Federated Learning for Digital Twin-Based Vehicular Networks: Architecture and Challenges

A digital twin uses a virtual model of the physical system to fulfill diverse requirements (e.g., latency, reliability, quality experience) for emerging vehicular network applications. Although twin-based implementation networks can offer performance optimization, modeling is significantly challenging task. Federated learning (FL) better privacy-preserving, distributed scheme that be used models. FL enhancement, it requires careful design. Therefore, in this article, we present an overview twinbased network. general architecture FL-enabled twins presented. Our proposed consists two spaces, such as space and space. all entities cars edge servers) required networks, whereas, refers logical deployment twins. implemented either using servers cloud servers. We also outline few use cases Finally, paper concluded outlook on open challenges