How to select proper relay nodes to ensure the successful delivery of messages is still a hot topic in delay tolerant networks (DTN). In this paper, we propose a probabilistic Spray-and-Wait routing algorithm based on node interest preference (called NIP-PSW). Firstly, considering the influence of the social attributes of nodes, we define a metric called node interest preference (NIP) to measure the probability of nodes becoming friends. Secondly, in view of the influence of node quality and connection time between nodes on message forwarding, we define the delivery probability (DP). Finally, according to the historical information of nodes, the node interest similarity (NIS) is proposed. In spray phase, NIP and DP are used to select the relay node and allocate the number of message copies adaptively. In wait phase, it is judged whether to forward the message to the encountering nodes again according to the NIS and the DP. In addition, the concept of message storage value (MSV) and the acknowledgment (ACK) mechanism are introduced to manage the buffer of nodes. The simulation results show that the NIP-PSW not only can significantly improve the delivery rate and reduce the average delay but also shows good performance in network overhead and average number of hops.

In delay-tolerant networks (DTN), node connection time and message transmission time are two important influencing factors that can improve the delivery rate. In this paper, we first define a new concept called communication capability (CC) and then apply this concept to the delivery predictability formulation in Prophet and improve it. Then, in Prophet, the selection of relay nodes relies only on the delivery predictability and ignores the caching and forwarding capability of the node. Therefore, we combine delivery predictability, buffering, and forwarding capability to develop a new adaptive relay node selection strategy. Subsequently, we define two metrics called message priority (MP) and message strength (MS). The node forwards messages sequentially based on message priority and discards messages based on message strength. Finally, we present a probabilistic routing algorithm based on node communication capability and message strength (CAMS). The simulation results show that compared with traditional routing algorithms, the CAMS can effectively improve the message delivery rate, reduce the overhead ratio, and keep average hop counts low.