# A Robust Routing Protocol in Cognitive Unmanned Aerial Vehicular Networks
## 6 Simulation Results
### Performance Comparison
By effectively handling changes in spectrum availability and maintaining stable communication links, the proposed protocol minimizes disruptions in data transmission, thereby maximizing throughput. This capability is particularly beneficial in high traffic density scenarios, where maintaining consistent and reliable data flow is crucial for network performance. According to Figure 11 comparing OLSR+GPSR [21] with the Proposed protocol, overhead increases as the number of nodes in the network grows. This is due to more nodes participating in data transmission, leading to more control messages and routing information exchanges. The Proposed protocol consistently shows lower overhead than OLSR+GPSR across all node densities. This improvement is likely due to more efficient routing algorithms, reduced control message exchanges, and advanced metrics for route selection. By effectively managing overhead, the Proposed protocol enhances network performance, particularly in dense environments, making it more scalable and responsive compared to OLSR+GPSR. According to Figure 12 comparing OLSR+GPSR [21] with the Proposed protocol, throughput decreases as the number of nodes in the network increases. This trend is evident in both protocols, but the Proposed protocol consistently achieves higher throughput than OLSR+GPSR. The Proposed protocol maintains higher throughput due to its efficient routing strategies and better handling of network traffic. Unlike OLSR+GPSR, which may suffer from increased packet collisions and retransmissions as the network grows, the Proposed protocol likely integrates advanced metrics for route selection, optimizing for factors such as link stability and queuing delays. This ensures that data packets are transmitted more reliably and efficiently, even in denser networks. By effectively managing network congestion and optimizing route selection, the Proposed protocol enhances overall network performance. This results in a more scalable and robust network, capable of maintaining higher throughput compared to OLSR+GPSR, particularly as the number of nodes increases. Figure 11: OLSR+GPSR vs. Proposed protocol Overhead. According to Figure 13 comparing OLSR+GPSR [21] with the Proposed protocol, the packet delivery ratio remains relatively stable across different numbers of nodes. Both protocols maintain high delivery ratios, but the Proposed protocol consistently achieves slightly better performance. The stability and higher performance of the Proposed protocol can be attributed to its effective routing strategies and robust handling of network traffic. Unlike OLSR+GPSR, which may experience occasional drops in packet delivery due to network congestion and packet collisions, the Proposed protocol likely uses advanced metrics for route selection. These metrics ensure reliable and efficient data transmission, resulting in a consistently high packet delivery ratio. By optimizing route selection and effectively managing network resources, the Proposed protocol ensures a high and stable packet delivery ratio even as the network grows denser. This highlights its robustness and reliability, making it a more effective solution compared to OLSR+GPSR in maintaining efficient data transmission across varying network conditions. According to Figure 14 comparing OLSR+GPSR [21] with the Proposed protocol, the end-to-end delay varies across different numbers of nodes. Both protocols manage network traffic, but the Proposed protocol consistently achieves significantly lower end-to-end delays. Figure 12: OLSR+GPSR vs. Proposed protocol Throughput. Figure 13: OLSR+GPSR vs. Proposed protocol Packet Delivery Ratio. The superior performance of the Proposed protocol can be attributed to its effective routing strategies and robust handling of network traffic. Unlike OLSR+GPSR, which shows a steady increase in end-to-end delay as the number of nodes increases, the Proposed protocol demonstrates a more controlled delay pattern.