The Relative Mobility of Vehicles Improves the Performance of Information Flow in Vehicle Ad Hoc Networks

Abstract

Vehicular ad hoc networks (VANET) are receiving significant attention due to their potential to provide a wide range of benefits. One key distinguishing feature of VANET from other ad hoc networks is their relative vehicular mobility. Therefore, to fully understand the significant benefits of these systems, it is necessary to understand the interaction between traffic flow characteristics and information propagation in VANET. This research presents an analytical model to characterize information flow in VANET incorporating macroscopic traffic characteristics, such as traffic density, relative speed between adjacent lanes, and driver composition. The information flow in VANET is characterized using an information flow network (IFN). The analytical expressions for the expected degree of the individual nodes as well as the reachability of an IFN are provided. Moreover, a state of the art simulation model is developed to validate the analytical results. The proposed analytical results not only provide us significant insights to evaluate the performance of information propagation in VANET, but also provide theoretical basis for the design of algorithms for the efficient routing of information based on average end-to-end performance.