# Federated Learning-Based Service Caching in Multi-Access Edge Computing System
## 5 Experiment and Evaluation
### Performance Evaluation  
#### 5.4.1 Comparison of Service Hit Ratio  
Figure 6 illustrates the service hit ratio of the service caching approaches inside a system with a computational capacity of 12-72 GHz on individual MEC servers. The system has 64 MEC servers and serves 300 mobile users. The efficacy of these approaches improves with an increase in resource capacity. This is because increased computational power directly relates to the capacity to fulfill client requests. Nevertheless, a significant performance gap exists between deep learning-based approaches and other methods. Specifically, with the 12 GHz MEC server, the service hit ratios for SCFL and FLAE are 0.26 and 0.2, respectively. In contrast, the corresponding ratios for LFU, LRU, and RC are 0.13, 0.1, and 0.04. When the computational resource reaches 72 GHz, SCFL has a service hit ratio of approximately 0.6, whereas LFU, LRU, and RC exhibit ratios below 0.3. Moreover, it is consistently shown that SCFL demonstrates superior performance compared to FLAE across all experimental settings. The results indicate that AAE can extract information about request data distribution more than the conventional AE model. Experiments are conducted to evaluate the model's performance with different numbers of users in the system. The MEC system has 64 MEC servers, each with a computational capacity of 36 GHz, while the number of users varies from 50 to 250. The experimental results are presented in Figure 7. When the system has only 50 users, SCFL and FLAE reach service hit ratios of 0.28 and 0.2, respectively, whereas LRU and RC are both equal to 0.08. It is evident that as the number of users consuming the system's service increases. This also raises the service hit ratio. When the number of users reaches 200, the service hit ratio of SCFL is 0.42, while those of FLAE and LFU are 0.23 and 0.15, respectively. This demonstrates that the proposed strategy chooses service caches that are suitable for fulfilling the user's requirements. This occurs because of the direct correlation between the number of users and the amount of data requested from the MEC servers. Enhancing the data enables the AAE model to more effectively capture distributions. When the user count in the system rises from 150 to 200, the service hit ratio of SCFL experiences an increase from 0.37 to 0.42. Nevertheless, despite this significant improvement, the service hit ratio of systems using SCFL only experiences a little rise from 0.42 to 0.43 when the user count increases from 200 to 250. This indicates that when the system has 200 users, the amount of user request data is sufficient for SCFL to achieve maximal efficiency. The saturation minimizes the impact of additional data on system performance. Figure 8 shows the service hit ratio when the system contains different numbers of MEC servers. Specifically, the number of users and computing resources of each MEC server are 300 and 36 GHz. The number of MEC servers used in the investigations varied from 16 to 64. Notably, the size and coordination of the simulation area remained unchanged. By increasing the quantity of MEC servers, the coverage area of each server is reduced. Consequently, when the number of MEC servers in a system increases, the number of users served by each MEC server decreases. As shown in Figure 8, SCFL consistently demonstrates higher performance in all experimental settings, outperforming other techniques. When there are only 16 MEC servers in the system, the service hit ratios for SCFL and FLAE are 0.5 and 0.4, respectively. The values for RC, LRU, and LFU are 0.13, 0.18, and 0.24, respectively. As stated above, increasing the quantity of MEC servers decreases the number of users using the services provided by each MEC. As a consequence, the quantity of data that each MEC server can gather to utilize in the model is constrained, which lowers model performance. SCFL and FLAE achieve service hit ratios of 0.42 and 0.37, respectively, when the system comprises 64 MEC servers.