Exploiting Schelling behavior for improving data accessibility in mobile peer-to-peer networks

In 1969, Thomas Schelling proposed one of the most cited models in economics to explain how similar people (e.g. people with the same race, education, community) group together in American neighborhoods. Interestingly, we observe that the analogies of this model indeed exist in numerous scenarios where co-located people communicate via their personal wireless devices in Peer-to-Peer (P2P) fashion. Schelling's model therefore can potentially serve as a mobility model and offer a unique opportunity to efficiently disseminate messages in mobile P2P networks. In this paper, we exploit the natural grouping and moving behavior of humans presented by Schelling to expedite data dissemination in such networks. Particularly, we design a push model for dense network areas to maximize data dissemination and a pull model for sparse network areas to utilize network bandwidth and node energy efficiently. We ensure that our scheme is lightweight since queries and responses are automatically limited within groups of mobile nodes carried by similar people. Moreover, we avoid broadcast storms by assigning each message a broadcast timer and applying overhearing mechanism to reduce redundant transmissions. Finally, our simulation results show that the proposed data dissemination scheme improves the query hit ratio significantly while utilizing network bandwidth efficiently.