## 4 Experiments and Results: Performance Analysis
### Simulation Results  
As shown in the simulation results (Tables 4 and 5), the proposed architecture achieved high packet delivery, low latency, and low jitter. The energy consumption of the architecture was also lower than other VANET architectures, which suggests that the proposed solution is energy efficient. As delineated in the table, the system consistently exhibited low latency figures, ranging from 5 ms to 28 ms. This range is indicative of the system's suitability for applications requiring real-time data transmission, such as emergency response systems in vehicles. Across the virtual machines, the average jitter ranged from 1.2 ms to 1.5 ms, while the maximum and minimum jitter values showed only slight variations. This stability in jitter contributes to the network's reliability and makes it suitable for time-sensitive applications in VANETs. \begin{table}
\begin{tabular}{c c c c} \hline
**Virtual Machine (VM)** & **Average Jitter** & **Maximum Jitter** & **Minimum Jitter** \\ \hline Node 1 & 1.2 ms & 2.3 ms & 0.4 ms \\ Node 2 & 1.5 ms & 2.5 ms & 0.3 ms \\ Node 3 & 1.4 ms & 2.4 ms & 0.5 ms \\ \hline \end{tabular}
\end{table} 
Table 4: Measured jitter for various network environments in VANET. \begin{table}
\begin{tabular}{c c c c} \hline
**Virtual Machine (VM)** & **Compromised Nodes** & **Transmitting Nodes** & **Miners** \\ \hline Node 1 & 10 & 50 & 20 \\ Node 2 & 90 & 200 & 100 \\ Node 3 & 300 & 300 & 200 \\ \hline \end{tabular}
\end{table} 
Table 2: NS3 Configuration for various network environments in VANET. \begin{table}
\begin{tabular}{c c} \hline
**Action** & **Probabilities** \\ \hline Malicious Node Addition & 5\% \\ Compromised Node & 10\% \\ \hline \end{tabular}
\end{table} 
Table 3: Various probabilities used for performance analysis. Furthermore, we analyzed the security of the proposed architecture against network attacks. Quality metrics were defined to evaluate the penetration of devices by attackers. During communications, network packets or users were injected into the system based on a subsequent distribution. Both worm and spoofing attacks were considered, with the former reducing system performance by reporting the transmission routes of the user requests and the latter arbitrarily discarding packets. 3.1 In-Depth Comparative Analysis of Dual-Layer Blockchain versus Traditional VANET Architectures: A Quantitative Performance Evaluation  
The results are visualized in Figures 11-14, which show wormhole, falsification, and packet drop probability over varying network densities. The graph compares the proposed system's effectiveness with respect to existing approaches for detecting malicious nodes (MNs) in the VANET related to corresponding nodes, including the probability of a falsification operation. Figure 12 provides insights into the likelihood of successful wormhole attacks at varying network densities. It is evident that the proposed method substantially outperformed the basic technique across the entire range of network densities, thereby suggesting increased security against wormhole attacks. As can be seen in Figure 13, the proposed method yielded significantly lower probabilities for successful falsification attacks, especially as the network density increased. This enhances the credibility of the information circulating in the network. Figure 14 illustrates that the proposed method significantly reduced the chances of successful packet-drop attacks across all tested network densities. This ensures higher data integrity and network reliability. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Virtual Machine (VM)** & **Average Latency** & **Maximum Latency** & **Minimum Latency** \\ \hline Node 1 & 15 ms & 25 ms & 5 ms \\ Node 2 & 18 ms & 28 ms & 6 ms \\ Node 3 & 16 ms & 26 ms & 5 ms \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Measured latency for various network environments in VANET. Figure 11: Wormhole, falsification, and packet drop probability over varying network densities.