Intelligent OLSR Routing Protocol Optimization for VANETs

TL;DR

This paper optimizes the OLSR routing protocol for VANETs using metaheuristic algorithms to improve network performance in city scenarios, outperforming standard configurations and expert settings.

Contribution

It introduces an automatic parameter tuning method for OLSR in VANETs using metaheuristics, enhancing routing efficiency in urban environments.

Findings

Optimized OLSR configurations outperform RFC 3626 standards.

Metaheuristic algorithms effectively find optimal protocol parameters.

Enhanced QoS demonstrated in realistic city scenarios.

Abstract

Recent advances in wireless technologies have given rise to the emergence of vehicular ad hoc networks (VANETs). In such networks, the limited coverage of WiFi and the high mobility of the nodes generate frequent topology changes and network fragmentations. For these reasons, and taking into account that there is no central manager entity, routing packets through the network is a challenging task. Therefore, offering an efficient routing strategy is crucial to the deployment of VANETs. This paper deals with the optimal parameter setting of the optimized link state routing (OLSR), which is a well-known mobile ad hoc network routing protocol, by defining an optimization problem. This way, a series of representative metaheuristic algorithms (particle swarm optimization, differential evolution, genetic algorithm, and simulated annealing) are studied in this paper to find automatically optimal configurations of this routing protocol. In addition, a set of realistic VANET scenarios (based in the city of M\'alaga) have been defined to accurately evaluate the performance of the network under our automatic OLSR. In the experiments, our tuned OLSR configurations result in better quality of service (QoS) than the standard request for comments (RFC 3626), as well as several human experts, making it amenable for utilization in VANET configurations.