CSR: Small: Towards Energy-efficient Internet Mobile Streaming

如今，越来越多的人在他们的移动的设备上随时随地享受流媒体服务。然而，在移动的设备上接收流服务从根本上受到移动的设备上有限的电池电源的限制。在流会话中，大量的电池电力被持续消耗以用于经由无线网卡接收流数据、利用CPU解码接收到的数据以及在屏幕上显示解码的数据。虽然已经做出了显著的努力来节省电池功耗，但是由于设备硬件、操作系统和应用算法等的异构性，现有的流媒体实践带来了许多新的复杂性。这些复杂性导致降低的能量效率。本研究旨在探讨新的方案，以促进能源效率的互联网移动的流媒体服务在不同阶段，从数据接收到图像显示。该项目主要通过研究移动的设备上的数据传输调度，研究编解码器感知的动态电压和频率缩放，以及为移动的设备设计流会话中的动态内容自适应显示方案来解决这些挑战。新设计的方案可以直接帮助移动的设备显着提高流媒体服务的能量效率。在其他耗电量大的移动的应用中，它们也具有节省电池功耗的巨大潜力。研究成果将被纳入课程开发，参与的本科生和研究生将接受计算机系统研究经验的培训，成为下一代计算机科学家和工程师。

Today more people are enjoying streaming services on their mobile devices from anywhere at anytime. However, receiving streaming services on mobile devices is fundamentally constrained by the limited battery power supply on a mobile device. In a streaming session, a large amount of battery power is consumed continuously for receiving the streaming data via the wireless network card, decoding the received data with the CPU, and displaying the decoded data on the screen. Although significant efforts have been made to save the battery power consumption, the existing streaming practice brings many new complexities due to the heterogeneity of device hardware, operating systems, and application algorithms, etc. These complexities lead to degraded energy efficiency. This project aims to investigate new schemes to facilitate energy-efficient Internet mobile streaming services at different phases, ranging from the data receiving to the image displaying. The project addresses the challenges by mainly looking into the data transmission schedule on mobile devices, studying codec-aware dynamic voltage and frequency scaling, and devising dynamic content-adaptive displaying schemes for mobile devices in streaming sessions. The newly designed schemes can directly help mobile devices significantly improve the energy efficiency in streaming services. They also have great potentials to save battery power consumption in other power-hungry mobile applications. The research outcomes will be integrated into curriculum development and the participating undergraduate and graduate students will be trained with computer system research experience as the next generation computer scientists and engineers.