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On Trajectory-Based Network Construction for Time-Constrained Data Delivery in VANETs

机译:基于轨迹的网络构建VANET中时间受限的数据

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This paper discusses the time-constrained data delivery problem in vehicular ad hoc networks (VANETs). The unique characteristics of the network present great challenges to the issue. First, there are no always-connected forwarding routes between vehicles. Second, there is an intrinsic tradeoff between communication cost and delivery quality. Third, there is great uncertainty about vehicular mobilities. Exploiting vehicular trajectories, we present a constructive approach called TNC to tackle the challenges. In TNC, contact-based data forwarding and communication connections through the mobile network are incorporated. TNC first predicts the time-stamped inter-vehicle contacts and establishes expected contact graph, based on which it then computes the configuration for enhancing the connectivity of the network while introducing minimum number of mobile communication connections. Extensive simulations based on three real vehicular traces collected from 2,000 taxis and 1,400 buses in Shanghai, and 2,500 taxis in Shenzhen have been conducted and results demonstrate the efficacy of our approach.
机译:本文讨论了车辆自组织网络(VANET)中时间受限的数据传递问题。网络的独特特性给这个问题带来了巨大的挑战。首先,车辆之间没有始终连接的转发路线。其次,在通信成本和交付质量之间存在内在的权衡。第三,车辆的机动性存在很大的不确定性。利用车辆轨迹,我们提出了一种称为TNC的建设性方法来应对挑战。在TNC中,包含了通过移动网络进行的基于联系人的数据转发和通信连接。 TNC首先预测带时间戳的车辆之间的联系并建立预期的联系图,然后根据该联系图计算配置以增强网络的连接性,同时引入最少数量的移动通信连接。基于从上海的2,000辆出租车和1,400辆公交车以及深圳的2,500辆出租车收集的3条真实车辆轨迹进行的广泛模拟,结果证明了该方法的有效性。

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