## 4 Performance Evaluation
### Performance Results in the Real Scenario  
In this section, we compare performance results of five schemes, which have to handle subsequent UAV handover processes and UAV dispatch exceptions, in the real scenario, where all events last for the fixed event duration (\(T_{ev}\)) and the starting time of each event is randomly chosen during the simulation time. Figure 11 shows how different UAV dispatch energy thresholds result in different average ratios of the event link communication time for five schemes. As the UAV dispatch energy threshold rises, the probability for UAVs in the GCS to become available to be dispatched is getting lower such that ratios of the event link communication time for USP and EAMUD-D decrease slowly. The reason for EAMUD-D to outperform USP is because whenever UAVs in the GCS are not available to be dispatched to the current sub-event, USP only drops this sub-event without dropping all other sibling ones as EAMUD-D does. Oppositely, ratios of the event link communication time of other schemes increase as the UAV dispatch energy threshold grows. As soon as EAUD-D cannot reserve a handover UAV in the GCS for a sub-event, it will drop this sub-event and all sibling ones but EAUD-P will postpone this sub-event and every sibling one with its processing time earlier than \(t_{i}+t_{delay}\) to \(t_{i}+t_{delay}\). By observing Figure 12a,b, which illustrates histograms of the average ratio of the event link communication time with respect to UAV dispatch energy threshold, EAUD-D has two peaks on the 0-0.05 and 0.85-1.0 ranges but more events with EAUD-P span on the larger 0.05-0.40 range. Figure 11: The average ratio of the event link communication time vs the UAV dispatch energy threshold. Figure 10: The average ratio of the event link communication time vs the event percentage in the ideal scenario. Hence, EAUD-D achieves higher average ratios of the event link communication time than EAUD-P does, which is shown in Figure 11.  
When the UAV dispatch energy threshold is smaller than 75%, EAMUD-P suffers the lower ratio of the event link communication time than EAMUD-D. The reason of this behavior is because EAMUD-P postpones the sub-event, which cannot reserve a handover UAV, and every sibling sub-event with its processing time earlier than \(t_{i}+t_{delay}\) to \(t_{i}+t_{delay}\). Though EAMUD-P gives this sub-event a second chance to reserve a UAV, this postpone method has a higher probability of reserving the UAV, whose battery energy may just exceed the UAV dispatch energy threshold. Hence, this kind of UAV will drain out its battery energy soon after being dispatched such that the number of UAV handover grows, which results in the lower ratio of the event link communication time for EAMUD-P in this case. Oppositely, as the UAV dispatch energy threshold grows larger than 75%, the dispatched UAV owns higher battery energy to extend its communication duration. Further, as shown in Figure 12, EAMUD-D and EAMUD-P have similar behaviors as EAUD-D and EAUD-P on their histograms of the ratio of the event link communication time. As compared to EAMUD-D, EAMUD-P is able to distribute UAV resources to most events for raising the ratio of the event link communication time, especially for the larger UAV dispatch energy threshold when \(E^{DTH}\) = 87.5% in Figure 12b. Consequently, EAMUD-P achieves the highest average ratio of the event link communication time among these five schemes. Figure 13 shows the relation between the number of UAV and the average ratio of the event link communication time for five schemes. As the number of UAV raises, the probability that the GCS can dispatch UAVs to serve all sub-events of the same parent event becomes higher, which increases average ratio of the event link communication time accordingly for all schemes until the number of UAVs is high enough, i.e., larger than 240, to satisfy all UAV requirements in the event queue.