Journal Articles Computer Networks Year : 2024

A Comprehensive Survey on Digital Twin for Future Networks and Emerging IoT Industry

Abstract

The rapid growth of industrial digitalization in the Industry 4.0 era is fundamentally transforming the industrial sector by connecting products, machines, and people, offering real-time digital models to allow self-diagnosis, and self-optimization and selfconfiguration. However, this uptake in such a digital transformation faces numerous obstacles. For example, the lack of real-time data feeds to perform custom closed-loop control and realize common, powerful industrial systems, the complexity of traditional tools and their inability in finding effective solutions to industry problems, lack of capabilities to experiment rapidly on innovative ideas, and the absence of continuous real-time interactions between physical objects and their simulation representations along with reliable two-way communications, are key barriers towards the adoption of such a digital transformation. Digital twins hold the promise of improving maintainability and deployability, enabling flexibility, auditability, and responsiveness to changing conditions, allowing continuous learning, monitoring and actuation, and allowing easy integration of new technologies in order to deploy open, scalable and reliable Industrial IoT (IIoT).

A critical understanding of this emerging paradigm is necessary to address the multiple dimensions of challenges in realizing digital twins at scale and create new means to generate knowledge in the industrial IoT. To address these requirements, this paper surveys existing digital twin software technologies, standardization efforts, and the wide range of recent and state-of-the-art projects on digital twin, presents diverse use cases that can benefit from this emerging technology, followed by an in-depth discussion of the major challenges in this area, and draws upon the research status and key trends in Digital Twins. Based on this critical analysis, this paper concludes by introducing an architectural overview of our HyPer-5G digital twin project that is geared towards enabling holistic management of Next Generation 5G IoT networks and beyond.

Keywords

Fichier principal
Vignette du fichier
ssrn-4535810.pdf (1.39 Mo) Télécharger le fichier

Dates and versions

hal-05547474 , version 1 (11-03-2026)

Licence

Identifiers

Cite

Akram Hakiri, Aniruddha Gokhale, Sadok Ben Yahia, Nedra Mellouli. A Comprehensive Survey on Digital Twin for Future Networks and Emerging IoT Industry. Computer Networks, 2024, 244, pp.110350. ⟨10.1016/j.comnet.2024.110350⟩. ⟨hal-05547474⟩

Collections

96 View
376 Download

Altmetric

Share

  • More