Experimental Design for Hybrid Optimization Using Ants in Grey Wolf Optimization to Minimize the Traffic Congestion in VANETs

Vehicular Adhoc Networks (VANETs) is the trending technology, here the vehicles are used as nodes and it is equipped with its (OBU) for performing the sensing operations and this kind of communication method. In the recent times, the urban traffic congestion problems are highly increased due to the increased number of vehicles and its high speed with unpredictable mobility. To overcome this issue many of the scientific research models are developed but however still it faces lots of challenges like network delay, insufficient bandwidth and power utilization and network link disconnections, etc. With the purpose of solving these issues in this article Hybrid Optimization using Ants in Grey Wolf Optimization for Traffic control (HOAGT) is developed and it finds the optimal path in two ways. They are initial stable path finding and optimal best solution section. At the primary level the vehicle-based network is constructed and among the vehicles the initial stable path is analyzed using the ant-based optimization. Secondly, the best solution to transmit the data is obtained with the help of the Grey Wolf Optimization (GWO) algorithm. Through this process the vehicles congestion is effectively handled and that leads to attain high stability in data transmission. Finally, to understand the betterment of the HOAGT its results are compared with QOSHA and HKMCO. From the results it is evaluated that the HOAGT attains 17% higher delivery ratio, 50 ms lower delay, 50 packets lower packet loss and 200 packets lower routing overhead.