NeTS: Small: Flexible Delivery of Streaming Video using Network-Aware MD-FEC Coding

NeTS：小型：使用网络感知 MD-FEC 编码灵活传输流视频

• 批准号: 1018398
• 负责人: Koushik Kar
• 金额: $ 40万
• 依托单位: Rensselaer Polytechnic Institute
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-07-01 至 2015-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1018398&HistoricalAwards=false
• 关键词: NeTS; Small; Flexible; Delivery; Streaming

Streaming video is envisioned to become the ?killer? networking application in the coming decade, and may determine whether the Internet and the current wireless technologies will live up to the explosive growth of multimedia demands of the next-generation network users. This project aims to develop coding and distribution mechanisms for transferring video over networks in a scalable and effective manner, which will be critical in meeting this challenge. In particular, the project investigates the design of a broad theoretical framework as well as specific mechanisms that would enable efficient delivery of streaming video through the use of video distribution networks (VDNs) and ?network-aware? Multiple Description Forward Error Correction (MD-FEC) coding. MD-FEC can be very effective in minimizing the overall distortion in video quality when delivering streaming video in a typical network environment that experiences time-varying bandwidth fluctuations and random packet losses. The project also explores how network coding can be integrated with MD-FEC coding to enhance live video streaming performance. This cross-disciplinary research is being done through a closely-integrated effort by an interdisciplinary team bringing together expertise in the areas of video coding and information theory; and network modeling, optimization and simulation. The results of this research project are expected to provide key insights on how streaming live video should be delivered for optimal performance over the Internet and last-hop wireless networks in the future. Proactive efforts are also being taken towards integrating the research findings into related graduate courses, and involving undergraduates in these research activities.

设想流媒体视频成为“杀手”吗？在未来十年中，网络应用程序可以确定Internet和当前的无线技术是否会辜负下一代网络用户多媒体需求的爆炸性增长。该项目旨在开发以可扩展有效的方式通过网络传输视频的编码和分发机制，这对于应对这一挑战至关重要。特别是，该项目研究了一个广泛的理论框架的设计以及可以通过使用视频发行网络（VDN）和“网络感知的”来实现有效传输视频的特定机制？多重描述向前误差校正（MD-FEC）编码。 MD-FEC在典型的网络环境中传递流媒体视频时，可以非常有效地最大程度地减少视频质量的整体失真，从而体验到时变带宽波动和随机数据包损失。该项目还探讨了如何将网络编码与MD-FEC编码集成，以增强实时视频流性能。这项跨学科研究是通过跨学科团队紧密融合的努力来完成的，在视频编码和信息理论领域汇集了专业知识。以及网络建模，优化和仿真。预计该研究项目的结果将提供有关如何在未来通过Internet和最后一跳无线网络提供流媒体实时视频的关键见解。还为将研究结果纳入相关的研究生课程，并参与这些研究活动而采取积极的努力。