面向移动内容中心网络的动态自适应流媒体技术研究

发布时间：2018-08-26 17:38

【摘要】：面向大规模用户的流媒体视频服务已经成为移动互联网上最主要的应用之一。移动流媒体服务占据了移动网络流量的很大部分,并且呈不断上升的趋势。移动环境的连接不稳定,带宽有限等特点,造成了移动终端观看视频的高时延,缓冲频繁,视频质量低等问题。动态自适应流媒体技术(DASH)支持用户根据设备能力与实时网络端到端带宽情况调整请求的媒体质量,可以自适应选择合适的码率播放视频,适合在移动网络提供平滑稳定的视频播放。内容中心网络(CCN)是一种新型网络架构,以内容为中心,不需要内容与节点位置的映射,对移动流媒体服务支持性较好。现有的DASH方案无法适应于移动CCN网络的特性,直接在移动CCN网络部署DASH服务会带来码率自适应低效,网络拥塞,缓存利用率低等问题。针对上述问题,本文提出了一系列面向移动内容中心网络的DASH技术研究方案,具体研究内容包括:(1) 一种面向移动内容中心网络的DASH解决方案,具体包括自学习的码率选择策略与兴趣包泛洪的控制机制,提升了 DASH服务的用户体验质量;(2)设计了一种针对CCN网络数据包的分层权重衡量方式,考虑了可伸缩视频编码(SVC)的不同分层的编解码特点与数据包的内容流行度,提升了数据包传输效率;(3)提出了一种可以提升移动CCN网络自适应流媒体服务的用户体验质量的缓存管理机制,在广播范围内将不同SVC分层数据包主动渐进式推送给移动节点,利用SVC编码的可拓展性提升了内容分发效率。为了评估方案的性能,本文搭建了基于NdnSIM仿真平台的移动仿真场景,分别进行了仿真验证。实验表明,算法从多个方面提升了移动流媒体用户体验质量。
[Abstract]:Streaming video service for large-scale users has become one of the most important applications on mobile Internet. Mobile streaming media service accounts for a large part of mobile network traffic and is on the rise. The unstable connection and limited bandwidth of mobile environment lead to the problems of high delay, frequent buffering and low video quality. The dynamic adaptive streaming media technology (DASH) allows users to adjust the media quality of the request according to the device capability and the end-to-end bandwidth of the real-time network, and can adaptively select the appropriate bit rate for playing video. Suitable for providing smooth and stable video playback in mobile networks. Content-centric network (CCN) is a new network architecture, which is content-centric and does not need mapping between content and node location, so it has good support for mobile streaming media services. The existing DASH schemes can not adapt to the characteristics of mobile CCN networks. The deployment of DASH services in mobile CCN networks will bring some problems, such as low rate adaptive efficiency, network congestion, low cache utilization and so on. In view of the above problems, this paper proposes a series of DASH technology research schemes for mobile content center network. The specific research contents include: (1) A DASH solution for mobile content center network. Specifically including the self-learning rate selection strategy and interest packet flooding control mechanism to improve the quality of user experience of DASH services. (2) designed a hierarchical weight measurement method for CCN network packets. Considering the different layered encoding and decoding characteristics of scalable video coding (SVC) and the popularity of packet content, (3) A buffer management mechanism which can improve the user experience quality of mobile CCN network adaptive streaming media service is proposed to push different SVC layered packets to mobile nodes in broadcast range. The extensibility of SVC coding improves the efficiency of content distribution. In order to evaluate the performance of the scheme, a mobile simulation scene based on NdnSIM simulation platform is built and verified. Experiments show that the algorithm improves the user experience quality of mobile streaming media from many aspects.
【学位授予单位】：北京邮电大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP393.02

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