# Overall Design of Satellite Networks for Internet Services with QoS Support
## 3 Performance Evaluation
### Performance Evaluation for the Delay-tolerant service  
In Scenario 1, we show the performance of the delay-tolerant service according to the traffic load and the burstiness. The burstiness was from 1-20 for considering the traffic pattern of various applications. The VBDC was used in the resource allocation. The delay constraint was from 3-10 s with the consideration of the resource allocation delay. Figures 4 and 5 indicate the throughput and the 95 th percentile end-to-end delay according to the traffic load for the spectral efficiencies of 1 bps/Hz, 2 bps/Hz, and 3 bps/Hz. In Figure 4, the burstiness does not highly affect the throughput. When the traffic load was more than the maximum transmission capacity, throughput values for the spectral efficiency of 1 bps/Hz, 2 bps/Hz, and 3 bps/Hz converged to about 5.5 Mbps, 12 Mbps, and 18 Mbps, respectively. However, the end-to-end delay was influenced by the burstiness, as shown in Figure 5. With increasing the burstiness, the 95 th percentile end-to-end delay increased because the heavy traffic load that needs many frames for the transmission was instantaneously imposed on the satellite network in the case of high burstiness. When the traffic load was more than the maximum transmission capacity, the 95 th percentile end-to-end delay exponentially increased. In this case, data were continually accumulated in the transmission buffer, resulting in the considerable queuing delay. Figures 6 and 7 show the satisfaction ratio and the goodput according to the traffic load for the spectral efficiency of 3 bps/Hz. Since the results for the spectral efficiencies of 1 bps/Hz, 2 bps/Hz, and 3 bps/Hz showed a similar tendency, the results for the spectral efficiency of 3 bps/Hz is only presented for the results of the satisfaction ratio and the goodput. It is shown that the satisfaction ratio and the goodput were reduced with increasing the burstiness due to the increase of the end-to-end delay by the burstiness. When the delay constraint decreased, these performances were degraded by the tight requirement, as shown in Figures 6 and 7. \begin{table}
\begin{tabular}{l c c c} \hline \hline
**Parameters** & **Sen.1** & **Sen. 2** & **Sen. 3** \\ \hline Resource allocation method & VBDC & RBDC & VBDC \\ Spectral efficiency (\(\text{bps}/\text{Hz}\)) & 1–3 & 1–3 & 1–3 \\ The number of UTs & 50 & 50 & 50–150 \\ The number of service flows & 50 & 50 & 50–150 \\ Total traffic load (Mbps) & 5–20 & 5–20 & 5–20 \\ Burstiness & & 1–20 & 1–10 & 1 \\ Ave. data TX rate for each service flow (kbps) & 100–400 & 100–400 & 33–400 \\ Ave. data size (KB) & 6.25–500 & 6.25–250 & 2–25 \\ Ave. inter-arrival time (s) & 0.5–10 & 0.5–5 & 0.5–10 \\ Delay constraint (s) & 3–10 & 1–4 & 3–10 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The simulation scenario. VBDC, volume-based dynamic capacity; RBDC, a rate-based dynamic capacity. Figure 4: Cont. Figure 4: The network throughput at the application layer according to the traffic load (Mbps) when burstiness varies from 1–20 (VBDC). Figure 5: Cont. Figure 5: The 95 th percentile delay according to the traffic load (Mbps) when burstiness varies from 1–20 (VBDC). Figure 6: Cont. Consequently, the factors such as the traffic load and the burstiness should be considered in the QoS policy for the delay-tolerant service in the satellite network. For example, to guarantee the QoS of UTs with the traffic with high burstiness, the number of UTs should be limited by the  
Figure 6: The satisfaction ratio when the spectral efficiency is \(3\,\mathrm{bps}/\mathrm{Hz}\) when the traffic load varies from 5–20 Mbps and burstiness varies from 1–20 (VBDC). Figure 7: The goodput when the spectral efficiency is \(3\,\mathrm{bps}/\mathrm{Hz}\) when the traffic load varies from 5–20 Mbps and burstiness varies from 1–20 (VBDC). admission control of UTs in the NMS considering the maximum goodput according to the burstiness.