A fuzzy-logic-based cluster head selection algorithm in VANETs

Due to vehicles high mobility, there have been many clustering-based MAC protocols proposed to control Vehicular Ad hoc Network topology more effectively. Cluster head (CH) selection and cluster formation is of paramount importance in a highly dynamic environment such as VANETs. In this paper, we propose a novel cluster head selection criteria where cluster heads are selected based on their relative speed and distance from vehicles within their neighborhood. The maintenance phase in the proposed algorithm is adaptable to drivers' behavior on the road and has a learning mechanism for predicting the future speed and position of all cluster members using fuzzy logic inference system. The simulation results show that the proposed algorithm has a high average cluster head lifetime and more stable cluster topology with less communication and coordination between cluster members compared to other schemes.