Research on the Topological Evolution of Uncertain Social Relations in Opportunistic Networks
Gang Xu, Ming Zhang, Hai-He Jin, Yan Wang · 2017
In the opportunistic network with social attributes, message forwarding based on social relations often has good communication efficiency. The existing opportunistic network routing algorithms are based on the static social relations. But in practical application scenarios, the moving nodes make the network social relations dynamic evolution with time, so the social relation of the opportunistic network is uncertain. In order to solve the problem of unpredictable social relations of the opportunistic network, in this paper, we propose a social relations prediction model based on Markov. The Markov model is used to predict the evolution of the uncertain social relations. The experimental results show that the accuracy of the uncertain social relations is more than 80%.