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Title	A Qos-Aware Data Distribution Platform For Edge-Based Vehicular Digital Twins In Smart Cities
ID_Doc	3914
Authors	Rosa L.; Calvio A.; Garbugli A.; Foschini L.
Year	2025
Published	IEEE Wireless Communications and Networking Conference, WCNC
DOI	http://dx.doi.org/10.1109/WCNC61545.2025.10978459
Abstract	Digital Twins (DTs) are emerging as key enablers for Connected and Autonomous Vehicles (CAVs), offering virtual representations that support various applications ranging from offline, large-scale traffic analysis to real-time driver assistance. These use cases pose significantly diverse Quality of Service (QoS) requirements on DTs, including ultra-low latency for real-time synchronization with the physical counterparts. Deploying DTs at the network edge offers a promising solution, considering the increasingly advanced compute and network resources potentially available in a city-wide infrastructure. However, edge deployments introduce additional complexity: DT developers must deal with heterogeneous resources, optimize their usage for different QoS levels, and handle vehicle mobility. That process requires a high level of specialization and makes development time-consuming and error-prone. In this paper, we first introduce a DT communication model based on three key interfaces: to physical devices, to peer DTs, and to centralized applications. We then analyze the distinct QoS requirements of these interfaces and propose the adoption of a data distribution platform that maps them directly to edge network capabilities, hiding complexity and easing the DT development process. Early evaluations on a real testbed demonstrate the platform's potential to meet CAV DTs' QoS demands efficiently. © 2025 IEEE.
Author Keywords	CAV; Digital Twin; Edge Computing; Vehicular Networks

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