## 5 Performance Evaluation and Discussion
### Experiment Results and Discussion
#### 5.2.2 System Performance  
As a means of demonstrating and validating the model, simulations were conducted under four different scenarios, which are as follows:  
* Local Policy (LP): In this policy, there is no offloading. The application's tasks are carried out locally on the device resources. Figure 5: Convergence of performance over different number of DNNs. Figure 6: Convergence of performance over different number of batch sizes. Full Offloading Policy (FOP): This policy involves offloading the application's tasks to GBSs for remote processing. * Proposed Model Policy: In this policy, according to our proposed model, the application's tasks will be processed according to the offloading decision, which will minimize the total overhead of the system in the end. * Task Offloading Policy (TOP [47]): This policy is set up to handle the application's tasks for mobile users based on the model proposed in [47] whereby each mobile user should send their application's tasks to the connected GBSs in the event that it does not take the selection of GBSs into consideration. First, Figure 7 depicts a comparison of total cost for various numbers of mobile users under the four different policies. According to the graph, the proposed model has the lowest system cost when compared to the other policies. With a small number of users, the total cost of TOP and FOP policies approaches that of the proposed model. However, there is an increasing gap among them as the number of users increases. Furthermore, when the number of users exceeds 60, the cost of the FOP policy exceeds the cost of the LP policy. The reason for this could be that the GBSs lack the computation capabilities to handle more users connected to them at the same time due to shared channels, which is one of the reasons for redistributing users among GBSs and using UAVs as assisting nodes, which significantly impacts the system's performance. Second, a comparison of total cost for different numbers of GBSs under the four different policies is illustrated in Figure 8. In light of this figure, it can be observed that LP is unaffected by the GBSs' number, whereas the other policies' costs are steadily decreasing. The LP policy does not utilize GBSs resources, whereas mobile users are allocated with more resources, resulting in a shorter processing time and thereby system cost. Furthermore, selecting the right GBSs and UAVs to perform transmission and processing tasks also has a significant impact on the system performance. Figure 7: A comparison of total cost for different numbers of mobile users (M = 5, N = 3). Furthermore, Figure 9 illustrates the comparison of the successful task processing ratio under different numbers of users, where this ratio denotes the proportion of successfully completed tasks relative to the total number of tasks. It is observed from the figure that the ratio is 100% for a small number of users (i.e., less than 20) for the three policies. However, it steadily degrades as the number of users increases and reaches 85% and 71% for TOP and FOP policies, whereas it slightly decreases for our proposed model and reaches 98% for 100 users. This variation can be explained by the fact that for TOP and FOP policies, as the number of users increases, the available resources at GBSs become competitive among users, whereas our model can balance the load among servers and UAVs can be used to efficiently utilize the computation resources of edge servers. Finally, Figure 10 shows how the total cost of the four strategies was calculated for five different types of applications (shown in Table 3). The figure shows that the total cost  
Figure 8: A comparison of total cost for different numbers of GBSs (K = 5, N = 3). Figure 9: A comparison of successful task processing ratio under different numbers of users (K = 5, N = 3). of the applications in categories A, B, and C for the FOP policy is higher than those in the other scenarios, whereas those in the LP policy for the other applications (D and E) are higher than those in the other policies.