## 3 Results and Discussion
### Average Delay Comparison
Although IOLSR maintains routes proactively, the reduced complexity in highway environments might alleviate some of the burdens typically associated with proactive routing, allowing it to maintain reasonably high PDR. Comparative Analysis: In comparing all the protocols across different scenarios, CM-QOS-AODV and CM-GPSR consistently outperformed IOLSR across all scenarios. This result highlights the superior adaptability of reactive and geographical routing protocols in diverse environ  
ments. CM-QOS-AODV variants (both TOM and DEM) demonstrate strong performance in handling dynamic network conditions, especially in highways, where reactive protocols excel in managing frequent route changes without the overhead of maintaining continuous route tables. Similarly, CM-GPSR's reliance on location-based information allows it to maintain highly efficient routing in both city and highway environments, making it one of the top-performing protocols in terms of PDR. Interestingly, IOLSR does outperform CM-GPSR in terms of PDR, which suggests that IOLSR can still be a competitive choice under certain conditions. The proactive nature of IOLSR gives it an advantage in situations where maintaining continuous routes is beneficial, particularly in environments with less mobility and fewer topological changes. However, as the environment becomes more dynamic (as in high-mobility scenarios), IOLSR's performance drops compared to the reactive and geographical protocols. The analysis of Figure 9 reveals clear distinctions between the routing protocols in terms of their PDR in both city and highway environments. CM-QOS-AODV, CM-QOS-AODV, and CM-GPSR consistently show superior performance, especially in dynamic environments like highways, where their adaptability allows them to handle frequent route changes effectively. IOLSR, while maintaining a reasonable PDR, struggles in high-mobility scenarios due to its proactive nature, though it still performs well in more stable environments. The overall conclusion from these observations is that reactive and geographically optimized protocols are better suited for networks with high mobility, while proactive protocols like IOLSR may still hold an advantage in environments where network topology remains relatively constant. Figure 10 offers a detailed comparison of the average delays observed for the CM-QOS-AODV, CM-GPSR, and IOLSR protocols across different scenarios, such as traffic generation, packet sizes, pause times, and mobility. Delay is a crucial performance metric in networking, referring to the time taken for a packet to travel from the source to the destination. Lower delays are generally preferred, as they indicate faster communication within the network. The IOLSR protocol consistently achieves the lowest delay across all scenarios, a result that can be attributed to its proactive routing behavior. In IOLSR, routes are continuously maintained and updated, ensuring that there is no need to search for a new route when packets are ready for transmission. This allows for immediate packet forwarding, reducing delay. The proactive nature of IOLSR is especially effective in environments with low mobility, where the network topology remains relatively stable. This protocol's ability to maintain pre-established routes allows it to quickly adapt to network conditions, thereby minimizing latency even in high-traffic situations up to 95% in the worst-case scenario. The highest observed average delay for IOLSR is 0.06 s, which was observed in the mobility comparison scenario. This relatively low delay, even in high-mobility situations, underscores the protocol's robustness. However, the slight increase in delay in mobility scenarios indicates that even proactive routing protocols are affected by frequent topology changes, although less so than reactive protocols. CM-QOS-AODV performance among the CM profiles: CM-QOS-AODV demonstrates superior performance in reducing delays in high-mobility scenarios.