# A Novel Context-Aware Reliable Routing Protocol and SVM Implementation in Vehicular Area Networks
## 5 Simulation Analysis
Figures 6-8 show the improvement in PDR with varying vehicular node density in the network areas 1000 \(\times\) 1000, 1200 \(\times\) 1200, and 1500 \(\times\) 1500, respectively. The proposed protocol shows improvement in PDR compared to CBLTR [21] and [PERSON] et al. [24] because of effective route selection using the k-means and SVM approach. The average PDR in the proposed protocol is improved by 2.5% as compared to [PERSON] et al. [24] protocol and by 8.2% compared to CBLTR [21] protocol considering the 50 vehicular nodes for the simulation work, as shown in Figure 6. \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Total Number of Vehicles**} & \multicolumn{3}{c}{**PDR**} \\ \cline{2-4}  & **PDR Proposed** & **[PERSON] et al. [24]** & **CBLTR [21]** \\ \hline
50 & 0.92114 & 0.901458 & 0.850015 \\ \hline
60 & 0.92847 & 0.89554 & 0.850314 \\ \hline
70 & 0.93145 & 0.882145 & 0.857059 \\ \hline
80 & 0.93259 & 0.87452 & 0.860566 \\ \hline
90 & 0.942234 & 0.86325 & 0.868399 \\ \hline
100 & 0.95112 & 0.923541 & 0.876087 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: PDR versus vehicular nodes in Area (1500 \(\times\) 1500). Figure 6: Comparison of results of the proposed system and existing systems ([PERSON] et al. [24] and CBLTR [21]) on PDR versus vehicular nodes in area 1000 \(\times\) 1000. Figure 7: Comparison of results of the proposed system and existing systems ([PERSON] et al. [24] and CBLTR [21]) on PDR versus vehicular nodes in area 1200 \(\times\) 1200. Average E2E delay is the average duration taken by a data packet to communicate between the source and destination. Tables 7 and 8 show the delay comparison with varying vehicle nodes for the proposed [PERSON] et al. (2014) and CBLTR (2011) protocols in network areas 1000 \(\times\) 1000 and 1500 \(\times\) 1500, respectively. In VANETs, the probability of connection and data packet delay also increases with an increase in the node's distance. However, constant paths have been chosen for the proposed protocol, and very few connections break during data broadcasting; this results in E2E delay reduction. Figures 9 and 10 show the improvement in delay with varying vehicular node density in the network areas 1000 \(\times\) 1000 and 1500 \(\times\) 1500, respectively. It is noted that when vehicular node traffic increases, E2E delay also rises. In CBLTR (2011), the E2E delay is maximum. The primary cause for maximum delay in the CBLTR (2011) is that it considers a \begin{table}
\begin{tabular}{c c c c} \hline \hline \multirow{2}{*}{**Total Number of Vehicles**} & \multicolumn{3}{c}{**Delay**} \\ \cline{2-4}  & **Proposed** & **[PERSON] et al. (2014)** & **CBLTR (2011)** \\ \hline
50 & 55.74125 & 61.7025 & 68.9633 \\ \hline
60 & 53.65745 & 61.62673 & 66.95025 \\ \hline
70 & 52.68301 & 59.20148 & 64.20894 \\ \hline
80 & 50.44252 & 57.73666 & 63.06623 \\ \hline
90 & 50.27617 & 53.77705 & 61.147 \\ \hline
100 & 48.32444 & 50.89118 & 58.76468 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Delay versus vehicular nodes in area (1000 \(\times\) 1000). Figure 8: Comparison of results of the proposed system and existing systems ([PERSON] et al. (2014) and CBLTR (2011)) on PDR versus vehicular nodes in 1500 \(\times\) 1500.  
single parameter for neighboring nodes, which will always be its nearest neighbor. The proposed protocol addressed this issue by utilizing k-means and considering various parameters for route selection. As revealed in Figure 9, the average E2E delay of diverse densities of vehicles reduced at a static rate.