Incentive evolutionary game model for opportunistic social networks

Opportunistic social networks transmit messages through the way of nodes cooperation. Because it is a kind of fully open networks, message forwarding is vulnerable to interference from abnormal nodes such as selfish and malicious nodes, who may result in disorder of network transmission. In order to suppress the bad impact on the network from those abnormal nodes, an incentive evolutionary game model for stimulating cooperation among nodes is proposed in this paper. By constructing our game model in routers, normal nodes and abnormal nodes are both encouraged to participate in network collaboration by self-evolution of gaming. Then after evolution, the entire network can reach a general cooperative state of nodes. In order to guide the evolution of gaming, a credit based incentive approach is proposed. The reward and punishment factor is designed in the revenue payment function of the game. The effectiveness is that the cooperative behavior is rewarded, and the non cooperative behavior is punished. Besides, nodes can update their policies of interaction with others by imitating their neighbors. The proposed model is implemented in several popular routers of opportunistic networks, and various scenarios are simulated. The experiments evaluate the performance of proposed model in terms of effectiveness, performance and scalability. The results show that our model is effective to improve the network performance when there are selfish nodes or malicious nodes, and It can be extended to a variety of network sizes. Besides, our incentive evolutionary game model can be easily applied to the current popular routers of opportunistic networks.