This Open Access book presents the results of the "Collaborative Embedded Systems" (CrESt) project, aimed at adapting and complementing the methodology underlying modeling techniques developed to cope with the challenges of the dynamic structures of collaborative embedded systems (CESs) based on the SPES development methodology.
In order to manage the high complexity of the individual systems and the dynamically formed interaction structures at runtime, advanced and powerful development methods are required that extend the current state of the art in the development of embedded systems and cyber-physical systems. The methodological contributions of the project support the effective and efficient development of CESs in dynamic and uncertain contexts, with special emphasis on the reliability and variability of individual systems and the creation of networks of such systems at runtime.
The project was funded by the German Federal Ministry of Education and Research (BMBF), and the case studies are therefore selected from areas that are highly relevant for Germany’s economy (automotive, industrial production, power generation, and robotics). It also supports the digitalization of complex and transformable industrial plants in the context of the German government's "Industry 4.0" initiative, and the project results provide a solid foundation for implementing the German government's high-tech strategy "Innovations for Germany" in the coming years.
Author(s): Wolfgang Böhm, Manfred Broy, Cornel Klein, Klaus Pohl, Bernhard Rumpe, Sebastian Schröck
Publisher: Springer
Year: 2021
Language: English
Pages: 404
City: Cham
Preface
Table of Contents
1 CrESt Use Cases
1.1 Introduction
1.2 Vehicle Platooning
1.3 Adaptable and Flexible Factory
1.4 Autonomous Transport Robots
2 Engineering of Collaborative Embedded Systems
2.1 Introduction
2.2 Background
2.3 Collaborating Embedded Systems
2.3.1 Collaborative and Collaborating Systems
2.3.2 Goals of System Networks
2.3.3 Coordination in System Networks
2.3.4 Dynamics in System Networks
2.3.5 Functions
2.4 Problem Dimensions of Collaborative Embedded Systems
2.4.1 Challenges Related to Collaboration
2.4.2 Challenges Related to Dynamics
2.5 Application in the Domains “Cooperative Vehicle Automation” and “Industry 4.0”
2.5.1 Challenges in the Application Domain “Cooperative Vehicle Automation”
Collaboration
Dynamics
2.5.2 Challenges in the Application Domain “Industry 4.0”
Collaboration
Dynamics
2.6 Concepts and Methods for the Development of Collaborative Embedded Systems
2.6.1 Enhancements Regarding SPES2020 and SPES_XT
2.6.2 Collaboration
Goals
Functions and Behavior
Architecture and Structure
Communication
2.6.3 Dynamics
Goals
Functions and Behavior
Architecture and Structure
Context
Uncertainty
2.7 Conclusion
2.8 Literature
2.9 Appendix
3 Architectures for Flexible Collaborative Systems
3.1 Introduction
3.2 Designing Reference Architectures
3.2.1 Method for Designing Reference Architectures
3.2.2 Application Example: Reference Architecture for Adaptable and Flexible Factories
3.3 Reference Architecture for Operator Assistance Systems
3.3.1 Simulation-Based Operator Assistance
3.3.2 Design Decisions
3.3.3 Technical Reference Architecture
3.3.4 Workflow of Services and Data Flow
3.3.5 Application Example for an Adaptable and Flexible Factory
3.4 Checkable Safety Cases for Architecture Design
3.4.1 Checkable Safety Case Models – A Definition
3.4.2 Checkable Safety Case Patterns
3.4.3 An Example of Checkable Safety Case Patterns
3.5 Conclusion
3.6 Literature
4 Function Modeling for Collaborative Embedded Systems
4.1 Introduction
4.2 Methodological Approach
4.3 Background
4.4 Metamodel for Functions of CESs and CSGs
4.4.1 Systems, CESs, and CSGs
4.4.2 Functions
4.4.3 Goal Contribution and Fulfillment
4.4.4 Roles
4.4.5 Context and Adaptivity
4.5 Evaluation of the Metamodel
4.5.1 Abstraction
4.5.2 Relationships between Functions
4.5.3 Openness and Dynamicity
4.5.4 Goal Contributions
4.5.5 Relationships Between Functions and Systems
4.5.6 Input/Output Compatibility
4.5.7 Runtime Restructuring
4.6 Application of the Metamodel
4.6.1 Example from the Adaptable and Flexible Factory
4.6.2 Modeling of Goals for Transport Robots
4.7 Related Work
4.8 Conclusion
4.9 Literature
5 Architectures for Dynamically Coupled Systems
5.1 Introduction
5.2 Specification Modeling of the Behavior of Collaborative System Groups
5.3 Modeling CES Functional Architectures
5.3.1 Scenario
5.3.2 Modelling
5.3.3 Analysis
5.4 Extraction of Dynamic Architectures
5.4.1 Methods
5.4.2 Software Product Line Engineering
5.4.3 Product-Driven Software Product Line Engineering
5.4.4 Family Mining — A Method for Extracting Reference Architectures from Model Variants
5.4.5 Summary
5.5 Functional Safety Analysis (Online)
5.5.1 Functional Testing
5.5.2 Communication Errors
5.6 Conclusion
5.7 Literature
6 Modeling and Analyzing Context-Sensitive Changes during Runtime
6.1 Introduction and Motivation
6.2 Solution Concept
6.3 Ontology and Modeling
6.3.1 Ontology Building
6.3.2 Capability Modeling
6.3.3 Variability Modeling for Context-Sensitive Reconfiguration
6.3.4 Scenario-Based Modeling
6.4 Model Integration and Execution
6.4.1 Model Generation for Simulation Models
Model Generation via Knowledge Graph
Application to a Real Production System
6.4.2 Capability Matching
6.5 Conclusion
6.6 Literature
7 Handling Uncertainty in
Collaborative Embedded
Systems Engineering
7.1 Uncertainty in Collaborative Embedded Systems
7.1.1 Conceptual Ontology for Handling Uncertainty
7.1.2 Different Kinds of Uncertainty
7.2 Modeling Uncertainty
7.2.1 Orthogonal Uncertainty Modeling
Modeling Concepts and Notation
Example
7.2.2 Modeling Uncertainty in Traffic Scenarios
Modeling Traffic Scenarios for CSGs
Behavioral Uncertainty Modeling
Risk Assessment
7.3 Analyzing Uncertainty
7.3.1 Identifying Epistemic Uncertainties
Uncertainty Sources at the Type Level
Uncertainty Sources at the Instance Level
EURECA
7.3.2 Assessing Data-Driven Uncertainties
Three Types of Uncertainty Sources
Managing Uncertainty during Operation
Uncertainty Wrapper – Architecture and Application
Uncertainty Wrappers – Limitations and Advantages
7.4 Conclusion
7.5 Literature
8 Dynamic Safety Certification for Collaborative Embedded Systems at Runtime
8.1 Introduction and Motivation
8.2 Overview of the Proposed Safety Certification Concept
8.3 Assuring Runtime Safety Based on Modular Safety Cases
8.3.1 Modeling CESs and their Context
Modeling the Context
Content Ontology
Modeling Context in the Adaptable Factory
8.3.2 Runtime Uncertainty Handling
Concept Overview
Development of a U-Map for the Adaptable Factory
8.3.3 Runtime Monitoring of CESs and their Context
Meta-model SQUADfps
Case Study Example
8.3.4 Integrated Model-Based Risk Assessment
8.3.5 Dynamic Safety Certification
8.4 Design and Runtime Contracts
8.4.1 Design-Time Approach for Collaborative Systems
Creating the CSG Specification
Safety-Relevant Activities
8.4.2 Contracts Concept
8.4.3 Runtime Evaluation of Safety Contracts
Simulative Approach for Validation of Safety Contracts
Case Study: Vehicle Platoon Example
8.5 Conclusion
8.6 Literature
9 Goal-Based Strategy Exploration
9.1 Introduction
9.2 Goal Modeling for Collaborative System Groups
9.3 Goal-Based Strategy Development
9.4 Goal Operationalization (KPI Development)
9.5 Modeling Methodology for Adaptive Systems with MATLAB/Simulink
9.6 Collaboration Framework for Goal-Based Strategies
9.6.1 Fleet Management in Collaborative Resource Networks
9.6.2 Collaboration Framework
9.6.3 Collaboration Design in Decentralized Fleet Management
9.7 Conclusion
9.8 Literature
10 Creating Trust in Collaborative Embedded Systems
10.1 Introduction
10.2 Building Trust during Design Time
Testing framework for CSGs
Model
View
Controller
10.3 Building Trust during Runtime
10.4 Monitoring Collaborative Embedded Systems
Runtime Monitoring
Runtime Monitoring of Collaborative System Groups
Distributedness:
Embeddedness:
Runtime Monitoring of Interaction Protocols
Monitoring Functional Correctness
Agreement:
Existence:
Maximum:
Monitoring Correct Timing Behavior
U
Ut
10.5 Conclusion
10.6 Literature
11 Language Engineering for Heterogeneous Collaborative Embedded Systems
11.1 Introduction
11.2 MontiCore
11.3 Language Components
11.4 Language Component Composition
11.5 Language Product Lines
11.6 Conclusion
11.7 Literature
12 Development and Evaluation of Collaborative Embedded Systems using Simulation
12.1 Introduction
12.1.1 Motivation
12.1.2 Benefits of Using Simulation
12.2 Challenges in Simulating Collaborative Embedded Systems
12.2.1 Design Time Challenges
12.2.2 Runtime Challenges
12.3 Simulation Methods
12.4 Application
12.5 Conclusion
12.6 Literature
13 Tool Support for CoSimulation-Based Analysis
13.1 Introduction
13.2 Interaction of Different Simulations
13.3 General Tool Architecture
13.4 Implementing Interoperability for Co-Simulation
13.5 Distributed Co-Simulation
13.6 Analysis of Simulation Results
13.7 Conclusion
13.8 Literature
14 Supporting the Creation of Digital Twins for CESs
14.1 Introduction
14.2.1 Demonstration
Automotive Smart Ecosystems
Smart Grids
14.2 Building Trust through Digital Twin Evaluation
14.3 Conclusion
14.4 Literature
15 Online Experiment-Driven Learning and Adaptation
15.1 Introduction
15.2 A Self-Optimization Approach for CESs
15.3 Illustration on CrowdNav
15.4 Conclusion
15.5 Literature
16 Compositional Verification using Model Checking and Theorem Proving
16.1 Introduction
16.2 Approach
16.3 Example
16.3.1 Specification
16.3.2 Verification
16.4 Conclusion
16.5 Literature
17 Artifact-Based Analysis for the Development of Collaborative Embedded Systems
17.1 Introduction
17.2 Foundations
UML/P
Class Diagrams in UML/P
Object Diagrams in UML/P
OCL
17.3 Artifact-Based Analysis
Artifact Model Creation
Specification of Artifact Data Analysis
Artifact-Based Analyses
17.4 Artifact Model for Systems Engineering Projects with Doors NG and Enterprise Architect
17.4.1 Artifact Modeling of Doors NG and Enterprise Architect
17.4.2 Static Extractor for Doors NG and Enterprise Architect Exports
17.4.3 Analysis of the Extracted Artifact Data
17.5 Conclusion
17.6 Literature
18 Variant and Product Line CoEvolution
18.1 Introduction
18.2 Product Line Engineering
18.3 Propagating Updates from Domain Engineering Level to Application Engineering Level
18.3.1 The Challenge of Propagating Updates
18.3.2 Artifact Evolution and Co-Changes
18.3.3 Changes to the Variant Derivation Process
18.3.4 Applicability and Limitations
18.3.5 Implementation
18.4 Propagating Changes from Application Engineering Level to Domain Engineering Level
18.4.1 The Challenge of Lifting Changes
18.4.2 A Process for Lifting Changes
18.4.3 Deducing Feature Information
Underlying Model
Seeding Feature Information
Assigning Changes to Features
18.4.4 Applicability and Limitations
18.5 Conclusion
18.6 Literature
19 Advanced Systems Engineering
19.1 Introduction
19.2 Advanced Systems Engineering
19.3 MBSE as an Essential Basis
19.4 The Integrated Approach of SPES and SPES_XT
19.5 Methodological Extensions: From SPES to ASE
19.6 Conclusion
19.7 Literature
Appendices
A – Author Index
B – Partner
Bertrandt GmbH
Expleo Germany GmbH
FEV Europe GmbH
fortiss GmbH
Fraunhofer Institute for Open Communication Systems FOKUS
Fraunhofer Institute for Experimental Software Engineering (IESE)
Helmut Schmidt University Hamburg
Humboldt-Universität zu Berlin
INCHRON AG
InSystems Automation GmbH
itemis AG
Model Engineering Solutions GmbH
OFFIS e.V.
PikeTec GmbH
pure-systems GmbH
Robert Bosch GmbH
RWTH Aachen University
Siemens AG
Technical University of Kaiserslautern
Technical University of Munich
Technische Universität Berlin – Daimler Center for Automotive Information Technology Innovations (DCAITI)
Technische Universität Braunschweig
University of Duisburg-Essen, paluno – The Ruhr Institute for Software Technology
C – List of Publications
