Towards a Distributed Data Mesh Model for the IoT-Edge-Cloud Continuum in Smart Cities

This paper makes a compelling case for the adoption of the recently proposed Data Mesh architecture within IoT–Edge–Cloud Continuum scenarios, particularly in the context of Intelligent Transportation Systems and Data driven Mobility Services. Unlike centralized cloud-based approaches, based on data warehouses/lakes connected with ETL (Extract, Transform, and Load) pipelines, Data Mesh promotes a decentralized data ownership model which brings several advantages in addressing open challenges in IoT–Edge–Cloud Continuum scenarios. First, we present an overview of the Data Mesh concepts, and how they advance the state of the art in data management architectures. Secondly, we discuss how their adoption might ease the development of IoT–Edge–Cloud applications in terms of: (i) hiding the heterogeneity of the IoT Layer, (ii) mitigating latency by enabling full domain migrations, and (iii) promoting the adoption of AI techniques, such as MLOps and Federated Learning at the edge of the network. Finally, we provide practical guidelines for implementing such an architecture to enhance the safety of pedestrians and vulnerable users, based on our experience with the Modena Automotive Smart Area.