scholarly journals Optimization of Quality of Experience for video traffic

2015 ◽  
Author(s):  
Qahhar Muhammad Qadir ◽  
Alexander A. Kist ◽  
Zhongwei Zhang
Keyword(s):  
Quality Of Experience ◽  
Video Traffic

Quality of Experience-based Routing of Video Traffic for Overlay and ISP Networks

2018 ◽  
Author(s):  
Giacomo Calvigioni ◽  
Ramon Aparicio-Pardo ◽  
Lucile Sassatelli ◽  
Jeremie Leguay ◽  
Paolo Medagliani ◽  
...  
Keyword(s):  
Quality Of Experience ◽  
Video Traffic

scholarly journals A Mobile Fog Computing-Assisted DASH QoE Prediction Scheme

2018 ◽  
Vol 2018 ◽  
pp. 1-10 ◽  
Author(s):  
Hongyun Zheng ◽  
Yongxiang Zhao ◽  
Xi Lu ◽  
Rongzhen Cao
Keyword(s):  
Quality Of Experience ◽  
Fog Computing ◽  
Video Quality ◽  
Adaptive Streaming ◽  
Network Operator ◽  
Video Traffic ◽  
Client Server ◽  
Prediction Scheme ◽  
Network Equipment

Video service has become a killer application for mobile terminals. For providing such services, most of the traffic is carried by the Dynamic Adaptive Streaming over HTTP (DASH) technique. The key to improve video quality perceived by users, i.e., Quality of Experience (QoE), is to effectively characterize it by using measured data. There have been many literatures that studied this issue. Some existing solutions use probe mechanism at client/server, which, however, are not applicable to network operator. Some other solutions, which aimed to predict QoE by deep packet parsing, cannot work properly as more and more video traffic is encrypted. In this paper, we propose a fog-assisted real-time QoE prediction scheme, which can predict the QoE of DASH-supported video streaming using fog nodes. Neither client/server participations nor deep packet parsing at network equipment is needed, which makes this scheme easy to deploy. Experimental results show that this scheme can accurately detect QoE with high accuracy even when the video traffic is encrypted.

scholarly journals Mechanisms for QoE optimisation of Video Traffic: A review paper

2020 ◽  
Author(s):  
qahhar muhammad qadir ◽  
Alexander A. Kist ◽  
ZHONGWEI ZHANG
Keyword(s):  
Quality Of Experience ◽  
Review Paper ◽  
End Users ◽  
The Internet ◽  
Video Traffic ◽  
Future Directions ◽  
The Past ◽  
New Methods ◽  
Increasing Demand

Transmission of video traffic over the Internet has grown exponentially in the past few years<br>with no sign of waning. This increasing demand for video services has changed user expectation of quality. Various mechanisms have been proposed to optimise the Quality of Experience (QoE) of end users’ video. Studying these approaches are necessary for new methods to be proposed or combination of existing ones to be tailored. We discuss challenges facing the optimisation of QoE for video traffic in this paper. It surveys and classifies these mechanisms based on their functions. The limitation of each of them is identified and future directions are highlighted.

scholarly journals Mechanisms for QoE optimisation of Video Traffic: A review paper

2015 ◽  
Vol 1 (1) ◽  
pp. 1-18 ◽  
Author(s):  
Qahhar Muhammad Qadir
Keyword(s):  
Quality Of Experience ◽  
Review Paper ◽  
The Internet ◽  
Video Traffic ◽  
Future Directions ◽  
The Past ◽  
New Methods ◽  
Video Services ◽  
Increasing Demand

Transmission of video traffic over the Internet has grown exponentially in the past few years with no sign of waning. This increasing demand for video services has changed user expectation of quality. Various mechanisms have been proposed to optimise Quality of Experience (QoE) of end user's video. Studying these approaches are necessary for new methods to be proposed or combination of existing ones to be tailored. We discuss challenges facing the optimisation of QoE for video traffic in this paper. It surveys and classifies these mechanisms based on their functions. The limitation of each of them is identified and future directions are highlighted.

scholarly journals A Novel Traffic Rate Measurement Algorithm for Quality of Experience-Aware Video Admission Control

2020 ◽  
Author(s):  
Alexander A. Kist ◽  
qahhar muhammad qadir ◽  
ZHONGWEI ZHANG
Keyword(s):  
Quality Of Experience ◽  
Service Providers ◽  
Video Quality ◽  
The Internet ◽  
Video Traffic ◽  
Internet Service ◽  
Trade Off ◽  
Available Bandwidth ◽  
Traffic Rate

With the inevitable dominance of video traffic on the Internet, providing perceptually good video quality is becoming a challenging task. This is partly due to the bursty nature of video traffic, changing network conditions and limitations of network transport protocols. This growth of video traffic has made Quality of Experience (QoE) of the end user the focus of the research community. In contrast, Internet service providers are concerned about maximizing revenue by accepting as many sessions as possible, as long as customers remain satisfied. However, there is still no entirely satisfactory admission algorithm for flows with variable rate. The trade-off between the number of sessions and perceived QoE can be optimized by exploiting the bursty nature of video traffic. This paper proposes a novel algorithm to determine the upper limit of the aggregate video rate that can exceed the available bandwidth without degrading the QoE of accepted video sessions. A parameter $\beta$ that defines the exceedable limit is defined. The proposed algorithm results in accepting more sessions without compromising the QoE of on-going video sessions. Thus it contributes to the optimization of the QoE-Session trade-off in support of the expected growth of video traffic on the Internet.

scholarly journals A quality of experience-aware cross-layer architecture for optimizing video streaming services

2020 ◽  
Author(s):  
qahhar muhammad qadir ◽  
Alexander A. Kist ◽  
ZHONGWEI ZHANG
Keyword(s):  
Video Streaming ◽  
Quality Of Experience ◽  
Video Quality ◽  
The Internet ◽  
Cross Layer ◽  
Video Traffic ◽  
Adaptive Architecture ◽  
Streaming Services ◽  
Simulation Results

The popularity of the video services on the Internet has evolved various mechanisms that target the Quality of Experience (QoE) optimization of video traffic. The video quality has been enhanced through adapting the sending bitrates. However, rate adaptation alone is not sufficient for maintaining a good video QoE when congestion occurs. This paper presents a cross-layer architecture for video streaming that is QoE-aware. It combines adaptation capabilities of video applications and QoE-aware admission control to optimize the trade-off relationship between QoE and the number of admitted sessions. Simulation results showed the efficiency of the proposed architecture in terms of QoE and number of sessions compared to two other architectures (adaptive architecture and non-adaptive architecture ).

scholarly journals Mechanisms for QoE optimisation of Video Traffic: A review paper

2020 ◽  
Author(s):  
qahhar muhammad qadir ◽  
Alexander A. Kist ◽  
ZHONGWEI ZHANG
Keyword(s):  
Quality Of Experience ◽  
Review Paper ◽  
End Users ◽  
The Internet ◽  
Video Traffic ◽  
Future Directions ◽  
The Past ◽  
New Methods ◽  
Increasing Demand

Transmission of video traffic over the Internet has grown exponentially in the past few years<br>with no sign of waning. This increasing demand for video services has changed user expectation of quality. Various mechanisms have been proposed to optimise the Quality of Experience (QoE) of end users’ video. Studying these approaches are necessary for new methods to be proposed or combination of existing ones to be tailored. We discuss challenges facing the optimisation of QoE for video traffic in this paper. It surveys and classifies these mechanisms based on their functions. The limitation of each of them is identified and future directions are highlighted.

scholarly journals QoE-Aware Cross-Layer Architecture for Video Traffic over Internet

2020 ◽  
Author(s):  
qahhar muhammad qadir ◽  
Alexander A. Kist ◽  
ZHONGWEI ZHANG
Keyword(s):  
Quality Of Experience ◽  
Rate Adaptation ◽  
Cross Layer ◽  
Foreseeable Future ◽  
Application Layer ◽  
Video Traffic ◽  
Transmission Rates ◽  
Active Video ◽  
Simulation Results

The emergence of video applications and video capable devices have contributed substantially to the increase of video traffic on Internet. New mechanisms recommending video rate adaptation towards delivering enhanced Quality of Experience (QoE) at the same time making room for more sessions. This paper introduces a cross-layer QoE-aware architecture for video traffic over the Internet. It proposes that video sources at the application layer adapt their rate to the network environment by controlling their transmitted bit rate dynamically; and the edge of network at the network layer protects the quality of the active video sessions by controlling the acceptance of new session through a video-aware admission control. In particular, it will seek the most efficient way of accepting new video session and adapting transmission rates to free up resources for more session while maintaining the QoE of active sessions. The proposed framework will contribute to the preparation for the extreme growth of video traffic in the foreseeable future. Simulation results show that the proposed cross-layer architecture guarantees the QoE for the admitted sessions and utilizes the link more efficiently comparing to the rate adaptation only architecture.

scholarly journals Optimization of Quality of Experience for Video Traffic

2020 ◽  
Author(s):  
qahhar muhammad qadir ◽  
Alexander A. Kist ◽  
ZHONGWEI ZHANG
Keyword(s):  
Quality Of Experience ◽  
Transmission Rate ◽  
Video On Demand ◽  
Video Traffic ◽  
Wired Networks ◽  
Internet Users ◽  
Strong Focus ◽  
Adaptive Architectures ◽  
Real Time Information

<div>The rapid shift toward video on-demand and real time information systems has affected mobile as well as wired networks. The research community has placed a strong focus on optimizing the Quality of Experience (QoE) of video traffic, mainly because video is popular among Internet users. Techniques have been proposed in different directions towards improvement of the perception of video users. This paper investigates the performance of a novel cross-layer architecture for optimizing the QoE of video traffic. The proposed architecture is compared to two other architectures; non-adaptive and adaptive. For the former, video traffic is sent without adaptation, whereas for the later video sources adapt their transmission rate. Both are compared in terms of the mean opinion score of video sessions, number of sessions, delay, packet drop ratio, jitter and utilization. The results from extensive simulations show that the proposed architecture outperforms the non-adaptive and adaptive architectures for video traffic.</div>

scholarly journals A Novel Traffic Rate Measurement Algorithm for Quality of Experience-Aware Video Admission Control

2020 ◽  
Author(s):  
Alexander A. Kist ◽  
qahhar muhammad qadir ◽  
ZHONGWEI ZHANG
Keyword(s):  
Quality Of Experience ◽  
Service Providers ◽  
Video Quality ◽  
The Internet ◽  
Video Traffic ◽  
Internet Service ◽  
Trade Off ◽  
Available Bandwidth ◽  
Traffic Rate

With the inevitable dominance of video traffic on the Internet, providing perceptually good video quality is becoming a challenging task. This is partly due to the bursty nature of video traffic, changing network conditions and limitations of network transport protocols. This growth of video traffic has made Quality of Experience (QoE) of the end user the focus of the research community. In contrast, Internet service providers are concerned about maximizing revenue by accepting as many sessions as possible, as long as customers remain satisfied. However, there is still no entirely satisfactory admission algorithm for flows with variable rate. The trade-off between the number of sessions and perceived QoE can be optimized by exploiting the bursty nature of video traffic. This paper proposes a novel algorithm to determine the upper limit of the aggregate video rate that can exceed the available bandwidth without degrading the QoE of accepted video sessions. A parameter $\beta$ that defines the exceedable limit is defined. The proposed algorithm results in accepting more sessions without compromising the QoE of on-going video sessions. Thus it contributes to the optimization of the QoE-Session trade-off in support of the expected growth of video traffic on the Internet.

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