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Industrial digital twins at the nexus of NextG wireless networks and computational intelligence: A survey
Journal of Network and Computer Applications
  • Shah Zeb, National University of Sciences and Technology, Pakistan
  • Aamir Mahmood, Mid Sweden University
  • Syed Ali Hassan, National University of Sciences and Technology, Pakistan
  • MD. Jalil Piran, Sejong University, South Korea
  • Mikael Gidlund, Mid Sweden University
  • Mohsen Guizani, Mohamed bin Zayed University of Artificial Intelligence
Document Type

By amalgamating recent communication and control technologies, computing and data analytics techniques, and modular manufacturing, Industry 4.0 promotes integrating cyber–physical worlds through cyber–physical systems (CPS) and digital twin (DT) for monitoring, optimization, and prognostics of industrial processes. A DT enables interaction with the digital image of the industrial physical objects/processes to simulate, analyze, and control their real-time operation. DT is rapidly diffusing in numerous industries with the interdisciplinary advances in the industrial Internet of things (IIoT), edge and cloud computing, machine learning, artificial intelligence, and advanced data analytics. However, the existing literature lacks in identifying and discussing the role and requirements of these technologies in DT-enabled industries from the communication and computing perspective. In this article, we first present the functional aspects, appeal, and innovative use of DT in smart industries. Then, we elaborate on this perspective by systematically reviewing and reflecting on recent research trends in next-generation (NextG) wireless technologies (e.g., 5G-and-Beyond networks) and design tools, and current computational intelligence paradigms (e.g., edge and cloud computing-enabled data analytics, federated learning). Moreover, we discuss the DT deployment strategies at different communication layers to meet the monitoring and control requirements of industrial applications. We also outline several key reflections and future research challenges and directions to facilitate industrial DT's adoption. © 2021 The Author(s)

Publication Date
  • Data Analytics,
  • Edge computing,
  • Green computing,
  • Industrial research,
  • Industry 4.0,
  • Internet of things,
  • Machine learning,
  • Wireless networks,
  • 5g-and-beyond/6g,
  • Age of information,
  • Cloud-computing,
  • Cyber-physical systems,
  • Cyber-physical systems,
  • Data analytics,
  • Edge computing,
  • Green communications,
  • Multi-access edge computing,
  • Multiaccess,
  • 5G mobile communication systems

Open Access version with thanks to Elsevier ScienceDirect License: CC BY 4.0 Uploaded 12 May 2022

Citation Information
S. Zeb, A. Mahmood, S.A. Hassan, M.D.J. Piran, M. Gidlund, and M. Guizani, "Industrial digital twins at the nexus of NextG wireless networks and computational intelligence: A survey", Journal of Network and Computer Applications, v. 200, Apr. 2022, doi: 10.1016/j.jnca.2021.103309