Leticia Lemus Cárdenas

Deployment-Aware Multi-Objective Optimization of Machine Learning Models for Predictive Congestion Control in Multi-Hop Vehicular Networks

Results across heterogeneous urban scenarios show that the proposed framework improves vehicular communication performance in terms of packet delivery reliability and communication delay, while preserving competitive machine learning performance under deployment-oriented constraints.