9 research outputs found
A Bit Stream Feature-Based Energy Estimator for HEVC Software Encoding
The total energy consumption of today's video coding systems is globally
significant and emphasizes the need for sustainable video coder applications.
To develop such sustainable video coders, the knowledge of the energy
consumption of state-of-the-art video coders is necessary. For that purpose, we
need a dedicated setup that measures the energy of the encoding and decoding
system. However, such measurements are costly and laborious. To this end, this
paper presents an energy estimator that uses a subset of bit stream features to
accurately estimate the energy consumption of the HEVC software encoding
process. The proposed model reaches a mean estimation error of 4.88% when
averaged over presets of the x265 encoder implementation. The results from this
work help to identify properties of encoding energy-saving bit streams and, in
turn, are useful for developing new energy-efficient video coding algorithms.Comment: arXiv admin note: text overlap with arXiv:2207.0267
A pixel-based complexity model to estimate energy consumption in video decoders
The increasing use of HEVC video streams in diverse multimedia applications is driving the need for higher user control and management of energy consumption in battery-powered devices. This paper presents a contribution for the lack of adequate solutions by proposing a pixel-based complexity model that is capable of estimating the energy consumption of an arbitrary software-based HEVC decoder, running on different hardware platforms and devices. In the proposed model, the computational complexity is defined as a linear function of the number of pixels processed by the main decoding functions, using weighting coefficients which represent the average computational effort that each decoding function requires per pixel.
The results shows that the cross-correlation of frame-based complexity estimation with energy consumption is greater than 0.86. The energy consumption of video decoding is estimated with the proposed model within an average deviation range of about 6.9%, for different test sequences.info:eu-repo/semantics/publishedVersio
Comparative Study of Hardware and Software Power Measurements in Video Compression
The environmental impact of video streaming services has been discussed as
part of the strategies towards sustainable information and communication
technologies. A first step towards that is the energy profiling and assessment
of energy consumption of existing video technologies. This paper presents a
comprehensive study of power measurement techniques in video compression,
comparing the use of hardware and software power meters. An experimental
methodology to ensure reliability of measurements is introduced. Key findings
demonstrate the high correlation of hardware and software based energy
measurements for two video codecs across different spatial and temporal
resolutions at a lower computational overhead.Comment: 5 page
Extended Signaling Methods for Reduced Video Decoder Power Consumption Using Green Metadata
In this paper, we discuss one aspect of the latest MPEG standard edition on
energy-efficient media consumption, also known as Green Metadata (ISO/IEC
232001-11), which is the interactive signaling for remote decoder-power
reduction for peer-to-peer video conferencing. In this scenario, the receiver
of a video, e.g., a battery-driven portable device, can send a dedicated
request to the sender which asks for a video bitstream representation that is
less complex to decode and process. Consequently, the receiver saves energy and
extends operating times. We provide an overview on latest studies from the
literature dealing with energy-saving aspects, which motivate the extension of
the legacy Green Metadata standard. Furthermore, we explain the newly
introduced syntax elements and verify their effectiveness by performing
dedicated experiments. We show that the integration of these syntax elements
can lead to dynamic energy savings of up to 90% for software video decoding and
80% for hardware video decoding, respectively.Comment: 5 pages, 2 figure
Component-wise Power Estimation of Electrical Devices Using Thermal Imaging
This paper presents a novel method to estimate the power consumption of
distinct active components on an electronic carrier board by using thermal
imaging. The components and the board can be made of heterogeneous material
such as plastic, coated microchips, and metal bonds or wires, where a special
coating for high emissivity is not required. The thermal images are recorded
when the components on the board are dissipating power. In order to enable
reliable estimates, a segmentation of the thermal image must be available that
can be obtained by manual labeling, object detection methods, or exploiting
layout information. Evaluations show that with low-resolution consumer infrared
cameras and dissipated powers larger than 300mW, mean estimation errors of 10%
can be achieved.Comment: 10 pages, 8 figure
Sweet Streams are Made of This: The System Engineer's View on Energy Efficiency in Video Communications
In recent years, the global use of online video services has increased
rapidly. Today, a manifold of applications, such as video streaming, video
conferencing, live broadcasting, and social networks, make use of this
technology. A recent study found that the development and the success of these
services had as a consequence that, nowadays, more than 1% of the global
greenhouse-gas emissions are related to online video, with growth rates close
to 10% per year. This article reviews the latest findings concerning energy
consumption of online video from the system engineer's perspective, where the
system engineer is the designer and operator of a typical online video service.
We discuss all relevant energy sinks, highlight dependencies with
quality-of-service variables as well as video properties, review energy
consumption models for different devices from the literature, and aggregate
these existing models into a global model for the overall energy consumption of
a generic online video service. Analyzing this model and its implications, we
find that end-user devices and video encoding have the largest potential for
energy savings. Finally, we provide an overview of recent advances in energy
efficiency improvement for video streaming and propose future research
directions for energy-efficient video streaming services.Comment: 16 pages, 5 figures, accepted for IEEE Circuits and Systems Magazin
Modeling the Energy Consumption of the HEVC Decoding Process
In this paper, we present a bit stream feature-based energy model that accurately estimates the energy required to decode a given High Efficiency Video Coding-coded bit stream. Therefore, we take a model from literature and extend it by explicitly modeling the in-loop filters, which was not done before. Furthermore, to prove its superior estimation performance, it is compared with seven different energy models from the literature. By using a unified evaluation framework, we show how accurately the required decoding energy for different decoding systems can be approximated. We give thorough explanations on the model parameters and explain how the model variables are derived. To show the modeling capabilities in general, we test the estimation performance for different decoding software and hardware solutions, where we find that the proposed model outperforms the models from the literature by reaching framewise mean estimation errors of less than 7% for software and less than 15% for hardware-based systems