Jacopo Massa, PhD

Holder of the research grant "Ambienti per la programmazione strutturata parallela e distribuita di infrastrutture di calcolo all'Edge" associated with the NOUS EU-funded project, under the Horizon Europe programme.

Holder of the scholarship "Efficient solutions and approaches for AI on Edge Computing platforms", associated with participation in the Ph.D. programme in Computer Science, funded by CNR-ISTI "A. Faedo".

This thesis investigates declarative methodologies for managing applications and networks across the Cloud-Edge continuum, focusing on data-aware placement and intent-based networking. The work introduces models and prototypes that enable automated, context-sensitive distributed service deployment, based on data properties and infrastructure dynamics. It also proposes novel approaches for intent modelling, translation, and conflict resolution to support scalable orchestration of application and network configurations. The solutions are validated through simulation, emulation, and real-world case studies.

This thesis proposes declarative modelling of Cloud-IoT infrastructures and multi-service applications that separately model computing and data services. Through formal logic reasoning, the methodology determines eligible service placements and data traffic routing over Cloud-IoT resources. The proposed methodology is prototyped in Prolog and assessed via simulation over a life-like use case.

This thesis presents the design and implementation of a hybrid voice-graphical interface for smart building environments, enabling natural language interaction with IoT devices through Amazon Alexa and a touchscreen display. The system integrates multiple microservices within the GIÒ framework, allowing users to access contextual information, manage smart room goals, and control devices via voice commands or graphical input. The solution is prototyped using Python and the Alexa Skills Kit, and its usability is evaluated through real-user testing in a university setting.