SDN-based VANET routing: A comprehensive survey on architectures, protocols, analysis, and future challenges

As the automotive and telecommunication industries advance, more vehicles are becoming connected, leading to the realization of intelligent transportation systems (ITS). Vehicular ad-hoc network (VANET) supports various ITS services, including safety, convenience, and infotainment services for drivers and passengers. Generally, such services are realized through data sharing among vehicles and nearby infrastructures or vehicles over multi-hop data routing mechanisms. Vehicular data routing faces many challenges caused by vehicle dynamicity, intermittent connectivity, and diverse application requirements. Consequently, the software-defined networking (SDN) paradigm offers unique features such as programmability and flexibility to enhance vehicular network performance and management and meet the quality of services (QoS) requirements of various VANET services. Recently, VANET routing protocols have been improved using the multilevel knowledge and an up-to-date global view of traffic conditions offered by SDN technology. The primary objective of this study is to furnish comprehensive information regarding the current SDN-based VANET routing protocols, encompassing intricate details of their underlying mechanisms, forwarding algorithms, and architectural considerations. Each protocol will be thoroughly examined individually, elucidating its strengths, weaknesses, and proposed enhancements. Also, the software-defined vehicular network (SDVN) architectures are presented according to their operation modes and controlling degree. Then, the potential of SDN-based VANET is explored from the aspect of routing and the design requirements of routing protocols in SDVNs. SDVN routing algorithms are uniquely classified according to various criteria. In addition, a complete comparative analysis will be achieved to analyze the protocols regarding performance, optimization, and simulation results. Finally, the challenges and upcoming research directions for developing such protocols are widely stated here. By presenting such insights, this paper provides a comprehensive overview and inspires researchers to enhance existing protocols and explore novel solutions, thereby paving the way for innovation in this field

Computational Intelligence Inspired Data Delivery for Vehicle-to-Roadside Communications

We propose a vehicle-to-roadside communication protocol based on distributed clustering where a coalitional game approach is used to stimulate the vehicles to join a cluster, and a fuzzy logic algorithm is employed to generate stable clusters by considering multiple metrics of vehicle velocity, moving pattern, and signal qualities between vehicles. A reinforcement learning algorithm with game theory based reward allocation is employed to guide each vehicle to select the route that can maximize the whole network performance. The protocol is integrated with a multi-hop data delivery virtualization scheme that works on the top of the transport layer and provides high performance for multi-hop end-to-end data transmissions. We conduct realistic computer simulations to show the performance advantage of the protocol over other approaches

Comparative study of proactive and reactive routing protocols in vehicular ad-hoc network

In recent years, the vehicular ad-hoc network (VANET), which is an ad-hoc network used by connected autonomous vehicles (CAV) for information processing, has attracted the interest of researchers in order to meet the needs created by the accelerating development of autonomous vehicle technology. The enormous amount of information and the high speed of the vehicles require us to have a very reliable communication protocol. The objective of this paper is to determine a topology-based routing protocol that improves network performance and guarantees information traffic over VANET. This comparative study was carried out using the simulation of urban mobility (SUMO) and network simulator (NS-3). Through the results obtained, we will show that the choice of the type of protocol to use depends on the size of the network and also on the metrics to be optimized