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

机译:CAVD:车辆自组织网络中的交通摄像机辅助实时视频流传输策略

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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:近年来,如何在车辆自组织网络(VANET)中提供实时视频流已成为热门话题。然而,由于车辆速度高,频繁断开连接和动态拓扑,难以保证实时数据的低延迟传递,并且迄今为止,还没有一种方案能够以令人满意的质量传递此类数据。在本文中,我们充分利用了现有的启用无线功能的交通摄像头,并提出了一种新颖的实时视频流传输策略CAVD。作为此策略的核心部分,我们设计了一种算法,用于针对实时视频流的每个片段自适应地选择适当的摄像机作为最佳缓冲点(OBP),并且通过这些OBP的协作,可以将实时视频流传递到移动设备目标车辆,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。对北京的真实出租车轨迹进行了广泛的模拟,结果表明我们提出的策略大大优于现有的解决方案。

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