A game-theoretic incentive scheme for social-aware routing in selfish mobile social networks

Cooperative data forwarding can improve the performance of data routing in Mobile Social Networks (MSNs). However, previous studies mainly assumed that mobile nodes show selfish behaviors in data relaying merely due to their limited device resources. Nevertheless, the observation of everyday experience infers that they mitigate their selfishness based on their social relationships and content knowledge to achieve their social objective, i.e., they are socially selfish (SS). Therefore, how to promote SS nodes to participate in data forwarding becomes peculiarly challenging in MSNs. In this paper, we propose Game-theoretic Incentive Scheme for Social-aware rOuting, namely GISSO, to stimulate SS nodes in message relaying and guarantee that the routing performance gets maximized when SS nodes follow the scheme. First, we identify the social utility of each message to an intermediate node based on the strength of her social ties and message properties. Then, we apply an alternating-offers bargaining game in which SS nodes trade their messages with the aim of maximizing their social utility. We not only use subgame perfect Nash equilibrium as the agreement of two players to prove the efficiency of our game but also extensively evaluate the performance of GISSO using simulations over two real datasets. The comparison of GISSO with some benchmark social-aware protocols illustrates that GISSO overcomes SS nodes and outperforms the other algorithms regarding message delivery ratio and delay while generates low communication cost. Socially selfish mobile nodes mitigate their selfishness level to achieve their social objectives.A bargaining-based incentive scheme to stimulate selfish nodes in cooperation is proposed.Two real-world datasets with contact and social information are employed to evaluate the system.Experiments analyze the schemes performance in delivery ratio, delay, and cost.