# Time-Sensitive Networking Mechanism Aided by Multilevel Cyclic Queues in LEO Satellite Networks
## 5 Performance Evaluation
### Result Analysis  
In order to observe the time-sensitive forwarding capability of different mechanisms, we calculated the service time-out ratio for different techniques. A service time-out occurs when the packet does not reach the destination node before the deadline. Figure 5a shows that TSN-MCQ could significantly reduce the time-out ratio. Moreover, as the load increased, the time-out ratio of time-sensitive traffic decreased. On the one hand, it benefited from the collaboration of multiple cyclic queues; on the other hand, removing the gating mechanism could improve the forwarding capacity of time-sensitive traffic. The figure shows that TSN-MCQ could reduce the time-out ratio by 14.5% compared to CQF in high-load cases.  
Figure 5b shows the different mechanisms' packet loss ratio performance. TSN-MCQ maintained the lowest packet loss ratio with different loads. For TSFs, the packet loss ratio of TSN-MCQ was below 0.001, which was more than 90% lower than those of the Ethernet switch and CQF. Moreover, its performance remained relatively stable under different ISL buffer sizes. CQF could also reduce the packet loss ratio. However, its packet loss ratio performance was the worst under low-load cases due to the strict gating mechanism and limited time-sensitive forwarding capability.  
We calculated the average latency performance of different mechanisms, including total and time-sensitive traffic, as shown in Figure 6. The latency in the figure does not include the propagation delay, because the propagation delay was large in the satellite network. Both CQF and TSN-MCQ could reduce the latency of time-sensitive traffic. However, CQF maintained the lowest average latency. Since TSN-MCQ had a lower packet loss ratio and forwarded more traffic at the same load case, its average latency was slightly higher than that of CQF.  
network could be increased by using multiple cyclic queues in a LEO satellite network. The proposed mechanism could also guarantee that more than 99.9% of the time-sensitive flows were successfully scheduled, preventing the network throughput degradation caused by packet loss.  
The results presented above show that the TSN-MCQ approach offered significant improvements in the time-out ratio and packet loss ratio performance of the network. However, the proposed algorithm demonstrated only a slight improvement in the average delay of the service. This marginal enhancement could be attributed to the relatively small proportion of queuing delay in the system, which was primarily caused by the large delay of the ISLs and the constrained queuing resources. The network size of the simulations used in this study was relatively small. If the number of satellites in the network increased to tens of thousands, the average hop count of the service significantly rose, leading to an increase in queuing delay. Furthermore, the method proposed in this paper requires additional queueing resources to support the distribution of multilevel services, which is a notable drawback of this approach. To address these limitations, future research will focus on optimizing the relationship between the number of queues and the overall network performance. Additionally, further investigation is required to determine the scalability of the TSN-MCQ approach for larger networks, including those with tens of thousands of satellites.