Context information prediction for social-based routing in opportunistic networks

Context information can be used to streamline routing decisions in opportunistic networks. We propose a novel social context-based routing scheme that considers both the spatial and the temporal dimensions of the activity of mobile nodes to predict the mobility patterns of nodes based on the BackPropagation Neural Networks model.