Social-Aware Data Dissemination via Device-to-Device Communications: Fusing Social and Mobile Networks with Incentive Constraints

Nowadays, pervasive mobile devices not only pose new challenges for existing wireless networks to accommodate the surging demands, but also offer new opportunities to support various services. For example, device-to-device (D2D) communications provide a promising paradigm for data dissemination with low resource cost and high energy efficiency. In this paper, we propose a three-phase approach for D2D data dissemination, which exploits social-awareness and opportunistic contacts with user mobility. The proposed approach includes one phase of seed selection and two subsequent phases of data forwarding. In Phase I, we build a social-physical graph model, which combines the social network and the mobile network with opportunistic transmissions. Then we partition the social-physical graph into communities using the Girvan-Newman algorithm based on edge-betweenness, and select seeds for the communities according to vertex-closeness. In Phase II, data forwarding only takes place among socially connected users. In Phase III, the base station intervenes to enable data forwarding among cooperative users. For Phases II and III, we propose the new mechanisms for message selection and cooperation pairing, which take into account both altruistic and selfish behaviors of users. The theoretical analysis for the message selection mechanism proves its truthfulness and approximation ratio in the worst case. Extensive simulation results further demonstrate the effectiveness of the proposed three-phase approach with various synthetic and real tracing datasets.