## 6 Simulations and Experiments
### Experimental Results in a Real Environment
The simulations conducted to evaluate the integrated Meshtastic protocol with the reputation model yielded promising results, demonstrating significant improvements in the security and trustworthiness of IoT networks. \begin{table}
\begin{tabular}{c c c c} \hline  & **TTGO LoRa32** & **Heltec Wireless Stick** & **Arduino Nano ESP32** \\ \hline
**Microcontroller** & ESP32 dual-core 32-bit & ESP32-S3 dual-core & 32-bit \\ \hline
**Frequency** & & 240 MHz & \\ \hline
**ROM Memory** & 4 MB & 8 MB & 16 MB \\ \hline
**RAM Memory** & & 520 KB & \\ \hline
**Built-in Modules** & Wi-Fi, BLE, and LoRa & Wi-Fi and BLE \\ \hline
**LoRa Module** & & & \\ \hline
**LoRa Antenna Gain** & 2 dbi & 1 dbi & 0 dbi \\ \hline
**Number of Nodes** & 8 nodes & 1 node & 1 node (malicious) \\ \hline \end{tabular}
\end{table} 
Table 2: Used devices. Figure 7: The malicious node (Arduino Nano ESP32) equipped with an external SX1276 868 MHz LoRa module. The analysis of network performance metrics revealed notable enhancements in latency, packet delivery rate, and energy efficiency compared to traditional IoT networks. Meshtastic's adaptive routing mechanisms, informed by reputation scores, enabled the establishment of robust communication paths, even in dynamic and challenging environments. Moreover, the security measures implemented within Meshtastic in response to potential threats, such as malicious or damaged nodes, proved effective in mitigating risks and preserving data integrity. By dynamically adjusting communication paths and isolating suspicious nodes based on reputation scores, the protocol demonstrated resilience against various security vulnerabilities. Overall, the results indicate that the integrated Meshtastic protocol with the reputation model holds significant promise for enhancing the security and trustworthiness of IoT networks. The scalability of the Meshtastic protocol was evaluated by increasing the number of nodes in the simulated network. The results indicated that the protocol maintained robust communication paths and efficient routing even as the network grew. Additionally, the efficiency of the integrated protocol was analysed in terms of resource utilisation, including energy consumption and bandwidth usage. The adaptive routing mechanisms enabled by Meshtastic, informed by reputation scores, optimised resource allocation and minimised overheads, leading to the more efficient utilisation of network resources. Moreover, the security measures implemented within Meshtastic in response to potential threats, such as malicious or compromised nodes, were found to be highly efficient. By dynamically adjusting communication paths based on reputation scores, the protocol effectively isolated suspicious nodes while maintaining uninterrupted data transmission for legitimate devices. Furthermore, the simulations provided valuable insights into the behaviour of the reputation model under varying network conditions and loads. Observations regarding the model's adaptability and performance scalability informed the refinement of reputation management strategies for enhanced efficiency and reliability in large-scale deployments. Overall, these results indicate that the Meshtastic protocol integrated with the reputation model offers a scalable, efficient, and secure solution for IoT networking. Future research directions may focus on further optimising resource utilisation, refining reputation management algorithms, and validating the approach through real-world deployments. Figure 8: Results of malicious node detection based on reputation score in the real environment with real nodes after 48 h.