A new approach in position-based routing protocol using learning automata for vanets in city scenario

TL;DR

This paper introduces PBLA, a position-based routing protocol for VANETs in urban environments, leveraging learning automata and traffic data to improve routing reliability and efficiency amidst high mobility and obstacles.

Contribution

The paper presents a novel routing protocol using learning automata that adaptively improves path selection in VANETs based on traffic information.

Findings

PBLA outperforms traditional routing protocols in urban VANET scenarios.

Learning automata enhance routing efficiency over time.

Traffic information usage decreases as the automata learn the optimal paths.

Abstract

One of the main issues in Vehicular Ad-hoc NETworks (VANETs) is providing a reliable and efficient routing in urban scenarios with regard to the high vehicle mobility and presence of radio obstacle. In this paper, we propose a Position-Based routing protocol using Learning Automata (PBLA). In addition, PBLA uses the traffic information for enhancing learning. As we know, a main characteristic of learning is increasing performance over time. We exploit this characteristic to decreasing use of traffic information. Initially, PBLA make effort to finding best and shortest path to mobile destination using traffic information.