Incentive-Driven and Privacy-Preserving Message Dissemination in Large-Scale Mobile Networks

In this paper, we propose a new type of incentive-driven and privacy-preserving systems for large-scale message dissemination in mobile networks. To distribute incentives which encourage forwarding behaviors, such as monetary rewards, we want to keep track of the forwarder list. In our algorithms, we rely on a Probabilistic one-ownership forwarding algorithm to record the list, so that the exchanged messages can be kept short and privacy preserving. More specifically, only one hop of forwarder information, instead of the complete list, is recorded, and the information is updated probabilistically following two ownership flipping models, namely, One-Flip and Always-Flip models. We also use a Bluetooth Service Discovery Protocol (SDP) toolkit to enable fast, configuration-free message exchange. Throughout the paper, we use coupon as a typical type of message to illustrate the core ideas. We have implemented the coupon dissemination system in Java ME. Our experiments on real-world mobile phones, such as Nokia and Samsung phones, and large-scale simulations show that our system is efficient in peer-to-peer message distribution and capable of massive deployment. We believe our key methodology can serve as a general framework for facilitating information propagation on mobile phones, where incentives and privacy protection are both essential.