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Video transport over VANETs: Multi-stream coding with multi-path and network coding

机译:VANET上的视频传输:具有多路径和网络编码的多流编码

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The emerging and promising Vehicular Ad hoc Networks (VANET) are receiving a lot of attention from both industry and academia due to the wide variety of services such as safe navigation support, entertainment and many more. Providing robust and reliable dissemination of data over VANET is the key issue. Due to varying network topology packet loss and delay are very common in such type of networks which severely influence the perceived video quality at receiving end. We need reliable transmission protocols for text data dissemination while the video data can tolerate a certain amount of packet loss. Therefore, we are more interested in robust Scalable Video Coding (SVC) based streaming over VANET for multi-purpose including safe navigation support, because SVC is a very good solution to alleviate the effects of the error-prone channels. In this paper, we propose a robust scheme for SVC-based streaming over an urban VANET with path diversity and network coding. The scheme calculates the quality of all candidate paths based on Grey Relational Analysis (GRA) and then assigns paths to different layers according to their importance. We also select some nearby nodes along the transmission path for recoding their received packets and store them in buffers for unit period of time. These network coded packets can be retransmit to receivers for recovering lost packets.
机译:由于安全导航支持,娱乐等多种服务,新兴且前景广阔的车载自组织网络(VANET)受到了业界和学术界的广泛关注。关键问题是通过VANET提供可靠而可靠的数据分发。由于网络拓扑结构的变化,分组丢失和延迟在这种类型的网络中非常普遍,这严重影响了接收端的感知视频质量。我们需要可靠的传输协议来分发文本数据,而视频数据可以容忍一定数量的数据包丢失。因此,我们对基于VANET的健壮可扩展视频编码(SVC)流进行更多兴趣,可用于包括安全导航支持在内的多种用途,因为SVC是减轻易错信道影响的非常好的解决方案。在本文中,我们提出了一种健壮的方案,用于在具有路径分集和网络编码的城市VANET上基于SVC的流。该方案基于灰色关联分析(GRA)计算所有候选路径的质量,然后根据其重要性将路径分配给不同的层。我们还沿着传输路径选择一些附近的节点,以对其接收到的数据包进行重新编码,并将它们存储在缓冲区中一段时间​​。这些网络编码的数据包可以重新发送到接收器,以恢复丢失的数据包。

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