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Federated Digital Twins as an Enabling Technology for Collaborative Decision-Making

Published: 24 June 2024 Publication History
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    Over the last few years, Digital Twin (DT) has emerged as an innovative concept that integrates multiple technologies to mirror physical assets, systems, and processes. Assisted by data analytics, predictive models, and optimisation techniques, DTs are suitable for enhancing operations in virtual space before transferring information into real-world counterparts. Moreover, initiatives considering DTs as part of a composite complex system might consider federated ecosystems for exchanging insights and relevant information. In this context, the Federated Digital Twin (FDT) concept is a potential solution to address interaction among virtual entities, enabling advanced operations and ensuring collaborative decision-making. This study describes a comprehensive FDT framework inspired by principles and methodologies considered by well-studied federated systems. Furthermore, a reference abstract architecture allowing seamless integration among multiple agent-based DTs is provided as a tool to develop a wide range of DT-based applications.

    References

    [1]
    Georgios Diamantopoulos, Nikos Tziritas, Rami Bahsoon, and Georgios Theodoropoulos. 2022. Digital Twins for Dynamic Management of Blockchain Systems. In 2022 Winter Simulation Conference (WSC). 2876–2887. https://doi.org/10.1109/WSC57314.2022.10015447
    [2]
    Forbes. [n. d.]. Digital Twin Technology Has The Potential To Radically Disrupt Healthcare. https://www.forbes.com/sites/saibala/2023/12/22/digital-twin-technology-has-the-potential-to-radically-disrupt-healthcare/?sh=4ffd3b51735f Accessed on Feb 15, 2024.
    [3]
    Adam Ghandar, Ayyaz Ahmed, Shahid Zulfiqar, Zhengchang Hua, Masatoshi Hanai, and Georgios Theodoropoulos. 2021. A Decision Support System for Urban Agriculture Using Digital Twin: A Case Study With Aquaponics. IEEE Access 9 (2021), 35691–35708. https://doi.org/10.1109/ACCESS.2021.3061722
    [4]
    Tianmeng Hu, Biao Luo, Chunhua Yang, and Tingwen Huang. 2023. MO-MIX: Multi-Objective Multi-Agent Cooperative Decision-Making With Deep Reinforcement Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence (2023).
    [5]
    Alessandro Ricci, Angelo Croatti, Stefano Mariani, Sara Montagna, and Marco Picone. 2022. Web of digital twins. ACM Transactions on Internet Technology 22, 4 (2022), 1–30.
    [6]
    Yara Rizk, Mariette Awad, and Edward W Tunstel. 2018. Decision making in multiagent systems: A survey. IEEE Transactions on Cognitive and Developmental Systems 10, 3 (2018), 514–529.
    [7]
    Christian Vergara, Rami Bahsoon, Georgios Theodoropoulos, Wendy Yanez, and Nikos Tziritas. 2023. Federated Digital Twin. In 2023 IEEE/ACM 27th International Symposium on Distributed Simulation and Real Time Applications (DS-RT). 115–116. https://doi.org/10.1109/DS-RT58998.2023.00027
    [8]
    Yuntao Wang, Zhou Su, Shaolong Guo, Minghui Dai, Tom H Luan, and Yiliang Liu. 2023. A survey on digital twins: architecture, enabling technologies, security and privacy, and future prospects. IEEE Internet of Things Journal (2023).
    [9]
    Yiwen Wu, Ke Zhang, and Yan Zhang. 2021. Digital twin networks: A survey. IEEE Internet of Things Journal 8, 18 (2021), 13789–13804.
    [10]
    youris.com. [n. d.]. Virtual cities for very real benefits: from Local Digital Twins to the Cityverse. https://www.youris.com/energy/ecobuildings/virtual-cities-for-very-real-benefits-from-local-digital-twins-to-the-cityverse.kl Accessed on Dec 12, 2023.
    [11]
    Nan Zhang, Rami Bahsoon, and Georgios Theodoropoulos. 2020. Towards Engineering Cognitive Digital Twins with Self-Awareness. In 2020 IEEE International Conference on Systems, Man, and Cybernetics (SMC). 3891–3891. https://doi.org/10.1109/SMC42975.2020.9283357
    [12]
    Nan Zhang, Rami Bahsoon, Nikos Tziritas, and Georgios Theodoropoulos. 2024. Explainable Human-in-the-Loop Dynamic Data-Driven Digital Twins. In Dynamic Data Driven Applications Systems, Erik Blasch, Frederica Darema, and Alex Aved (Eds.). Springer Nature Switzerland, Cham, 233–243.

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      cover image ACM Conferences
      SIGSIM-PADS '24: Proceedings of the 38th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation
      June 2024
      155 pages
      ISBN:9798400703638
      DOI:10.1145/3615979
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Published: 24 June 2024

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