## 5 Simulation Results and Discussions  
### Simulation Settings  
In our simulations, we employ ns-3 as the network simulator and MATLAB R2022b for plotting the results. Notably, the mobility scenarios are generated using BonnMotion [43], a tool developed by the University of Bonn, which produces node movement trace files for the UAV network based on various mobility models. The detailed simulation parameters [15,44] are summarized in Table 1.  
We adopt four performance metrics [22,38,44] to quantify the improvements in the proposed routing protocol, and--by holding all other factors constant--evaluate its behavior under varying node densities, mobility speeds, and CBR connections.  
* Packet Loss Ratio (PLR):The PLR is defined as the ratio of lost packets to the total packets sent by the source, reflecting packet losses due to routing failures, congestion, or channel errors: \[\text{PLR}=\frac{N_{\text{lost}}}{N_{\text{sent}}}.\] (36) A lower PLR indicates higher reliability and robustness in dynamic topologies and interference-prone environments.
* End-to-End Delay (E2 ED): E2 ED measures the total time a packet takes from transmission at the source to reception at the destination, capturing the timeliness of the protocol: \[\text{E2 ED}=\frac{1}{N_{\text{recv}}}\sum_{p=1}^{N_{\text{recv}}}\bigl{(}t_ {\text{recv},p}-t_{\text{send},p}\bigr{)},\] (37) where \(N_{\text{recv}}\) is the number of successfully received packets, and \(t_{\text{send},p}\), \(t_{\text{recv},p}\) are the send and receive timestamps of packet \(p\).  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Simulator & ns-3.31, MATLAB \\ Packet Size & 512 bytes \\ Simulation Time & 150 s \\ Simulation Area & \(2000\,\text{m}\times 2000\,\text{m}\times 300\,\text{m}\) \\ Speed Range & 10–30 m/s \\ Communication Range & 250 m \\ Bandwidth & 10 MHz \\ Number of Nodes & 30, 40, 50, 60, 70, 80, 90, 100 \\ Traffic Type & CBR \\ CBR Rate & 2 Mbps \\ Number of CBR Connections & 10, 20, 30, 40, 50 \\ HELLO interval & 1 s \\ Frequency of trajectory updates & 5 Hz \\ MAC Protocol & IEEE 802.11p \\ Transport Protocol & UDP \\ Initial Energy & 900–1000 J \\ Energy Threshold & 100 J \\ Propagation Model & Nakagami Model \\ Mobility Model & Gauss–Markov Mobility Model \\ \hline \hline \end{tabular}
\end{table}
Table 1: Simulation parameters.  
Routing Efficiency: To assess resource utilization in multi-hop scenarios, we define routing efficiency as the average ratio of successfully delivered packets per forwarding hop: \[\text{RoutingEfficiency}=\frac{1}{N}\sum\biggl{(}\frac{\text{totalRx}}{\text{ totalTx}\times\text{HopCount}}\biggr{)}.\] (38) This metric minimizes forwarding overhead while ensuring successful delivery. A higher value indicates better path optimization and resource efficiency.
* Throughput: Throughput quantifies the network's capacity to successfully deliver payload data per unit time, in bits per second (bps): \[\text{Throughput}=\frac{\text{totalRx}\times\text{PacketSize}\times 8}{\text{ simtime}}.\] (39) It directly reflects the protocol's data delivery capability and bandwidth utilization under given network conditions.  
In addition, this study examines node energy consumption and routing overhead to complement the performance evaluation. Energy consumption reflects the protocol's impact on forwarding-related power usage, while routing overhead quantifies control message load required for maintaining connectivity and route discovery under dynamic conditions.