# DRL-Based Dynamic SFC Orchestration Algorithm for LEO Satellite Networks
## 5 Simulation and Results Analysis
When the network operates near capacity limits with increased readjustment demands, PPOSFC effectively identifies globally optimal orchestration strategies that maximize operator profits, despite inevitable deployment and readjustment constraints. Next, we investigated how immediate reward parameter settings influence the orchestration strategy preferences of the PPOSFC algorithm during training. In the algorithm's training process, immediate reward parameters were configured to affect the agent's bias toward deployment or readjustment in orchestration schemes. We examined the impact of parameters \(\zeta\) and \(\theta\) on the deployment success rate and readjustment costs under various user service request arrival rates, where \(\zeta\) represents the immediate reward for successful SFC deployment, and \(\theta\) represents the immediate reward for successful SFC readjustment. As shown in Figure 4, the simulation results demonstrate that increasing the immediate reward for successful deployment causes the algorithm to favor SFC deployment in its strategy, achieving higher deployment success rates under high user service request intensity, albeit at the cost of increased readjustment expenses. Conversely, increasing the immediate reward for successful readjustment leads the algorithm to prioritize reducing readjustment costs, selecting solutions with lower readjustment costs when readjustment frequency is limited, though this may impact SFC deployment schemes. The simulations confirm that adjusting the immediate reward coefficients for successful deployment and readjustment enables strategy adaptation under different user service request intensities: for instance, reducing readjustment costs in the low user service request intensity or maintaining higher deployment success rates in the high user service request intensity. Next, we investigated the impact of incorporating future network topology information on the performance of the PPOSFC algorithm. Our analysis examined the effect of topology information inclusion on cumulative profit under varying user service request  
Figure 3: Algorithm performance on SFC orchestration success rates across different user request arrival rates: (**a**) deployment success rates; (**b**) readjustment success rates. arrival rates. The detailed results are presented in Table 3. The simulation results demonstrate that incorporating future network topology information significantly influences the algorithm's optimization objectives, yielding an average improvement of 5.46% in cumulative profit. These findings substantiate the positive impact of supplementary topology information in the observation space on the algorithm's orchestration performance. We further examined the adaptability of our algorithm across different LEO satellite network configurations. Building upon our previous simulation framework, we modified the orbital parameters to create a new simulation environment. In this modified configuration, the number of satellites per orbit was adjusted to 10, resulting in a total constellation of 180 satellites. Simulations were conducted with a user service request arrival rate of 20 per unit time slice, with the results illustrated in Figure 5. The simulation outcomes demonstrate that our proposed algorithm maintains robust orchestration performance across satellite networks of varying sizes, consistently achieving higher cumulative operator profits. These results validate the algorithm's adaptability and effectiveness across satellite networks of different scales. Figure 4: SFC orchestration performance across different immediate reward parameters: (**a**) deployment success rates across different \(\zeta\); (**b**) readjustment success rates across different \(\zeta\); (**c**) deployment success rates across different \(\theta\); (**d**) readjustment success rates across different \(\theta\). Figure 5: Algorithm performance across different satellite configurations.