## 4 Performance Evaluation and Analysis  
### Simulation Setup  
To construct a highly realistic simulation environment for more accurately evaluating the performance of energy-efficient routing strategies, we developed a dual-layer inclined orbital constellation model with 1152 satellites, based on the Starlink project's publicly available constellation parameters [30]. These satellites are distributed over various orbits to simulate the actual satellite layout of Starlink, thus ensuring the practical application value of our simulation results. The deployment of ground stations is a crucial component of this simulation. We established 155 ground stations worldwide, considering a wide geographical distribution and actual communication demands to capture regional disparities in satellite communication system performance. The simulation process utilizes a fixed-duration snapshot method, with each snapshot lasting five minutes, covering a full 24 h day and generating a total of 1440 snapshots. An example diagram of snapshot transition states is shown in Figure 1. This approach enables us to meticulously document the satellite network's performance variations throughout the day, providing substantial data for analysis. Static services are employed in this simulation. Such services persist continuously from the simulation initiation, and the number of concurrent services running in each snapshot remains stable. This setup enables observation of network performance under varying load conditions. For energy consumption simulation, emphasis is placed on the energy consumption status of satellite nodes when they are in the shadow zone. In contrast, when nodes are in the sunlight zone, solar power supply is adopted by default, and the battery-powered mode is not activated. All pertinent parameters, including satellite orbits, ground station locations, and other essential settings, are detailed in Table 1 of the paper. The simulation was conducted in a C++ environment, utilizing the boost library and the NS-3 tool to simulate satellite communication. Service source nodes generate data packets at a fixed rate, representing the service bandwidth. Static service models were used, ensuring that services persisted from the start of the simulation, maintaining a stable number of concurrent services in each snapshot to analyze network performance under various loads. Initial values for the weight coefficients to X:Y:Z = 1:1:1 (corresponding to the importance ratios of network lifetime, packet loss rate, and delay in solving the ultimate objectives), primarily based on the following considerations: In the initial research stage of satellite optical networks, network lifetime, packet loss rate, and delay are all core indicators for evaluating the performance of routing schemes. Network lifetime is directly related to the sustainable operation capability of satellite systems, while packet loss rate and delay affect the reliability and real-time performance of data transmission. The three hold equal foundational significance in the scenario of \"energy-efficient routing in edge AI-driven satellite networks\" focused on in this study. Given the current lack of an established quantitative standard for the relative importance of these three factors in this specific scenario, and considering that the core objective of this research is to validate the effectiveness of the \"GreenRP in balancing multi-objective performance\" rather than comparing the priority rankings of individual indicators, we chose the equal weight setting as a baseline. Four different routing algorithms were compared to evaluate their performance in terms of energy efficiency and network performance. The first, the shortest path algorithm, does not consider energy savings and makes no modifications to the topology, focusing solely on shortest path routing. Second is the GreenRP algorithm introduced in this paper, which aims to balance energy consumption and service quality by optimizing the network topology.