71 citations · 144 across the 18 of their papers we have counts for
9 papers · 1 filter
Value-Based Massive Access through Goal-Oriented Irregular Repetition Slotted ALOHA
Pietro Talli, Andrea Munari, Federico Mason +2
The goal-oriented communication paradigm is poised to enable novel real-time applications by easing the burden on communication networks while still delivering task-relevant inform…
PRATA: A Framework to Enable Predictive QoS in Vehicular Networks via Artificial Intelligence
Federico Mason, Tommaso Zugno, Matteo Drago +3
Predictive Quality of Service (PQoS) makes it possible to anticipate QoS changes, e.g., in wireless networks, and trigger appropriate countermeasures to avoid performance degradati…
Fast Context Adaptation in Cost-Aware Continual Learning
Seyyidahmed Lahmer, Federico Mason, Federico Chiariotti +1
In the past few years, DRL has become a valuable solution to automatically learn efficient resource management strategies in complex networks with time-varying statistics. However,…
Towards Decentralized Predictive Quality of Service in Next-Generation Vehicular Networks
Filippo Bragato, Tommaso Lotta, Gianmaria Ventura +4
To ensure safety in teleoperated driving scenarios, communication between vehicles and remote drivers must satisfy strict latency and reliability requirements. In this context, Pre…
Artificial Intelligence in Vehicular Wireless Networks: A Case Study Using ns-3
Matteo Drago, Tommaso Zugno, Federico Mason +3
Artificial intelligence (AI) techniques have emerged as a powerful approach to make wireless networks more efficient and adaptable. In this paper we present an ns-3 simulation fram…
A Reinforcement Learning Framework for PQoS in a Teleoperated Driving Scenario
Federico Mason, Matteo Drago, Tommaso Zugno +3
In recent years, autonomous networks have been designed with Predictive Quality of Service (PQoS) in mind, as a means for applications operating in the industrial and/or automotive…
No Free Lunch: Balancing Learning and Exploitation at the Network Edge
Federico Mason, Federico Chiariotti, Andrea Zanella
Over the last few years, the DRL paradigm has been widely adopted for 5G and beyond network optimization because of its extreme adaptability to many different scenarios. However, c…
An Adaptive Broadcasting Strategy for Efficient Dynamic Mapping in Vehicular Networks
Federico Mason, Marco Giordani, Federico Chiariotti +2
In this work, we face the issue of achieving an efficient dynamic mapping in vehicular networking scenarios, i.e., to obtain an accurate estimate of the positions and trajectories…
Quality-Aware Broadcasting Strategies for Position Estimation in VANETs
Federico Mason, Marco Giordani, Federico Chiariotti +2
The dissemination of vehicle position data all over the network is a fundamental task in Vehicular Ad Hoc Network (VANET) operations, as applications often need to know the positio…