Paolo Lo Giacco
TUTORIAL
Title Here
Paolo Lo Giacco
Sebyone
ABSTRACT
The paradigm of Data as a Service (DaaS) redefines the role of communication infrastructures in the field of measurement and monitoring. In metrology, data must not only be acquired but also transported, interpreted, and utilized across diverse systems. DaaS addresses this need by enabling fully integrated environments where nodes are temporally synchronized and capable of dynamically selecting the most suitable communication channel and protocol.
This approach simplifies the deployment of monitoring and Machine Learning solutions by allowing developers to focus on application-level challenges, minimizing the traditional complexities of edge and fog computing. Unlike conventional architectures, DaaS nodes autonomously manage message storage and replication, ensuring scalable and resilient data flows without the need for centralized brokers.
The benefits of this approach are validated through a heterogeneous deployment involving low-power embedded devices and high-performance computing nodes, demonstrating the feasibility of DaaS for the next generation of distributed measurement systems and showing how nodes syncrhonize to a common time reference, interact at a defined network frequency, and adaptively optimize communication pathways.
