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        Digital Twin

        Architectures, Networks, and Applications

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        Author(s)
        Zhang, Yan
        Language
        English
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        Abstract
        This open access book offers comprehensive, self-contained knowledge on Digital Twin (DT), which is a very promising technology for achieving digital intelligence in the next-generation wireless communications and computing networks. DT is a key technology to connect physical systems and digital spaces in Metaverse. The objectives of this book are to provide the basic concepts of DT, to explore the promising applications of DT integrated with emerging technologies, and to give insights into the possible future directions of DT. For easy understanding, this book also presents several use cases for DT models and applications in different scenarios. The book starts with the basic concepts, models, and network architectures of DT. Then, we present the new opportunities when DT meets edge computing, Blockchain and Artificial Intelligence, and distributed machine learning (e.g., federated learning, multi-agent deep reinforcement learning). We also present a wide application of DT as an enabling technology for 6G networks, Aerial-Ground Networks, and Unmanned Aerial Vehicles (UAVs). The book allows an easy cross-reference owing to the broad coverage on both the principle and applications of DT. The book is written for people interested in communications and computer networks at all levels. The primary audience includes senior undergraduates, postgraduates, educators, scientists, researchers, developers, engineers, innovators and research strategists.
        URI
        https://library.oapen.org/handle/20.500.12657/87638
        Keywords
        Digital Twin; Edge Computing; Machine Learning; 6G; Internet of Things
        DOI
        10.1007/978-3-031-51819-5
        ISBN
        9783031518195, 9783031518195, 9783031518188
        Publisher
        Springer Nature
        Publisher website
        https://www.springernature.com/gp/products/books
        Publication date and place
        Cham, 2024
        Imprint
        Springer Nature Switzerland
        Series
        Simula SpringerBriefs on Computing, 16
        Classification
        Maths for engineers
        Communications engineering / telecommunications
        WAP (wireless) technology
        Network hardware
        Artificial intelligence
        Machine learning
        Pages
        126
        Rights
        http://creativecommons.org/licenses/by/4.0/
        • Imported or submitted locally

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        License

        • If not noted otherwise all contents are available under Attribution 4.0 International (CC BY 4.0)

        Credits

        • logo EU
        • This project received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 683680, 810640, 871069 and 964352.

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