## 2 Related Works
### The Proposed Context-Ignorant Routing Algorithms  
In opportunistic social networks, context-ignorant algorithms do not use the contextual information related to nodes to make suitable message delivery decisions in the data transmission process. Additionally, according to the context-ignorant algorithm, a mass of message copies will be diffused all over the network and the behavior of relay nodes can be reasonably used to transmit messages to the destination. [PERSON] et al. [23] proposed a community division algorithm based on multiple attribute similarities of nodes in opportunistic social networks. This strategy proposedthat each attribute of a node contains a series of keywords, and each keyword corresponds to a feature vector. Each user in opportunistic social networks may possess a great number of social attributes, and each social attribute of a node plays a different role in the data transmission process. Therefore, this algorithm attempts to give different weights to each keyword of node attributes and calculates the social similarity between nodes. [PERSON] and [PERSON] [16] recommended a socially-based routing algorithm using the location prediction of users, where the data transmission in this strategy is divided into two situations--i.e., the destination is an occasional contact node or a frequent contact node. This algorithm adopts a backpropagation neural network (BNN) model [24] to predict the future meeting probability of nodes, and the message carrier makes a suitable decision on when and where to transmit messages to the relay node. In this algorithm, the mobile periodicity of nodes is creatively adopted to predict the location and time of node encounters.  
Most context- ignorant algorithms may also focus on the interests of, the trust relationships between, or the influence of users in the community. [PERSON] et al. [25] recommended a routing algorithm based on the interest and trust models of users. This algorithm employs the interest and trust relationships of nodes to determine the similarity degrees between them. Meanwhile, the interest similarity between nodes can be obtained through the calculation and updating of users' attributes. In addition, the trust relationships between nodes can be employed to accurately assess the reliability of data transmission in opportunistic social networks. [PERSON] et al. [26] presented a routing-forwarding algorithm based on exploiting user interest similarity and social links for micro-blogging in opportunistic social networks. This scheme pays attention to the activities and interests of nodes, uses the push-based protocols of micro-blogs to forward utterance information, and adopts different methods to evaluate the friendship or interest similarity between nodes in real scenarios. Additionally, interest and trust management is also commonly used to ensure the secure mechanism of opportunistic social networks, [PERSON] et al. [27] proposed a secure routing algorithm (TRSS) based on the social similarity between nodes in opportunistic social networks. The TRSS scheme adopts a novel trust management mechanism to distinguish between malicious, selfish, misbehaving, and normal nodes in the networks, and attempts to determine the node's trustworthiness through special relationships between users.