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.

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The wirelessly connected networks of vehicular nodes are Vehicular Ad Hoc Networks (VANET). According to the limited bandwidth of the wireless interface, dynamic topology, frequently disconnected networks with the vital role in vehicular communication is best path. To address this problem, this research proposes a Clustering-based Adaptive Elephant Herd Optimization (CAEHO) for VANETs. The proposed CAEHONET protocol is used to forms optimized clusters for robust communication. In CAEHONET is utilized to control the overhead can be efficiently. The main objective of the paper is to analyse the energy efficient and provide the security analysis in VANET. By calculating an enhanced fitness function, it works intelligently to select the optimal route and most stable route among known routes. The aim of the paper is to maintain the stability in the system of polar coordinate and the obstacles as objective of probability of occurrence. 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. Especially, the CAEHONET enhances the packet delivery, network throughput, packet loss ratio and ratio end-to-end delay than other routing protocols and the entire simulation works are handled in NS2 tool.

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