# Stochastic Modeling for Intelligent Software-Defined Vehicular Networks: A Survey
## 4 Integrating into VANET System Model for iSDVN
### Systems under Test  
In this section, the systems under test in iSDVN performance benchmarking are examined by considering two components, infrastructure and infrastructure-less, which are discussed in the following subsections. Many performance benchmarks are evaluated on the EstiNet OpenFlow network simulator and emulator and OMNeT discrete event simulator. _Control Plane_:In SDN, network intelligence is logically centralized in software-based controllers (i.e., control plane). Server decisions determine how the network nodes will forward data packets. In the centralized implementation, vehicles do not need to maintain any control information [37; 38]. The control plane maintains switches and routers that deal with connectivity and data forwarding. In transmission, this applies to both single-hop and multi-hop scenarios. The iSDVN architecture provides network protocol management through a logical central controller. Registration should be permitted for each device, including the OBU, and for vehicles as well. Controller status reports, including the position and volume of data, are provided periodically. Based on the information collected, it is determined how to reconfigure network protocols and their control parameters and how to distribute and exchange network resources. By doing so, the network can maximize its performance. Figure 5: The general architecture for iSDVN. Data Plane: During RSU communications, data traffic is forwarded to vehicles through the data plane. A data plane and overlay network are established to eliminate heterogeneity in the vehicular scenario. SDN provides a network management tool by abstracting vehicles, RSUs, and BSs as switches. Depending on its mobility, an SDN switch can be divided into mobile and stationary data planes. RSUs are regarded as mobile data planes, and BSs are referred to as stationary data planes. Different policies are applied to data plane management [37]. To transmit data effectively, an iSDVN uses V2V and vehicle-to-RSU communication links [108]. Multi-hop V2V transmissions to distant destinations that are not covered by RSUs can be carried out using connections. Network Function Virtualization: An important aspect of Network Function Virtualization (NFV) is segmenting network node functions into functional blocks [109]. Software now implements the technology independently from hardware, and it is not limited by hardware architecture any longer [50]. These capabilities are usually found in hardware, such as network access, services, and applications. By utilizing standard servers instead of custom devices, NFV provides network functionality. The NFV-enabled SDVN improves service provisioning, flexibility, service delivery, and reliability. An SDVN can be effectively used to deploy advanced applications, such as NFV. Software-Defined Heterogeneous Vehicular Networks: Due to heavy data traffic [41; 110], it is difficult to have load balancing among vehicles and RSUs in SDN. Therefore, integrating SDN and HetVNET (called a software-defined heterogeneous vehicular network (SDHVN)) balances the load and provides cooperative data dissemination between vehicles and RSUs [67]. A centralized service architecture enhances the distribution of data in SDHVN environments, as shown in Figure 6. The SDHVN makes transport networks coordinated and safer [111]. Moreover, it plays a significant role in managing network services and providing reliable communication [47]. Vehicle users benefit from the SDHVN's wide coverage and high throughput through the use of cellular networks. A Virtual Network Function (VNF) allows flexible resource scheduling in an SDHVN. Packet Scheduling: Packet scheduling ensures that packets are transmitted efficiently and fairly across the network while meeting different applications' quality-of-service (QoS) requirements. Packet scheduling becomes more challenging in certain scenarios, such as networks with high traffic loads, heterogeneous traffic, or real-time applications requiring low latency and high reliability [113].