# Packet-Forwarding Algorithm in DTN Based on the Pheromone of Destination Node
## 2 Related Works  
The traditional packet-forwarding algorithm cannot perform efficiently because of the intermittent link among nodes and because the network topology changes with a high frequency. Thus, the strategy of \"store-carry-forward\" is proposed to overcome the problem caused by the frequent interruptions of links among nodes in DTN. The selection of a relay node will significantly affect the forwarding delay  
Figure 1: Packet-forwarding path in a community without a core node. and packet delivery success rate in the process of \"store-carry-forward\". Hence, such selection has recently become a crucial research area. A community can be classified into two types according to whether social features are to be used in the process of selecting relay nodes. The first type uses social features in the packet-forwarding process [2; 5; 7; 8; 9; 10; 11], whereas the second type does not consider these features [12; 13; 14; 15]. [PERSON] et al. [13] proposed the epidemic algorithm for DTN, which was a typical algorithm belonging to the second type. When one node meets another node, they should exchange messages that are different between them. Consequently, all non-isolated nodes will receive messages after a certain number of information exchanges. Although the high packet delivery success rate is the most notable feature of the epidemic algorithm, high resource consumption will occur during the packet-forwarding process. Consequently, this algorithm cannot achieve good performance in a real network that cannot provide sufficient resources. [PERSON] et al. [14] divided the packet-forwarding process into two stages, namely, spray and wait. During the spray stage, the source node spreads the message to its neighbors. The message spread by the source will then be carried until it meets the destination node during the wait stage. Taking advantage of the fixed quota for copying, this process can optimize the consumption of node resources in the epidemic algorithm. Compared with the previous forwarding algorithm, the relations among node carriers are utilized in the second type of forwarding algorithm. The nodes are classified into different communities based on several special characteristics of node carriers. The relationship among the inner nodes of the community is tighter than that among the outer nodes. In [7], [PERSON] et al. proposed the bubble algorithm, which would select the relay node with high betweenness centrality or that belonged to the community of the destination node during the packet-forwarding process. The global betweenness centrality of a node controls the selection of the relay node until the packet enters the destination community. The local betweenness centrality of a node will then replace the global one to influence the selection of the relay node in the destination community. Nevertheless, if every node holds low global betweenness centrality, then bubble may not achieve satisfactory performance. A routing protocol based on clustering structure is proposed [10], which classifies the nodes with similar mobility traces into a cluster of recent social circle. The entire process of the routing protocol is divided into three stages, namely, spraying, forwarding among clusters, and \"flooding\" in the inner cluster. Given the lack of an appropriate node removal mechanism in the cluster, the scalar of the number of clusters may become significantly large, and the routing protocol will evolve into \"flooding\" over time. [PERSON] et al. [9] defined communities C1 and C2 that were maintained by the same node within different time windows. According to the Jaccard index, the similarity between C1 and C2 can be represented as:  
\[J\left(C_{1},C_{2}\right)=\frac{\left|C_{1}\cap C_{2}\right|}{\left|C_{1}\cup C _{2}\right|}, \tag{1}\]  
The similarity between C1 and C2 is identified by computing the ratio between their common and total numbers.