# An On-Demand Fault-Tolerant Routing Strategy for Secure Key Distribution Network
## 5 Simulations and Discussion
### Results and Discussion  
Based on the above simulation environment configuration, this section will conduct a comprehensive comparison of the proposed solution and the other three methods based on the above metrics in two fault scenarios. **Packet Delivery Ratio**: Figure 8 shows the packet delivery ratio (PDR) of the four methods under different faulty nodes ratio (FNR) in the BHA scenario of different numbers of nodes. The vertical line segments depict the 95% confidence intervals of the results. As FNR increases, the PDR of the four different methods decreases, in line with expectations. We found that the proposed solution has a higher PDR than the other three methods at the same FNR. When the FNR is low, the proposed solution can identify based on different evidence that there is a greater chance that the cause of the fault is benign, so it can perform a dynamic route discovery and plan a better path for communication key forwarding. While the other methods have no identification mechanism, and both paths are relatively fixed, they have a lower PDR. ASR's load balancing ability can improve the PDR a little but not much. MPCS reduces the possibility of key leakage by transmitting it on redundant paths. However, this leads to a proportional acceleration of local key consumption, resulting in a decrease in system availability. When FNR increases, the probability of the proposed solution detecting the faulty nodes is greater. Although partitioning the network causes performance degradation and PDR reduction, the faulty nodes are isolated and the accuracy of path discovery information is improved, so the PDR is still higher than the other two methods. As the number of nodes increases, the distributed scalability of the proposed solution enables the system to maintain a high PDR. It can be observed that when the number of nodes is 40, the proposed solution has a significant decrease in PDR when FNR is around 0.1 to 0.2, while when the number of nodes is 60, 80, and 100, PDR drops significantly when FNR is greater than 0.25. This shows that when the number of nodes increases, even though the proposed solution isolates faulty nodes under the same FNR, complex topology provides more available paths. Figure 9 shows the PDR of the four methods under FNR in the TRA scenario of different numbers of nodes. The vertical line segments depict the 95% confidence intervals of the results. As the FNR increases, the PDR under different methods decreases. However, compared to the BHA scenario, using OSPF, ASR, and MPCS under TRA causes PDR to drop rapidly. This is because the faulty node propagates erroneous status information during the process of route discovery, causing path establishment to pass through the faulty nodes. As the FNR increases, this phenomenon becomes more serious. It can be seen that compared with the BHA scenario, when the proposed solution is used, erroneous status information can easily cause too many paths to be concentrated on faulty nodes, and the PDR will inevitably drop sharply. However, the inconsistency between status information and PDR improves the fault detection efficiency. Therefore, the proposed solution also avoids related faulty nodes in the subsequent path discovery process, ensuring a relatively stable PDR level. Therefore, we observe that at each FNR, the proposed solution performs better than the other three methods. **Key Material Utilization**: Figure 10 shows the key material utilization (KMU) of the three methods under FNR in the BHA scenario of different numbers of nodes. The vertical line segments depict the 95% confidence intervals of the results. KMU reflects the proportion of key material used to successfully forward communication keys among the total key consumption, and is affected by the PDR and the overhead of the local keys used for other than communication key forwarding. Compared with OSPF and ASR, the KMU of the proposed solution is slightly lower, because it has more frequent detection and path discovery under high FNR.