Peer-Paired Collaboration for On-Demand Streaming Applications and an Improved Error Recovery Technique

Previous studies on streaming media networks have mainly focused on how to conserve the network bandwidth, especially the Internet backbone bandwidth, while maintaining a desired quality. This paper tackles the problem from another perspective, trying to improve the individual streaming quality while not increasing the backbone traffic. Specifically, we apply a peer-paired collaborative streaming architecture that exploits the power of peer-to-peer networking and extends the peer-paired collaboration from a live broadcasting scenario to the more general on-demand streaming scenario by introducing a unique catch-up scheme. Experimental results show that the peer-paired collaboration can bring about a significant performance gain for on-demand streaming application scenarios, in addition, we propose a forward error correction based error recovery technique that can resist up to 50% packet losses regardless of whether the losses are independent or shared.     

一种分布式视频点播系统管理模型及实现

作为典型的分布式多媒体应用 (DMA) ,分布式视频点播系统 (DVOD)的实用迫切需要一个能够支持开放环境的分布式管理框架。采用面向对象的建模语言—— U ML分析了 DVOD系统 ,建立了一个以分布式组件和目录服务为核心的模型 CD- Vod MS,该模型不但支持异构平台 ,而且具备良好的可扩展性和重用性。在此基础上 ,采用 CORBA规范和 L DAP服务器实现了一个 CD- Vod MS原型系统。另外还针对流式媒体 ,讨论了约会、 QOS、资源管理等等方面技术     

基于细粒度可扩展编码的多源视频流化方案

为解决现有多源流化方案存在的无法适应Internet网络异构性和动态性的问题,提出了一种新的多源流化方案.其中,传统的细粒度可扩展编码被改造成一种适合于多源流化的多子流传输模型.在此基础上,提出了基于优化峰值信噪比(PSNR)的多源流化码流分配算法.实验表明,较之平均分配码流,该算法能在相同条件下将视频的图像质量提高约1 dB.整个多源流化方案对于异构而动态变化的In-ternet网络环境具有良好的适应能力,可用于在内容分发网络(CDN)中提供流媒体服务.     

新的变码率视频服务器缓存管理策略

提出的 ROC(resist- overload capability)缓存管理策略 ,包括缓存准入策略和替换算法 ,解决了变码率视频服务器间隔缓存的缓存管理问题。 ROC缓存准入策略基于统计缓存准入策略 ,能提供概率的缓存服务质量保证和较高的缓存利用率。实验结果表明 :在典型系统配置下 ,ROC可以提高约 2 5 %的系统吞吐量 ;相对确定性缓存准入策略和STP- L缓存替换算法 ,可以多服务约 17%的视频流 ,平均缓存利用率也要高出约 38%。仿真实验结果证明了 :ROC充分发挥了间隔缓存算法优势 ,是一种非常有效的变码率视频服务器缓存管理策略     

Optimal Rate Allocation Algorithm for Multiple Source Video Streaming

Video streaming is one of the most important applications used in the best-effort Internet. This paper presents a new scheme for multiple source video streaming in which the traditional fine granular scalable coding was rebuilt into a multiple sub-streams based transmission model. A peak signal to noise ratio based stream rate allocation algorithm was then developed based on the transmission model. In tests, the algorithm performance is about 1 dB higher than that of a uniform rate allocation algorithm. Therefore, this scheme can overcome bottlenecks along a single link and smooth jitter to achieve high quality and stable video.