# Routing Algorithm Based on Trajectory Prediction in Opportunistic Networks
## 2 Related Work  
Many previous research results have shown that the acquisition of node location information has a very significant impact on the performance of the opportunistic network routing. At present, the way to obtain location information of nodes is mainly through location system. When a node transmits information, it only needs to obtain the location information of the neighbor and destination node to select the appropriate next-hop node, thus reducing the network resource overhead. Nodes only need to obtain location information, which can improve the utilization of network bandwidth. The distance between neighbors can be calculated by using location information, which can save energy consumption [13]. In recent years, the routing algorithm based on location information has many advantages over the routing algorithm based on network topology, so the routing protocol based on location information has attracted the attention of many researchers [14; 15; 16]. According to the routing strategies, location-based routing can be roughly divided into two categories: proactive routing protocol and reactive routing protocol. Among them, proactive routing protocols represent algorithms such as LOTAR, GPSR, DREAM, and reactive routing protocols represent algorithms such as LAR, GLS, DIG, etc. LAR routing protocol is a location aided routing algorithm. Based on the node location information, the algorithm finds the path of data transmission so as to narrow the routing search area and improve the data delivery ratio. In the LAR [9] algorithm, each node carries a positioning system that can obtain its current location information at any time, and assumes that each node in the network knows the mobility rate of other nodes. GLS [12] is a hierarchical routing protocol consisting of two parts: location information acquisition and data forwarding. The GLS algorithm divides the whole network into several small grids. The nodes in the grid periodically broadcast their own geographical location information. The other nodes update their own location information table according to the broadcast information. The nodes outside the grid act as the location information server through the selected nodes in the grid. By using these nodes to update and query the location information in time, the neighbor nodes closest to the destination node are selected as the next-hop data forwarding node. DREMA (Distance routing effect algorithm for mobility) [17] algorithm shows that each node in the network carries its own location information and periodically broadcasts the information. Other nodes in the network receive the location information, update and store the new location information in their own location information table. This method can effectively reduce the network control information overhead and ensure the accuracy of the link information. Although the algorithm has very good performance, it is not suitable for networks with relatively large network topology, and the performance of the algorithm will gradually decrease when the path between nodes does not exist. The approach in [18] proposes a Centrality History-Based Prediction Routing Protocol (CHBPR). The algorithm focuses on the use of the concept of centrality to achieve information transfer between nodes. Unlike other nodes in the network, the central node is more likely to act as a communication hub for message forwarding. [PERSON] et al. [19] proposed a centrally-based mechanism (HiBOp) to improve the performance of history-based routing protocols. GEAR [20] is an algorithm of greedy forwarding and energy efficiency. The core idea of the GEAR is to combine the energy information of each neighbor node with the distance between the neighbor node and the destination node when selecting the next-hop data forwarding node. GR (Greedy Routing) [21], the selection of the next-hop forwarding node must satisfy that the node is the closest distance to the target node among all neighbor nodes, and the distance is smaller than the distance from the current node to the target node.