## 4 Simulation Analysis
### Simulation Results Analysis
#### 4.4.2 Comparison Results Analysis  
This paper employs an Iridium-like satellite constellation architecture for comparative simulation experiments. Leveraging the relatively stable inter-satellite link configuration characteristic of Iridium systems, we primarily simulate link failures and node malfunctions through stochastic edge deletion and restoration in the graph representation. The simulation constrains the maximum number of simultaneous link failures during any single routing process to five, enabling a systematic analysis of routing algorithm performance under inter-satellite link disruption scenarios. Figure 6 illustrates the average delay performance of the MARL-JR, DR-BM, and Q-routing algorithms under varying traffic load conditions. The total latency is defined as the cumulative time required for all data packets to traverse from the source node to the destination node. By dividing the total latency by the number of transmitted data packets, the average latency can be obtained. As shown by the curves in the figure, under low traffic loads, DR-BM can rapidly acquire global information and select paths with shorter delays due to the small number of data packets. However, as the load of the network increases, the instability of both DR-BM and Q-routing becomes evident. The DR-BM algorithm, which relies on obtaining global information, suffers from inefficient packet forwarding decisions and increased queuing delays, leading to a rise in the overall average delay. Similarly, the  
Q-routing algorithm demonstrates limitations in handling highly dynamic networks under high traffic loads, resulting in suboptimal performance. Figure 7 illustrates the packet loss rates under varying traffic load conditions. In the case of the DR-BM algorithm, under high traffic loads, increased queuing delays during packet forwarding can lead to situations where the intended link is no longer available at the time of forwarding, resulting in packet loss. In contrast, the MARL-JR algorithm adopts a distributed approach, leveraging information from neighboring nodes to make forwarding decisions more efficiently. This enables MARL-JR to maintain a significantly lower packet loss rate, demonstrating superior robustness as compared to the Q-routing algorithm. Figure 8 demonstrates the load balancing performance of different algorithms under a traffic load of 3000 packets in the network. In this study, the load balancing condition is represented by the variance of the packet counts across nodes, where a lower variance indicates a more balanced network load, while a higher variance suggests an imbalanced  
Figure 6: Comparison of the average delay time. Figure 7: Comparison of loss rate. load, potentially leading to congestion. As illustrated in Figure 8, when the network contains 3000 data packets, MARL-JR achieves a more balanced load distribution across satellite nodes, thereby reducing the likelihood of congestion. Figure 9 presents a comparison of the packet delivery rates between MARL-JR and the distributed Q-routing algorithm under the condition of 3000 packets circulating in the network. The initial phase corresponds to the commencement of online training. DR-BM utilizes a centralized routing approach where complete routing tables are computed at ground stations and uploaded to satellites, which allows satellite nodes to execute forwarding strategies without undergoing training-based convergence. Therefore, the routing performance of DR-BM during the initial satellite deployment phase need not be considered. By leveraging ground-based pre-training, the MARL-JR algorithm equips satellites with effective packet forwarding strategies from the initial deployment phase, enabling the rapid convergence of the routing algorithm. In contrast, the Q-routing algorithm relies on obtaining link-state information through data packet forwarding, which limits its ability to promptly adapt to changes in link states compared to MARL-JR.  
Figure 8: Load comparison diagram. Figure 9: Packet arrival rate comparison diagram.