## 2 Related Works
### The Proposed Context-Aware Routing Algorithms  
In the proposed context-aware algorithms of opportunistic social networks, the similarity degree among nodes is usually used to evaluate transmission relationships between users, such as the future meeting probability between, the mobility patterns of, or the community division of users. [PERSON] et al. [15] presented a context-based social matching system based on the contextual information of nodes. This algorithm uses the relationships between and the social and personal context of users to predict the matching opportunities of data transmission between nodes. Meanwhile, the matching opportunity between users can be adopted to implement end-to-end communication in the network. To evaluate the impact of the position information of nodes, [PERSON] et al. [12] proposed a routing algorithm (PaSS) based on the social and positional similarities of nodes in opportunistic social networks. The PaSS scheme adopts the position and contact information of nodes to judge the degree of similarity between them. Moreover, in this algorithm, a node with a relatively high similarity degree to the destination may be a reliable relay node in the data transmission process. Nevertheless, the PaSS routing algorithm doesn't consider the time factor when determining the degree of similarity between a pair of nodes. In order to effectively evaluate the influence of the time factor, [PERSON] et al. [19] presented a new routing protocol (GD-CAR) based on the varying contextual information of each node. The GD-CAR routing algorithm collects and updates the constantly changing contextual information of nodes, determines the properties of the neighbors by executing the genetic search operation, and eventually forwards messages to the destination. In the GD-CAR scheme, the genetic search operation finds and collects only a small amount of social information of users in the networks, so the transmission relationships between users may not be accurately assessed.  
In context-aware algorithms, mathematical methods and models are often used to optimize the routing and forwarding of messages, such as the graph theory, set theory, or the Markov model. [PERSON] et al. [20] recommended a message delivery algorithm based on the graph theory and the context data of users in opportunistic smartphone networks. This algorithm uses a certain number of message replications to improve the delivery ratio of message forwarding, but only pays attention to the data information transmitted by nodes, which implies that the decision of message delivery is not always accurate in the data transmission process. [PERSON] et al. [21] proposed a context-based routing protocol based on the game theory in opportunistic networks. In this algorithm, the contextual information of nodes is used to establish a stable combination of contexts through the analysis and transformation of the game theory. [PERSON], [PERSON], and [PERSON] [22] recommended a context-based strategy based on human-centric information and crowd-sensing assignment in opportunistic social networks. This method only uses human-centric information of nodes to implement the individual coverage of a social vertex, and the data transmission process can be performed by using the graph theory.