3,793 research outputs found

    Monitoring and Information Alignment in Pursuit of an IoT-Enabled Self-Sustainable Interoperability

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    To remain competitive with big corporations, small and medium-sized enterprises (SMEs) often need to be more dynamic, adapt to new business situations, react faster, and thereby survive in today‘s global economy. To do so, SMEs normally seek to create consortiums, thus gaining access to new and more opportunities. However, this strategy may also lead to complications. Due to the different sources of enterprise models and semantics, organizations are experiencing difficulties in seamlessly exchanging vital information via electronic means. In their attempt to address this issue, most seek to achieve interoperability by establishing peer-to-peer mappings with different business partners, or by using neutral data standards to regulate communications in optimized networks. Moreover, systems are more and more dynamic, frequently changing to answer new customer‘s requirements, causing new interoperability problems and a reduction of efficiency. Another situation that is constantly changing is the devices used in the enterprises, as the Enterprise Information Systems, devices are used to register internal data, and to be used to monitor several aspects. These devices are constantly changing, following the evolution and growth of the market. So, it is important to monitor these devices and doing a model representation of them. This dissertation proposes a self-sustainable interoperable framework to monitor existing enterprise information systems and their devices, monitor the device/enterprise network for changes and automatically detecting model changes. With this, network harmonization disruptions are detected in a timely way, and possible solutions are suggested to regain the interoperable status, thus enhancing robustness for reaching sustainability of business networks along time

    Novel strategies for global manufacturing systems interoperability

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    Intelligent negotiation mechanism for supporting the interoperability within the sensing enterprise

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    The authors wish to acknowledge the support of the European Commission through the funding of the UNITE, MSEE and IMAGINE FP7 projects, and the European Space Agency - Concurrent Design Facility (ESA-CDF) for their support in the development of the business case presented in this paper.The Sensing Enterprise is a novel concept that refers to an enterprise anticipating future decisions by using multi-dimensional information captured through physical and virtual objects. The Sensing Enterprise concept is shifting focus towards a borderless enterprise, having at its core the collaboration and continuous interactions among smart objects and systems. But in the actual competitive and global business context, the maintenance of the collaboration environment through the interoperation among heterogeneous smart virtual and physical objects in a collaborative organizational environment becomes difficult to achieve. Therefore, in a dynamic context a change in any component of the networked partners affects the others, creating difficulties to sustain operating networked environment. In this respect, this paper proposes an intelligent negotiation framework as a key mechanism to achieve and maintain the interoperability between the organisations' smart objects and applications, and its validation in an industrial scenario. To allow a sustainable, flexible and generic approach towards the infrastructure implementation in global scale, a cloud-based platform is proposed for setting of the Sensing Enterprise framework.publishersversionpublishe

    A Tale of Two Data-Intensive Paradigms: Applications, Abstractions, and Architectures

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    Scientific problems that depend on processing large amounts of data require overcoming challenges in multiple areas: managing large-scale data distribution, co-placement and scheduling of data with compute resources, and storing and transferring large volumes of data. We analyze the ecosystems of the two prominent paradigms for data-intensive applications, hereafter referred to as the high-performance computing and the Apache-Hadoop paradigm. We propose a basis, common terminology and functional factors upon which to analyze the two approaches of both paradigms. We discuss the concept of "Big Data Ogres" and their facets as means of understanding and characterizing the most common application workloads found across the two paradigms. We then discuss the salient features of the two paradigms, and compare and contrast the two approaches. Specifically, we examine common implementation/approaches of these paradigms, shed light upon the reasons for their current "architecture" and discuss some typical workloads that utilize them. In spite of the significant software distinctions, we believe there is architectural similarity. We discuss the potential integration of different implementations, across the different levels and components. Our comparison progresses from a fully qualitative examination of the two paradigms, to a semi-quantitative methodology. We use a simple and broadly used Ogre (K-means clustering), characterize its performance on a range of representative platforms, covering several implementations from both paradigms. Our experiments provide an insight into the relative strengths of the two paradigms. We propose that the set of Ogres will serve as a benchmark to evaluate the two paradigms along different dimensions.Comment: 8 pages, 2 figure

    Interoperable manufacturing knowledge systems

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    For many years now, the importance of semantic technologies, that provide a formal, logic based route to sharing meaning, has been recognized as offering the potential to support interoperability across multiple related applications and hence drive manufacturing competitiveness in the digital manufacturing age. However, progress in support of manufacturing enterprise interoperability has tended to be limited to fairly narrow domains of applicability. This paper presents a progression of research and understanding, culminating in the work undertaken in the recent EU FLEXINET project, to develop a comprehensive manufacturing reference ontology that can (a) support the clarification of understanding across domains, (b) support the ability to flexibly share information across interacting software systems and (c) provide the ability to readily configure company knowledge bases to support interoperable manufacturing systems
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