## 2 Materials and Methods
### Optimization Mechanism Design
\begin{table}
\begin{tabular}{l l l l l} \hline \hline RSUP & 231 & 2 & OCM & 0.1, 30, 10 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: OCM for AODV with id = 231 and k = 2. Figure 8: Process for optimization implementation in the Road-Side Unit (RSU). VANET scenarios implemented in this research are design based on the roads and traffic of Changlun map [1]. Changlun map was chosen because it provides a realistic highway and city VANET scenario. Also, the geographical placement of the highway crossing the city is suitable for the purposes of evaluating the proposed mechanisms in a combined scenario. Further, the Changlun map is used to form 3 scenarios: city, highway, and combined VANET scenarios. The city scenario depicts the internal roads of the map and considers the highway part crossing the city as internal road. The city canvas dimensions are 1000 m in width and 1000 m in length. Vehicles move in the city within the speed range of 30-60 Km/h and follow the trajectory of the internal roads. Meanwhile, the number of vehicles varied for different experiments. RSUs are placed on the tops of buildings and simulated with the static mobility module to specify their placements in the map. The highway scenario presents a realization for the highway across the test site. The canvas dimensions are 50 m in width and 2000 m in length. Vehicles move in linear trajectories toward the ends of the highway within the speed range of 90-110 Km/h. RSUs are placed on the roadside with fixed distances of 200 to 300 m between them. The number of vehicles varies for different experiments. The combined scenario is a mix of the city and highway scenarios mentioned above. The key simulation parameters of these scenarios are shown in Table 2. The performance evaluations of CM-AODV and CM-GPSR were performed in three VANET scenarios (city, highway, and hybrid), based on the Changlun map. OMNET++ and INET3.5 simulation tools were used for the experiments throughout this research. The simulation module of Changlun city follows the geographical maps provided by Google in 2016, which include improved real-time traffic data and vehicle mobility was implemented by utilizing mobility models in the INET3.5 framework. Table 3 shows the comparison of three scenarios for optimization scaling with an increasing number of vehicles (high, medium, and low). \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **City** & **Highway** \\ \hline Simulation area & 1000 m \(\times\) 1000 m & 50 m \(\times\) 2000 m \\ \hline Number of vehicles & 30–60 & 20–40 \\ \hline Number of RSUs & 5 & 5 \\ \hline Vehicle’s speed & 40–60 km/h & 80–110 km/h \\ \hline Simulation time & NILL & NILL \\ \hline Data packet size & 512–1024 bytes & 512–1024 bytes \\ \hline MAC protocol & IEEE 802.11p & IEEE 802.11p \\ \hline Vehicle Mobility Module & road trajectory & linear \\ \hline \hline \end{tabular}
\end{table} 
Table 2: VANET scenarios key simulation parameters. \begin{table}
\begin{tabular}{l l l l} \hline \hline
**Scenario** & **Rural** & **City/Urban** & **Highway** \\ \hline Node density & Low & High & Medium \\ \hline Mobility—speed & Medium & Low & High \\ \hline Propagation/Challenges & \begin{tabular}{l} Non-free-space/Reflection, \\ attenuation \\ \end{tabular} & \begin{tabular}{l} Non-free-space/shadowing, \\ multi-path, fading \\ \end{tabular} & \
\begin{tabular}{l} Free-space/suffers \\ reflections \\ \end{tabular} \\ \hline Topology & Random (fields, hills) &
\begin{tabular}{l} Shapes (city roads, junctions, \\ blocks) \\ \end{tabular} & Linear, curvy \\ \hline Node distance & Hundreds of meters & 10 m & Less than 10 m \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comparison between three VANET scenarios.