## 2 Related Works
### The Proposed Profile-Based Routing Algorithms  
The profile-based routing algorithm is more likely to adopt the contextual information to select a relay node from the neighbors. Meanwhile, the profile-based routing algorithm predicts the possibility of the future encounter between nodes through the historical meeting information, which is a major research orientation in OppNet. [PERSON] et al. [19] proposed the PRoPHET algorithm, which tries to copy message groups and to estimate the probability of successful message forwarding. Moreover, the algorithm effectively reduces invalid message group copies and improves the resource utilization. [PERSON] et al. [22] suggested the MaxProp routing algorithm based on setting the priority for message groups. When two nodes meet, the replication order is determined through the grouping priority of the node, and the message group with a low priority cannot obtain the data transmission opportunity, which helps to avoid generating the message group with inefficient message forwarding.  
[PERSON] et al. [23] presented a routing algorithm based on information transmission probability and cache management. This algorithm proposed that each node in the network can identify its surrounding neighbors by evaluating the meeting probability between them. Additionally, the node explores the special relationships with its neighbors and makes distribution adjustment for cache data. In [24], [PERSON] et al. recommended the MobySpace algorithm based on the MobySpace space. The length of the axis in MobySpace space represents the possibility of two nodes meeting each other. Moreover, the message carrier selects a suitable relay node as the next hop through the length of the axis. [PERSON] et al. [25] suggested a routing algorithm in a mobility pattern space (MV) based on node encounters and the historical record of node visiting an area. The algorithm proposed that the source node transmits message groups to the next hop by calculating and comparing the probability of the future meeting between users.  
In [26], [PERSON] et al. proposed a contact probability and data packet freshness perception routing algorithm based on the operation rule of opportunistic networks. This algorithm uses the previous contact information to calculate the average contact interval of two nodes, which can not only update the data packet but also gain enough delay for a utility function. Finally, the node makes the forwarding decision by the utility function and Epidemic algorithm [27]. [PERSON] and [PERSON] [28] recommended a social context-based routing algorithm based on context information prediction. This algorithm tries to predict the context information related to the node through historical communication statistics of nodes. Meanwhile, by analyzing this context information, the source node can make an accurate delivery decision as to where and when to send messages to the relay node. In [29], [PERSON] et al. presented a routing algorithm based on predicting node meeting location in OppNet. This algorithm is dedicated to predict the distance between nodes and to determine their current geographical position through the Markov model, and implements the efficient buffer management strategy.  
In this paper, the Predict and Forward routing algorithm proposed for opportunistic networks is based on the research, analysis and innovation of related works.