Marco Alfredo Loaiza Carrillo


Raffaele Gravina


Michael Prisco

Research Topic

Machine learning approach for system management and application deployment in IoT-Edge-Cloud continuum

Research Abstract

With the exponential growth of IoT services across the IoT-Edge-Cloud Continuum, the management of this large-scale ecosystem has become such a challenging task. Nowadays, there are some rule-based approaches that are not efficient in managing this type of services due to its highly heterogeneous and dynamicity. However, the advancement of ML models can provide promising ways to address these tasks by inferring some policies to handle the system management and application deployment based on its own real time data generation. The goal of this project is to find ML/AI techniques or approaches to manage the IoT-edge-cloud ecosystem