80 research outputs found

    Service-oriented design of environmental information systems

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    Service-orientation has an increasing impact upon the design process and the architecture of environmental information systems. This thesis specifies the SERVUS design methodology for geospatial applications based upon standards of the Open Geospatial Consortium. SERVUS guides the system architect to rephrase use case requirements as a network of semantically-annotated requested resources and to iteratively match them with offered resources that mirror the capabilities of existing services

    SoaML-basierter Entwurf eines dienstorientierten Überwachungssystems. [Workshop]

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    Von einem Überwachungssystem zur Begleitung von Personen innerhalb von Gebäuden wird häufig gefordert, sich in die bestehende Anwendungslandschaft eines Unternehmens integrieren zu lassen und vorhandene Anwendungsfunktionalität möglichst wiederzuverwenden. Anwendungslandschaften werden verstärkt in Form dienstorientierter Architekturen strukturiert, weshalb ein integrierbares Überwachungssystem ebenfalls dienstorientiert entworfen werden sollte. Mit der Service oriented architecture Modeling Language (SoaML) existiert ein Standard, der eine Modellierung eines dienstorientierten Überwachungssystems ermöglicht. In dieser Arbeit werden die hierfür notwendigen Elemente der SoaML identifiziert und in einen Entwicklungsprozess eingeordnet

    MULTI-AGENT LEARNING FRAMEWORK FOR ENVIRONMENT REDUNDANCY IDENTIFICATION FOR MOBILE SENSORS IN AN IOT CONTEXT

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    From an IoT point of view, the continuous growth of cheap and versatile sensor technologies has generated a massive data flow in communication networks, which most of the time carries unnecessary or redundant information that requires larger storage centers and more time to process and analyze data. Most of this redundancy is due to fact that network nodes are unable to identify environmental cues showing measurement changes to be considered and instead remain at a static location getting the same data. In this work we propose a multi-agent learning framework based on two theoretical tools. Firstly, we use Gaussian Process Regression (GPR) to make each node capable of getting information from the environment based on its current measurement and the measurements taken by its neighbors. Secondly, we use the rate distortion function to define a boundary where the information coming from the environment is neither redundant nor misunderstood. Finally, we show how the framework is applied in a mobile sensor network in which sensors decide to be more or less exploratory by means of the parameter s of the Blahut-Arimoto algorithm, and how it affects the measurement coverage in a spatial area being sensed

    Model similarity evidence and interoperability affinity in cloud-ready Industry 4.0 technologies

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    Cloud computing is revolutionizing IT environments in most fields of economy. Its service-based approach enables collaboration and data exchange on higher level, with better efficiency and parallel decreasing costs. Also manufacturing environments can benefit from cloud technology and better fulfill fast changes in market demands, by applying diverse cloud deployment models and by virtualizing manufacturing processes and assets into services. As cloud becomes the basis of most innovative manufacturing IT systems, its future role in Cyber-physical Production Systems has to be properly investigated, as their interoperability will play a role of vital importance. In this paper, after a brief introduction to cloud criticality and cloud-based manufacturing, the mutual conceptual similarities in modelling distributed industrial services of two of the major standardization frameworks for industrial Internet architectures are presented: the Industrial Internet Reference Architecture (IIRA) and the Reference Architectural Model Industrie (RAMI 4.0). It is also introduced how their integration feasibility finds a strong affinity in specifications of the Open Connectivity Unified Architecture, a service-oriented architecture candidate to the standardization of Industrial Internet of Things based manufacturing platforms. Finally, the preliminary architecture of a prototype Smart Factory is presented as a case study

    Agile Service Engineering in the Industrial Internet of Things

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    The emerging Industrial Internet of Things (IIoT) will not only leverage new and potentially disruptive business models but will also change the way software applications will be analyzed and designed. Agility is a need in a systematic service engineering as well as a co-design of requirements and architectural artefacts. Functional and non-functional requirements of IT users (in smart manufacturing mostly from the disciplines of mechanical engineering and electrical engineering) need to be mapped to the capabilities and interaction patterns of emerging IIoT service platforms, not to forget the corresponding information models. The capabilities of such platforms are usually described, structured, and formalized by software architects and software engineers. However, their technical descriptions are far away from the thinking and the thematic terms of end-users. This complicates the transition from requirements analysis to system design, and hence the re-use of existing and the design of future platform capabilities. Current software engineering methodologies do not systematically cover these interlinked and two-sided aspects. The article describes in a comprehensive manner how to close this gap with the help of a service-oriented analysis and design methodology entitled SERVUS (also mentioned in ISO 19119 Annex D) and a corresponding Web-based Platform Engineering Information System (PEIS)
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