A QoS-Aware Data Distribution Platform for Edge-Based Vehicular Digital Twins in Smart Cities

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.