# Enhanced Message Replication Technique for DTN Routing Protocols
## 4 Simulation Studies
### Simulation Results
Figure 4 shows the relationship between the latency average and node density, where it is clear that the latency average increases as the number of nodes increases. This is because more nodes become involved, leading to congestion in the network, and information processing at each node takes time, resulting in an overall increase in latency. In addition, buffering messages at a node causes delays in message delivery. The figure also shows the results of applying the EMRT to Spray and Wait, EBR, and the DBRP in terms of latency average. The increased latency average at higher densities with the original protocols is due to more nodes sending copies of the message, leading to a delay in message delivery. It can be seen that the latency average of the Spray and Wait-EMRT, EBR-EMRT, and DBRP-EMRT protocols is reduced by up to 51%, 14%, and 13%, respectively. This is because the rate of dropping messages is controlled by selecting a number of replicas appropriate for the available network resources. An uncontrolled number of replicas can lead to buffer congestion or inefficient use of network resources. By reducing congestion, the rate of message drops is reduced, resulting in a decrease in the latency average. Figure 5 shows the composite metric combining delivery ratio and latency average. The results show that applying the EMRT to Spray and Wait can improve both the delivery ratio and the latency average by up to 60%. This is due to the individual improvements in each of these metrics, as explained in Figures 2 and 4, respectively. Additionally, there is an improvement of up to 25% in this composite metric for EBR and the DBRP. These improvements are less compared to Spray and Wait, and this is due to the more targeted forwarding strategy used in these protocols. The composite metric in Figure 6, which evaluates both delivery ratio and overhead, shows an improvement of up to 14% for all considered protocols when the EMRT is applied. The EMRT increases the number of replicas when there are sufficient resources, leading to an expected increase in overhead. However, when there are insufficient resources, the number of replicas decreases. Therefore, the EMRT is not expected to lead to a significant improvement in the overhead ratio. However, the high dissemination rate resulting from the production of more replicas increases the delivery ratio, leading to the impact shown in Figure 6. This trade-off between overhead and delivery ratio is why the EMRT has an impact on this composite metric. Finally, Figure 7 shows a clear image of the performance of the EMRT when applied to the considered protocols and the delivery ratio, average latency, and overhead are all combined. The results for all protocols show an improvement of up to 72%. This is because the improvement of applying the EMRT can be seen in all individual metrics as well. The EMRT results show that making the number of replicas adaptive increases the overall  
Figure 5: The DL composite metric (DR \(\times\) (1/latency average)). Figure 6: The DO composite metric (DR \(\times\) (1/overhead)). performance of the routing protocol. This is because the number of copies is not dependent on the number of encounters and remains fixed for each generated message.