Thesis (Ph.D.)--University of California, Irvine, 2007
Recent advances in processor, wireless and graphics technology have fueled a convergence of traditional PDA and cellphone functionality into complex, media-centric mobile devices. A popular class of applications emerging on these platforms is represented by multimedia, in particular content streaming (video, audio). However, all this added functionality has not come without an expense in one of the most important area for a mobile device: battery life. Multimedia streaming in particular, with its stringent computation, communication and quality of service requirements further aggravates battery life on these already constrained devices
On the other hand, multimedia applications have very regular execution patterns, the only changes being introduced by variations in the data stream itself. This thesis presents a new way to optimize power consumption for multimedia applications, based on content analysis and annotations. Specifically, we pre-process the multimedia streams and utilize annotations to capture and carry content-related information to the client device at the receiving end. Annotations allow us to perform more accurate and aggressive optimizations, with knowledge of the actual content and without relying to less accurate prediction models
We investigate the use of annotation for content-aware optimizations at all levels of abstraction (hardware/OS, network, application) for the most important system components in a mobile device: CPU/memory, network interface, display. Our experimental results show that important energy savings can be achieved for all these components through annotations. Finally, we integrate the techniques at all levels of abstraction for an increased user experience and battery functionality. We also show how cross-layer trade-offs between power and quality can lead to even higher energy savings with minimal quality degradation
