scholarly journals User-Centric Quality of Experience Measurement

2014 ◽  
pp. 33-46 ◽  
Author(s):  
Bachir Chihani ◽  
Khalil ur Rehman Laghari ◽  
Emmanuel Bertin ◽  
Denis Collange ◽  
Noël Crespi ◽  
...  
Keyword(s):  
Quality Of Experience ◽  
User Centric

Quality of Experience (QoE) for Wireless Video Over Critical Communication Systems

2017 ◽  
pp. 132-167
Author(s):  
Emad Danish ◽  
Mazin I. Alshamrani
Keyword(s):  
Resource Allocation ◽  
Quality Of Service ◽  
Energy Consumption ◽  
Communication Systems ◽  
Quality Of Experience ◽  
Service Providers ◽  
Wireless Video ◽  
User Centric ◽  
Near Future

Video streaming is expected to acquire a massive share of the global internet traffic in the near future. Meanwhile, it is expected that most of the global traffic will be carried over wireless networks. This trend translates into considerable challenges for Service Providers (SP) in terms of maintaining consumers' Quality of Experience (QoE), energy consumption, utilisation of wireless resources, and profitability. However, the majority of Radio Resource Allocation (RRA) algorithms only consider enhancing Quality of Service (QoS) and network parameters. Since this approach may end up with unsatisfied customers in the future, it is essential to develop innovative RRA algorithms that adopt a user-centric approach based on users' QoE. This chapter focus on wireless video over Critical communication systems that are inspired by QoE perceived by end users. This chapter presents a background to introduce the reader to this area, followed by a review of the related up-to-date literature.

User-Centric Quality-of-Experience Optimization and Scheduling of Multicolor LEDs in VLC Systems

2019 ◽  
Vol 13 (3) ◽  
pp. 2275-2284 ◽  
Author(s):  
Xu Bao ◽  
Xinxin Gu ◽  
Wence Zhang ◽  
Hsiao-Hwa Chen
Keyword(s):  
Quality Of Experience ◽  
User Centric

scholarly journals Definition of QoE Fairness in Shared Systems

2017 ◽  
Author(s):  
Tobias Hobfeld ◽  
Lea Skorin-Kapov ◽  
Poul E. Heegaard ◽  
Martin Varela
Keyword(s):  
Quality Of Experience ◽  
System Optimization ◽  
Web Content ◽  
End User ◽  
Fairness Index ◽  
Application Management ◽  
Bottleneck Link ◽  
User Centric ◽  
Definition Of

IEEE Communications Letters Vol.21 Nr.1, 184-187 ; User-centric service and application management focuses on the quality of experience (QoE) as perceived by the end user. Thereby, the goal is to maximize QoE while ensuring fairness among users, e.g., for resource allocation and scheduling in shared systems. Although the literature suggests to consider consequently QoE fairness, there is currently no accepted definition of QoE fairness. The contribution of this letter is the definition of a generic QoE fairness index F , which has desirable key properties as well as the rationale behind it. By using examples and a measurement study involving multiple users downloading web content over a bottleneck link, we differentiate the proposed index from QoS fairness and the widely used Jain's fairness index. Based on results, we argue that neither QoS fairness nor Jain's fairness index meet all of the desirable QoE-relevant Properties, which are met by F . Consequently, the proposed index F may be used to compare QoE fairness across systems and applications, thus serving as a benchmark for QoE management mechanisms and system optimization.

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.

Sign in / Sign up

Export Citation Format

Share Document