Optimizing Real‐Time Vehicular Communications With a Cross‐Layer Model for Energy‐Efficient Clustering and Blockchain‐Based Congestion Control

Abstract

Vehicular ad hoc networks (VANETs) are essential components of intelligent transportation systems that facilitate real‐time communication between vehicles (V2V) and between vehicles and infrastructure (V2I). Despite their importance, VANETs face challenges, such as high node mobility, energy limitations, security risks, and ever‐changing network topologies. Existing clustering and routing algorithms often struggle to manage the instability caused by mobility, energy disparities, and secure congestion‐free communication simultaneously. To address these challenges, this work introduced an integrated cross‐layer framework featuring three innovative algorithms: mobility‐aware black hole clustering (M‐BHC), energy‐aware piranha optimization algorithm (EPOA), and cross‐layer multi‐attribute blockchain routing with congestion control (CL‐MABRC). The M‐BHC algorithm enhances the stability of clusters and counters black‐hole attacks by forming clusters dynamically based on real‐time vehicle mobility patterns. EPOA optimizes the selection of cluster heads (CHs) by reducing energy consumption through a bio‐inspired resource allocation strategy modeled on piranha predation behavior. CL‐MABRC addresses network congestion and security using blockchain‐based verification and cross‐layer routing decisions informed by multi‐attribute metrics. Extensive simulations were conducted with a setting of 100 veh/km2. The proposed framework showed significant performance improvements over benchmark protocols, such as optimal security‐aware cluster‐based hybrid geographical and opportunistic routing (OSC‐GOR), enhanced location‐aided ant colony routing (ELAACR), trust‐based multi‐objective honey badger algorithm (TMOHBA), and robust cryptographic scheme for reliable data communication (RCSRC). It achieved a throughput of 99.89 Kbps, end‐to‐end delay of 3.9 ms, collision rate of 21.8%, energy consumption of 41.98%, and jitter of 0.05 ms. Together, the M‐BHC, EPOA, and CL‐MABRC algorithms create a robust, energy‐efficient, and secure communication framework for VANETs, enhancing scalability, reliability, and real‐time performance in transportation systems.