Collaborative Research: Redesigning Video Streaming Infrastructure to Systematically Reduce Mobile Device Video Display Energy Consumption in the Video-rich Era

摘要：本研究的目的是开发新的解决方案，可以系统地减少未来的视频丰富的移动的设备的能源消耗，通过重新发明整个视频流基础设施的设计。最小化显示器能量消耗具有很大的实际重要性，因为其占移动终端能量消耗的非常高的百分比。这项研究的意义在于，这是一种新的整体方法，其中从整个流媒体基础设施的角度来利用显示能量降低。这种方法是从探索每个移动终端上的能量减少的现有方案的范式转变，并且将为视频流传输到移动的设备开辟新的研究途径。这个高风险、高回报的项目具有超越本提案中提出的研究的更广泛和变革性的影响。首先，这项研究与以云为中心的信息技术基础设施的大趋势保持一致，并将为构建未来的视频流系统建立一个新的工业服务方向。其次，开发的算法，源代码和测量结果将在线提供给公众和广泛使用，使工业和学术研究人员受益。最后，对本科生和研究生的研究培训将培养出在信息技术和计算机行业具有多学科经验的研究人员和工程师。这项研究旨在克服目前在每设备处理方面的两个基本缺点：（一）从全局的角度来看，这是非常低效的节能，因为相同的计算将在接收到该请求的数千或数百万个移动的设备之间重复。相同的视频流。(2)由于在节省的显示能量和附加处理所需的能量之间的固有权衡，在设备级的非最佳显示能量减少阻止采用复杂的算法。本研究的智力价值在于开发了一种范式转换设计，将每设备本地处理移动到基于数据中心的全局处理，沿着对视频内容进行智能编码，以实现显示节能流。特别是，在这个项目中进行了两个主要的研究方向。为了将显示感知集成到视频流基础设施中，首先开发数据中心处的面向显示的视频处理以利用视频源特性和不同类别的移动的设备，以便生成一系列比特流，每个比特流具有用于在移动的设备处降低显示能量的嵌入式参数。然后，在移动的接入网关处的上下文感知视频适配被设计成转码视频比特流，以便匹配设备观看环境和无线信道状态，以增强体验质量（QoE）。为了克服视频流数量的增加导致的数据存储开销和视频缓存效率的下降，语法感知的视频数据重复数据删除在数据中心进行了研究，以减少数据存储开销。然后，数据中心辅助的通用转码在网关的开发，以减少视频缓存丢失惩罚在接入网关。最后，一个固态数据存储方案优化的视频缓存的设计，以充分利用闪存的视频缓存的潜力。

Abstract: The objective of this research is to develop novel solutions that can systematically reduce the energy consumption of future video-rich mobile devices through re-inventing the entire video streaming infrastructure design. Minimizing display energy consumption is of great practical importance since it accounts for a very high percentage of mobile device energy consumption. The significance of this research is that this is a new holistic approach in which display energy reduction is exploited from the entire streaming infrastructure point of view. Such an approach is a paradigm shift from existing schemes that explore the energy reduction on each mobile device and shall open up new research avenues for video streaming to mobile devices. This high-risk, high-payoff project has broader and transformational impact beyond the research proposed in this proposal. First, this research is well aligned with the grand trend towards cloud-centric information technology infrastructure and will establish a new industrial service direction on architecting future video streaming systems. Second, the developed algorithms, source code, and measurement results will be made available online for public and wide-range usage, benefiting both industrial and academic researchers. Finally, the research training to both undergraduate and graduate students shall produce researchers and engineers with multidisciplinary experience in information technology and computer industries.This research aims at overcoming two fundamental drawbacks of current practice in per-device processing: (1) highly inefficient energy saving from global perspective since the same computation shall be repeated among thousands or millions of mobile devices that receive the same video stream. (2) Non-optimal display energy reduction at device level because the inherent trade-off between saved display energy and the energy needed for additional processing is preventing from adopting sophisticated algorithms. The intellectual merit of this research lies in the development of a paradigm shifting design to move the per-device local processing to data center-based global processing along with the intelligent encoding of the video content for display energy efficient streaming. In particular, two major research directions are carried out in this project. To integrate display awareness into the video streaming infrastructure, display-oriented video processing at data centers is developed first to exploit video source characteristics and different classes of mobile devices in order generate a family of bitstreams, each with embedded parameters for display energy reductions at mobile devices. Then, a context-aware video adaptation at mobile access gateways is designed to transcode the video bitstreams in order to match device viewing environments and wireless channel status for enhanced quality of experience (QoE). To overcome increasing number of video streams leading to significant data storage overhead and degradation of video caching efficiency, a syntax-aware video data deduplication at data centers is investigated to reduce the data storage overhead. Then, a data center assisted universal transcoding at gateways is developed to reduce video cache miss penalty at access gateways. Finally, a solid-state data storage scheme optimized for video caching is designed to fully exploit the potential of using flash memory for video caching.