Fog computing pour l'intégration d'agents et de services Web dans un middleware réflexif autonome

International audienceService Oriented Architecture (SOA) has emerged as a dominant architecture for interoperability between applications, by using a weak-coupled model based on the flexibility provided by Web Services, which has led to a wide range of applications, what is known as cloud computing. On the other hand, Multi-Agent System (MAS) is widely used in the industry, because it provides an appropriate solution to complex problems, in a proactive and intelligent way. Specifically, Intelligent Environments (Smart City, Smart Classroom, Cyber Physical System, and Smart Factory, among others) obtain great benefits by using both architectures, because MAS endows intelligence to the environment, while SOA enables users to interact with cloud services, which improve the capabilities of the devices deployed in the environment. Additionally, the fog computing paradigm extends the cloud computing paradigm to be closer to the things that produce and act on the intelligent environment, allowing to deal with issues like mobility, real time, low latency, geo-localization, among other aspects. In this sense, in this article we present a middleware, which not only is capable of allowing MAS and SOA to communicate in a bidirectional and transparent way, but also, it uses the fog computing paradigm autonomously, according to the context and to the system load factor. Additionally, we analyze the performance of the incorporation of the fog-computing paradigm in our middleware and compare it with other works

MiSCi Middleware for smart cities extended with linked data

This article proposes an extension of the capabilities of the MiSCi middleware, by adding a new layer called Linked Data, to identify, describe, connect, relate and exploit the various user-generated data and applications of the smart city using the Linked Data paradigm. This new layer is composed of different agents that automate the specification, modeling, generation, linking, publication and exploitation of data based on MEDAWEDE. Such agents can enrich existing MiSCi ontologies, generate knowledge models required by MiSCi services, generate data to build knowledge models for MiSCi, and recommend information in contexts of uncertainty through hybrid inference based on descriptive/dialectical logic. In addition, this work specifies a case study, where the MiSCi's capabilities to handle different critical situations are shown, supported by the new data link layeEste artículo propone una ampliación de las capacidades del middleware MiSCi, al agregar una nueva capa denominada Datos Enlazados, para identificar, describir, conectar, relacionar y explotar los distintos datos generados por los usuarios y las aplicaciones de la ciudad inteligente usando el paradigma de datos enlazados. Esta nueva capa está compuestas por distintos agentes que permiten automatizar las etapas de especificación, modelado, generación, vinculación, publicación y explotación de los datos basados en MEDAWEDE. Dichos agentes pueden enriquecer ontologías existentes en MiSCi, generar modelos de conocimiento requeridos por los servicios de MiSCi, generar datos para construir modelos de conocimiento para MiSCi, y recomendar información en contextos de incertidumbre a través de una inferencia híbrida basada en lógica descriptiva/dialéctica. Además en este trabajo se especifica un caso de estudio, donde se muestran las capacidades del MiSCi para manejar distintas situaciones críticas, apoyado en la nueva capa de enlazado de datos

Self-managed Workflows for Cyber-physical Systems

Workflows are a well-established concept for describing business logics and processes in web-based applications and enterprise application integration scenarios on an abstract implementation-agnostic level. Applying Business Process Management (BPM) technologies to increase autonomy and automate sequences of activities in Cyber-physical Systems (CPS) promises various advantages including a higher flexibility and simplified programming, a more efficient resource usage, and an easier integration and orchestration of CPS devices. However, traditional BPM notations and engines have not been designed to be used in the context of CPS, which raises new research questions occurring with the close coupling of the virtual and physical worlds. Among these challenges are the interaction with complex compounds of heterogeneous sensors, actuators, things and humans; the detection and handling of errors in the physical world; and the synchronization of the cyber-physical process execution models. Novel factors related to the interaction with the physical world including real world obstacles, inconsistencies and inaccuracies may jeopardize the successful execution of workflows in CPS and may lead to unanticipated situations. This thesis investigates properties and requirements of CPS relevant for the introduction of BPM technologies into cyber-physical domains. We discuss existing BPM systems and related work regarding the integration of sensors and actuators into workflows, the development of a Workflow Management System (WfMS) for CPS, and the synchronization of the virtual and physical process execution as part of self-* capabilities for WfMSes. Based on the identified research gap, we present concepts and prototypes regarding the development of a CPS WFMS w.r.t. all phases of the BPM lifecycle. First, we introduce a CPS workflow notation that supports the modelling of the interaction of complex sensors, actuators, humans, dynamic services and WfMSes on the business process level. In addition, the effects of the workflow execution can be specified in the form of goals defining success and error criteria for the execution of individual process steps. Along with that, we introduce the notion of Cyber-physical Consistency. Following, we present a system architecture for a corresponding WfMS (PROtEUS) to execute the modelled processes-also in distributed execution settings and with a focus on interactive process management. Subsequently, the integration of a cyber-physical feedback loop to increase resilience of the process execution at runtime is discussed. Within this MAPE-K loop, sensor and context data are related to the effects of the process execution, deviations from expected behaviour are detected, and compensations are planned and executed. The execution of this feedback loop can be scaled depending on the required level of precision and consistency. Our implementation of the MAPE-K loop proves to be a general framework for adding self-* capabilities to WfMSes. The evaluation of our concepts within a smart home case study shows expected behaviour, reasonable execution times, reduced error rates and high coverage of the identified requirements, which makes our CPS~WfMS a suitable system for introducing workflows on top of systems, devices, things and applications of CPS.:1. Introduction 15 1.1. Motivation 15 1.2. Research Issues 17 1.3. Scope & Contributions 19 1.4. Structure of the Thesis 20 2. Workflows and Cyber-physical Systems 21 2.1. Introduction 21 2.2. Two Motivating Examples 21 2.3. Business Process Management and Workflow Technologies 23 2.4. Cyber-physical Systems 31 2.5. Workflows in CPS 38 2.6. Requirements 42 3. Related Work 45 3.1. Introduction 45 3.2. Existing BPM Systems in Industry and Academia 45 3.3. Modelling of CPS Workflows 49 3.4. CPS Workflow Systems 53 3.5. Cyber-physical Synchronization 58 3.6. Self-* for BPM Systems 63 3.7. Retrofitting Frameworks for WfMSes 69 3.8. Conclusion & Deficits 71 4. Modelling of Cyber-physical Workflows with Consistency Style Sheets 75 4.1. Introduction 75 4.2. Workflow Metamodel 76 4.3. Knowledge Base 87 4.4. Dynamic Services 92 4.5. CPS-related Workflow Effects 94 4.6. Cyber-physical Consistency 100 4.7. Consistency Style Sheets 105 4.8. Tools for Modelling of CPS Workflows 106 4.9. Compatibility with Existing Business Process Notations 111 5. Architecture of a WfMS for Distributed CPS Workflows 115 5.1. Introduction 115 5.2. PROtEUS Process Execution System 116 5.3. Internet of Things Middleware 124 5.4. Dynamic Service Selection via Semantic Access Layer 125 5.5. Process Distribution 126 5.6. Ubiquitous Human Interaction 130 5.7. Towards a CPS WfMS Reference Architecture for Other Domains 137 6. Scalable Execution of Self-managed CPS Workflows 141 6.1. Introduction 141 6.2. MAPE-K Control Loops for Autonomous Workflows 141 6.3. Feedback Loop for Cyber-physical Consistency 148 6.4. Feedback Loop for Distributed Workflows 152 6.5. Consistency Levels, Scalability and Scalable Consistency 157 6.6. Self-managed Workflows 158 6.7. Adaptations and Meta-adaptations 159 6.8. Multiple Feedback Loops and Process Instances 160 6.9. Transactions and ACID for CPS Workflows 161 6.10. Runtime View on Cyber-physical Synchronization for Workflows 162 6.11. Applicability of Workflow Feedback Loops to other CPS Domains 164 6.12. A Retrofitting Framework for Self-managed CPS WfMSes 165 7. Evaluation 171 7.1. Introduction 171 7.2. Hardware and Software 171 7.3. PROtEUS Base System 174 7.4. PROtEUS with Feedback Service 182 7.5. Feedback Service with Legacy WfMSes 213 7.6. Qualitative Discussion of Requirements and Additional CPS Aspects 217 7.7. Comparison with Related Work 232 7.8. Conclusion 234 8. Summary and Future Work 237 8.1. Summary and Conclusion 237 8.2. Advances of this Thesis 240 8.3. Contributions to the Research Area 242 8.4. Relevance 243 8.5. Open Questions 245 8.6. Future Work 247 Bibliography 249 Acronyms 277 List of Figures 281 List of Tables 285 List of Listings 287 Appendices 28

Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas

Next Generation Internet of Things – Distributed Intelligence at the Edge and Human-Machine Interactions

This book provides an overview of the next generation Internet of Things (IoT), ranging from research, innovation, development priorities, to enabling technologies in a global context. It is intended as a standalone in a series covering the activities of the Internet of Things European Research Cluster (IERC), including research, technological innovation, validation, and deployment.The following chapters build on the ideas put forward by the European Research Cluster, the IoT European Platform Initiative (IoT–EPI), the IoT European Large-Scale Pilots Programme and the IoT European Security and Privacy Projects, presenting global views and state-of-the-art results regarding the next generation of IoT research, innovation, development, and deployment.The IoT and Industrial Internet of Things (IIoT) are evolving towards the next generation of Tactile IoT/IIoT, bringing together hyperconnectivity (5G and beyond), edge computing, Distributed Ledger Technologies (DLTs), virtual/ andaugmented reality (VR/AR), and artificial intelligence (AI) transformation.Following the wider adoption of consumer IoT, the next generation of IoT/IIoT innovation for business is driven by industries, addressing interoperability issues and providing new end-to-end security solutions to face continuous treats.The advances of AI technology in vision, speech recognition, natural language processing and dialog are enabling the development of end-to-end intelligent systems encapsulating multiple technologies, delivering services in real-time using limited resources. These developments are focusing on designing and delivering embedded and hierarchical AI solutions in IoT/IIoT, edge computing, using distributed architectures, DLTs platforms and distributed end-to-end security, which provide real-time decisions using less data and computational resources, while accessing each type of resource in a way that enhances the accuracy and performance of models in the various IoT/IIoT applications.The convergence and combination of IoT, AI and other related technologies to derive insights, decisions and revenue from sensor data provide new business models and sources of monetization. Meanwhile, scalable, IoT-enabled applications have become part of larger business objectives, enabling digital transformation with a focus on new services and applications.Serving the next generation of Tactile IoT/IIoT real-time use cases over 5G and Network Slicing technology is essential for consumer and industrial applications and support reducing operational costs, increasing efficiency and leveraging additional capabilities for real-time autonomous systems.New IoT distributed architectures, combined with system-level architectures for edge/fog computing, are evolving IoT platforms, including AI and DLTs, with embedded intelligence into the hyperconnectivity infrastructure.The next generation of IoT/IIoT technologies are highly transformational, enabling innovation at scale, and autonomous decision-making in various application domains such as healthcare, smart homes, smart buildings, smart cities, energy, agriculture, transportation and autonomous vehicles, the military, logistics and supply chain, retail and wholesale, manufacturing, mining and oil and gas

A Multi-Stakeholder Information Model to Drive Process Connectivity In Smart Buildings

Smart buildings utilise IoT technology to provide stakeholders with efficient, comfortable, and secure experiences. However, previous studies have primarily focused on the technical aspects of it and how it can address specific stakeholder requirements. This study adopts socio-technical theory principles to propose a model that addresses stakeholders' needs by considering the interrelationship between social and technical subsystems. A systematic literature review and thematic analysis of 43 IoT conceptual frameworks for smart building studies informed the design of a comprehensive conceptual model and IoT framework for smart buildings. The study's findings suggest that addressing stakeholder requirements is essential for developing an information model in smart buildings. A multi-stakeholder information model integrating multiple stakeholders' perspectives enhances information sharing and improves process connectivity between various systems and subsystems. The socio-technical systems framework emphasises the importance of considering technical and social aspects while integrating smart building systems for seamless operation and effectiveness. The study's findings have significant implications for enhancing stakeholders' experience and improving operational efficiency in commercial buildings. The insights from the study can inform smart building systems design to consider all stakeholder requirements holistically, promoting process connectivity in smart buildings. The literature analysis contributed to developing a comprehensive IoT framework, addressing the need for holistic thinking when proposing IoT frameworks for smart buildings by considering different stakeholders in the building

A generic architecture style for self-adaptive cyber-physical systems

Die aktuellen Konzepte zur Gestaltung von Regelungssystemen basieren auf dynamischen Verhaltensmodellen, die mathematische Ansätze wie Differentialgleichungen zur Ableitung der entsprechenden Funktionen verwenden. Diese Konzepte stoßen jedoch aufgrund der zunehmenden Systemkomplexität allmählich an ihre Grenzen. Zusammen mit der Entwicklung dieser Konzepte entsteht eine Architekturevolution der Regelungssysteme. In dieser Dissertation wird eine Taxonomie definiert, um die genannte Architekturevolution anhand eines typischen Beispiels, der adaptiven Geschwindigkeitsregelung (ACC), zu veranschaulichen. Aktuelle ACC-Varianten, die auf der Regelungstheorie basieren, werden in Bezug auf ihre Architekturen analysiert. Die Analyseergebnisse zeigen, dass das zukünftige Regelungssystem im ACC eine umfangreichere Selbstadaptationsfähigkeit und Skalierbarkeit erfordert. Dafür sind kompliziertere Algorithmen mit unterschiedlichen Berechnungsmechanismen erforderlich. Somit wird die Systemkomplexität erhöht und führt dazu, dass das zukünftige Regelungssystem zu einem selbstadaptiven cyber-physischen System wird und signifikante Herausforderungen für die Architekturgestaltung des Systems darstellt. Inspiriert durch Ansätze des Software-Engineering zur Gestaltung von Architekturen von softwareintensiven Systemen wird in dieser Dissertation ein generischer Architekturstil entwickelt. Der entwickelte Architekturstil dient als Vorlage, um vernetzte Architekturen mit Verfolgung der entwickelten Designprinzipien nicht nur für die aktuellen Regelungssysteme, sondern auch für selbstadaptiven cyber-physischen Systeme in der Zukunft zu konstruieren. Unterschiedliche Auslösemechanismen und Kommunikationsparadigmen zur Gestaltung der dynamischen Verhalten von Komponenten sind in der vernetzten Architektur anwendbar. Zur Bewertung der Realisierbarkeit des Architekturstils werden aktuelle ACCs erneut aufgenommen, um entsprechende logische Architekturen abzuleiten und die Architekturkonsistenz im Vergleich zu den originalen Architekturen basierend auf der Regelungstheorie (z. B. in Form von Blockdiagrammen) zu untersuchen. Durch die Anwendung des entwickelten generischen Architekturstils wird in dieser Dissertation eine künstliche kognitive Geschwindigkeitsregelung (ACCC) als zukünftige ACC-Variante entworfen, implementiert und evaluiert. Die Evaluationsergebnisse zeigen signifikante Leistungsverbesserungen des ACCC im Vergleich zum menschlichen Fahrer und aktuellen ACC-Varianten.Current concepts of designing automatic control systems rely on dynamic behavioral modeling by using mathematical approaches like differential equations to derive corresponding functions, and slowly reach limitations due to increasing system complexity. Along with the development of these concepts, an architectural evolution of automatic control systems is raised. This dissertation defines a taxonomy to illustrate the aforementioned architectural evolution relying on a typical example of control application: adaptive cruise control (ACC). Current ACC variants, with their architectures considering control theory, are analyzed. The analysis results indicate that the future automatic control system in ACC requires more substantial self-adaptation capability and scalability. For this purpose, more complicated algorithms requiring different computation mechanisms must be integrated into the system and further increase system complexity. This makes the future automatic control system evolve into a self-adaptive cyber-physical system and consistitutes significant challenges for the system’s architecture design. Inspired by software engineering approaches for designing architectures of software-intensive systems, a generic architecture style is proposed. The proposed architecture style serves as a template by following the developed design principle to construct networked architectures not only for the current automatic control systems but also for self-adaptive cyber-physical systems in the future. Different triggering mechanisms and communication paradigms for designing dynamic behaviors are applicable in the networked architecture. To evaluate feasibility of the architecture style, current ACCs are retaken to derive corresponding logical architectures and examine architectural consistency compared to the previous architectures considering the control theory (e.g., in the form of block diagrams). By applying the proposed generic architecture style, an artificial cognitive cruise control (ACCC) is designed, implemented, and evaluated as a future ACC in this dissertation. The evaluation results show significant performance improvements in the ACCC compared to the human driver and current ACC variants

Towards an efficient indexing and searching model for service discovery in a decentralised environment.

Given the growth and outreach of new information, communication, computing and electronic technologies in various dimensions, the amount of data has explosively increased in the recent years. Centralised systems suffer some limitations to dealing with this issue due to all data is stored in central data centres. Thus, decentralised systems are getting more attention and increasing in popularity. Moreover, efficient service discovery mechanisms have naturally become an essential component in both large-scale and small-scale decentralised systems and. This research study is aimed at modelling a novel efficient indexing and searching model for service discovery in decentralised environments comprising numerous repositories with massive stored services. The main contributions of this research study can be summarised in three components: a novel distributed multilevel indexing model, an optimised searching algorithm and a new simulation environment. Indexing model has been widely used for efficient service discovery. For instance; the inverted index is one of the popular indexing models used for service retrieval in consistent repositories. However, redundancies are inevitable in the inverted index which is significantly time-consuming in the service discovery and retrieval process. This theeis proposes a novel distributed multilevel indexing model (DM-index), which offers an efficient solution for service discovery and retrieval in distributed service repositories comprising massive stored services. The architecture of the proposed indexing model encompasses four hierarchical levels to eliminate redundancy information in service repositories, to narrow the searching space and to reduce the number of traversed services whilst discovering services. Distributed Hash Tables have been widely used to provide data lookup services with logarithmic message costs which only require maintenance of limited amounts of routing states. This thesis develops an optimised searching algorithm, named Double-layer No-redundancy Enhanced Bi-direction Chord (DNEB-Chord), to handle retrieval requests in distributed destination repositories efficiently. This DNEB-Chord algorithm achieves faster routing performances with the double-layer routing mechanism and optimal routing index. The efficiency of the developed indexing and searching model is evaluated through theoretical analysis and experimental evaluation in a newly developed simulation environment, named Distributed Multilevel Bi-direction Simulator (DMBSim), which can be used as cost efficient tool for exploring various service configurations, user retrieval requirements and other parameter settings. Both the theoretical validation and experimental evaluations demonstrate that the service discovery efficiency of the DM-index outperforms the sequential index and inverted index configurations. Furthermore, the experimental evaluation results demostrate that the DNEB-Chord algorithm performs better than the Chord in terms of reducing the incurred hop counts. Finally, simulation results demonstrate that the proposed indexing and searching model can achieve better service discovery performances in large-scale decentralised environments comprising numerous repositories with massive stored services.N/

Computation Against a Neighbour: Addressing Large-Scale Distribution and Adaptivity with Functional Programming and Scala

Recent works in contexts like the Internet of Things (IoT) and large-scale Cyber-Physical Systems (CPS) propose the idea of programming distributed systems by focussing on their global behaviour across space and time. In this view, a potentially vast and heterogeneous set of devices is considered as an “aggregate” to be programmed as a whole, while abstracting away the details of individual behaviour and exchange of messages, which are expressed declaratively. One such a paradigm, known as aggregate programming, builds on computational models inspired by field-based coordination. Existing models such as the field calculus capture interaction with neighbours by a so-called “neighbouring field” (a map from neighbours to values). This requires ad-hoc mechanisms to smoothly compose with standard values, thus complicating programming and introducing clutter in aggregate programs, libraries and domain-specific languages (DSLs). To address this key issue we introduce the novel notion of “computation against a neighbour”, whereby the evaluation of certain subexpressions of the aggregate program are affected by recent corresponding evaluations in neighbours. We capture this notion in the neighbours calculus (NC), a new field calculus variant which is shown to smoothly support declarative specification of interaction with neighbours, and correspondingly facilitate the embedding of field computations as internal DSLs in common general-purpose programming languages—as exemplified by a Scala implementation, called ScaFi. This paper formalises NC, thoroughly compares it with respect to the classic field calculus, and shows its expressiveness by means of a case study in edge computing, developed in ScaFi