Social Relationship Enhanced Predicable Routing in Opportunistic Network

Routing is one of the most challenging problems in the opportunistic network owing to the occasion-connected mobile wireless environment. To overcome this weakness, many routing protocols have been put forward to solve it by exploiting the nodes´ mobility history. Meanwhile, to parallel the current trend of the social network, some of them design the solution by utilizing the social relationship characteristics from the real world. Nevertheless, few of these works could close the gap between the two totally different meanings and improve the efficiency of the whole network based on both. In this paper, we propose social relationship enhanced predicable routing (SREP) in the opportunistic network. The whole algorithm depends on this truth- the nodes in the opportunistic network only visits some defined place because of its necessary relationship with other people, thus we could adapt the semi-deterministic Markov process to model the behavior of the node. And we also introduce Page Rank algorithm to quantify social degree of node. The simulation shows that SREP is an effective routing protocol in a specific scenario based on the human motion.