918 research outputs found

    Enabling Communication Technologies for Automated Unmanned Vehicles in Industry 4.0

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    Within the context of Industry 4.0, mobile robot systems such as automated guided vehicles (AGVs) and unmanned aerial vehicles (UAVs) are one of the major areas challenging current communication and localization technologies. Due to stringent requirements on latency and reliability, several of the existing solutions are not capable of meeting the performance required by industrial automation applications. Additionally, the disparity in types and applications of unmanned vehicle (UV) calls for more flexible communication technologies in order to address their specific requirements. In this paper, we propose several use cases for UVs within the context of Industry 4.0 and consider their respective requirements. We also identify wireless technologies that support the deployment of UVs as envisioned in Industry 4.0 scenarios.Comment: 7 pages, 1 figure, 1 tabl

    Massive-Scale Automation in Cyber-Physical Systems: Vision & Challenges

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    The next era of computing is the evolution of the Internet of Things (IoT) and Smart Cities with development of the Internet of Simulation (IoS). The existing technologies of Cloud, Edge, and Fog computing as well as HPC being applied to the domains of Big Data and deep learning are not adequate to handle the scale and complexity of the systems required to facilitate a fully integrated and automated smart city. This integration of existing systems will create an explosion of data streams at a scale not yet experienced. The additional data can be combined with simulations as services (SIMaaS) to provide a shared model of reality across all integrated systems, things, devices, and individuals within the city. There are also numerous challenges in managing the security and safety of the integrated systems. This paper presents an overview of the existing state-of-the-art in automating, augmenting, and integrating systems across the domains of smart cities, autonomous vehicles, energy efficiency, smart manufacturing in Industry 4.0, and healthcare. Additionally the key challenges relating to Big Data, a model of reality, augmentation of systems, computation, and security are examined

    Artificial intelligence (AI) methods in optical networks: A comprehensive survey

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    Producción CientíficaArtificial intelligence (AI) is an extensive scientific discipline which enables computer systems to solve problems by emulating complex biological processes such as learning, reasoning and self-correction. This paper presents a comprehensive review of the application of AI techniques for improving performance of optical communication systems and networks. The use of AI-based techniques is first studied in applications related to optical transmission, ranging from the characterization and operation of network components to performance monitoring, mitigation of nonlinearities, and quality of transmission estimation. Then, applications related to optical network control and management are also reviewed, including topics like optical network planning and operation in both transport and access networks. Finally, the paper also presents a summary of opportunities and challenges in optical networking where AI is expected to play a key role in the near future.Ministerio de Economía, Industria y Competitividad (Project EC2014-53071-C3-2-P, TEC2015-71932-REDT

    Smart Grid Communications: Overview of Research Challenges, Solutions, and Standardization Activities

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    Optimization of energy consumption in future intelligent energy networks (or Smart Grids) will be based on grid-integrated near-real-time communications between various grid elements in generation, transmission, distribution and loads. This paper discusses some of the challenges and opportunities of communications research in the areas of smart grid and smart metering. In particular, we focus on some of the key communications challenges for realizing interoperable and future-proof smart grid/metering networks, smart grid security and privacy, and how some of the existing networking technologies can be applied to energy management. Finally, we also discuss the coordinated standardization efforts in Europe to harmonize communications standards and protocols.Comment: To be published in IEEE Communications Surveys and Tutorial

    Self-interested service-oriented agents based on trust and QoS for dynamic reconfiguration

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    Progressively increasing complexity of dynamic environments, in which services and applications are demanded by potential clients, requires a high level of reconfiguration of the offer to better match that ever changing demand. In particular, the dynamic change of the client’s needs, leading to higher exigency, may require a smart and flexible automatic composition of more elementary services. By leveraging the service-oriented architectures and multi-agent system benefits, the paper proposes a method to explore the flexibility of the decision support for the services’ reconfiguration based on several pillars, such as trust, reputation and QoS models, which allows the selection based on measuring the expected performance of the agents. Preliminary experimental results, extracted from a real case scenario, allow highlighting the benefits of the proposed distributed and flexible solution to balance the workload of service providers in a simple and fast manner. The proposed solution includes the agents’ intelligent decision-making capability to dynamically and autonomously change services selection on the fly, towards more trustworthy services with better quality when unexpected events happen, e.g. broken machines. We then propose the use of competitive self-interested agents to provide services that best suits to the client through dynamic service composition.info:eu-repo/semantics/publishedVersio
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