Traffic-Aware Data Delivery Scheme for Urban Vehicular Sensor Networks

Vehicular sensor network (VSN) is a promising technology which could be widely applied to monitor the physical world in urban areas. In such a scenario, the efficient data delivery plays a central role. Existing schemes, however, cannot choose an optimal route, since they either ignore the impact of vehicular distribution on connectivity, or make some unreasonable assumptions on vehicular distribution. In this paper, we propose a traffic-aware data delivery scheme (TADS). The basic idea of TADS is to choose intersections to forward packets dynamically as the route from a source to destination based on link quality and remaining Euclidean distance to destination. Specifically, we first present an optimal utility function as the criteria of intersection selection. Besides the packet forwarding through intersections, we also propose an improved geographically greedy routing algorithm for packet forwarding in straightway mode. Moreover, in order to decrease the routing overhead brought by the traffic information gathering, we build a traffic condition prediction model to estimate the link quality. The simulation results show that our TADS outperforms existing works on packet delivery ratio, end-to-end delay, and routing overhead.