Genetic tuning of fuzzy rule-based systems for multi-hop broadcast protocols for VANETs

Vehicular ad-hoc networks (VANETs) have been identified as a key technology to enable intelligent transport systems (ITS), which in turn have the potential to radically enhance the safety and comfort of vehicles on the road as well as the potential to reduce their environmental impact. Nevertheless, several issues still must be addressed in order to fully exploit the potential of VANETs in favor of ITSs. Particularly, one key open issue in VANETs is the multi-hop broadcast message dissemination (MBMD) for safety and infotainment applications. In this context, fuzzy rule-based systems (FRBSs) have been proved to be useful when designing MBMD protocols for VANETs. However, a methodological tuning of the FRBS for such MBMD protocols to improve their performance in terms of metrics like packet delivery ratio still remains open. This paper deals with the problem of determining the best position and overlap between fuzzy states (FSs) of the MFs for FRBS-based MBMD protocols in order to enhance its performance. Specifically, a component-based methodology using genetic algorithm (GA) for the MFs tuning problem is proposed. The proposed methodology is validated by tuning two relevant FRBS-based MBMD protocols found in the literature. The tuned MBMD protocols have been evaluated over a range of realistic scenarios. Obtained results from the evaluations show that the tuned MBMD protocols provide better performance than the heuristically defined FRBSs in terms of important metrics like packet delivery ratio.