Using the Model of Markets with Intermediaries as an Incentive Scheme for Opportunistic Social Networks

Abstract

The popularity of smart phones and other intelligent devices has made it possible for us to organize social activities by means of opportunistic social networks. However, message dissemination performance in opportunistic social networks is highly dependent on the cooperation between different users. In this paper, we put forward the model of markets with intermediaries as an incentive mechanism. In this model, users can overcome their selfishness in order to get profits, thus cooperation can be strengthened. Based on this incentive mechanism, we propose a broker selection algorithm: the Ranger Algorithm. Rangers are those users who not only have met with users in other communities for multiple times, but also have a high probability of meeting these users. Experiments are implemented using the MIT Reality Mining Dataset. Results show that the model of markets with intermediaries can serve as an incentive mechanism to stimulate collaboration, and Ranger Algorithm outperforms other baseline algorithms in improving message dissemination performance. On the basis of the above work, a prototype system is built to help organize offline social activities.