# Optimizing Time-Sensitive Traffic Scheduling in Low-Earth-Orbit Satellite Networks
## 4 Simulation Analysis
### Performance Results Analysis
While CQF can also reduce packet loss ratios, its performance for TSF packet loss is the worst under low load conditions due to its strict gating mechanism and limited queue forwarding capability for time-sensitive flows. Additionally, we investigated packet loss performance under varying ISL buffer sizes. The core advantage of TPC-CQF lies in its differentiated forwarding and flexible scheduling. The traditional CQF's dual-queue mechanism is prone to packet loss due to buffer overflow under high load or bursty traffic, whereas TPC-CQF's three-queue design effectively mitigates this issue. The packet loss ratio for TSFs is below 0.001, representing a reduction of over 95% compared to CQF. The improvement in packet loss for total traffic  
Figure 7: Packet loss ratio. is attributed to enhanced resource utilization. Although the introduction of the Q8 queue may slightly increase queuing delay for regular flows, the overall packet loss ratio remains comparable to that of CQF. The average delay reflects the time from packet transmission to reception (excluding propagation delay). We calculated the average delay for both TSFs and total traffic across different mechanisms. Figure 8 shows that TPC-CQF's TSFs delay is lower than that of ES but slightly higher than CQF under high load, while the delay for total traffic may be slightly higher. The delay performance of TPC-CQF is directly related to its algorithmic design. Traditional CQF maintains lower TSFs delay through strict gating and dual-queue switching but sacrifices packet loss performance. In contrast, TPC-CQF achieves a lower packet loss ratio and forwards more traffic under the same load, resulting in a slightly higher average delay compared to CQF. TPC-CQF optimizes the packet loss rate by utilizing the Q8 backup queue, at the cost of delaying some packets by one time slot T (e.g., from slot 1 to slot 2). This results in TSF average delay being slightly higher than CQF under high load but still significantly lower than ES. The slightly higher delay for total traffic is due to the additional queue for handling TSFs, which increases the queuing time for regular traffic, thereby impacting the overall average delay. Throughput is a measure of the network's transmission capacity, and we calculated it separately for TSFs and non-TSFs (regular traffic). Figure 9 shows that TPC-CQF's TSF throughput significantly increases with load, and its overall throughput surpasses that of CQF. The throughput improvement of TPC-CQF stems from its differentiated forwarding mechanism and flexible scheduling strategy. Traditional CQF is limited by packet loss under high load, which restricts TSF throughput. In contrast, TPC-CQF leverages the Q8 backup storage and dynamic priority scheduling to fully utilize network resources. The results demonstrate that TPC-CQF effectively enhances the scheduling capability for TSFs in large-scale satellite networks while maintaining high overall network performance. Additionally, we evaluated the scalability of TPC-CQF across different constellation scales. Table 3 data shows that when satellite nodes increase from 64 to 225, the TSF packet loss rate rises from 0.02% to 0.36%, average latency increases by only 3.4%, and the timeout rate escalates from 7.0% to 13.6%. Although performance metrics exhibit  
Figure 8: Average delay. slight fluctuations with scale expansion, the packet loss rate consistently remains below 0.4%, demonstrating the sustained effectiveness and stability of its queuing management mechanism in large-scale networks. The results demonstrate that the TPC-CQF method delivers significant improvements in timeout ratio and packet loss ratio performance, addressing core limitations of conventional CQF in satellite time-sensitive networks (high packet loss, limited forwarding capacity).