A QoE-Aware Quality-Level Switching Algorithm for Adaptive Video Streaming

Azumi, Minoru; Kurosaka, Takumi; Bandai, Masaki

doi:10.1109/glocom.2015.7417622

Cited by 17 publications

(7 citation statements)

References 7 publications

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“…Many studies have been cited in this paper (Table ) to offer a view of the video streaming algorithms literature. These algorithms are classified into three categories based on network bandwidth (TBA), buffer monitoring (BBA), and hybrid algorithms, using combinations of TBA and BBA algorithms.…”

Section: Discussionmentioning

confidence: 99%

“…In the literature, several studies that propose ABR methods have been presented using the DASH standard. These studies can be classified into three types, which are based on the throughput rate (TBA), the buffer level (BBA), and the hybrid methods and use a combination of the BBA and TBA methods. Presented below and illustrated in Table are several studies proposing ABR methods.…”

Section: Related Workmentioning

confidence: 99%

“…These methods select the best video segment quality in order to ensure a good user experience (QoE). They are classified into three categories: throughput‐based methods (TBA), buffer‐based methods (BBA), and hybrid methods, using combinations of TBA and BBA methods.…”

Section: Introductionmentioning

confidence: 99%

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Q2ABR: QoE‐aware adaptive video bit rate solution

Amour

Souihi

Mellouk

2019

Int J Communication

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KEYWORDSadaptive bit rate streaming (ABR), breakpoint detection (BPD), boosting gradient regression (GBR), controlled-laboratory, mean opinion score (MOS), machine learning (ML), quality of experience (QoE), reinforcement learning, QoE assessment, streaming video Abbreviations: ABR, adaptive bit rate streaming; BPD, breakpoint detection; GBR, boosting gradient regression; ML, machine learning; MOS, mean opinion score; QoE, quality of experience; RL, reinforcement learning.Int J Commun Syst. 2020;33:e4204.wileyonlinelibrary.com/journal/dac

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

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Q2ABR: QoE‐aware adaptive video bit rate solution

Amour

Souihi

Mellouk

2019

Int J Communication

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“…Three different approaches have been introduced: traditional, machine learning-based, and edge computing-based approach. Most of the papers are written with the traditional approach, and the first ABR algorithms belong to this group [10][11][12][13][14]. There are three sub approaches in this approach: throughput-based, buffer-based, and a hybrid of those two.…”

Section: Introductionmentioning

confidence: 99%

“…There are three sub approaches in this approach: throughput-based, buffer-based, and a hybrid of those two. Throughput-based algorithms presented in [10][11], are characterized by high average bitrate, but they do not deal well with buffer underflow and the number of bitrate switches. Those algorithms use the calculation of throughput of the last delivered segment, and they set the bitrate of the next segment to that value.…”

Section: Introductionmentioning

confidence: 99%

Untitled

2023

Adv. Electr. Comp. Eng.

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Video streaming takes the largest share of internet traffic today, and MPEG dynamic adaptive streaming over HTTP (DASH) has become dominant among other video streaming standards and protocols. According to the DASH standard, multimedia content is encoded in different quality levels with different bitrates located on the server, and users can request multimedia content of any available bitrate. The user side determines the desired bitrate in the unit called adaptation bitrate (ABR) logic. Many ABR algorithms have been proposed to improve the quality of experience (QoE). The main criteria for determining QoE are average bitrate, number of switches between resolutions, and number of buffer underflows. This paper presents a hybrid DASH adaptation algorithm that uses the following input values: current buffer occupancy level, network throughput value calculated on the last downloaded DASH segment, and Takagi-Sugeno-Kang model output that represents expected throughput in the next segment download iteration. We compared the proposed algorithm with several other algorithms and the results show that it outperforms others in average bitrate and number of bitrate switches. Furthermore, our algorithm prevented all buffer underflows.

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Effective client-driven three-level rate adaptation (TLRA) approach for adaptive HTTP streaming

Kesavan

Jayakumar

2017

Multimed Tools Appl

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A QoE-Aware Quality-Level Switching Algorithm for Adaptive Video Streaming

Cited by 17 publications

References 7 publications

Q2ABR: QoE‐aware adaptive video bit rate solution

Q2ABR: QoE‐aware adaptive video bit rate solution

Untitled

Effective client-driven three-level rate adaptation (TLRA) approach for adaptive HTTP streaming

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