Research On Time-Varying Character Of Information Transmission In Mobile Social Networks

Mobiles Social Network is a kind of Delay Tolerant Network (DTN) where the nodes have social relation of each other. In those networks, nodes mobility causes intermittent connectivity among nodes, so there is no steady path between an end-to-end pair, which brings big difficulties for the data transmission in the networks. DTNs employ a "store-carry-forward" mechanism to transfer data among DTN nodes; the key problem in it is how to select the proper next hop relay to transfer data packets. In recent years, some researchers have proposed several opportunistic routing which consider the nodes’sociality to help choosing the relay node, these mechanism have greatly improved the transmission efficiency in mobile social networks. While those routing mechanism cannot adapt the highly dynamic networks such as mobile social networks well. This paper analyzes the time-varying character in the mobile social networks, and then proposes a temporal social metric based opportunistic routing mechanism to improve the transmission efficiency in the networks.The paper first analyzes the flaws of static contact graph, which have been widely used in the traditional social DTN routing. While divide the static graph into several time-varying subgraphs, it proves that the static graph cannot capture the dynamic character of contacts between social nodes. So this paper proposes to describe and analyze the mobile networks by time-varying graph. While analyze the properties of time-varying graph, it finds that some of them accord with node contact rules in social networks and then proves it in real world data sets. It is useful to predict future contact by using time-varying graph. Through the above analysis, this paper improves the traditional static metrics and defines new temporal social metrics by adding the time element in the formula; these metrics can reveal the nodes’ real forwarding capability in the present moment. Then the paper sets a new opportunistic forwarding mechanism base on the temporal social metrics to improve the data handover rate in the networks. In order to verify the performance of this mechanism, a lot of simulations have been run in the opportunistic network environment simulator. The results prove this temporal social metric-based forwarding mechanism can effectively improve the information transmission efficiency in mobile social networks.