Dynamically Transient Social Community Detection for Mobile Social Networks

In mobile social networks (MSNs), mobile users communicate with each other via mobile devices, such as smartphones and tablets, transmitting data through intermittent connections. Mobile users have high mobility, which creates higher requirements for efficient data forwarding in MSNs. Therefore, forwarding data efficiently and quickly becomes a key problem. To tackle this problem, this article proposes a routing method based on a dynamic transient social community (DTSC) to optimize the routing and forwarding performance in MSNs. In this process, combined with the duration of intensive contact between nodes and the social relations of mobile users, the similarity of each pair of contact nodes is calculated, and community detection is carried out. Then, by analyzing the emergence mode of the DTSC, the measurement value and corresponding routing algorithm of the community's ability to deliver messages are designed. Our algorithm fully considers the duration of the node's direct encounter and the social connection of the indirect contact to ensure that the node can deliver successfully in a short time. The experimental results show that the DTSC has an excellent performance in data forwarding.