# An Opportunistic Network Routing Algorithm Based on Cosine Similarity of Data Packets between Nodes
## 2 Related Work  
Due to the dynamic change of the network topology caused by the node's movement, the traditional routing protocols of wireless network are difficult to apply to the OppNet. Therefore, how to reasonably select the next hop to implement information forwarding effectively has become an important research direction of the OppNet [20]. The Epidemic algorithm [21] is based on the flooding strategy. The main idea is that nodes meet each other to exchange information which is missing from each other. The routing algorithm can enhance the delivered ratio of the network and reduce the transmission delay effectively, but it will generate a great deal of copies of messages in OppNet, which will easily lead to excessive routing overhead in the network. Based on the traditional Epidemic algorithm, [PERSON] et al. [22] proposed an Epidemic routing algorithm with adaptive capabilities. By observing the buffer status of the surrounding nodes, the algorithm adjusts the number of message copies injected by the node into the network in real time, which improves the performance of the Epidemic algorithm and effectively reduces the routing overhead. A Spray and Wait algorithm is proposed in the literature [23]. The algorithm is divided into two stages: the Spray stage and the Wait stage. In the Spray stage, the sender forwards the message carried by itself to the network in a certain amount, and enters the Wait stage if it does not send the message to the receiver. During the Wait stage, all nodes carrying the message transmit the information to the receiving end through the Direct Delivery strategy. The main advantage of the Spray and Wait algorithm is that the routing overhead is significantly smaller than the Epidemic algorithm, and it has better scalability and can be well adapted to OppNets of various sizes. The literature [24] proposed a routing algorithm based on the historical information (HBPR), which divides the network into different regional units and numbers them according to geographical locations. Each node uses GPS to record its own location information and count the most frequently visited areas. The source node transmits the message to a relay node that is geographically closer to the destination node, and continuously shortens the distance between the node carrying the message and the destination node, and achieves the effect of meeting the destination node and transmitting the message to it. In the literature [25], the SRBet routing algorithm is proposed. First, the algorithm uses the temporal evolution graph model to accurately capture the dynamic topology structure of the OppNet. Based on the model, the algorithm introduces the social relationship metric for detecting the quality of human social relationship from contact history records. Utilizing this metric, the algorithm proposes social relationship based betweenness centrality metric to identify influential nodes to ensure messages forwarded by the nodes with stronger social relationship and higher likelihood of contacting other nodes. The literature [26] proposed a protocol-social aware networking (SANE), it's the first forwarding strategy that combines the advantages of both social-aware and stateless approaches in OppNet (also called pocket switched network, PSN) routing. Although cosine distance is used in the literature [26] and this article, there are obvious differences. The SANE protocol sets an interest space for each node in the network, and represents the interest space as an m-dimensional vector. And the cosine distance is used to calculate the similarity between nodes' interest spaces. In this paper, we express the data packets of nodes by means of vectors, and the cosine distance is used to calculate the similarity between nodes' data packets. [PERSON] et al. [27] proposed a new sociable routing that selects a subset of optimal forwarders among all the nodes and relies on them for an efficient delivery.