## 3 Results and Discussion
### Average Delay Comparison
In contrast, CM-QOS-AODV exhibits strong performance in dynamic, high-mobility scenarios, benefiting from its reactive routing design that adapts effectively to frequent topology changes. CM-GPSR shows mixed results--while it handles mobility well due to its geographic routing approach, it struggles with variations in packet size and pause times. Notably, CM-QOS-AODV maintains consistent delay performance across all tested scenarios, indicating its robustness and adaptability to diverse traffic patterns and mobility levels. Overall, protocol selection should align with the specific network context: IOLSR for stable, low-mobility networks; CM-QOS-AODV for highly dynamic environments; and CM-GPSR for cases where geographic awareness enhances routing efficiency. The PDR comparison presented in Tables 7 and 8 demonstrate that the TOM-optimized profiles (QOS-AODV-TOM and GPSR-TOM) consistently achieved the highest packet delivery ratios, maintaining values around 89% across varying traffic generation rates. This stability underscores TOM's effectiveness in adapting to changing network conditions without compromising delivery reliability. In contrast, the baseline QOS-AODV and GPSR protocols show a noticeable decline in PDR, dropping below 83% as traffic intensity increases. While the DEM profiles offer a clear improvement over their respective baselines, they still fall short of the high reliability achieved by TOM. This is primarily due to DEM's multi-metric focus, which balances throughput, delay, and PDR, leading to only modest gains in delivery performance. These findings are consistent with recent studies, such as Ref. [22], which emphasize the benefits of targeted optimization strategies in improving PDR under dynamic VANET conditions, where protocols optimized for PDR, such as TOM, show superior performance in dynamic environments like VCNs. Based on the current results, with packet loss conditions, TOM's optimization focus on throughput helps maintain a steady flow of data even as traffic increases, thereby minimizing packet loss and reducing network congestion. The ability of TOM profiles to maintain high PDR even with fluctuating traffic generation makes it a favorable choice for environments with high variability in node mobility and data flow. Furthermore, the DEM profiles' slightly reduced PDR due to balancing with other metric findings in research on robust parameter optimization protocols, as seen in Ref. [28]. \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Traffic Generation (Interval)** & **QOS- AODV** & **QOS- AODV- TOM** & **QOS- AODV- DEM** & **GPSR** & **GPSR- TOM** & **GPSR- DEM** \\ \hline
0.11 s & 0.38 & 0.45 & 0.43 & 0.30 & 0.47 & 0.33 \\ \hline
0.21 s & 0.36 & 0.43 & 0.41 & 0.28 & 0.44 & 0.31 \\ \hline
0.31 s & 0.34 & 0.40 & 0.39 & 0.25 & 0.42 & 0.29 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Throughput comparison (Mbps). Figure 10: Comparison of average throughputs across varying traffic delay and packet sizes. (**a**) Delay with traffic generation; (**b**) delay with packet size. \begin{table}
\begin{tabular}{p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt} p{56.9 pt}} \hline \hline
**Traffic Generation (Interval)** & **QOS- AODV** & **QOS- AODV- TOM** & **QOS- AODV- DEM** & **GPSR** & **GPSR- TOM** & **GPSR- DEM** \\ \hline
0.11 s & 80 & 89 & 87 & 79 & 89 & 85 \\ \hline
0.21 s & 79 & 88 & 85 & 78 & 88 & 84 \\ \hline
0.31 s & 78 & 87 & 84 & 77 & 87 & 83 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: PDR comparison (%). In Table 9, the average delay results indicate that GPSR-TOM achieves the lowest delay across all traffic generations, with an average of 0.01 s. QOS-AODV-TOM follows closely, maintaining delays below 0.025 s. The consistently low delay achieved by TOM profiles highlights their efficiency in reducing packet transmission time, making them highly suitable for delay-sensitive applications.