## 5 Performance Evaluation and Analysis
During the simulation process, we set k = 2 as an example to verify the performance of different \(\beta\) on connection interruption ratio under the same \(\alpha\) value. We can see that when the value of alpha is fixed, as the value of beta increases, the CIR gradually decreases. This is because node-upgrade probability is an important factor that influences the connection interruption of the service supply. By providing a higher weight to the upgrade probability, the risk of service interruption and traffic loss caused by node upgrade can be effectively reduced. Apparently, the proposed _BMA-RSA_ algorithm achieves considerable benefits in connection interruption ratio. For example, as shown in Figure 7a, at 620 Erlang traffic load, _BMA-RSA_ algorithm which sets the weight coefficient of node upgrade probability to 2, 5, and 10, respectively, decreases the connection interruption ratio by 0.38%, 0.73%, and 1.12% compared with the _SP-RSA_ algorithm which sets the weight coefficient of node upgrade probability as 0. Meanwhile, the connection interruption ratio decreases as the value of parameter \(\beta\) increases. This can be explained as follows: in fixed/flex-grid optical networks, node update has a huge influence on the performance of data transmission. The traditional algorithm does not consider the impact of node upgrade, in the process of data transmission, when a node on the path carrying the traffic upgrades, the data transmission is interrupted, resulting in data loss, thus leading to a high connection interruption ratio. Meanwhile, the connection interruption ratio under the non-uniform traffic model decreases faster than that under uniform traffic model. This is because, under  
Figure 5: Simulation and results. (**a**) BBR under uniform traffic model when 16 nodes are upgraded in USNET; (**b**) BBR under non-uniform traffic model when 16 nodes are upgraded in USNET; (**c**) BBR under uniform traffic model when 10 nodes are upgraded in NSFNET; (**d**) BBR under non-uniform traffic model when 10 nodes are upgraded in NSFNET. the non-uniform traffic model in which traffic is unevenly distributed, some nodes have relatively high probability are easier to be upgraded to flex-grid, causing a large number of data loss. The proposed algorithm can effectively avoid this situation. Figure 7a-d illustrates the connection interruption ratio versus different traffic loads in _USNET_ with 16 upgraded nodes and _NSFNET_ with 10 upgraded nodes. Similarly, in Figure 7b, at 780 Erlang traffic load, the _BMA-RSA_ algorithm, which sets the node upgrade probability weight coefficient as 2,5,10, creates the gap of 0.43%, 0.93%, and 1.23% lower than the SP-RSA algorithm, which sets the weight coefficient of node upgrade probability as 0, respectively. Meanwhile, under the same traffic load, the network with 16 upgraded nodes achieves a higher connection interruption ratio compared with the network with 8 upgraded nodes. We obtain a similar conclusion under the _NSFNET_ topology. This can be explained that much more upgraded nodes (i.e., 50% of the nodes in the network) will promote more interruptions caused by nodes. For example, at the 820 Erlang traffic load under the non-traffic model, the connection interruption ratio is as high as 8.43%. Through the analysis of the simulation results, we can conclude that the proposed _BMA-RSA_ algorithm has great advantages. This is because it can greatly reduce the connection interruption ratio while increasing the extremely small bandwidth blocking ratio, which can be almost negligible. Additionally, by taking the node probability into consideration, _brown  
Figure 6: **(a)** CIR under uniform traffic model when 8 nodes are upgraded in USNET; **(b)** CIR under non-uniform traffic model when 8 nodes are upgraded in USNET; **(c)** CIR under uniform traffic model when 5 nodes are upgraded in NSFNET; **(d)** CIR under non-uniform traffic model when 5 nodes are upgraded in NSFNET.