## 5 Simulation Results and Discussion
### Discussion of ns-3 Simulation Results
For this simulation period, in response to the failure of network \(\mathcal{N}_{1,\text{ the PMU}}\) reroutes data through an alternative route at interface 170.1.2.1, which is through network \(\mathcal{N}_{3}\) over the Internet \(\mathcal{N}_{2}\). Nevertheless, network \(\mathcal{N}_{4}\) is now available and configured with only 25% background traffic (with a data rate of 30 Kbps). This ensures a backup path with sufficiently high bandwidth between the PMU and PDC. Therefore, the PDC receives all 4000 packets transmitted by the PMU at interface 170.1.2.1, resulting in a packet loss ratio of 0%. Consequently, the performance of the network in terms of \(PDR\) is superior to that in earlier case studies. Specifically, the average \(PDR\) corresponding to both flows is equal, which can be corroborated by Table 3.  
A graph of \(PDR\) as a function of the simulation time corresponding to all case studies is plotted in Figure 10. From the figure, it can be seen that the first failure event of network \(\mathcal{N}_{1}\) occurs at 50 s. Before the failure of the network, the \(PDR\) remains equal to 1. As there is no backup path under this case study, \(PDR\) drops to 0 in response to the failure event. Moreover, during the 50 s to 110 s simulation time, \(PDR\) remains at 0. Thus, the SCN loses its functionality. Furthermore, the degradation rate using Equation (3) can be estimated to be \(\xi_{\text{deg}}=-0.1\). From Figure 10, \(t_{1}=50\) s, \(t_{2}=60\) s, \(PDR_{t_{1}}=1\), and \(PDR_{t_{2}}=0\). The performance graph for case study-II shows the period of 110 s to 210 s. Network \(\mathcal{N}_{1}\) restores at 110 s, which improves the \(PDR\) to 1 compared with the failure event of case study-I, where the \(PDR\) is 0. Furthermore, the recovery rate using the equation can be estimated to be \(\xi_{rec}=+0.1\). From Figure 10, \(t_{4}=110\), \(t_{5}=120\), \(PDR_{t_{4}}=0\), and \(PDR_{t_{5}}=1\). Here, network \(\mathcal{N}_{1}\) fails again at 150 s; thus, the \(PDR\) degrades. However, the \(PDR\) does not become 0, i.e., \(0<PDR<1\). Moreover, the degradation rate using Equation (3) can be estimated to be \(\xi_{\text{deg}}=-0.0188\). From Figure 10, \(t_{1}=150\), \(t_{2}=170\), \(PDR_{t_{1}}=1\), and \(PDR_{t_{2}}=0.624\). Further, the recovery rate using Equation (4) can be estimated to be \(\xi_{rec}=+0.0376\). From Figure 10, \(t_{4}=210\), \(t_{5}=220\), \(PDR_{t_{4}}=0.624\), and \(PDR_{t_{5}}=1\). Hence, the performance of the SCN is better in the event of a failure than in the earlier case study, where there is no alternative route. Moreover, the recovery rate is better when  
Figure 10: Resiliency curve using the simulation framework of the SCN. network \(\mathcal{N}_{1}\) restores at 110 s as compared with that at 210 s. The performance graph for case study-III shows the period from 210 s to 300 s. Network \(\mathcal{N}_{1}\) restores at 210 s, which improves the _PDR_ to 1 compared with the failure events of case study-II and, of course, case study-I. Here, network \(\mathcal{N}_{1}\) fails again at 240 s. However, the _PDR_ remains at 1, as a backup path with sufficiently large bandwidth exists. Hence, it is conclusive that the performance of the SCN is superior to that in the earlier case studies in the event of failure.