Open access
Sep 2026
Attention-guided deep embedding framework for heterogeneous vehicular clustering and cluster head selection in dynamic VANETs
The paper proposes an attention-guided deep embedding framework that jointly models long-range structural interactions and heterogeneous vehicular influence, rather than restricting learning to immediate neighbours, and provides a robust solution for stable V2V communication.
Ajaybeer Kaur, M. Ali, Parveen Kumar et al.
· Discover Computing · 0 citations