Volume 8 Issue 4 ( December 2021 )

VANETs (Vehicular Ad hoc Networks) have pulled in enormous considerations because of their real-time application and business value. Due to the limited bandwidth of the wireless interface, dynamic topology, frequently disconnected networks, the communication between vehicles is a challenging task. Clustering is seen as one of the possible solutions to achieve effective communication in VANETs; this research proposes a Clustering Adaptive Elephant Herd Optimization (CAEHO) technique for VANETs. The proposed CAEHO protocol is used to form optimized clusters for robust communication. Cluster head (CH) selection depends upon the fuzzy logic method by selecting parameters like connectivity levels, lane weighting, direction and speeds of vehicles. Based on a fitness function, these parameters are utilized to choose the optimal route between sender and receiver. The NS2 platform is used to implement the proposed work then it is contrasted with previous techniques such as Ant Colony Optimization algorithm (ACO) and Improved Whale Optimization algorithm (IWOA) respectively. Significantly, the CAEHO protocol enhances the packet delivery ratio, throughput and comparatively reduces overhead than other routing protocols.

Keywords: CAEHO protocol, EHO, Improved whale optimization algorithm, clustering, ACO and NS2 platform.