aimed at both researchers and practitioners who are interested in various modeling paradigms across computer science and engineering."--Page 4 of cover