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Link to original content: https://unpaywall.org/10.1007/978-3-030-86960-1_37
A Cloud-Edge Orchestration Platform for the Innovative Industrial Scenarios of the IoTwins Project | SpringerLink
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A Cloud-Edge Orchestration Platform for the Innovative Industrial Scenarios of the IoTwins Project

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Computational Science and Its Applications – ICCSA 2021 (ICCSA 2021)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 12950))

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Abstract

The concept of digital twins has growing more and more interest not only in the academic field but also among industrial environments thanks to the fact that the Internet of Things has enabled its cost-effective implementation. Digital twins (or digital models) refer to a virtual representation of a physical product or process that integrate data from various sources such as data APIs, historical data, embedded sensors and open data, giving to the manufacturers an unprecedented view into how their products are performing. The EU-funded IoTwins project plans to build testbeds for digital twins in order to run real-time computation as close to the data origin as possible (e.g., IoT Gateway or Edge nodes), and whilst batch-wise tasks such as Big Data analytics and Machine Learning model training are advised to run on the Cloud, where computing resources are abundant. In this paper, the basic concepts of the IoTwins project, its reference architecture, functionalities and components have been presented and discussed.

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Acknowledgements

This work was partially supported by EU H2020 IoTwins Innovation Action project (g.a. 857191).

Author information

Authors and Affiliations

  1. INFN -CNAF, Bologna, Italy

    Alessandro Costantini, Doina Cristina Duma, Barbara Martelli, Matteo Galletti, Simone Rossi Tisbeni & Daniele Cesini

  2. INFN-Bari, Bari, Italy

    Marica Antonacci

  3. Università di Bologna, Bologna, Italy

    Paolo Bellavista & Giuseppe Di Modica

  4. Fraunhofer FOKUS, TU, Berlin, Germany

    Daniel Nehls

  5. ESI GROUP, Rungis, France

    Jean-Christian Ahouangonou & Cedric Delamarre

Authors
  1. Alessandro Costantini
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  2. Doina Cristina Duma
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  3. Barbara Martelli
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  4. Marica Antonacci
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  5. Matteo Galletti
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  6. Simone Rossi Tisbeni
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  7. Paolo Bellavista
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  8. Giuseppe Di Modica
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  9. Daniel Nehls
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  10. Jean-Christian Ahouangonou
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  11. Cedric Delamarre
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  12. Daniele Cesini
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Corresponding author

Correspondence to Alessandro Costantini .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. University of Cagliari, Cagliari, Italy

    Chiara Garau

  5. University of Cagliari, Cagliari, Italy

    Ivan Blečić

  6. Monash University, Clayton, VIC, Australia

    David Taniar

  7. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  8. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  9. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

  10. Polytechnic University of Bari, Bari, Italy

    Carmelo Maria Torre

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Costantini, A. et al. (2021). A Cloud-Edge Orchestration Platform for the Innovative Industrial Scenarios of the IoTwins Project. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2021. ICCSA 2021. Lecture Notes in Computer Science(), vol 12950. Springer, Cham. https://doi.org/10.1007/978-3-030-86960-1_37

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  • DOI: https://doi.org/10.1007/978-3-030-86960-1_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-86959-5

  • Online ISBN: 978-3-030-86960-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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