## 2 Materials and Methods
### Crucial Factors Summarization and Experimental Methodology
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Factors** & **Cruciality** & **Levels** \\ \hline \multirow{3}{*}{Number of EDs} & Has an indirect significant impact & \multirow{3}{*}{10–6000} \\  & on PDR and determines how & \\  & scalable the network is. & \\ \hline \multirow{3}{*}{Number of GWs} & In most cases more GWs cause the & \multirow{3}{*}{1–8} \\  & whole network to operate & \\ \cline{1-1}  & differently by impacting the & \\ \cline{1-1}  & overall performance. & \\ \hline \multirow{3}{*}{Distance from ED to GW} & By combining distance & \multirow{3}{*}{50 m–10 km} \\  & measurements with connectivity & \\ \cline{1-1}  & metrics such as RSSI and SNR can & \\ \cline{1-1}  & determine the effective range for & \\ \cline{1-1}  & each GW and thus the coverage of & \\ \cline{1-1}  & the network. & \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Crucial factors to control and observe. The fact that commercial network deployments can include thousands of EDs force us to make some observations in a simulator-based manner. This method offers us the ability to stress-test the network while at the same time we can evaluate numerous different parametrizations per ED. In this way the derivation of observations about scalability limits of the protocol, which seems to be the most important, will be facilitated. The ns3 simulator is being used with the addition of the LoRaWAN module. Previous experiments that were reviewed in the literature--which also utilize this software--seem from the insights to be very powerful. To accomplish our goals we need to test LoRaWAN limits by developing some measurement setups based on Table 1. Several repeats of the tests need to be made for every factor as well as for every level of each factor. We will also randomly make observations between the different setups on different variables to enrich our statistical approach. In each simulation scenario a LoRaWAN network is created in an environment with modeled congestion to evaluate each time the possibility of message loss. Specifically, the height of the GW antenna has been set to 15 m, the height of the ED antenna to 2 m and the path loss exponent to 3.76. A crowd of EDs is created and placed with random distribution within a disc (Figure 1) of a specific radius or in the periphery of such discs (Figure 2) or even in disc rings (Figure 3), depending on the scenario under consideration. As of this study, path loss staticness and ED distribution randomness, but also external interference and downlinks absence are perceived as the uncontrolled variables that can cause false correlations or improper analysis of the results. Then, we are assigning values for the parameters SF, TX as well as whether the messages that will be sent require acknowledgement, and if so, which is the maximum number of retransmissions. In addition, GWs are placed in selected spatial positions. Finally, the size of the payload and the intermediate period of creation and sending messages from each ED (uplink) as well as the total simulation time of the test are noted. ADR will be disabled in all cases because in some cases it caused more issues than it solved [28]. It is found that while ADR decides to update SF for a node based on channel conditions, it does