Incentive mechanism for opportunistic social networks: the market model with intermediaries

The wide use of smart phones and other intelligent devices equipped for short-range wireless communications makes it possible for people to organize social activities via opportunistic social networks. However, message delivery can be easily disturbed due to the selfishness of nodes. This paper introduces a model of markets with intermediaries as an incentive scheme. On the basis of this model, an agent selection algorithm called "Ranger Algorithm" is proposed. Rangers refer to those users who not only have met with users in other communities for multiple times, but also have a higher probability of meeting those users. Experiments using MIT Reality Mining dataset is implemented and the effects of using market model with intermediaries as an incentive mechanism are analyzed. Results show that this model can effectively serve as an incentive mechanism to assist message delivery. In addition, this paper also finds that Ranger Algorithm outperforms other methods at improving communication performance. Based on the above work, a prototype system is built to help organize social activities.