Social routing based on location preference prediction in DTN

In modern society, with the pad, smart phones and other wireless devices have a large number of wireless communication interface, people carry these devices that act as network nodes, the random movement of such a network has many characteristics of social networks. The social DTN also has many human social characteristics, such as high predictability and high similarity, so in this paper, we focus on effective routing among different regions. As for the real world, we can adjust the Spray strategy according to the regional prediction and the similarity of the encounter nodes to reduce the noneffective duplicate and decrease the consumption of networks resources. Simulation results show that compared with spray and wait routing, this algorithm could not only improve the delivery rate but also significantly reduce the average latency of network.