## 4 Performance Evaluation and Analysis
### Comparison of Algorithm Performance Under Fixed Loads  
The above simulation results validate that GreenRP is capable of sustaining satisfactory network performance across diverse network loads. The forthcoming analysis aims to assess the performance of various algorithms under a constant service concurrency, highlighting the complex challenge of balancing energy efficiency with network performance. This will particularly involve scenarios exhibiting packet loss, specifically those with a service concurrency of 4000, to provide focused insights into how each algorithm performs under stressed network conditions. Figure 4: Comparison of algorithm performance under different loads: (**a**) latency performance; (**b**) packet loss rate and load sleep variation. By calculating the average inter-satellite link utilization for each snapshot duration, data corresponding to 1440 snapshots were plotted as a probability density graph. Figure 5 illustrates the distribution of network-wide inter-satellite link utilization across various snapshot periods. With 24% as the baseline for link utilization, GreenRP's rates were always above this level, whereas SP's rates fell below this baseline about 52% of the time, and GreenSR's about 38% of the time. The average link utilization for the SP strategy peaked at only 40% throughout the simulation period, primarily due to uneven traffic distribution with many links carrying low traffic volumes, resulting in low overall bandwidth utilization. GreenSR's link utilization improved relative to SP, as dormant links were excluded from the utilization calculations, with fewer links handling communications. Additionally, GreenSR's longer average service paths and the additional hops consumed more bandwidth resources. SGA generally exhibited higher link utilization than SP but did not consistently surpass GreenRP, particularly under high traffic conditions. GreenRP consistently demonstrated high link utilization rates. This indicates that by deactivating some links, GreenRP maintained high network-wide link utilization, thus efficiently utilizing communication resources. Figure 6 illustrates the distribution of the remaining battery percentage of satellites network-wide at the end of the simulation under various algorithms. Since some satellites were continuously exposed to sunlight, maintaining full battery levels, such data were excluded from the analysis. The graph reveals that the lowest remaining battery percentage network-wide under the four algorithms was 25% for SP, 43% for GreenSR, 49% for SGA, and 58% for GreenRP. This indicates that GreenRP performed best in maintaining higher battery levels across the network, effectively preventing excessive discharge of satellites. The steep curve of SP's power distribution indicates uneven energy consumption among satellites in shaded areas, with some experiencing rapid battery depletion due to overuse, while others remain idle. In contrast, the smoother curves under the energy-efficient routing algorithms GreenSR, SGA, and GreenRP suggest a more balanced power consumption among satellites. This balance is achieved primarily by alternating the workload among different satellites. What is noteworthy about GreenRP is its optimized power management and load distribution. It ensures communication quality in shadowed areas while minimizing the number of operational satellites, thereby significantly improving satellite energy utilization. Figure 5: Link utilization cumulative distribution function (CDF). Figure 7 illustrates the network lifetime consumption produced by different algorithms. Every 100 min, data on network lifetime consumption by each algorithm were recorded, with the x-axis representing the time segment number and the y-axis the total network lifetime consumption for that period.