## 4 Results and Discussion
Regarding HopCount, we can see that for the first subscenario, DFA and Epidemic try to deliver more messages through more hops, PROPHET and Spray and Wait don't change the number of hops  
Figure 10: Results for scenario 1.1. Average delay in seconds with different Buffer Sizes, generating 2 MB messages every 1 to 2 min, (**a**) MAPs moving randomly on the path; (**b**) MAPs following the path in only one direction. DFA: Distributed Forwarding Algorithm. Figure 9: Results for scenario 1.1. Delivery probabilities with different Buffer Sizes, generating 2 MB messages every 1 to 2 min, (**a**) MAPs moving randomly on the path. (**b**) MAPs following the path in only one direction. DFA: Distributed Forwarding Algorithm. when the buffer size changes (Figure 11). For the other subscenarios (Figures 15, 19 and 23), the hop count remains steady, with all protocols very close, but Spray and Wait having the least number of hops, followed by PROPHETv2 and then by DFA and Epidemic. The hop count for all protocols in all subscenarios of Scenario 2 (Figures 27, 31, 35 and 39) remains very stable. With PROPHETv2 using the minor number of hops and the other protocols having very similar figures between them. Finally, for Scenario 1, overhead performance is plotted in Figures 12, 16, 20 and 24. In the first subscenario (Figure 12), we can see that our DFA has the worst performance by replicating more messages than it is delivering. PROPHETv2 has the best performance when the MAPs move randomly, and Spray and Wait has the best performance when the MAPs move in only one direction. For all other subscenarios, all protocols have a very similar overhead performance, with Spray and Wait having a bigger overhead in general. Regarding the overhead performance for Scenario 2, it can be seen from Figures 28, 32, 36 and 40 that Spray and Wait and PROPHETv2 have the best performance for this metric, with similar figures, while DFA and Epidemic have a bigger overhead in general, with almost the same figures between them. Figure 14: Results for scenario 1.2. Average delay in seconds with different Buffer Sizes, generating 2 kB messages every 1 to 2 min, (**a**) MAPs moving randomly on the path; (**b**) MAPs following the path in only one direction. DFA: Distributed Forwarding Algorithm. Figure 13: Results for scenario 1.2. Delivery probabilities with different Buffer Sizes, generating 2 kB messages every 1 to 2 min, (**a**) MAPs moving randomly on the path; (**b**) MAPs following the path in only one direction. DFA: Distributed Forwarding Algorithm. Figure 15: Results for scenario 1.2. Average hop count with different Buffer Sizes, generating 2 kB messages every 1 to 2 min, (**a**) MAPs moving randomly on the path; (**b**) MAPs following the path in only one direction. DFA: Distributed Forwarding Algorithm. Figure 16: Results for scenario 1.2. Average overhead with different Buffer Sizes, generating 2 kB messages every 1 to 2 min, (**a**) MAPs moving randomly on the path; (**b**) MAPs following the path in only one direction. DFA: Distributed Forwarding Algorithm. Figure 17: Results for scenario 1.3. Delivery probabilities with different Buffer Sizes, generating 2 kB messages every 1 to 2 h, (**a**) MAPs moving randomly on the path; (**b**) MAPs following the path in only one direction. DFA: Distributed Forwarding Algorithm. Figure 18: Results for scenario 1.3. Average delay in seconds with different Buffer Sizes, generating 2 kB messages every 1 to 2 h, (**a**) MAPs moving randomly on the path; (**b**) MAPs following the path in only one direction. DFA: Distributed Forwarding Algorithm. Figure 19: Results for scenario 1.3. Average hop count with different Buffer Sizes, generating 2 kB messages every 1 to 2 h, (**a**) MAPs moving randomly on the path; (**b**) MAPs following the path in only one direction. DFA: Distributed Forwarding Algorithm. Figure 10:0 Results for scenario 1.3.