Service-based Fault Tolerance for Cyber-Physical Systems: A Systems Engineering Approach

Cyber-physical systems (CPSs) comprise networked computing units that monitor and control physical processes in feedback loops. CPSs have potential to change the ways people and computers interact with the physical world by enabling new ways to control and optimize systems through improved connectivity and computing capabilities. Compared to classical control theory, these systems involve greater unpredictability which may affect the stability and dynamics of the physical subsystems. Further uncertainty is introduced by the dynamic and open computing environments with rapidly changing connections and system configurations. However, due to interactions with the physical world, the dependable operation and tolerance of failures in both cyber and physical components are essential requirements for these systems.The problem of achieving dependable operations for open and networked control systems is approached using a systems engineering process to gain an understanding of the problem domain, since fault tolerance cannot be solved only as a software problem due to the nature of CPSs, which includes close coordination among hardware, software and physical objects. The research methodology consists of developing a concept design, implementing prototypes, and empirically testing the prototypes. Even though modularity has been acknowledged as a key element of fault tolerance, the fault tolerance of highly modular service-oriented architectures (SOAs) has been sparsely researched, especially in distributed real-time systems. This thesis proposes and implements an approach based on using loosely coupled real-time SOA to implement fault tolerance for a teleoperation system.Based on empirical experiments, modularity on a service level can be used to support fault tolerance (i.e., the isolation and recovery of faults). Fault recovery can be achieved for certain categories of faults (i.e., non-deterministic and aging-related) based on loose coupling and diverse operation modes. The proposed architecture also supports the straightforward integration of fault tolerance patterns, such as FAIL-SAFE, HEARTBEAT, ESCALATION and SERVICE MANAGER, which are used in the prototype systems to support dependability requirements. For service failures, systems rely on fail-safe behaviours, diverse modes of operation and fault escalation to backup services. Instead of using time-bounded reconfiguration, services operate in best-effort capabilities, providing resilience for the system. This enables, for example, on-the-fly service changes, smooth recoveries from service failures and adaptations to new computing environments, which are essential requirements for CPSs.The results are combined into a systems engineering approach to dependability, which includes an analysis of the role of safety-critical requirements for control system software architecture design, architectural design, a dependability-case development approach for CPSs and domain-specific fault taxonomies, which support dependability case development and system reliability analyses. Other contributions of this work include three new patterns for fault tolerance in CPSs: DATA-CENTRIC ARCHITECTURE, LET IT CRASH and SERVICE MANAGER. These are presented together with a pattern language that shows how they relate to other patterns available for the domain

Design and evaluation of a cloud native data analysis pipeline for cyber physical production systems

Since 1991 with the birth of the World Wide Web the rate of data growth has been growing with a record level in the last couple of years. Big companies tackled down this data growth with expensive and enormous data centres to process and get value of this data. From social media, Internet of Things (IoT), new business process, monitoring and multimedia, the capacities of those data centres started to be a problem and required continuos and expensive expansion. Thus, Big Data was something that only a few were able to access. This changed fast when Amazon launched Amazon Web Services (AWS) around 15 years ago and gave the origins to the public cloud. At that time, the capabilities were still very new and reduced but 10 years later the cloud was a whole new business that changed for ever the Big Data business. This not only commoditised computer power but it was accompanied by a price model that let medium and small players the possibility to access it. In consequence, new problems arised regarding the nature of these distributed systems and the software architectures required for proper data processing. The present job analyse the type of typical Big Data workloads and propose an architecture for a cloud native data analysis pipeline. Lastly, it provides a chapter for tools and services that can be used in the architecture taking advantage of their open source nature and the cloud price models.Fil: Ferrer Daub, Facundo Javier. Universidad Católica de Córdoba. Instituto de Ciencias de la Administración; Argentin

Increasing dependability in Safety Critical CPSs using Reflective Statecharts

Dependability is crucial in Safety Critical Cyber Physical Systems (CPS). In spite of the research carried out in recent years, implementation and certification of such systems remain costly and time consuming. In this paper, a framework for Statecharts based SW component development is presented. This framework called CRESC (C++ REflective StateCharts), in addition to assisting in transforming a Statechart model to code, uses reflection to make the model available at Run Time. Thus, the SW components can be monitored at Run Time in terms of model elements. Our framework helps the developer separate monitoring from functionality. Any monitoring strategy needed to increase dependability can be added independently from the functional part. The framework was implemented in C++ because this programming language, together with the Statechart formalism constitute widely used choices for the Safety Critical CPS domain

A Semantic Agent Framework for Cyber-Physical Systems

The development of accurate models for cyber-physical systems (CPSs) is hampered by the complexity of these systems, fundamental differences in the operation of cyber and physical components, and significant interdependencies among these components. Agent-based modeling shows promise in overcoming these challenges, due to the flexibility of software agents as autonomous and intelligent decision-making components. Semantic agent systems are even more capable, as the structure they provide facilitates the extraction of meaningful content from the data provided to the software agents. In this book chapter, we present a multi-agent model for a CPS, where the semantic capabilities are underpinned by sensor networks that provide information about the physical operation to the cyber infrastructure. As a specific example of the semantic interpretation of raw sensor data streams, we present a failure detection ontology for an intelligent water distribution network as a model CPS. The ontology represents physical entities in the CPS, as well as the information extraction, analysis and processing that takes place in relation to these entities. The chapter concludes with introduction of a semantic agent framework for CPS, and presentation of a sample implementation of the framework using C++

Survivability modeling for cyber-physical systems subject to data corruption

Cyber-physical critical infrastructures are created when traditional physical infrastructure is supplemented with advanced monitoring, control, computing, and communication capability. More intelligent decision support and improved efficacy, dependability, and security are expected. Quantitative models and evaluation methods are required for determining the extent to which a cyber-physical infrastructure improves on its physical predecessors. It is essential that these models reflect both cyber and physical aspects of operation and failure. In this dissertation, we propose quantitative models for dependability attributes, in particular, survivability, of cyber-physical systems. Any malfunction or security breach, whether cyber or physical, that causes the system operation to depart from specifications will affect these dependability attributes. Our focus is on data corruption, which compromises decision support -- the fundamental role played by cyber infrastructure. The first research contribution of this work is a Petri net model for information exchange in cyber-physical systems, which facilitates i) evaluation of the extent of data corruption at a given time, and ii) illuminates the service degradation caused by propagation of corrupt data through the cyber infrastructure. In the second research contribution, we propose metrics and an evaluation method for survivability, which captures the extent of functionality retained by a system after a disruptive event. We illustrate the application of our methods through case studies on smart grids, intelligent water distribution networks, and intelligent transportation systems. Data, cyber infrastructure, and intelligent control are part and parcel of nearly every critical infrastructure that underpins daily life in developed countries. Our work provides means for quantifying and predicting the service degradation caused when cyber infrastructure fails to serve its intended purpose. It can also serve as the foundation for efforts to fortify critical systems and mitigate inevitable failures --Abstract, page iii

REMIND: A Framework for the Resilient Design of Automotive Systems

In the past years, great effort has been spent on enhancing the security and safety of vehicular systems. Current advances in information and communication technology have increased the complexity of these systems and lead to extended functionalities towards self-driving and more connectivity. Unfortunately, these advances open the door for diverse and newly emerging attacks that hamper the security and, thus, the safety of vehicular systems. In this paper, we contribute to supporting the design of resilient automotive systems. We review and analyze scientific literature on resilience techniques, fault tolerance, and dependability. As a result, we present the REMIND resilience framework providing techniques for attack detection, mitigation, recovery, and resilience endurance. Moreover, we provide guidelines on how the REMIND framework can be used against common security threats and attacks and further discuss the trade-offs when applying these guidelines

Road2CPS priorities and recommendations for research and innovation in cyber-physical systems

This document summarises the findings of the Road2CPS project, co-financed by the European Commission under the H2020 Research and Innovation Programme, to develop a roadmap and recommendations for strategic action required for future deployment of Cyber-Physical Systems (CPS). The term Cyber-Physical System describes hardware-software systems, which tightly couple the physical world and the virtual world. They are established from networked embedded systems that are connected with the outside world through sensors and actuators and have the capability to collaborate, adapt, and evolve. In the ARTEMIS Strategic Research Agenda 2016, CPS are described as ‘Embedded Intelligent ICT Systems’ that make products smarter, more interconnected, interdependent, collaborative, and autonomous. In the future world of CPS, a huge number of devices connected to the physical world will be able to exchange data with each other, access web services, and interact with people. Moreover, information systems will sense, monitor and even control the physical world via Cyber-Physical Systems and the Internet of Things (HiPEAC Vision 2015). Cyber-Physical Systems find their application in many highly relevant areas to our society: multi-modal transport, health, smart factories, smart grids and smart cities amongst others. The deployment of Cyber-Physical Systems (CPS) is expected to increase substantially over the next decades, holding great potential for novel applications and innovative product development. Digital technologies have already pervaded day-to-day life massively, affecting all kinds of interactions between humans and their environment. However, the inherent complexity of CPSs, as well as the need to meet optimised performance and comply with essential requirements like safety, privacy, security, raises many questions that are currently being explored by the research community. Road2CPS aims at accelerating uptake and implementation of these efforts. The Road2CPS project identifying and analysing the relevant technology fields and related research priorities to fuel the development of trustworthy CPS, as well as the specific technologies, needs and barriers for a successful implementation in different application domains and to derive recommendations for strategic action. The document at hand was established through an interactive, community-based approach, involving over 300 experts from academia, industry and policy making through a series of workshops and consultations. Visions and priorities of recently produced roadmaps in the area of CPS, IoT (Internet of Things), SoS (System-of-Systems) and FoF (Factories of the Future) were discussed, complemented by sharing views and perspectives on CPS implementation in application domains, evolving multi-sided eco-systems as well as business and policy related barriers, enablers and success factors. From the workshops and accompanying activities recommendations for future research and innovation activities were derived and topics and timelines for their implementation proposed. Amongst the technological topics, and related future research priorities ‘integration, interoperability, standards’ ranged highest in all workshops. The topic is connected to digital platforms and reference architectures, which have already become a key priority theme for the EC and their Digitisation Strategy as well as the work on the right standards to help successful implementation of CPSs. Other themes of very high technology/research relevance revealed to be ‘modelling and simulation’, ‘safety and dependability’, ‘security and privacy’, ‘big data and real-time analysis’, ‘ubiquitous autonomy and forecasting’ as well as ‘HMI/human machine awareness’. Next to this, themes emerged including ‘decision making and support’, ‘CPS engineering (requirements, design)’, ‘CPS life-cycle management’, ‘System-of-Systems’, ‘distributed management’, ‘cognitive CPS’, ‘emergence, complexity, adaptability and flexibility’ and work on the foundations of CPS and ‘cross-disciplinary research/CPS Science’