Digital Twin Networks: A Survey
Abstract
Digital twin network (DTN) is an emerging network that utilizes digital twin (DT) technology to create the virtual twins of physical objects. DTN realizes co-evolution between physical and virtual spaces through DT modeling, communication, computing, data processing technologies. In this article, we present a comprehensive survey of DTN to explore the potentiality of DT. First, we elaborate key features and definitions of DTN. Next, the key technologies and the technical challenges in DTN are discussed. Furthermore, we depict the typical application scenarios, such as manufacturing, aviation, healthcare, 6G networks, intelligent transportation systems, and urban intelligence in smart cities. Finally, the new trends and open research issues related to DTN are pointed out.
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Digital twins are high-value targets precisely because their outputs directly and continuously influence operational decision-making across production, maintenance, and quality domains.
“Digital twins are high-value targets precisely because their outputs directly and continuously influence operational decision-making across production, maintenance, and quality domains.[9], [16]”
From Zero Trust Architecture for Smart Factories: Securing Digital Twins and Cyber-Physical OT Systems (2026) · cites this paper as [16]
Cites
Digital Twin in Industry: State-of-the-Art
Tao, F., Zhang, H., Liu, A., & Nee, A. Y. C. (2019) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2873186 · Cited by 4,391 · see citing works
Digital twin-driven product design, manufacturing and service with big data
Tao, F., Cheng, J., Qi, Q., Zhang, M., Zhang, H., & Sui, F. (2018) · The International Journal of Advanced Manufacturing Technology · doi:10.1007/s00170-017-0233-1 · Cited by 2,920 · see citing works
Reengineering aircraft structural life prediction using a digital twin
Tuegel, E. J., Ingraffea, A. R., Eason, T. G., & Spottswood, S. M. (2011) · International Journal of Aerospace Engineering · doi:10.1155/2011/154798 · Cited by 1,119 · see citing works
Communication-Efficient Federated Learning for Digital Twin Edge Networks in Industrial IoT
Lu, Y., Huang, X., Zhang, K., Maharjan, S., & Zhang, Y. (2021) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2020.3010798 · Cited by 316 · see citing works
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Wang, Y., Su, Z., Guo, S., Dai, M., Luan, T. H., & Liu, Y. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3263909 · Cited by 357 · see citing works
A Survey on Digital Twin for Industrial Internet of Things: Applications, Technologies and Tools
Xu, H., Wu, J., Pan, Q., Guan, X., & Guizani, M. (2023) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2023.3297395 · Cited by 304 · see citing works
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RetractedA comprehensive review of Digital Twin technologies in smart cities
Huzzat, A., Anpalagan, A., Khwaja, A. S., Woungang, I., Alnoman, A. A., & Pillai, A. S. (2025) · Digital Engineering · doi:10.1016/j.dte.2025.100040 · Cited by 65 · see citing works
Tran-Dang, H., & Kim, D.-S. (2025) · ICT Express · doi:10.1016/j.icte.2025.01.002 · Cited by 38 · see citing works
Zero Trust Architecture for Smart Factories: Securing Digital Twins and Cyber-Physical OT Systems
Alagappan, V. (2026) · International Journal of Artificial Intelligence, Data Science, and Machine Learning · doi:10.63282/3050-9262.ijaidsml-v7i2p109
- Authors
- Wu, Y., Zhang, K., & Zhang, Y.
- Affiliations
- University of Electronic Science and Technology of China (CN)
- University of Oslo (NO)
- Venue
- IEEE Internet of Things Journal
- Published
- 2021-09-15
- Volume
- 8
- Issue
- 18
- Pages
- 13789-13804
- ISSN
- 2327-4662 (ISSN-L)
- 2372-2541
- OpenAlex
- W3163246710
- Cited by
- 847
- References
- 4
- Citations by year
- 2026: 114 · 2025: 203 · 2024: 206 · 2023: 200 · 2022: 107 · 2021: 17
- FWCI
- 68.56
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Internet of Things Journal (publishedVersion)
- Funders
- National Natural Science Foundation of China (61941102, 62071092)
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Digital Transformation in Industry
- Physical Sciences › Computer Science › Computer Networks and Communications › Software-Defined Networks and 5G
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Data and IoT Technologies
- Keywords
- network digital twin, digital twin, manufacturing industry, aviation, health care, 6G, intelligent transportation systems, smart cities, urban intelligence
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