Abstract

The paper proposes an improvised vehicular Networks (VANETs) in an environment which is constantly subject to changes that gives various problems in VANETs, like topology replacement, and also to equalizing small routing paths. The remedy for such problem is clubbing. The proposed work is about to study five different routing procedure using “Dynamic Ant flying Cluster (DAFC)” method and Dynamic Self-Configured Weights to meet minimum clubbing, more accuracy, less time, low cost and Quality of Service (QoR) by choosing efficient cluster-head derived from dynamic clustering. In this study by correcting the steps for updating setting evaporation rate we applied very large improvement on basic DAFC.in this aspect for better performance evaluation of proposed routing procedure, two different phases of experiments are conducted. In the initial phase, the classic “Ant Colony Optimization (ACO), DAFC” which is Clustering method for Vehicular Ad Hoc Networks (VANET) were examined and compared. Subsequently, in the second stage, clustering systems such as “Centre Position and Mobility (CPM)”, “Angle-based Clustering Algorithm (ACA) and Highest-Degree algorithm (HD)” are evaluated using MATLAB and SUMO simulation tools. Through this process, we observed the anticipated behavior and demonstrated that our proposed method achieves enhanced node connectivity and cluster stability compared to existing approaches. Before delving into the original condition, it is important to note that assessing the efficiency of routing algorithms plays a challenging role in evaluating the performance of routing protocols in VANETs. This study contributes to understanding the statistical “Design of Experiments (DOE)” techniques as advanced alternative to the “One Factor at a Time (OFAT)” approach for assessing and demonstrating VANET routing protocol concert. The study employed the 2-level full factorial technique, the Placket–Burman method, and the Taguchi method, comparing and applying them with three design of experiments methods. Four key factors were considered in this work: black hole attacks, the number of connections, node density, and wormhole spasms. Their impacts on four measured outputs, namely “throughput, packet loss ratio, average end-to-end delay (EED)”, and routing overhead of the AODV routing protocol, were simultaneously examined and analysed.