## 3 Results and Discussion
### Packet Delivery Ratio Comparison  
The results presented in Figure 6 offer a detailed comparison of the packet delivery ratio (PDR) achieved by QOS-AODV, GPSR, CM-QOS-AODV, and CM-GPSR under varying traffic generation rates. As shown in Figure 6a, both QOS-AODV and GPSR, when configured with the TOM (Throughput Optimized Method) profile, maintain high average PDR values around 89%, indicating strong reliability in packet delivery. In contrast, their baseline counterparts--QOS-AODV and GPSR without any optimization--consistently perform below 83%, showing weaker resilience under dynamic traffic conditions [15]. A key observation from these results is that both TOM and DEM (the Delay and PDR Enhanced Method) profiles significantly enhance PDR compared to their unoptimized versions, achieving approximately a 10% average improvement. Notably, the TOM profile exhibits outstanding robustness against increasing traffic, maintaining a relatively stable PDR across all traffic generation rates [16]. This stability suggests that TOM effectively tunes routing parameters to prioritize reliable data transmission, making it particularly suitable for dynamic Vehicular Communication Networks (VCNs) where traffic loads fluctuate frequently. In contrast, Figure 6b reveals that while the DEM profile also improves upon  
Figure 5: (**a**) Throughput comparison between (**a**) QOS-AODV, QOS-AODV-TOM, and QOS-AODV-DEM and (**b**) GPSR, GPSR-TOM, and GPSR-DEM for different traffic generations. the baseline, it shows greater sensitivity to increasing traffic loads. For instance, GPSR with the DEM profile experiences a noticeable decline in PDR as traffic generation intensifies. This degradation highlights a core trade-off within DEM's design: by attempting to balance multiple performance metrics (PDR, throughput, and delay), DEM sacrifices some degree of consistency in any single metric, particularly under stress conditions such as high traffic volumes. Further analysis suggests that TOM's single-objective optimization--specifically targeting PDR--results in more consistent and reliable packet delivery, particularly in high-traffic environments where communication reliability is critical [17]. In contrast, DEM's multi-objective approach, while beneficial in achieving broader performance improvements, results in a less focused optimization for PDR alone. Consequently, although DEM outperforms the baseline protocols, it falls short of the PDR levels achieved by TOM. This comparison between TOM and DEM underscores the strategic value of targeted optimization in vehicular network routing. TOM's consistent performance under varying conditions highlights its robustness and suitability for delay-sensitive, high-reliability applications. Meanwhile, DEM's performance variability reinforces the importance of carefully aligning optimization strategies with specific application requirements and network dynamics in VCNs [17]. TOM's strong emphasis on PDR makes it particularly well-suited for applications where reliable packet delivery is critical, such as safety-critical systems or real-time data transmissions in Vehicular Communication Networks (VCNs). In contrast, DEM's trade-offs are more appropriate for scenarios that require a balanced performance across multiple metrics, including throughput and latency, rather than prioritizing packet delivery alone. The results suggest that TOM is the preferred choice for high-throughput, delay-sensitive applications where maintaining high PDR is non-negotiable [18]. Conversely, DEM may be better suited for networks with more flexible PDR requirements but a stronger need to balance overall network efficiency and delay constraints. In conclusion, the findings from Figure 6 clearly illustrate the superior performance of the TOM profile in optimizing PDR for both QOS-AODV and GPSR protocols. TOM consistently outperforms DEM and the baseline configurations, maintaining stable and high PDR even under fluctuating traffic conditions.