# Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey
## 1 Introduction
### Motivation for This Survey  
SDN has become an increasingly popular approach to network architecture, enabling additional flexibility and programmability in network management [17]. In the context of VANETs, SDN has the potential to improve network performance and efficiency by providing a centralized controller to manage network traffic and resources. However, while there have been many surveys on SDN and VANET separately, there is currently a lack of comprehensive surveys on the intersection of these two fields [18]. This survey aims to fill that gap by providing state-of-the-art literature on SDN for VANETs. Specifically, in this survey, we examine the various use cases and architectures of SDN in VANETs and the challenges and opportunities presented by this intersection. Here, we also analyze  
Figure 1: The SDVN architecture [16]. the existing survey papers in this area and identify the gaps and limitations in the current research. To differentiate this survey from existing surveys, we focus specifically on the intersection of SDN and VANETs, rather than simply offering a general overview of SDN or VANETs [19]. Additionally, we provide a more comprehensive and up-to-date analysis of the existing literature in this field and identify potential future research directions. Ultimately, this survey provides a valuable resource for researchers and practitioners working with SDN and VANETs [20]. This survey discusses the challenges of traffic accidents and highway congestion and the need to optimize resource allocation techniques to improve the QoS in VANETs [21]. Information technology and ITSs can be used to improve traffic efficiency in VANETs [22]. Mobility-prediction-based routing protocols and multi-hop communication can provide network stability and reliability for the high dynamic flow of vehicles in VANETs. Network connectivity [23] is controlled by RSUs and BSs for traffic safety and efficiency [24; 25]. The survey also emphasizes the importance of the accurate stochastic modeling of multi-hop routing and cooperative data dissemination to enhance transportation and increase QoS [26; 27; 28]. Finally, the survey suggests using multi-hop cooperative data dissemination methods to improve system performance and resource utilization in VANETs [29]. The performance of SDN scenarios in VANET systems depends on optimal traffic load balancing. In the VANET system, an analysis of enhanced reliability of service (eRELSERV)-SDVN is needed based on queueing theory. Vehicular networks are ad hoc and, therefore, challenging to manage due to the random connection of end-to-end network devices. Integrating SDN with a VANET brings programmability and flexibility to the vehicular network, improving its performance [30]. The SDN controller can manage packet flow-table performance through the OpenFlow protocol, which helps handle heavy traffic flow in VANET communications and potentially prevent link breaks. A queueing analysis is also valuable for estimating SDN and managing high arrival and service demands. This can enable upcoming V2V and V2I services and simplify vehicular network optimization and mobility management. The SDHVN system uses queueing theory to provide optimal packet scheduling for efficient resource utilization among V2V and V2I communications in VANETs [31]. It improves the QoS of packet scheduling and enhances network utility while reducing traffic casualties. The intelligent digital twin (IDT) is a promising technique for simulating intelligent networking models. It can be used to observe and understand current and historical data to enhance routing efficiency, maintenance, traffic flow, and security in the physical network [32]. This survey acknowledges current research in software-defined vehicular networks (SDVNs) and identifies challenges and limitations in implementing SDN. The survey does not introduce new concepts or solutions but provides a comprehensive overview of existing techniques. It analyzes their strengths and weaknesses and identifies research opportunities.