User-Oriented Fuzzy Logic-Based Clustering Scheme for Vehicular Ad-Hoc Networks

Vehicular ad-hoc networks (VANETs) are considered to have an enormous potential in enhancing road traffic safety and traffic efficiency. Socio-economic challenges, network scalability and stability are identified among the main challenges in VANETs. In response to these challenges, this paper proposes a novel user-oriented Fuzzy Logic-based k-hop distributed clustering scheme for VANETs that takes into consideration the vehicle passenger preferences. The novelty element introduced is the employment of Fuzzy Logic as a prominent player in the clustering scheme. To the best knowledge of the authors, there are no Fuzzy Logic-based clustering algorithms designed for VANETs. Simulation-based testing demonstrate how the proposed solution increases the stability of vehicular networks, lifetime and stability of cluster heads compared to both the classic Lowest ID algorithm and an utility function-based clustering scheme previously proposed by the same authors.