Multi-paradigm modelling for cyber–physical systems: a descriptive framework

The complexity of cyber–physical systems (CPSS) is commonly addressed through complex workflows, involving models in a plethora of different formalisms, each with their own methods, techniques, and tools. Some workflow patterns, combined with particular types of formalisms and operations on models in these formalisms, are used successfully in engineering practice. To identify and reuse them, we refer to these combinations of workflow and formalism patterns as modelling paradigms. This paper proposes a unifying (Descriptive) Framework to describe these paradigms, as well as their combinations. This work is set in the context of Multi-Paradigm Modelling (MPM), which is based on the principle to model every part and aspect of a system explicitly, at the most appropriate level(s) of abstraction, using the most appropriate modelling formalism(s) and workflows. The purpose of the Descriptive Framework presented in this paper is to serve as a basis to reason about these formalisms, workflows, and their combinations. One crucial part of the framework is the ability to capture the structural essence of a paradigm through the concept of a paradigmatic structure. This is illustrated informally by means of two example paradigms commonly used in CPS: Discrete Event Dynamic Systems and Synchronous Data Flow. The presented framework also identifies the need to establish whether a paradigm candidate follows, or qualifies as, a (given) paradigm. To illustrate the ability of the framework to support combining paradigms, the paper shows examples of both workflow and formalism combinations. The presented framework is intended as a basis for characterisation and classification of paradigms, as a starting point for a rigorous formalisation of the framework (allowing formal analyses), and as a foundation for MPM tool development

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++

Agent-based analysis and mitigation of failure for cyber-physical systems

Techniques exist for assessment, modeling, and simulation of physical and cyber infrastructures, respectively; but such isolated analysis is incapable of fully capturing the interdependencies that occur when they intertwine to create a cyber-physical system (CPS). The first contribution of this doctoral research includes qualitative representation of the operation of a CPS in a single multi-agent model. Dependable operation of a CPS is contingent upon correct interpretation of data describing the state of the system. To this end, we propose agent-based semantic interpretation services that extract useful information from raw sensor data. We utilize the summary schemas model to reconcile differences in data resolution, syntax, and semantics; and to facilitate imprecise query of databases that maintain historical information, including failure mitigation techniques. Another contribution of the research is in developing ontologies that enable automated reasoning in the classification and mitigation of failures in CPS operation. As a measure of dependability, we quantify the effectiveness of our proposed ontology-based approach in identifying correct mitigation techniques. Our methodology and models are applicable to a broad range of CPSs; however, they are described in the context of intelligent water distribution networks (WDNs), which are cyber-physical critical infrastructure systems responsible for reliable delivery of potable water. We illustrate the use of game theory in agent-based decision support for allocation of water. As a precursor to empirical validation with field data, we developed an integrated cyber-physical WDN simulator using EPANET and MATLAB, and illustrate the use of this simulator in validating our agent-based model and ontology-based approach to automated mitigation of failure --Abstract, page iii

Fusion of Information and Analytics: A Discussion on Potential Methods to Cope with Uncertainty in Complex Environments (Big Data and IoT)

International audienceInformation overload and complexity are core problems to most organizations of today. The advances in networking capabilities have created the conditions of complexity by enabling richer, real-time interactions between and among individuals, objects, systems and organizations. Fusion of Information and Analytics Technologies (FIAT) are key enablers for the design of current and future decision support systems to support prognosis, diagnosis, and prescriptive tasks in such complex environments. Hundreds of methods and technologies exist, and several books have been dedicated to either analytics or information fusion so far. However, very few have discussed the methodological aspects and the need of integrating frameworks for these techniques coming from multiple disciplines. This paper presents a discussion of potential integrating frameworks as well as the development of a computational model to evolve FIAT-based systems capable of meeting the challenges of complex environments such as in Big Data and Internet of Things (IoT)

Industrial agents in the era of service-oriented architectures and cloudbased industrial infrastructures

The umbrella paradigm underpinning novel collaborative industrial systems is to consider the set of intelligent system units as a conglomerate of distributed, autonomous, intelligent, proactive, fault-tolerant, and reusable units, which operate as a set of cooperating entities (Colombo and Karnouskos, 2009). These entities are forming an evolvable infrastructure, entering and/or going out (plug-in/plugout) in an asynchronous manner. Moreover, these entities, having each of them their own functionalities, data, and associated information are now connected and able to interact. They are capable of working in a proactive manner, initiating collaborative actions and dynamically interacting with each other in order to achieve both local and global objectives.info:eu-repo/semantics/publishedVersio

Semantic-Driven Architecture for Autonomic Management of Cyber-Physical Systems (CPS) for Industry 4.0

International audienceToday we are living a new industrial revolution, which has its origin in the vertiginous deployment of ICT technologies that have been pervasively deployed at all levels of the modern society. This new industrial revolution, known as Industry 4.0, evolves within the context of a totally connected Cyber-Physic world in which organizations face immeasurable challenges related to the proper exploitation of ICT technologies to create and innovate in order to develop the intelligent products and services of tomorrow's society. This paper introduces a semantic-driven architecture intended to design, develop and manage Industry 4.0 systems by incrementally integrating monitoring, analysis, planning and management capabilities within autonomic processes able to coordinate and orchestrate Cyber-Physical Systems (CPS). This approach is also intended to cope with the integrability and interoperability challenges of the heterogeneous actors of the Internet of Everything (people, things, data and services) involved in the CPS of the Industry 4.0

Semantical Markov Logic Network for Distributed Reasoning in Cyber-Physical Systems

The challenges associated with developing accurate models for cyber-physical systems are attributable to the intrinsic concurrent and heterogeneous computations of these systems. Even though reasoning based on interconnected domain specific ontologies shows promise in enhancing modularity and joint functionality modelling, it has become necessary to build interoperable cyber-physical systems due to the growing pervasiveness of these systems. In this paper, we propose a semantically oriented distributed reasoning architecture for cyber-physical systems. This model accomplishes reasoning through a combination of heterogeneous models of computation. Using the flexibility of semantic agents as a formal representation for heterogeneous computational platforms, we define autonomous and intelligent agent-based reasoning procedure for distributed cyber-physical systems. Sensor networks underpin the semantic capabilities of this architecture, and semantic reasoning based on Markov logic networks is adopted to address uncertainty in modelling. To illustrate feasibility of this approach, we present a Markov logic based semantic event model for cyber-physical systems and discuss a case study of event handling and processing in a smart home

Mist and Edge Computing Cyber-Physical Human-Centered Systems for Industry 5.0: A Cost-Effective IoT Thermal Imaging Safety System

While many companies worldwide are still striving to adjust to Industry 4.0 principles, the transition to Industry 5.0 is already underway. Under such a paradigm, Cyber-Physical Human-centered Systems (CPHSs) have emerged to leverage operator capabilities in order to meet the goals of complex manufacturing systems towards human-centricity, resilience and sustainability. This article first describes the essential concepts for the development of Industry 5.0 CPHSs and then analyzes the latest CPHSs, identifying their main design requirements and key implementation components. Moreover, the major challenges for the development of such CPHSs are outlined. Next, to illustrate the previously described concepts, a real-world Industry 5.0 CPHS is presented. Such a CPHS enables increased operator safety and operation tracking in manufacturing processes that rely on collaborative robots and heavy machinery. Specifically, the proposed use case consists of a workshop where a smarter use of resources is required, and human proximity detection determines when machinery should be working or not in order to avoid incidents or accidents involving such machinery. The proposed CPHS makes use of a hybrid edge computing architecture with smart mist computing nodes that processes thermal images and reacts to prevent industrial safety issues. The performed experiments show that, in the selected real-world scenario, the developed CPHS algorithms are able to detect human presence with low-power devices (with a Raspberry Pi 3B) in a fast and accurate way (in less than 10 ms with a 97.04% accuracy), thus being an effective solution that can be integrated into many Industry 5.0 applications. Finally, this article provides specific guidelines that will help future developers and managers to overcome the challenges that will arise when deploying the next generation of CPHSs for smart and sustainable manufacturing.Comment: 32 page

Ontology for cyber-physical-social systems self-organisation

Cyber-Physical-Social Systems (CPSSs) integrate various resources from physical, cyber, and social worlds. Efficient interaction of these resources is essential for CPSSs operation. Ontologies do not only provide for semantic operability between different resources but also provide means to create sharable ontology-based context models specified for actual settings. Usage of the context supports situation-driven behavior of CPSSs resources and thus is an enabler for their self-organisation. The present research inherits the idea of context ontologies usage for modelling context in CPSSs. In this work, an upper level context ontology for CPSSs is proposed. This ontology is applied in the domain of self-organising resource network

Evaluating Resilience of Cyber-Physical-Social Systems

Nowadays, protecting the network is not the only security concern. Still, in cyber security, websites and servers are becoming more popular as targets due to the ease with which they can be accessed when compared to communication networks. Another threat in cyber physical social systems with human interactions is that they can be attacked and manipulated not only by technical hacking through networks, but also by manipulating people and stealing users’ credentials. Therefore, systems should be evaluated beyond cy- ber security, which means measuring their resilience as a piece of evidence that a system works properly under cyber-attacks or incidents. In that way, cyber resilience is increas- ingly discussed and described as the capacity of a system to maintain state awareness for detecting cyber-attacks. All the tasks for making a system resilient should proactively maintain a safe level of operational normalcy through rapid system reconfiguration to detect attacks that would impact system performance. In this work, we broadly studied a new paradigm of cyber physical social systems and defined a uniform definition of it. To overcome the complexity of evaluating cyber resilience, especially in these inhomo- geneous systems, we proposed a framework including applying Attack Tree refinements and Hierarchical Timed Coloured Petri Nets to model intruder and defender behaviors and evaluate the impact of each action on the behavior and performance of the system.Hoje em dia, proteger a rede não é a única preocupação de segurança. Ainda assim, na segurança cibernética, sites e servidores estão se tornando mais populares como alvos devido à facilidade com que podem ser acessados quando comparados às redes de comu- nicação. Outra ameaça em sistemas sociais ciberfisicos com interações humanas é que eles podem ser atacados e manipulados não apenas por hackers técnicos através de redes, mas também pela manipulação de pessoas e roubo de credenciais de utilizadores. Portanto, os sistemas devem ser avaliados para além da segurança cibernética, o que significa medir sua resiliência como uma evidência de que um sistema funciona adequadamente sob ataques ou incidentes cibernéticos. Dessa forma, a resiliência cibernética é cada vez mais discutida e descrita como a capacidade de um sistema manter a consciência do estado para detectar ataques cibernéticos. Todas as tarefas para tornar um sistema resiliente devem manter proativamente um nível seguro de normalidade operacional por meio da reconfi- guração rápida do sistema para detectar ataques que afetariam o desempenho do sistema. Neste trabalho, um novo paradigma de sistemas sociais ciberfisicos é amplamente estu- dado e uma definição uniforme é proposta. Para superar a complexidade de avaliar a resiliência cibernética, especialmente nesses sistemas não homogéneos, é proposta uma estrutura que inclui a aplicação de refinamentos de Árvores de Ataque e Redes de Petri Coloridas Temporizadas Hierárquicas para modelar comportamentos de invasores e de- fensores e avaliar o impacto de cada ação no comportamento e desempenho do sistema