## 4 Simulation Experiments and Result Analysis
### Analysis of Simulation Experiments
#### 4.2.2 High-Speed Mobile Scenario  
Thereafter, simulation experiments verify the performance of ICCDRL compared to other different TCP algorithms when the nodes run at 40-60 km/h in a high-speed mobile scenario. Unlike the performance of CC in the static case, each algorithm has a surge in RTT and a drop in throughput. The results show that ICCDRL achieves very low RTT and maximum throughput with stable control, even in the high-speed moving case. In the network simulation parameter environment described in Section 4.1, the transmission of different services such as file, image, video, and voice were completed using ICCDRL with NewReno, Cubic, Westwood and DRL-based DCC, respectively. A comparison of the congestion window was carried out, and the comparison graph is shown in Figure 8.  
Figure 8 shows the comparison of real-time _cwnd_ in a vehicle communications scenario. Unlike the traditional TCP protocols that increase their _cwnd_ in a fixed manner, the advantages of DRL-based DCC and ICCDRL algorithms are very definite. In NewReno, once packet loss is detected, it causes the congestion window CWND to decrease frequently, and when the multiplicative reduction mechanism is activated, NewReno will directly reduce the window value to the minimum. However, DRL-based DCC and ICCDRL do not blindly reduce the size of the congestion window whenever a packet is lost, as NewReno does, and eventually keeps the size of _cwnd_ at a high level. In addition, ICCDRL has a more stable _cwnd_ than DRL-based DCC, due to the congestion factor set by ICCDRL. ICCDRL can quickly increase _cwnd_ to an estimated target size, set the appropriate new window parameters, and then, at each switching interrupt, fine-tune around that target size so that the congestion window _cwnd_ continues to trend upward. In this way, ICCDRL achieves maximum throughput with minimum _RTT_ in the case of a short transmission gap between two switches. Figure 7: Throughput and RTT performances in the static scene. (2) Comparison of Bottleneck Link Utilization  
Figure 9 depicts the comparison of bottleneck link utilization when using ICCDRL with NewReno, Cubic, Westwood, and DRL-based DCC respectively. Westwood was not able to efficiently utilize the growing bottleneck bandwidth and aggregated very slowly, mainly due to the simultaneous sending of data flows at 0 to 100 s. Compared to Westwood, NewReno, Cubic and DRL-based DCC significantly improve bottleneck link utilization, but bottleneck link utilization is still low compared to ICCDRL. (3) Comparison of Throughput  
The FTP was used to transfer 50-200 MB files in the same simulation environment. Meanwhile, the real-time throughput in the network was collected using Wireshark analysis software to compare the average throughput of ICCDRL with NewReno, Cubic, Westwood and DRL-based DCC at different packet loss rates, and the results of the experiment are shown in Figure 10.  
Figure 8: Comparison of Congestion Window. Figure 9: Comparison of bottleneck link utilization. It can be seen from Figure 10 that, after a period of simulation, ICCDRL outperforms the NewReno, Cubic, Westwood and DRL-based DCC algorithms in terms of throughput when the packet loss rate is low. However, the throughput of all four algorithms decreases when the packet loss rate increases, but the average throughput of ICCDRL and DRL-based DCC maintains a high and relatively stable level when transferring files. NewReno does not distinguish packet loss types and blindly reduces _cvnd_, leading to an unnecessary waste of resources and a relatively low average throughput. Cubic uses a cubic function to detect the congestion window, and packet loss and retransmission causes the size of the congestion window to drop abruptly, which inevitably degrades network transmission performance. Westwood uses a conservative type of congestion avoidance with high jitter, resulting in some overall throughput degradation and relatively poor network performance.