Propagation routing for hybrid bandwidth allocation with reinforcement learning in VANET infrastructure analysis
Year: 2025
Type: article
Abstract: Advances in Vehicular Ad Hoc Networks (VANETs) require better security protocols to give automobiles and other VANET components impenetrable security. VANETs have several security challenges due to the openness of their communication architecture. The security and privacy issues related to vehicle-to-vehicle (V2V) communication have been addressed through various mutual authentication systems that researchers have recently put out. The investigation of the VANET infrastructure using artificial intelligence is proposed in this paper as a unique approach to smart V2V data transfer. The infrastructure study uses a hybrid multi-channel technique based on bandwidth allocation. The data are sent using reinforcement Q-learning techniques in conjunction with propagation routeing. The experimental investigation focuses on throughput, delay, QoS, computational cost and data transmission rate.
Source: Automatika
Authors: G. Michael, A. Selvakumar, Ramesh Sundar, S. Manikandan, R. Gnanajeyaraman, U. Arul
Institutions: Saveetha University, SRM Institute of Science and Technology
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $850
OpenAlex ID: W4410080597