# Packet-Forwarding Algorithm in DTN Based on the Pheromone of Destination Node
## 3 The Model of Pheromone and Community
### Community Model Based on Pheromone
#### 3.3.1 Detailed Description of Community Construction Algorithm
In FABP, by applying the advantage of using the pheromone P of the node to represent the betweenness centrality used in bubble, the delivery ratio of FABP is improved 3% than that in bubble. In the second set of simulations, we change the cache of the node to 10 M, 20 M, 50 M, 80 M, and 120 Mbits, and determine the delivery ratio of the three algorithms, as shown in \[C=Num(H_{0})+\sum_{i=1}^{4}Num\left(S_{i}\right), \tag{14}\]1 A larger cache capacity of a node can improve the delivery ratio of epidemic and FABP significantly. However, if the cache of a node is over 80 M, then the delivery ratio growth of epidemic will tend to be slow. In epidemic, a large number of redundant packets will be created, and packet loss will occur when the space to cache packets is insufficient. The situation may be changed when the cache becomes larger, but this effort will not always be effective. Considering that the queuing latency time will become longer with increasing cache, the growth of the delivery ratio may be stopped because packet loss reappears. For FABP, considering the requirement to diffuse the pheromone to nearby nodes in the processes of constructing and maintaining the community, an additional cache is taken. Hence, its packet loss rate is higher than bubble when the node's cache is less than 40 Mbit. However, this phenomenon will change as the cache becomes larger, and have a delivery ratio of 5% higher than bubble, because of the strategy that the furthest node delivery is outside the community and the best path is inside community. \begin{table}
\begin{tabular}{c c} \hline
**Parameters** & **Value** \\ \hline K value for bubble & 5 \\ Threshold for joining the local community in bubble & 0.5 \\ TTL(h) & 3, 6, 12, 24 \\ Interval of message generation (s) & 60–120 \\ \hline \end{tabular}
\end{table} 
Table 1: Primary Parameters. Figure 7: Comparison of the delivery ratio under different TTL values. In the third set of simulations, we analyze the average latency time of the three algorithms under various node caches. The results are shown in Figure 9. The simulation results indicate that when the length of the queue becomes longer, the queuing latency time will increase. Given that the copy of the packet is restricted in bubble and FABP, the length of the packet queue will be shorter than epidemic. Thus, the increase in delivery time tends to slow down. By taking advantage of the relatively stable community structure in the MIT Reality dataset, the community based on the pheromone can be constructed rapidly. Packets will then be forwarded to the core node through the best path and, at the average packet forwarding times, FABP has two hops less than bubble inside the community, and three hops outside the community. The latency time in FABP will be reduced 13% than that in bubble. In the fourth set of simulations, the overhead ratio of FABP is 10% higher than that of bubble, as presented in Figure 10. The key reason for this result is that the community based on the pheromone is required to forward additional packets to maintain and update during the running of the algorithm. Figure 8: Comparison of the delivery ratio under different caches. Figure 9: Comparison of the average latency time under different caches. The highest overhead ratio appears in the epidemic algorithm because of the used contagion mode for packet forwarding. ## 6 Conclusions

In this study, we propose a new initiative community structure based on the core node pheromone-computing model. We also design an efficient packet-forwarding algorithm based on the core node pheromone. The core node pheromone is computed and spread periodically by the nodes in the communication radius of the core nodes. The core node pheromone received by a node can be the betweenness centrality of the current node in the community and does not require the topology of other nodes in the community.