## 3 Results and Discussions
### Beacon/Hello Interval
Figure 7 presents the delay behavior of AODV and GPSR in both city and highway environments, analyzed against varying Hello/Beacon Intervals. For AODV, the observed delay consistently decreases as the Hello interval increases in both scenarios, indicating that less frequent Hello packet broadcasting leads to improved delay performance. On the other hand, GPSR demonstrates an opposite trend, with lower delay observed for higher Hello/Beacon packet frequency in both city and highway environments. The reduction in delay for AODV with increasing Hello intervals can be explained by the reduction in protocol overhead. AODV relies on the frequent broadcasting of Hello packets to maintain accurate routing tables, and this broadcast contributes to network congestion, especially in dense environments. When Hello packets are sent too frequently, they consume additional bandwidth, increasing the likelihood of collisions and the need for retransmissions, which leads to higher overall delay. Since delay is measured only for successfully received packets, an increase in collisions due to frequent Hello broadcasting elevates the waiting time for successful transmission. In city environments, where node density is higher, frequent Hello packet transmissions lead to increased network traffic, exacerbating collisions. As a result, reducing the frequency of Hello packets alleviates congestion, thus decreasing the observed delay. Similarly, in highway scenarios, though node density is lower than in cities, the higher mobility requires rapid adaptation to topology changes, but excessive Hello packet broadcasting still induces unnecessary traffic, contributing to delays. In contrast, GPSR's delay performance is improved with a higher frequency of Beacon packets in both city and highway settings. GPSR's operation relies heavily on its knowledge of neighboring nodes, obtained through Beacon messages. When Beacon intervals are short, the protocol maintains fresher information about the positions of its neighbors, allowing for quicker and more efficient route selection. In this case, more frequent updates mean the network is better equipped to respond to changes in topology, leading to faster transmission of packets and reduced delays. This behavior is particularly beneficial in the city, where node density is high and dynamic, and frequent position updates are crucial for GPSR's greedy forwarding strategy. In highway environments, where node mobility is high, having frequent Beacon updates allows GPSR to make more accurate decisions in real time, ensuring that packets can be forwarded efficiently to their next hop, thereby reducing delay. For AODV, increasing the Hello interval works by minimizing network overhead, resulting in fewer collisions and less traffic congestion, thereby improving the delay. Conversely, GPSR benefits from more frequent Beacon messages because its stateless routing mechanism requires constant updates on neighbor positions to maintain low delays. In both city and highway environments, GPSR relies on real-time information to reduce delays, whereas AODV's delay is mitigated by reducing protocol-induced traffic. In conclusion, Figure 7  
Figure 6: Throughput comparison between VANET scenarios and Beacon/Hello intervals. demonstrates that while AODV benefits from reducing Hello packet frequency to lower delay, GPSR's delay is improved by increasing the frequency of Beacon packets. This highlights the different operational requirements of the two protocols. AODV, which relies on route discovery and table maintenance, performs better with lower overhead, while GPSR, which depends on accurate and timely neighbor information, requires frequent updates to optimize delay performance in both city and highway environments. Figure 8 presents the Packet Delivery Ratio (PDR) trends of AODV and GPSR in city and highway environments for varying Hello/Beacon intervals. The results show that GPSR's PDR in both environments decreases as the Beacon interval increases.