Power Distribution Scheduling for Electric Vehicles in Wireless Power Transfer Systems
We study the presence of social communities in mobility traces from vehicular fleets. By analyzing publicly available sets of fleet vehicle mobility traces obtained from two real-world deployments - consisting of more than 2000 taxis in Shanghai and Beijing respectively, we confirm the existence of small numbers of distinct social communities in vehicular networks, which is in direct contrast to the general belief that vehicular networks are best modeled as a relatively homogeneous system. We examine the spatio-temporal characteristics of social communities, gaining the insight that they are driven primarily by social proximity induced by geographic locality. We then develop a parsimonious multi-community ordinary differential equation (ODE) model, which uses the heterogeneous structure introduced by social communities to model information dissemination. We show through simulations that this approach dramatically outperforms the conventional homogeneous ODE model in capturing the dynamics of the dissemination process. We further demonstrate that the use of the ODE model to optimize seeding of an initial set of vehicles results in improved utility for information dissemination compared to seed-optimization using a homogeneous model.