TSF: Trajectory-based Statistical Forwarding for Infrastructure-to-Vehicle Data Delivery in Vehicular Networks

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TSF: Trajectory-based Statistical Forwarding for Infrastructure-to-Vehicle Data Delivery in Vehicular Networks

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2010-03-12

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We consider the scenarios where Internet access points are sparsely deployed in road networks to provide individual vehicles with customized road condition information for the driving safety, such as holes and bumps along their trajectories. Due to the limited communication coverage, vehicular ad-hoc networks are used to support the multi-hop data forwarding. State-of-the-art schemes have demonstrated their effectiveness in the data forwarding from vehicles to stationary points (e.g., Internet access points). However, they are not designed for the reverse data forwarding from Internet access points to vehicles, a much more challenging problem because of the mobility of the packet destination. This paper proposes a data forwarding scheme called Trajectory-based Statistical Forwarding (TSF), tailored for the infrastructure-to-vehicle data delivery in vehicular networks. TSF forwards packets over multi-hop to a selected target point where the vehicle is expected to pass by. Such a target point is selected optimally to minimize the packet delivery delay while satisfying the required packet delivery probability. The optimality is achieved analytically by utilizing the packet's delivery delay distribution and the destination vehicle's travel delay distribution. To our knowledge, this paper presents the first attempt to investigate how to effectively utilize the destination vehicle's trajectory to compute such an optimal target point. Through theoretical analysis and extensive simulation, it is shown that our design provides an efficient data forwarding under a variety of vehicular traffic conditions.

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Jeong, Jaehoon; Guo, Shuo; Gu, Yu; He, Tian; Hung-Chang Du, David. (2010). TSF: Trajectory-based Statistical Forwarding for Infrastructure-to-Vehicle Data Delivery in Vehicular Networks. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/215825.

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