Streaming Lower Quality Video over LTE: How Much Energy Can You Save?

Aqil, Azeem; Atya, Ahmed Osama Fathy; Krishnamurthy, Srikanth V.; Papageorgiou, George

doi:10.1109/icnp.2015.50

Cited by 9 publications

(9 citation statements)

References 23 publications

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“…Energy optimization for video transmission has been studied by many researchers. In [17], the authors developed a framework to estimate the energy consumption of the video based on the channel state and video characteristics. However, the unequal importance of multiple transmissions was not fully investigated.…”

Section: A Energy Optimization For Video Transmissionmentioning

confidence: 99%

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Energy Optimization For Wireless Video Transmission Employing Hybrid ARQ

Zhang

Cosman

Milstein

2019

IEEE Trans. Veh. Technol.

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Section: A Energy Optimization For Video Transmissionmentioning

confidence: 99%

“…The complexity of the proposed UEP algorithm is composed of two parts: parameter estimation of σ 2 0 and α, and solving Equations (16) and (17). The complexity for the first part depends on the algorithm of curve fitting and the complexity for the second part depends on the algorithm of solving the convex problem.…”

Section: B Complexity Analysismentioning

confidence: 99%

Energy Optimization For Wireless Video Transmission Employing Hybrid ARQ

Zhang

Cosman

Milstein

2019

IEEE Trans. Veh. Technol.

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“…Video coding affects the quality perception of video streaming as stated in literature [12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31]. A variety of video coding standards have been analysed in this context, such as H.264/ advanced video coding (AVC) or H.265/HEVC.…”

Section: Related Workmentioning

confidence: 99%

“…Furthermore, bitrate is related to the transmission efficiency. Simulation of video transmission with different resolutions has shown that higher resolution means higher quality [12,20,21,24,26,28], but also requires more bits to transmit through a network.…”

Section: Related Workmentioning

confidence: 99%

Impact of media-related SIFs on QoE for H.265/HEVC video streaming

Osmanovic¹,

Husić

Baraković

2018

JCOMSS

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Abstract-Long term evolution (LTE) has distinguished itself compared to other mobile broadband technologies in its ability to handle the growth of video traffic that has become an important part of user's mobile broadband experience. Growing trend of video consumption implies that that media-related system influence factors (SIFs) should be identified and well understood in order to determine how they affect the user's quality of experience (QoE). Therefore, this paper aims to provide a deeper understanding of media-related SIFs and their impact on QoE for video streaming. Experimental study has included two phases, i.e., H.265/ high efficiency video coding (HEVC) coded video streaming emulation over LTE network and end-user survey for collecting mean opinion score (MOS). The original scientific contribution of this study and its results is twofold. For the first time it has been shown that there exists strong and statistically significant impact of media-related SIFs and their interactions on QoE for H.265/HEVC video streaming, and a quantification of relation between QoE and selected media-related SIFs, i.e., prediction model has been provided. The knowledge of these impacts and interactions, as well as prediction model, contributes to increase the awareness of and improvement of video streaming service. This leads to better understanding of end user's QoE and provides a starting point for development of multidimensional QoE model.

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“…Even though there are a lot of enhancement already done in the previous studies that the problem of low battery lifespan is still intact and has become a key issue among smartphone users for video streaming online [2]- [6], [13]. Previously, some studies depicts that video content adaptation has a massive space for energy optimizationsthe optimization and alteration based on the modification of video content, application and algorithm [4], [7], [10]. Thus, the need of an energy-aware framework that satisfies user perspective and energy usage must be developed within a smartphone streaming environment.…”

Section: Introductionmentioning

confidence: 99%

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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Streaming Lower Quality Video over LTE: How Much Energy Can You Save?

Cited by 9 publications

References 23 publications

Energy Optimization For Wireless Video Transmission Employing Hybrid ARQ

Energy Optimization For Wireless Video Transmission Employing Hybrid ARQ

Impact of media-related SIFs on QoE for H.265/HEVC video streaming

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

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