Trustworthy Cyber-Physical Systems Engineering

Alexander Romanovsky, Fuyuki Ishikawa, Alexander Romanovsky, Fuyuki Ishikawa

• Publisher: Chapman and Hall/CRC
• Year: 2016
• ISBN:
  9781315352091
• Edition: 1
• Topic: Computer Science
• Subtopic: Programming Games
• Index: Computer Science

• Focuses on various issues related to engineering trustworthy cyber-physical systems
• Contributes to the improved understanding of system concepts and standardization, and presents a research roadmap
• Emphasizes tool-supported methods, and focuses on practical issues faced by practitioners
• Covers the experience of deploying advanced system engineering methods in industry
• Includes contributions from leading international experts
• Offers supplementary material on the book website: http://research.nii.ac.jp/tcps/

CHAPTER 1

Concepts of Dependable
Cyber-Physical Systems
Engineering

Model-Based Approaches

John Fitzgerald, Claire Ingram, and Alexander Romanovsky

CONTENTS

1. 1.1 Introduction
2. 1.2 Definitions and Concept Bases of CPS
3. 1.3 Types of System
   1. 1.3.1 Defining Cyber-Physical Systems
   2. 1.3.2 Systems of Systems
   3. 1.3.3 Embedded Systems
   4. 1.3.4 Some Properties of CPS
4. 1.4 Dependability
   1. 1.4.1 Achieving Dependability
   2. 1.4.2 Fault Tolerance in a CPS
   3. 1.4.3 Security in a CPS
5. 1.5 Modeling and Simulation
   1. 1.5.1 CPS Architectural Modeling
   2. 1.5.2 CPS Behavior Modeling
   3. 1.5.3 Real-Time Concepts
   4. 1.5.4 Modeling Complete Heterogeneous Systems
   5. 1.5.5 Modeling and Simulation for Validation and Verification
   6. 1.5.6 Fault Modeling
6. 1.6 Conclusions
7. Glossary
8. References

THE ENGINEERING OF CYBER-PHYSICAL SYSTEMS (CPS) is inherently multidisciplinary, requiring the collaborative effort of engineers from a wide range of backgrounds, often with significantly different models, methods, and tools. In such an environment, shared understanding of common concepts and the points at which terminology differs is essential. This is particularly the case in engineering dependable CPS.

In this chapter, we introduce some key concepts for CPS engineering, with a focus on the delivery of dependable systems and the role of model-based techniques.

1.1 INTRODUCTION

The design, development, deployment, and maintenance of dependable CPSs require collaboration among a variety of disciplines such as software, systems, mechanics, electronics, and system architectures, each with well-established notations, models, and methods. As might be expected in this context, terms and concepts that are well known in one discipline may be unknown or understood differently in another. This assumes particular significance in developing CPSs on which reliance is to be placed, where it is necessary to provide a demonstrably sound integration of diverse models. Here we provide a brief introduction to some key concepts for model-based engineering of dependable CPSs, and a short glossary of terms. It should be stressed that we do not seek to provide a survey of CPS engineering, but rather to provide the reader with a platform for subsequent chapters.

We first distinguish the subclass of systems we call cyber-physical systems in Section 1.3. In Section 1.4 we consider some concepts useful for dependability. Approaches to development of dependable CPSs are increasingly underpinned by model-based and simulation techniques, which differ among the disciplines involved. We discuss some basic concepts for CPS modeling in Section 1.5. In Section 1.6 we present our conclusions and a brief glossary.

1.2 DEFINITIONS AND CONCEPT BASES OF CPS

The European Commission (EC), the National Science Foundation, and other U.S. agencies* have made significant investments in methods and tools for CPS engineering. Among the efforts to provide a common conceptual basis for this emerging field, perhaps the most comprehensive to date is the NIST draft framework for CPS [1]. Among EC projects, work on the DESTECS^† [2] and COMPASS^‡ [3] projects developed concept bases of embedded systems and systems of systems, respectively. Among more recent EC projects, several have surveyed the state of the art in CPS and embedded systems engineering. The CyPhERS^§ action produced a report to characterize the CPS domain, including key terms and concepts [4]. The ongoing TAMS4CPS^¶ project has published a definitional framework [5] of key concepts for a transatlantic CPS engineering audience, highlighting key commonalities in usage of terms and concepts in Europe and North America.

1.3 TYPES OF SYSTEM

A system can be defined as a collection of interacting elements, organized to achieve a given purpose [6]. A system interacts with its environment; in model-based design, interactions between the system and its environment are represented as a series of stimuli provided by the environment to the system and as responses from the system to its environment [7]. There are many subtypes of system, and one system may fit simultaneously into several different categories.

1.3.1 Defining Cyber-Physical Systems

In a cyber-physical system (CPS), some elements are computational and some involve interactions with the physical environment [8, 9, 10, 11, 12 and 13], integrating “computation, communication, sensing, and actuation with physical systems to fulfill time-sensitive functions with varying degrees of interaction with the environment, including human interaction” [1,14]. A CPS incorporates multiple connected systems, producing a system capable of developing an awareness of its physical environment and context [15], making decisions based on that information, and enacting work that can effect changes in its physical environment [16].

As an example, consider a traffic management system (TMS). In many jurisdictions, road networks are divided into regions, each controlled by a separate autonomous TMS. The TMS is intended to meet several goals, some of which may conflict. These can include, for example, ensuring optimal throughput with minimum congestion, improving road safety, reducing air pollution and fuel burned, ensuring consistent travel times, etc. The TMS relies on data transmitted by large numbers of monitoring devices that are typically installed roadside or buried under the road surface and connected to a local traffic control center (TCC). The TCC conducts analysis, making predictions based on current data about likely congestion in the near future, identifying current problems or hazards, and suggesting appropriate strategies. Decisions made by the TCC are communicated to a variety of further roadside devices that can influence traffic behavior, such as variable speed limits and message boards, dynamic lane closures, and variable timings on traffic lights.

This is an example of a large-scale CPS; it relies on devices that can observe or affect the real world, gathering data from sensors, analyzing it, and making adjustments as necessary to improve performance. It enables a flexible solution that identifies problems and quickly adapts (e.g., by imposing speed limits or opening extra lanes). However, it is a complex system with an enormous variety of sensor types (and therefore significant heterogeneity), as well as complex analysis and data visualization. The application domain demands a high degree of dependability, which in turn is reliant on the behavior of different participating systems, from sensors to communications systems to analysis algorithms. Dependability includes real-time requirements; the situation on the road can change relatively quickly, and if analysis takes too long, the recommendations produced will be based on out-of-date information.

This traffic management example provides an illustration of a CPS in one domain, but the same principle of combining sensors, actuators, and intelligent analysis can be used to build CPSs that deliver improved performance, flexibility, or efficiency in many other domains. For example, assisted living systems can rely on wearable sensors or nonintrusive devices installed around a building to identify when an elderly person who lives alone needs help. CPSs can be used in manufacturing to monitor quality and make adjustments automatically that improve performance and reduce waste or allow a manufacturing line or other industrial process to adapt dynamically to volatile requirements. CPSs are suitable for these domains and a wide range of others.

CPSs can cross organizational boundaries, with one or more organizations contributing constituent parts toward the whole. In addition, a CPS crosses multiple engineering, computer science, and social science disciplines by incorporating elements that interact with the real world, human systems, and complex software systems capable of intelligently processing the large amounts of data that CPSs may encounter [9,17].

The TAMS4CPS definitional framework [5] points out a variety of definitions that exist for CPSs. For example, some define CPS as “integrations of computation and physical processes” [18] or “smart systems that encompass computational (i.e., hardware and software) and physical components, seamlessly integrated and closely interacting to sense the changing state of the real world” [19]. Other definitions emphasize the “cyber” aspects of CPS engineering, for example, defining CPS as

• “ICT systems (sensing, actuating, computing, communication, etc.) embedded in physical objects, interconnected (including through the Internet) and providing citizens and businesses with a wide range of innovative applications and services” [20].
• “Computation, communication and control components tightly combined with physical processes of different nature, e.g., mechanical, electrical, and chemical. Typically a CPS is defined and understood (evaluated) in a socia...

Table of contents

• Cover
• Half Title
• Title Page
• Copyright Page
• Table of Contents
• Foreword
• Preface
• Acknowledgments
• Editors
• Contributors
• Chapter 1 ■ Concepts of Dependable Cyber-Physical Systems Engineering: Model-Based Approaches
• Chapter 2 ■ Pathways to Dependable Cyber-Physical Systems Engineering
• Chapter 3 ■ A Rigorous Definition of Cyber-Physical Systems
• Chapter 4 ■ A Generic Model for System Substitution
• Chapter 5 ■ Incremental Proof-Based Development for Resilient Distributed Systems
• Chapter 6 ■ Formalizing Goal-Oriented Development of Resilient Cyber-Physical Systems
• Chapter 7 ■ Formal Reasoning about Resilient Cyber-Physical Systems
• Chapter 8 ■ Collaborative Modeling and Simulation for Cyber-Physical Systems
• Chapter 9 ■ Verifying Trustworthy Cyber-Physical Systems Using Closed-Loop Modeling
• Chapter 10 ■ Stop-and-Go Adaptive Cruise Control: A Case Study of Automotive Cyber-Physical Systems
• Chapter 11 ■ Model-Based Analysis of Energy Consumption Behavior
• Chapter 12 ■ A Formal DSL for Multi-Core System Management
• Chapter 13 ■ New Standards for Trustworthy Cyber-Physical Systems
• Chapter 14 ■ Measurement-Based Identification of Infrastructures for Trustworthy Cyber-Physical Systems
• Chapter 15 ■ MDD-Based Design, Configuration, and Monitoring of Resilient Cyber-Physical Systems
• Chapter 16 ■ Education of Scientific Approaches to Trustworthy Systems for Industry: After 10 Years
• Index