## 5 Results and Analysis
### The Effect of Allowed Space  
The effect of the allowed space in the simulation is carried out by varying the simulation area. The number of UAVs is set at 50, while the allowed spaces are varied to 1 \(\times\) 2, 1.5 \(\times\) 3, 2 \(\times\) 4, 2.5 \(\times\) 5, and 3 \(\times\) 6 km \(\times\) km to investigate the behaviors of the four different routing protocols in small and large areas. The results (Figure 14) show that as the space of the mission (allowed space) increases, PDR increases for all routing protocols. This happens because, as the distance between UAVs increases, the number of transmitted packets decreases and the number of dropped packets also decreases. The simulation results (shown in Figure 14) also indicate that ML-OLSR achieves the highest throughput throughput compared to other protocols.  
Figure 12: Energy consumption vs. number of UAVs.  
Figure 13: Throughput vs. number of UAVs.  
PDR as compared to other protocols in various areas. This happens because ML-OLSR selects the stable and reachable MPR UAV to deliver packets to the UAV's destination. On the other hand, standard OLSR provides poor performance in terms of PDR due to increases in packet loss. P-OLSR provides slightly better PDR performance than D-OLSR, especially in areas of 2.5 \(\times\) 5 and 3 \(\times\) 6 km \(\times\) km.  
Figure 15 displays the latency performance of the four routing protocols. The latency metrics increase when the allowed space increases. This is due to the fact that as the allowed area expands, the flying UAV's relative distance increases, increasing the propagation delay and length of time needed to deliver the data packets. According to the results, the ML-OLSR protocol provides a lower latency compared to other protocols over a large area, specifically after 2 \(\times\) 4 km \(\times\) km, due to the lower traffic. The OLSR protocol shows poor performance and generates the highest latency in the area of 3 \(\times\) 6 km \(\times\) km. The P-OLSR protocol provides lower latency than the standard OLSR protocol and higher latency than the ML-OLSR protocol. This is due to the poor prediction of wireless link quality used to select the path to the destination, leading to a decrease in route discovery.  
Figure 14: PDR vs. allowed space.  
Figure 15: Latency vs. allowed space.  
Energy efficiency should be considered when designing a routing protocol for UAVs. The comparison of energy consumed by the OLSR, D-OLSR, ML-OLSR, and P-OLSR is depicted in Figure 16. Results indicate that as the allowed space for UAVs increases, the energy consumption for the four routing protocols decreases. This is because the number of transmitted data packets decreases, as shown in Table 4. Further, it was noted that ML-OLSR achieves the lowest energy consumption compared to other protocols for various allowed areas. D-OLSR provides better energy efficiency than the OLSR protocol as it reduces the number of overhead packets by selecting a minimum MPR.  
Figure 17 illustrates a comparison of the throughput of the four routing protocols. If the allowable space for UAVs increases, the throughput value drops because the distance between UAVs increases and some UAVs fall out of transmission range, resulting in fewer packets received. Results indicate that ML-OLSR obtains the highest performance compared to other protocols in a low-congestion UAV environment, increasing the number of data packets received. The OLSR protocol, on the other hand, has poor throughput performance due to its high packet loss. In all allowed locations, the P-OLSR and D-OLSR protocols achieve better throughput than OLSR.