Intelligent distributed routing scheme based on social similarity for mobile social networks

Abstract In mobile social networks (MSNs), the social attributes of nodes are important factors driving the mobility of nodes. By studying the mobility of the daily activities of node carriers, an intelligent distributed routing algorithm based on social context information prediction was proposed. First, we study the data forwarding problem of mobile social networks from two aspects, the daily behavior of mobile nodes and the similarity of social attributes respectively. Then, our algorithm uses BP neural network to predict the encounter regularity of mobile nodes in terms of time and space dimensions. This information can provide a basis for routing decisions. Finally, a routing algorithm with predictive capability is designed in combination with synchronous delivery and asynchronous delivery. Simulation analysis and experimental results show that the proposed routing algorithm can effectively improve the message delivery ratio and reduce the network overhead.

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