C. Chiasserini

Wireless Evidence Acquisition for Multimodal Inference Constrained by Temporal Windows

Multimodal inference in safety-critical applications, such as autonomous driving and robot navigation, requires heterogeneous sensor observations to reach an edge server within a task-prescribed temporal window. Referenced to the event or state being inferred, this window ends at the latest time an observation remains...

Virtual Sensing

MEC-based Extended Virtual Sensing

Data mining for energy analysis of a large data set of flats

A use case for improving the traceability, monitoring and efficiency of EV battery transportation using innovative approaches in federated data spaces, AI-powered inference and orchestration of a multi-objective computational continuum is given.

Reliability and Traffic Aware Resource Allocation for UAV-Assisted Vehicular O-RAN

The rapid advancements of next-generation vehicular networks require intelligent, low-latency, and efficient resource management to support heterogeneous services. In this work, we propose a Traffic-aware Dynamic Resource Allocation (TADRA) architecture for UAV-assisted vehicular O-RAN to address the challenges of dyna...

CORMO-RAN: Energy Efficiency at the Near-RT RIC via Lossless Migration of O-RAN xApps

This paper proposes CORMO-RAN, a data-driven orchestrator that dynamically activates compute nodes based on xApp load to save energy, and performs lossless migration of xApps from nodes to be turned off to active ones while ensuring xApp availability during migration.

Efficient Management of Composite Heterogeneous Applications at the Network Edge

Edge computing is a promising paradigm for deploying latency-sensitive applications (Apps) as it brings resources closer to end users. Edge Apps often adopt a microservice (MS) architecture, breaking monolithic Apps into lightweight, containerized MSs that can be dynamically and independently deployed. However, managin...