Today, intelligent transportation systems (ITS) have received a lot of attention due to their significant impact on increasing the safety, efficiency, and convenience of transportation. One of the main applications of ITS is vehicular ad hoc networks (VANETs). In particular, a more flexible, reliable, real-time, and scalable routing scheme across the large urban areas is one of the most critical issues for VANETs. Past VANET routing methods have various technical issues with VANET evolutions. On the other hand, clustering improves the reliability and scalability of routing schemes in VANETs. In this paper, a cluster-based, Traffic-aware and Low-Latency Routing Schema (TaLAR) is proposed for VANETs. In the proposed scheme, the Harris hawks optimization (HHO) algorithm is used to select cluster head (CH) nodes by considering appropriate parameters such as intracluster distance, link reliability, and relative speed of vehicles. The path between source and destination CH nodes is identified by using the HHO algorithm; it chooses the appropriate route based on link reliability and intercluster distance. Also, in the interconnection area, a traffic-aware and reliable route is identified by using a digital map of the streets and the Dijkstra algorithm. The performance evaluation of the proposed scheme is analyzed in terms of packet delivery rate (PDR), average end-to-end delay, and throughput. The output of the proposed scheme is compared with the Clustering Routing Based on PSO (Particle Swarm Optimization) (CRBP) and Grey Wolf Optimization Based Clustering in Vehicular Ad Hoc Network (GWOCENT) methods. Simulation results show that the proposed scheme improves PDR (22 and 19%), throughput (25 and 21%), and average end-to-end delay (23 and 18%).
Summary In a vehicular ad‐hoc network (VANET), each vehicle is equipped with an on‐board unit to communicate vehicle to vehicle or vehicle to fixed infrastructure. VANET technology is offered to provide many facilities to passengers and drivers, including safety, entertainment, mobile commerce, driver assistance, and emergency alarms. VANET has unique features such as high‐speed node mobility and network topology dynamics. These special features cause many problems such as increased transmission delays and packet loss. On the other hand, providing a good routing plan for VANET is a critical issue. Therefore, this article proposes a cluster‐based routing using in‐vehicle meta‐heuristic algorithms (CRMHA‐VANET) which has two phases. In the first stage, the vehicles are clustered and the most suitable cluster head (CH) is selected using the gray wolf optimization algorithm (GWO). In the next step, the next suitable CH is selected for data transmission in direct paths using the technique for order of preference by similarity to ideal solution (TOPSIS). The performance of the proposed method is analyzed through several criteria such as package delivery rate, end‐to‐end delay and throughput. CRMHA‐VANET results in a 10% to 25% improvement over all performance metrics, that is, packet delivery rate, latency, and throughput, over CRBP (clustering routing based on PSO [particle swarm optimization]), WCV (weight based clustering for VANET), and AODV‐CD methods.
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