Selfish mules: Social profit maximization in sparse sensornets using rationally-selfish human relays

Future smart cities will require sensing on a scale hitherto unseen. Fixed infrastructures have limitations regarding sensor maintenance, placement and connectivity. Employing the ubiquity of mobile phones is one approach to overcoming some of these problems. Here, mobility and social patterns of phone owners can be exploited to optimize data forwarding efficiency. The question remains, how can we stimulate phone owners to serve as data relays? In this paper, we combine network science principles and Lyapunov optimization techniques, to maximize global social profit across this hybrid sensor and mobile phone network. Sensor data packets are produced and traded (transmitted) over a virtual economic network using a lightweight social-economic-aware backpressure algorithm, combining rate control, routing, and resource pricing. Phone owners can get benefits through relaying sensor data. Our algorithm