Distributed Cloud-Edge architectures for intelligent IoT services

I offer expertise in the design, development and experimental validation of Cloud–Edge IoT architectures that tightly integrate data-oriented communication and lightweight AI execution with 5G and emerging 6G networks.

A central aspect of my work is data-centric and decentralized IoT communication. I have extensive hands-on experience with the Zenoh protocol, which I have studied, deployed and evaluated as a unifying middleware across cloud, edge and constrained devices. My research demonstrates how Zenoh enables efficient publish/subscribe and query-based data exchange, supports mobility and intermittent connectivity, and provides low-latency and resilient communication in decentralized scenarios, outperforming traditional IoT protocols in Cloud–Edge and 5G-enabled environments.

I also specialize in lightweight execution environments based on WebAssembly (WASM) for deploying services and AI workloads close to data sources. By leveraging WASM, I design portable, secure and resource-efficient execution models that are particularly suitable for edge and 5G/6G scenarios, including privacy-preserving and collaborative AI approaches such as federated learning. This allows computation to be dynamically distributed across heterogeneous nodes while respecting latency, energy and resource constraints.

Another key component of my expertise is the orchestration of services and dataflows across the Cloud–Edge continuum. I work on orchestration mechanisms that combine microservice and serverless architectures with dataflow programming models, enabling workload-aware placement and dynamic adaptation of services according to network conditions and computing availability. This includes performance modeling and execution-time prediction for edge and serverless workloads, which is essential for meeting the stringent requirements of 5G and future 6G applications.