Digital Twin Network

System, Protocol and Security
Erscheinungsjahr 2027
ISBN: 978-981-9256-36-5
Verlag: Springer Singapore

Buch, Englisch, Format (B × H): 155 mm x 235 mm

This book presents unique insights and cutting-edge research on the digital twin (DT)-powered smart city system based on the authors’ previous research. The contributing authors explore the specific challenges associated with this system and offer innovative perspectives.

This book systematically evaluates key technologies for DT collaboration in smart cities, focusing on data synchronization within DTs and data collaboration between DTs. DT technology refers to the process of digitizing and mapping physical entities in a smart city to virtual models in the digital realm. These DT entities integrate cloud computing resources and data, utilizing artificial intelligence (AI) techniques to analyze and comprehend the operational patterns of the city in the virtual space. They create cross-modal learning and knowledge graphs by integrating data with different attributes. As a result, DT enables accurate analysis, systematic prediction, joint command, and scenario-based services for the modelled physical entities. In this sense, DT entities can be seen as “intelligent software agents” operating in the cloud, integrating data, and AI. Different DT can achieve data sharing and collective intelligence through collaborative networking, enabling the collaboration of the entire city entity, which is known as integrated city operations.

This book emphasizes the vital role of DT technology in real-time analysis, accurate prediction, and collaborative command within smart city construction. The contributing authors address the main challenges of building AI-powered smart cities with a core of digital twin intelligent agents. This book will be valuable for readers interested in developing effective systems based on digital twins. Additionally, it will benefit those seeking to gain insights into how digital twin technology is transforming our lives by presenting innovative ideas and insightful visions.

Zielgruppe

Research

Autoren/Hrsg.

Luan, Tom H.

Gao, Longxiang

Yu, Shui

Inhaltsverzeichnis

Chapter 1. Digital Twin Analysis: Foundations, Architecture, and Privacy.- Chapter 2. Digital Twin-Enabled Secure and Efficient Handover Authentication in 5G-V2X.- Chapter 3. Digital Twin-Enhanced Task Offloading in IoV.- Chapter 4. Digital Twin-Accelerated Remote Data Sharing in IoV.- Chapter 5. A Privacy-Preserving and Distributed-Storage Digital Twin Data Sharing System.- Chapter 6. Game-Theoretic Framework for Ensuring Data Asset Security in Digital Twin Networks.- Chapter 7. Conclusion and Future Directions in Digital Twin Networks.

Über Autor(innen)

Tom H. Luan received the B.E. degree in electrical and computer engineering from Xi’an Jiaotong University, Xi’an, China, the master’s degree in electrical and computer engineering from the Hong Kong University of Science and Technology, Hong Kong, and the Ph.D. degree in electrical and computer engineering from the University of Waterloo, Waterloo, ON, Canada. He is currently with the School of Cyber Science and Engineering, Xi’an Jiaotong University, Xi’an, China. He has authored or coauthored more than 300 peer-reviewed papers in journal and conferences, including IEEE Transactions on Networking, IEEE Transactions on Mobile Computing, IEEE Transactions on Multimedia, IEEE Transactions on Vehicular Technology, and INFOCOM. His research interests include digital twin network, large language model system, Internet of agents , and protocol design, performance evaluation of digital network, and edge computing. He is a Fellow of IEEE, and was the recipient of the 2017 IEEE VTS Best Land Transportation Best Paper Award and IEEE ICCS 2018 Best Paper Award.

Longxiang Gao received his PhD in Computer Science from Deakin University, Australia. He is currently a Professor at Qilu University of Technology (Shandong Academy of Sciences) and Shandong Computer Science Center (National Supercomputer Center in Jinan). He was a senior lecturer at School of Information Technology, Deakin University, and a postdoctoral research fellow at IBM Research and Development, Australia. His research interests include Fog/Edge computing, Blockchain, data analysis, and privacy protection. Dr. Gao has over 100 publications, including patent, monograph, book chapter, journal, and conference papers. Some of his publications have been published in the top venue, such as IEEE TMC, IEEE TPDS, IEEE IoTJ, IEEE TDSC, IEEE TVT, IEEE TCSS, IEEE TII, and IEEE TNSE. He has been chief investigator (CI) for more than 20 research projects (the total awarded amount is over $5million), from pure research project to contracted industry research. He is a Senior Member of IEEE.

Shui Yu obtained his PhD from Deakin University, Australia, in 2004. He currently is a professor of School of Computer Science, University of Technology Sydney, Australia. Dr Yu’s research interest includes Network Science, Security and Privacy, Big Data, and Mathematical Modelling. He has published five monographs and edited two books, more than 500 technical papers at various venues, such as IEEE TPDS, TDSC, TIFS, TC, TMC, TKDE, TETC, ToN, and INFOCOM. His h-index is 66. Dr Yu promoted the research field of networking for big data in 2013, and his research outputs have been widely adopted by industrial systems, such as Amazon cloud security. He is passionate for professional services for his communities. He is currently serving a couple of prestigious editorial boards, including IEEE Communications Surveys and Tutorials (Area Editor), IEEE Internet of Things Journal, and so on. He served as a distinguished lecturer of IEEE Communications Society (2018–2021) and is a distinguished lecturer of IEEE Vehicular Technology Society, a distinguished visitor of IEEE Computer Society, a member of IEEE ComSoc Educational Services Board, an elected member of Board of Governors of IEEE ComSoc, and VTS. He is a member of ACM and AAAS and a Fellow of IEEE.