Decentralized Digital Twin Networks

Digital twin networks (DTNs) enable largescale modeling and simulation of complex physical systems by interconnecting virtual replicas of physical objects. However, existing DTNs are highly centralized, which inherently limits their performance during digital twin generation and fault tolerance when facing device failures or malicious attacks. To address these limitations, we propose a novel decentralized digital twin network (DeDTN) paradigm based on blockchain and edge computing technologies. DeDTN achieves high scalability by enabling digital twins to be generated through decentralized edge devices contributed by individual device owners. When confronted with failures or attacks, digital twin consistency is maintained through blockchain consensus among participating devices. Additionally, digital twins are tokenized on-chain to secure ownership and enable seamless sharing between stakeholders. To demonstrate DeDTN's effectiveness, we implement a prototype for transportation traffic modeling in smart cities. Evaluation results show that DeDTN significantly outperforms traditional centralized DTNs in terms of latency and bandwidth efficiency. We also outline several open challenges and future research directions for DeDTN and its applications.