Quality of Experience Inference for Video Services in Home WiFi Networks

2018 ◽  
Vol 56 (3) ◽  
pp. 187-193 ◽  
Author(s):  
Amir Ligata ◽  
Erma Perenda ◽  
Haris Gacanin
Keyword(s):  
Quality Of Experience ◽  
Wifi Networks ◽  
Video Services

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 Assessment of Quality of Experience (QoE) of Web and Video Services over a Mobile Network Using a Network Emulator

2020 ◽  
Vol 08 (05) ◽  
pp. 89-95
Author(s):  
Akpovi Ominike ◽  
Jonah Joshua ◽  
Oludele Awodele ◽  
Achimba Ogbonna
Keyword(s):  
Quality Of Experience ◽  
Mobile Network ◽  
Network Emulator ◽  
Video Services

scholarly journals Quality-of-experience assessment and its application to video services in lte networks

2015 ◽  
Vol 22 (1) ◽  
pp. 70-78 ◽  
Author(s):  
Kan Zheng ◽  
Xiaoli Zhang ◽  
Qiang Zheng ◽  
Wei Xiang ◽  
Lajos Hanzo
Keyword(s):  
Quality Of Experience ◽  
Lte Networks ◽  
Video Services

scholarly journals Providing 3D Video Services: The Challenge From 2D to 3DTV Quality of Experience

2012 ◽  
Vol 16 (4) ◽  
pp. 115-134 ◽  
Author(s):  
José María Cubero ◽  
Jesús Gutiérrez ◽  
Pablo Pérez ◽  
Enrique Estalayo ◽  
Julián Cabrera ◽  
...  
Keyword(s):  
Quality Of Experience ◽  
3D Video ◽  
Video Services

scholarly journals Peripheral Sensing: Monitoring Quality of Experience for Video Services Based on Mobile Terminals

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 92778-92790
Author(s):  
Xiwen Liu ◽  
Xiaoming Tao ◽  
Yafeng Zhan ◽  
Jianhua Lu
Keyword(s):  
Quality Of Experience ◽  
Mobile Terminals ◽  
Video Services ◽  
Monitoring Quality

Quality of Experience for Video Services

2010 ◽  
pp. 258-273
Author(s):  
Marcio Nieblas Zapater ◽  
Graça Bressan
Keyword(s):  
Quality Assurance ◽  
Performance Measures ◽  
Network Performance ◽  
Quality Of Experience ◽  
Ip Networks ◽  
End User ◽  
Services Delivery ◽  
Video Services ◽  
And Performance

This chapter discusses the quality assurance of multimedia services over IP networks from the end user standpoint and introduces the concept of quality of experience (QoE). The discussion of quality assurance includes aspects that range from the network and application layers to the end user perspective. The focus of the discussion presented in this chapter is oriented to the video services delivery that can be considered a significant evolution of services providers’ portfolio. This chapter presents quality requirements for video and TV services and performance measures that focuses on the quality perceived by the end user. This approach is broader than that oriented to quality of service (QoS), which focuses on the performance measures from the network perspective. QoE takes into account how well a service meet customers goals and expectations rather than focusing only on the network performance.

UBAR

2021 ◽  
Vol 20 (3) ◽  
pp. 1-25
Author(s):  
Elham Shamsa ◽  
Alma Pröbstl ◽  
Nima TaheriNejad ◽  
Anil Kanduri ◽  
Samarjit Chakraborty ◽  
...  
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
State Of The Art ◽  
State Of Charge ◽  
User Preference ◽  
Management Approach ◽  
High Quality ◽  
Trade Off ◽  
Run Time

Smartphone users require high Battery Cycle Life (BCL) and high Quality of Experience (QoE) during their usage. These two objectives can be conflicting based on the user preference at run-time. Finding the best trade-off between QoE and BCL requires an intelligent resource management approach that considers and learns user preference at run-time. Current approaches focus on one of these two objectives and neglect the other, limiting their efficiency in meeting users’ needs. In this article, we present UBAR, User- and Battery-aware Resource management, which considers dynamic workload, user preference, and user plug-in/out pattern at run-time to provide a suitable trade-off between BCL and QoE. UBAR personalizes this trade-off by learning the user’s habits and using that to satisfy QoE, while considering battery temperature and State of Charge (SOC) pattern to maximize BCL. The evaluation results show that UBAR achieves 10% to 40% improvement compared to the existing state-of-the-art approaches.

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