Error-Correction and Distributed-Storage for Wireless Video Streaming

无线视频流的纠错和分布式存储

• 批准号: RGPIN-2014-04019
• 负责人: Khisti, Ashish
• 金额: $ 2.26万
• 依托单位: University of Toronto
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=587556
• 关键词: Error; Correction; Distributed; Storage; Wireless

Video is considered to be the killer application in future wireless communication systems. Video traffic has dramatically increased in the last few years, and is projected to continue a similar trend in the future. The proposed research will develop highly efficient and scalable mechanisms for storage and communication of both on-demand and live-video. Novel techniques for authentication, quality-control, and security will be developed for our proposed solutions. The proposed research is divided into three topics, each of which addresses some immediate challenges in today's wireless networks. The first topic of the proposed research will investigate the theory and practice of streaming error-correction codes. Forward Error Correction (FEC) codes provide a natural mechanism for protecting video packets against errors over communication channels. In contrast to classical FEC, that have been studied for several decades, error correction for low-delay, real-time, video streaming applications remains a fertile area of research. Theoretical properties of streaming-codes will be studied and connections to the dynamical systems theory of convolutional codes will be made. On the practical side, new source and channel models will be developed based upon real-world applications and performance gains will be evaluated in realistic environments. Ultimately such streaming-codes could significantly increase the efficiency of high-end video conferencing systems, and make them affordable to small business owners. The second topic will develop a scalable mechanism for the distribution of video, using storage that will be available in next generation access points and base-stations. A particular focus will be on the optimal storage for HTTP Adaptive Bit-Rate Streaming --- the dominant mechanism for delivering on-demand video. Our proposed techniques will be assessed on a local testbed, consisting of software defined radios and a computer cluster at U of T, as well as a national testbed consisting of computing nodes at several universities across Canada. The proposed research will exploit an untapped resource --- caching in access points and base-stations --- to significantly reduce the congestion due to the explosive growth in mobile traffic and will provide a new cutting edge technology for mobile operators. The third topic will focus on security and privacy mechanisms in video distribution systems. Principles from distributed source coding will be used to develop a real-time authentication and quality-control mechanism in these systems. In a different direction, we will also develop novel approaches for providing privacy in a network of smart-meters. Smart-meters report real-time measurements of electricity usage, which can leak sensitive information about end users. To address this, novel techniques that mask the electricity consumption from utility companies by using local energy storage will be developed. Such techniques may be implemented in appliances such as plug-in hybrid vehicles, which already support built in mechanisms for energy storage at homes. The HQP in the proposed research will obtain expertise in some of the most pressing challenges faced by today's wireless industry: (1) efficient and scalable distribution of video traffic, and (2) security and privacy. Such a training will enable the HQP to contribute to standardization activities in wireless and multimedia, as well as in developing algorithms and architectures for next generation communication systems. The proposed topics closely align with the PI's long-term research program of creating a ubiquitous, reliable, and trustworthy data network, based on sound engineering principles, to support our economy and national infrastructure.

视频被认为是未来无线通信系统中的杀手级应用。视频流量在过去几年中急剧增加，预计未来将继续保持类似的趋势。拟议的研究将开发高效和可扩展的机制，用于存储和通信的点播和直播视频。将为我们提出的解决方案开发用于身份验证、质量控制和安全的新型技术。拟议的研究分为三个主题，每个主题都解决了当今无线网络面临的一些紧迫挑战。 本研究的第一个主题将探讨串流式错误校正码的理论与实务。前向纠错（FEC）码提供了一种用于保护视频分组免受通信信道上的错误的自然机制。 与已经研究了几十年的经典FEC相比，低延迟、实时、视频流应用的纠错仍然是一个肥沃的研究领域。将研究流式编码的理论特性，并将其与卷积码的动力系统理论相联系。在实践方面，将根据实际应用开发新的来源和渠道模型，并在现实环境中评估性能增益。最终，这样的流媒体代码可以显着提高高端视频会议系统的效率，并使小企业主负担得起。 第二个主题将开发一个可扩展的视频分发机制，使用下一代接入点和基站中可用的存储。 一个特别的重点将是HTTP自适应比特率流的最佳存储-提供点播视频的主导机制。我们提出的技术将在当地的测试平台上进行评估，该测试平台由软件定义的无线电和T大学的计算机集群组成，以及由加拿大几所大学的计算节点组成的国家测试平台。该研究将利用接入点和基站缓存这一尚未开发的资源，来显著减少由于移动的业务爆炸性增长而导致的拥塞，并将为移动的运营商提供一种新的前沿技术。 第三个主题将集中在视频分发系统中的安全和隐私机制。分布式源代码的原则将用于开发这些系统中的实时认证和质量控制机制。 在另一个方向，我们还将开发新的方法，在智能电表网络中提供隐私。智能电表报告用电量的实时测量结果，这可能会泄露有关最终用户的敏感信息。为了解决这个问题，将开发新技术，通过使用本地能源存储来掩盖公用事业公司的电力消耗。这样的技术可以在诸如插电式混合动力车辆之类的电器中实现，这些电器已经支持用于家庭能量存储的内置机制。 HQP在拟议的研究中将获得当今无线行业面临的一些最紧迫挑战的专业知识：（1）高效和可扩展的视频流量分配，以及（2）安全和隐私。这种培训将使HQP有助于无线和多媒体的标准化活动，以及为下一代通信系统开发算法和架构。拟议的主题与PI的长期研究计划密切相关，该计划旨在基于合理的工程原理创建一个无处不在，可靠和值得信赖的数据网络，以支持我们的经济和国家基础设施。