In this paper, we derive an accurate power model for video streaming which we condense to the essential components contributing the most to the overall power consumption. As a use case, we choose mobile devices on the receiver side performing video streaming in broadcasting or end-to-end scenarios. In modeling, we consider the complete video streaming toolchain, which mainly consists of data acquisition, video processing, display, and audio handling. We compose an overall power model with the help of models from the literature and propose a dedicated feature selection approach to reveal the most important factors related to power consumption. The resulting models achieve mean estimation errors below 7.61%. Results from feature selection indicate that the display brightness, the bitrate, and the frame rate have the highest impact on the power consumption.

This paper presents an efficient method for encoding common projection formats in 360 • video coding, in which we exploit inactive regions. These regions are ignored in the reconstruction of the equirectangular format or the viewport in virtual reality applications. As the content of these pixels is irrelevant, we neglect the corresponding pixel values in ratedistortion optimization, residual transformation, as well as inloop filtering and achieve bitrate savings of up to 10%.

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This paper derives optimal spatial scaling and rate control parameters for power-efficient wireless video streaming on portable devices. A video streaming application is studied, which receives a high-resolution and high-quality video stream from a remote server and displays the content to the end-user. We show that the resolution of the input video can be adjusted such that the quality-power trade-off is optimized. Making use of a power model from the literature and subjective quality evaluation using a perceptual metric, we derive optimal combinations of the scaling factor and the rate-control parameter for encoding. For HD sequences, up to 10% of power can be saved at negligible quality losses and up to 15% of power can be saved at tolerable distortions. To show general validity, the method was tested for Wi-Fi and a mobile network as well as for two different smartphones.

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