Traffic-aware Routing Protocol in VANET using Adaptive Autoregressive Crow Search Algorithm

Abstract

The traffic-aware routing in the geographical area is essential in Vehicular Ad Hoc Network (VANETs). VANET is highly significant in the research area for transmitting the sensing information between the vehicular nodes. In VANET, there exist few mobility patterns, which assist to predict the path of the vehicle. Due to the demand in developing the traffic-aware routing protocol in VANET, and effective routing protocol named Adaptive Autoregressive Crow Search optimization Algorithm (Adaptive-ARCSA) is proposed in this work to predict the traffic in road segments. The traffic prediction is achieved by using the Exponential Weighted Moving Average (EWMA) based on the traffic density and vehicle speed. Hence, the optimal path is selected by using the proposed Adaptive-ARCSA by utilizing the objective function. The analysis of the proposed algorithm is made and the performances are evaluated using the metrics, like End to End Delay (EED), average traffic density, distance, and throughput, which acquired with the values of 2,343, 0.034, 2.0896 and 0.1, respectively.