Digital Twin Networks: A Survey

• Published in: IEEE internet of things journal Vol. 8; no. 18; pp. 13789 - 13804
• Main Authors: Wu, Yiwen, Zhang, Ke, Zhang, Yan
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 15.09.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Computational modeling; Data models; Data processing; Digital twin; Digital twin (DT); digital twin network (DTN); Digital twins; DT modeling; Intelligent transportation systems; Mirrors; Predictive models; Smart cities; Transportation networks
• ISSN: 2327-4662; 2327-4662
• DOI: 10.1109/JIOT.2021.3079510

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.