Power consumption and bandwidth savings with video transcoding to mobile device-specific spatial resolution

Dragić, Leon; Hofman, Daniel; Kovač, Mario; Žagar, Martin; Knezović, Josip

doi:10.1109/csndsp.2014.6923852

Cited by 2 publications

(7 citation statements)

References 9 publications

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“…VCA ={ νc (1) , νc (2) , νc (3) , νc (4) , νc (5) , νc (6) } Classification of VCA instances by sorting them down to the list and then the leaf node trees represent disjunction ^ of conjunctions of constraints on the attribute values of instances. Replacing if rule meets the condition of the energy-efficient, then the value will be resulting in weather is pruning or no pruning as follows: Then the value is map into the tree with a certain condition in order to compare the value for possible energyefficient variation.…”

Section: Resultsmentioning

confidence: 99%

“…c illustrates an energy consumption of smartphone specification devices while b is the baseline energy experiment that already done earlier. There are six variation of video content adaptation (νc (1) , νc (2) , νc (3) , νc (4) , νc (5) , νc (6) ). This tree of possible variation has two conditions to meet in order to pass the pruning level.…”

Section: Resultsmentioning

confidence: 99%

“…We alter these video formats into numerical order for experimental propose. VCA = νc (1) , νc (2) , νc (3) , νc (4) (5) 720p and νc (6) 1080p. This VCA can be added to equation 1 and compare with baseline and device energy.…”

Section: Video Content Selectionmentioning

confidence: 99%

“…This figure also shows the energy (mAh) versus video content adaptation νc (n) . All smartphone device specification δs are undergone with this experiments including video content adaptation (νc (1) , νc (2) , νc (3) , νc (4) , νc (5) , νc (6) ). The result shows the dissemination of scattered energy data.…”

Section: Video Content Selectionmentioning

confidence: 99%

“…Also, measuring the energy consumption on smartphone devices will face the challenge from across different applications, and its energy estimation is uncorrelated with execution time, suggesting experimenting method profilers may help in optimizing applications for energy use [14]. Many researchers focus on many methods of frameworks design, and the energy consumption based on a particular function, including software and instruments, approaches that the smartphone device needs to become an energy-efficient tool for the user to continue using their equipment [2], [3], [6] [14]. Another perspective has been engaged in the development of energy efficiency.…”

Section: Introductionmentioning

confidence: 99%

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PowerDoW (Power Digital Offset Weightage): Video Content-Adaptation (VCA) Profiling in Smartphone Devices for Energy Efficiency

Jofri

Lubis

Fudzee

et al. 2020

Int. J. Adv. Sci. Eng. Inf. Technol.

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Nowadays, the rapid enhancement of Internet connectivity and the recent progression of smartphone technologies lead to better smartphones quality towards video streaming activity. With the massive production of smartphone devices today, motivate studies of energy consumption behaviors to extend the smartphone device battery-life. Therefore, existing designs for smartphone devices occasionally lack energy-aware thus it need profiling optimization technique that reduces energy usage. Energy profiling in smartphone devices is one of the practical criteria for saving energy in smartphone devices during video streaming session. Energy efficiency features for smartphone devices, profiling and video content adaptation approach are the most critical parts for the energy-efficient while streaming in course. However, the consideration of energy-aware profiling area has not yet been discovered widely. In this case, appointing promising approaches will be used to reduce energy consumption in the smartphone devices during video streaming session. A framework called PowerDoW will be benefited towards adding energy adaptation strategies. PowerDoW framework manage and utilize system profiling status to attain the entire streaming session activity and classify the streaming video format depending on the selective video parameter. Selection of the best quality depending on low energy usage will be determined in the profiling experimentation. The experimentations are based on the Android operating system in smartphone devices—instrumentation setup testing by using PowerTutor application to measure energy consumption in real-time. The result indicates that PowerDoW framework can reduce a huge energy consumption by selecting suitable video content adaptation during video streaming session.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Video Content Selectionmentioning

confidence: 99%

Section: Video Content Selectionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

PowerDoW (Power Digital Offset Weightage): Video Content-Adaptation (VCA) Profiling in Smartphone Devices for Energy Efficiency

Jofri

Lubis

Fudzee

et al. 2020

Int. J. Adv. Sci. Eng. Inf. Technol.

View full text Add to dashboard Cite

show abstract

Power-Efficient Video Streaming on Mobile Devices Using Optimal Spatial Scaling

Herglotz

Kaup

Coulombe

et al. 2019

2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin)

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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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Power consumption and bandwidth savings with video transcoding to mobile device-specific spatial resolution

Cited by 2 publications

References 9 publications

PowerDoW (Power Digital Offset Weightage): Video Content-Adaptation (VCA) Profiling in Smartphone Devices for Energy Efficiency

PowerDoW (Power Digital Offset Weightage): Video Content-Adaptation (VCA) Profiling in Smartphone Devices for Energy Efficiency

Power-Efficient Video Streaming on Mobile Devices Using Optimal Spatial Scaling

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