首页> 外文学位 >Caching and Adaptive Multiple Description Coding for Fine-grained Scalable Video Transmission
【24h】

Caching and Adaptive Multiple Description Coding for Fine-grained Scalable Video Transmission

机译:细粒度可伸缩视频传输的缓存和自适应多描述编码

获取原文
获取原文并翻译 | 示例

摘要

The problem of fine-grained scalable video multicasting to heterogenous users is considered. In this problem the scalable video data is channel-coded through multiple description over forward error correction (MD-FEC) coding, sent from the server to the intermediate node and then split to multiple users. We designed an algorithm to perform the adaptive MD-FEC at the server side that would allow the intermediate node to send an appropriate part of the original data to users with different network environments. Numerical results show that the adaptive MD-FEC algorithm can provide higher average Peak Signal-to-Noise Ratio (PSNR) performance than layered multiple description coding (MDC), simulcast with FEC, and conventional point-to-point MD-FEC. Secondly, we study the interaction of fine-grained scalable video coding (SVC) and caching. Fine-grained scalable video is applied at intermediate caches to allow online video users to fetch video clips at different qualities. Also, a cache space allocation algorithm is provided to optimize the average PSNR performance on the users' side. Moreover, the work of scalable video caching is extended to two-cache scenarios. Besides the cache space allocation algorithm, exclusive-or (XOR) network coding is also introduced to combine the sending of data from the server to each cache to reduce the backhaul bandwidth consumption. Numerical results with actual YouTube and Netflix Prize data set input show that the algorithm and network coding not only provide improved luma PSNR performance, but also reduce the backhaul data traffic. Finally we extend the two-cache scalable video caching model to a more generalized multiple-cache model. The problem is solved by grouping caches into pairs, which simplify it to a two-cache network coding problem. Various cache pairing algorithms, including maximum weighted matching and the heuristic algorithm, are applied to optimize the backhaul traffic saving and numerical results show that the proposed pairing algorithms can achieve higher backhaul traffic saving than not having inter-cache cooperations.
机译:考虑到向异构用户的细粒度可伸缩视频多播的问题。在此问题中,可伸缩视频数据通过前向纠错(MD-FEC)编码的多个描述进行通道编码,然后从服务器发送到中间节点,然后分配给多个用户。我们设计了一种在服务器端执行自适应MD-FEC的算法,该算法将允许中间节点将原始数据的适当部分发送给具有不同网络环境的用户。数值结果表明,与分层多描述编码(MDC),FEC同播和常规点对点MD-FEC相比,自适应MD-FEC算法可提供更高的平均峰值信噪比(PSNR)性能。其次,我们研究了细粒度可伸缩视频编码(SVC)与缓存的交互作用。细粒度的可伸缩视频应用于中间缓存,以允许在线视频用户获取不同质量的视频片段。另外,提供了一种缓存空间分配算法来优化用户端的平均PSNR性能。此外,可伸缩视频缓存的工作扩展到两个缓存方案。除了缓存空间分配算法外,还引入了异或(XOR)网络编码,以结合从服务器到每个缓存的数据发送,以减少回程带宽消耗。实际的YouTube和Netflix Prize数据集输入的数值结果表明,该算法和网络编码不仅提供改进的亮度PSNR性能,而且减少了回程数据流量。最后,我们将两缓存可扩展视频缓存模型扩展为更通用的多缓存模型。通过将高速缓存分成几对来解决该问题,从而将其简化为两个高速缓存的网络编码问题。应用各种缓存配对算法,包括最大加权匹配和启发式算法,以优化回程流量节省,数值结果表明,与不进行缓存间协作相比,所提出的配对算法可以实现更高的回程流量节省。

著录项

  • 作者

    Gong, Qiushi.;

  • 作者单位

    Rensselaer Polytechnic Institute.;

  • 授予单位 Rensselaer Polytechnic Institute.;
  • 学科 Communication.
  • 学位 Ph.D.
  • 年度 2018
  • 页码 141 p.
  • 总页数 141
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

  • 入库时间 2022-08-17 11:53:07

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号