eff-HAS: Achieve higher efficiency in data and energy usage on dynamic adaptive streaming

Kim, Seohyang; Oh, Hayoung; Kim, Chong-kwon

doi:10.1109/jcn.2018.000045

Cited by 7 publications

(3 citation statements)

References 46 publications

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“…Dynamic adaptive streaming over hypertext transfer protocol (HTTP), also known as MPEG‐DASH [2] or 3GP‐DASH [3], is a popular standard for video streaming on the internet. By storing different representations (e.g.…”

Section: Related Workmentioning

confidence: 99%

“…Content delivery of live video is typically streamed or downloaded using dynamic adaptive streaming over hypertext transfer protocol (DASH). During video transmission, the client provides real‐time radio information to the server, according to this information, the server will select an appropriate video bit rate version for the next transmission [2, 3]. However, due to cloud architecture flaws, cellular network fluctuations, and occasional congestion on the internet have seriously constrained real‐time streaming services.…”

Section: Introductionmentioning

confidence: 99%

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MEC‐enabled video streaming in device‐to‐device networks

et al. 2020

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

MEC‐enabled video streaming in device‐to‐device networks

et al. 2020

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“…Some studies dedicated to only use a buffer to complete the bitrate selection [13]- [17]. Some studies combine buffer and throughput information [18]- [21]. Some studies have turned to the use of Quality of Experience (QoE) as feedback rate choice research [22]- [26].…”

Section: Introductionmentioning

confidence: 99%

PREPARE-Playback RatE and Priority Adaptive BitRate Selection

et al. 2019

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HAS (HTTP-based Adaptive Streaming) based on ABR (Adaptive Bitrate Rate selection) has become a prevalent solution to media transmission. In order to improve the performance of HAS, many studies focus on how to reduce the unfairness, the instability and the inefficiency in a multi-clients scenario. However, the unfairness problem of the multi-clients with different priority levels and different playback rates, and the instability problem caused by the changes of the playback rate are still unresolved. To solve these problems, a novel ABR algorithm called PREPARE is proposed in this paper. In addition to normally considered throughput and client buffer information in HAS system model, the client priority and the playback rate are also incorporated to make the system model more accurate. With the feedback from servers, PREPARE algorithm is able to estimate the bandwidth much precisely and to reduce the unfairness among the multi-clients. The stability in bitrate selection is improved by introducing the buffer status in conjunction with the real-time playback rate. Moreover, the buffer underflow is prevented in download scheduling by advancing download according to the real-time playback rate. NS-3 simulator is used to evaluate the performance of PREPARE. The performance results show that PREPARE reduces the unfairness among multi-clients by more than 42% comparing to other three algorithms including ESTC, PANDA, FDASH. Meanwhile, PREPARE simultaneously keeps high stability and high efficiency. INDEX TERMS Streaming media, ABR, bitrate, bandwidth estimation. RUIXING SONG received the B.S. degree in communication engineering from the Huazhong University of Science and Technology, Wuhan, China, in 2014. She is currently pursuing the Ph.D. degree in signal and information processing with the

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MO-QoE: Video QoE using multi-feature fusion based Optimized Learning Models

Ghosh

Singhal

2022

Signal Processing: Image Communication

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eff-HAS: Achieve higher efficiency in data and energy usage on dynamic adaptive streaming

Cited by 7 publications

References 46 publications

MEC‐enabled video streaming in device‐to‐device networks

MEC‐enabled video streaming in device‐to‐device networks

PREPARE-Playback RatE and Priority Adaptive BitRate Selection

MO-QoE: Video QoE using multi-feature fusion based Optimized Learning Models

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