19,187 research outputs found

    Managed ecosystems of networked objects

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    Small embedded devices such as sensors and actuators will become the cornerstone of the Future Internet. To this end, generic, open and secure communication and service platforms are needed in order to be able to exploit the new business opportunities these devices bring. In this paper, we evaluate the current efforts to integrate sensors and actuators into the Internet and identify the limitations at the level of cooperation of these Internet-connected objects and the possible intelligence at the end points. As a solution, we propose the concept of Managed Ecosystem of Networked Objects, which aims to create a smart network architecture for groups of Internet-connected objects by combining network virtualization and clean-slate end-to-end protocol design. The concept maps to many real-life scenarios and should empower application developers to use sensor data in an easy and natural way. At the same time, the concept introduces many new challenging research problems, but their realization could offer a meaningful contribution to the realization of the Internet of Things

    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

    Semantic-based policy engineering for autonomic systems

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    This paper presents some important directions in the use of ontology-based semantics in achieving the vision of Autonomic Communications. We examine the requirements of Autonomic Communication with a focus on the demanding needs of ubiquitous computing environments, with an emphasis on the requirements shared with Autonomic Computing. We observe that ontologies provide a strong mechanism for addressing the heterogeneity in user task requirements, managed resources, services and context. We then present two complimentary approaches that exploit ontology-based knowledge in support of autonomic communications: service-oriented models for policy engineering and dynamic semantic queries using content-based networks. The paper concludes with a discussion of the major research challenges such approaches raise

    Middleware Technologies for Cloud of Things - a survey

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    The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

    Middleware Technologies for Cloud of Things - a survey

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    The next wave of communication and applications rely on the new services provided by Internet of Things which is becoming an important aspect in human and machines future. The IoT services are a key solution for providing smart environments in homes, buildings and cities. In the era of a massive number of connected things and objects with a high grow rate, several challenges have been raised such as management, aggregation and storage for big produced data. In order to tackle some of these issues, cloud computing emerged to IoT as Cloud of Things (CoT) which provides virtually unlimited cloud services to enhance the large scale IoT platforms. There are several factors to be considered in design and implementation of a CoT platform. One of the most important and challenging problems is the heterogeneity of different objects. This problem can be addressed by deploying suitable "Middleware". Middleware sits between things and applications that make a reliable platform for communication among things with different interfaces, operating systems, and architectures. The main aim of this paper is to study the middleware technologies for CoT. Toward this end, we first present the main features and characteristics of middlewares. Next we study different architecture styles and service domains. Then we presents several middlewares that are suitable for CoT based platforms and lastly a list of current challenges and issues in design of CoT based middlewares is discussed.Comment: http://www.sciencedirect.com/science/article/pii/S2352864817301268, Digital Communications and Networks, Elsevier (2017

    Addressing the Challenges in Federating Edge Resources

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    This book chapter considers how Edge deployments can be brought to bear in a global context by federating them across multiple geographic regions to create a global Edge-based fabric that decentralizes data center computation. This is currently impractical, not only because of technical challenges, but is also shrouded by social, legal and geopolitical issues. In this chapter, we discuss two key challenges - networking and management in federating Edge deployments. Additionally, we consider resource and modeling challenges that will need to be addressed for a federated Edge.Comment: Book Chapter accepted to the Fog and Edge Computing: Principles and Paradigms; Editors Buyya, Sriram

    Special Session on Industry 4.0

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    ¿Pueden los MOOC cerrar la brecha de oportunidades?: La contribución del diseño pedagógico social inclusivo

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    Massive Open Online Courses (MOOCs) are open courses made available online at no cost to the user and designed to scale up, allowing for a large number of participants. As such, they are a disruptive new development which has the potential to widen access to higher education since they contribute to social inclusion, the dissemination of knowledge and pedagogical innovation. However, assuring quality learning opportunities to all cannot be simply reduced to allowing free access to higher education. On the contrary, it implies assuring equitable opportunities for every participant to succeed in their learning experience. This goal depends on the quality of the learning design. To be successful, a massive open online learning experience has to empower learners and to facilitate a networked learning environment. In fact, MOOCs are designed to serve a high heterogeneity of profiles, with many differences regarding learning needs and preferences, prior knowledge, contexts of participation and diversity of online platforms. Personalization can play a key role in this process. In this article, the authors describe the iMOOC pedagogical model and its later derivative, the sMOOC model, and explain how they contributed to the introduction of the principles of diversity and learner equity to MOOC design, allowing for a clear differentiation of learning paths and also of virtual environments, while empowering participants to succeed in their learning experiences. Using a design-based research approach, a comparative analysis of two course iterations each representing each model is also presented and discussed.Los cursos en lĂ­nea abiertos y masivos (MOOC) son cursos abiertos disponibles en lĂ­nea sin costo para el usuario y diseñados para ampliarse, permitiendo un gran nĂșmero de participantes. Como tales, son un nuevo desarrollo disruptivo que tiene el potencial de ampliar el acceso a la educaciĂłn superior, ya que contribuyen a la inclusiĂłn social, la difusiĂłn del conocimiento y la innovaciĂłn pedagĂłgica. Sin embargo, garantizar oportunidades de aprendizaje de calidad para todos no puede reducirse simplemente a permitir el acceso gratuito a la educaciĂłn superior. Por el contrario, implica asegurar oportunidades equitativas para que cada participante tenga Ă©xito en su experiencia de aprendizaje. Este objetivo depende de la calidad del diseño de aprendizaje. Para tener Ă©xito, una experiencia de aprendizaje en lĂ­nea abierta y masiva debe empoderar a los alumnos y facilitar un entorno de aprendizaje en red. De hecho, los MOOC estĂĄn diseñados para servir a una gran heterogeneidad de perfiles, con muchas diferencias con respecto a las necesidades y preferencias de aprendizaje, conocimiento previo, contextos de participaciĂłn y diversidad de plataformas en lĂ­nea. La personalizaciĂłn puede jugar un papel clave en este proceso. En este artĂ­culo, los autores describen el modelo pedagĂłgico iMOOC y su derivada posterior, el modelo sMOOC, y explican cĂłmo contribuyeron a la introducciĂłn de los principios de diversidad y equidad en el diseño MOOC, lo que permite una clara diferenciaciĂłn de las rutas de aprendizaje y tambiĂ©n de entornos virtuales, al tiempo que permite a los participantes tener Ă©xito en sus experiencias de aprendizaje. Usando un enfoque de design-based research, tambiĂ©n se presenta y discute un anĂĄlisis comparativo de dos iteraciones del curso, cada una representando cada modelo

    Complex learning communities

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    A new breed of learning community which is driven by the need to generate learning, creativity and economic capacity is emerging as a result of the demands of the Information Society. Radical heterogeneity and multiple drivers make these learning communities significantly different from previously identified learning communities such as corporate Communities of Practice or Virtual Learning Communities. If full benefit is to be realised from such Complex Learning Communities (CLCs), then better understanding of their complex behaviour and methods of maximising their effectiveness are required. This short paper presents an overview of CLCs and reports on the development of a research agenda designed to address the identified gaps in knowledge
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