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CAVD: A Traffic-Camera Assisted Live Video Streaming Delivery Strategy in Vehicular Ad Hoc Networks

机译:CAVD:车辆临时网络中的交通摄像机辅助实时视频流传递策略

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How to deliver live video streaming in vehicular ad hoc networks (VANETs) has been a hot topic in recent years. However, due to high vehicular speed, frequent disconnection and dynamic topology, it's difficult to guarantee the low-delay delivery of real-time data, and up to now, there exists no scheme that can deliver such kind of data with satisfied quality. In this paper, we take fully advantage of the existing wireless enabled traffic cameras, and propose CAVD, a novel live video streaming delivery strategy. As the core part of this strategy, we design an algorithm to adaptively select proper camera as Optimal Buffering Point (OBP) for each segment of live video streaming, and through the cooperations of these OBPs, the live video streaming could be delivered to a mobile target vehicle with the minimal start-up delay while satisfying the required visual quality and playback performance. Extensive simulations have been done on real-life taxi trace of Beijing, and the results show that our proposed strategy outperforms existing solutions greatly.
机译:如何在车辆临时网络中提供实时视频流(VANET)近年来一直是一个热门话题。但是,由于车速高,频繁断开和动态拓扑,难以保证实时数据的低延迟传送,现在,没有能够以满意的质量提供这种数据的方案。在本文中,我们充分利用了现有的无线交通摄像头,并提出了一种小说实时视频流传递策略。作为这种策略的核心部分,我们设计了一种算法,以便为实时视频流的每个段自适应地选择适当的摄像头(OBP),并且通过这些OBP的协作,可以将实时视频流传递给移动到移动目标车辆具有最小的启动延迟,同时满足所需的视觉质量和播放性能。在北京的现实出租车踪迹中已经完成了广泛的模拟,结果表明,我们提出的策略大大突出了现有解决方案。

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