## 4 Results and Discussion
Figures 17 and 21 show results for sensor nodes generating differently-sized messages every 1 to 2 h. Here, it can be seen that with this low frequency message generation, DTN-nodes can deliver most messages even with small-sized buffers. The exception in these results are for Spray and Wait protocol, but it can be due to configuration parameters and the bottleneck at the Gateway. The number of copies in Spray and Wait was chosen from simulation results from TheONE simulator, we used the file snw_comparison_settings.txt given in the simulator to compare different values of this parameter. From these simulations we deduced that for copy values over 8, in small sized scenarios, the delivery rate does not change considerably (less than 3 percent). We added this Spray and Wait comparison file to our GitHub project repository [26]. Figures 17 and 21 show that our proposal performs at the same level or even better than Epidemic and PROPHETv2 protocols when the messages are generated every 1 to 2 h and the buffer size per node is \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Parameter** & **Subscenario X.1** & **Subscenario X.2** & **Subscenario X.3** & **Subscenario X.4** \\ \hline Message Size & 2 MB & 2 kB & 2 kB & 2 MB \\ Message Interval & 1–2 min & 1–2 min & 1–2 h & 1–2 h \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Simulation scenarios. X = 1. Wireless Sensor Network (WSN) nodes in the river. X = 2. WSN nodes all around the map. \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Definition** \\ \hline Gateway & 1 node \\ Sensor Nodes & 5 nodes \\ ICS & 1 node (destination node) \\ Mobile APs & 10 nodes going through the defined path \\ RandomMvmt & MAPs going through the path in a random fashion \\ MapReduce & MAPs going through the path following one direction \\ Buffer Size & Going from 5 MB to 1000 MB. How much information a node can hold \\ Message Size & Size of each message. It goes from 2 kB to 2 MB \\ Message Interval & It determines how often messages are generated \\ SnWCopies & Spray and Wait copies set to 8 \\ DFA & Distributed Forwarding Algorithm (Our proposal) \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Simulation parameters. ICS: Internet Connected Server. MAP: Mobile Access Point. equal to or greater than 10 MB. All results show that the delivery probability is slightly better when the MAPs follow the same direction at a constant speed than when they move randomly over the path. Results for Scenario 2 (Sensor nodes moving randomly over all paths) show that our proposal performs as well as the other routing protocols or even better (in the case where large messages (2 MB) are generated every 1 to 2 min and the nodes have buffers with 100 MB or more). For the other sub-scenarios in Scenario 2, results indicate that all protocols deliver all or almost all messages when sensor nodes can freely move around the map and messages are small or are generated less frequently (1 to 2 h between each new message). We can also see from Figure 10 that the delay acts as a non-decreasing function of the buffer size for all protocols in the first subscenario of Scenario 1. Spray and Wait shows the minor delay as the buffer increases, followed by PROPHETv2 and our DFA. For all other subscenarios of Scenario 1, all protocols show a very stable behaviour of their delay (Figures 14, 18, and 22). They experience less delay when the MAPs follow one direction in the map. For Scenario 2, DFA has the best delay performance overall. It can be seen that even in the most demanding subscenario (Subscenario 2.1), DFA increases its delay as the buffer size increases but it does it at a lower rate than the other protocols. For all other subscenarios, the delay stays stable, with DFA and Epidemic having the minor delays, followed by Spray and Wait and PROPHETv2 with the bigger delays.