4,340 research outputs found

    Middleware for Wireless Sensor Networks: An Outlook

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    In modern distributed computing, applications are rarely built directly atop operating system facilities, e.g., sockets. Higher-level middleware abstractions and systems are often employed to simplify the programmer’s chore or to achieve interoperability. In contrast, real-world wireless sensor network (WSN) applications are almost always developed by relying directly on the operating system. Why is this the case? Does it make sense to include a middleware layer in the design of WSNs? And, if so, is it the same kind of software system as in traditional distributed computing? What are the fundamental concepts, reasonable assumptions, and key criteria guiding its design? What are the main open research challenges, and the potential pitfalls? Most importantly, is it worth pursuing research in this field? This paper provides a (biased) answer to these and other research questions, preceded by a brief account on the state of the art in the field

    Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

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    The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

    Quality interoperability within digital libraries: the DL.org perspective

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    Quality is the most dynamic aspect of DLs, and becomes even more complex with respect to interoperability. This paper formalizes the research motivations and hypotheses on quality interoperability conducted by the Quality Working Group within the EU-funded project DL.org (<a href="http://www.dlorg.eu">http://www.dlorg.eu/</a>). After providing a multi-level interoperability framework – adopted by DL.org - the authors illustrate key-research points and approaches on the way to the interoperability of DLs quality, grounding them in the DELOS Reference Model. By applying the DELOS Reference Model Quality Concept Map to their interoperability motivating scenario, the authors subsequently present the two main research outcomes of their investigation - the Quality Core Model and the Quality Interoperability Survey

    Middleware for Wireless Sensor Networks: An Outlook

    Get PDF
    In modern distributed computing, applications are rarely built directly atop operating system facilities, e.g., sockets. Higher-level middleware abstractions and systems are often employed to simplify the programmer’s chore or to achieve interoperability. In contrast, real-world wireless sensor network (WSN) applications are almost always developed by relying directly on the operating system. Why is this the case? Does it make sense to include a middleware layer in the design of WSNs? And, if so, is it the same kind of software system as in traditional distributed computing? What are the fundamental concepts, reasonable assumptions, and key criteria guiding its design? What are the main open research challenges, and the potential pitfalls? Most importantly, is it worth pursuing research in this field? This paper provides a (biased) answer to these and other research questions, preceded by a brief account on the state of the art in the field

    An Analysis of Service Ontologies

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    Services are increasingly shaping the world’s economic activity. Service provision and consumption have been profiting from advances in ICT, but the decentralization and heterogeneity of the involved service entities still pose engineering challenges. One of these challenges is to achieve semantic interoperability among these autonomous entities. Semantic web technology aims at addressing this challenge on a large scale, and has matured over the last years. This is evident from the various efforts reported in the literature in which service knowledge is represented in terms of ontologies developed either in individual research projects or in standardization bodies. This paper aims at analyzing the most relevant service ontologies available today for their suitability to cope with the service semantic interoperability challenge. We take the vision of the Internet of Services (IoS) as our motivation to identify the requirements for service ontologies. We adopt a formal approach to ontology design and evaluation in our analysis. We start by defining informal competency questions derived from a motivating scenario, and we identify relevant concepts and properties in service ontologies that match the formal ontological representation of these questions. We analyze the service ontologies with our concepts and questions, so that each ontology is positioned and evaluated according to its utility. The gaps we identify as the result of our analysis provide an indication of open challenges and future work
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