# DTN Trustworthiness for Permafrost Telemetry IoT Network
## 5 Simulation Tests  
As mentioned before, the first tests we performed to assess the system's trustworthiness in this use case [7] showed that it was possible to have an STR greater than 0.7 in some circumstances. However, we noticed that the DTN approach of using opportunistic bulk data transfers when the NVIS link becomes available produced network congestion in these periods. On the other hand, we also compared, evaluated, and designed modern transport protocols for heterogeneous LFNs to improve the performance of data transfers over this type of network. Our tests showed that our protocol, the EAATP, maximized throughput and minimized packet losses in LFNs. However, we did not evaluate how the use of these protocols could affect the trustworthiness of a system. Given that the NVIS links in the remote Antarctic WSN use case can be considered an LFN (with a \(BDP\) greater than 12,500 bytes, from Equation (1)), we thought that using a particular transport protocol might affect the system's trustworthiness. For this reason, we decided to run a second round of tests and check if the hypothesis was correct. In order to (1) foresee which problems may occur during the Antarctic campaign, (2) decide which transport protocol to use, and (3) build more accurate expectations of the system's performance and outcomes, we applied our trustworthiness model to measure and evaluate them in this use case. For this purpose, the use case scenario was represented and evaluated in the Riverbed Modeler simulator. The first step is the modeling of the different elements that characterize our use case. More details about the modeling of this scenario and its technologies and protocols can be found in [7; 11]. Firstly, the backbone network (NVIS) and the access network (LoRa) were modeled separately, characterized as stated in Table 1 following the aforementioned description of the network architecture (please revisit Section 3) and the link availability results from [4] and [65]. On the one hand, LoRa does not experience any availability variation between daytime and nighttime, being fully available if there is LoS between the sensor and the gateway, and with partial availability in the case of no LoS. On the other hand, NVIS is not affected by not having LoS. However, its availability varies hour by hour, depending on the ionosphere state, which is highly correlated to solar activity. During nighttime (5 p.m. to 6 a.m.), the NVIS links are not available, while during daytime (6 a.m. to 5 p.m.), their availability varies between 70% and 100%. Secondly, we modeled the following transport protocols as in our previous work [11]: BBR, Copa, CUBIC, EAATP, Indigo, and Verus. We focused on modern transport protocols that have been proven to perform well [45] and TCP CUBIC, which is the standard transport protocol in most operating systems nowadays. These protocols were modeled according to the results from our previous work in physical testbeds and simulations [5; 11] and the Pantheon tests [45]. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **NVIS** & **LoRa** \\ \hline Transmission Band & 4.3 MHz & 868 MHz \\ Channel Bandwidth & 2.3 kHz & 125 kHz \\ Channel Bitrate & 4.6 kbps & 5.47 kbps \\ Coverage Range & Up to 250 km & Up to 30 km \\ Daytime Availability (6 a.m.–5 p.m.) & 70–100\% & 100\% (LoS), 2–100\% (No LoS) \\ Night Availability (5 p.m.–6 a.m.) & 0\% & 100\% (LoS), 2–100\% (No LoS) \\ Maximum Payload Size & 242 bytes & 140 bytes \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Network parameters used to model the scenario. Thirdly, we needed to model the Byzantine behavior of nodes. As stated in [67], the probability \(Pb\) of a node having a Byzantine fault is unlikely to be constant over time. The node reliability can be related to the battery charge level by associating the battery discharge with the WSN node aging process.