Transactions on Emerging Telecommunications Technologies (ETT) Quality of experience in wireless multimedia systems

2011 ◽  
Vol 22 (7) ◽  
pp. 433-434 ◽  
Keyword(s):  
Quality Of Experience ◽  
Multimedia Systems ◽  
Wireless Multimedia

ETT special issue on ‘Quality of Experience in Wireless Multimedia Systems’

2013 ◽  
Vol 24 (3) ◽  
pp. 257-258
Author(s):  
Markus Fiedler ◽  
Yuming Jiang ◽  
Kan Zheng ◽  
Periklis Chatzimisios ◽  
Wei Xiang
Keyword(s):  
Quality Of Experience ◽  
Multimedia Systems ◽  
Wireless Multimedia ◽  
Special Issue

A quality of experience handover architecture for heterogeneous mobile wireless multimedia networks

2013 ◽  
Vol 51 (6) ◽  
pp. 152-159 ◽  
Author(s):  
Jose Jailton ◽  
Tassio Carvalho ◽  
Warley Valente ◽  
Carlos Natalino ◽  
Renato Frances ◽  
...  
Keyword(s):  
Quality Of Experience ◽  
Multimedia Networks ◽  
Wireless Multimedia ◽  
Mobile Wireless

Recent Advances and Challenges in Wireless QoE-Aware Multimedia Streaming Systems

2012 ◽  
pp. 224-243
Author(s):  
Rosinei Oliveira ◽  
Ádamo L. Santana ◽  
João C. W. A. Costa ◽  
Carlos R. L. Frances ◽  
Elisangela Aguiar ◽  
...  
Keyword(s):  
Quality Of Experience ◽  
Video Quality ◽  
Similarity Index ◽  
Multimedia Streaming ◽  
Ieee 802.11E ◽  
Wireless Multimedia ◽  
Recent Advances ◽  
The Impact ◽  
Streaming Systems

It is expected that multimedia applications will be the most abundant application in the Internet and thousands of new wireless and mobile users will produce and share multimedia streaming content ubiquitously. In this multimedia-aware system, it is important to assure the end-to-end quality level support for video and voice applications in wireless systems. Traditional Quality of Service techniques assure the delivery of those services with packet differentiation assurance and indicate the impact of multimedia traffic only on the network performance; however, they do not reflect the user’s perception. Recent advances in multimedia are exploring new Quality of Experience approaches and including metrics and control schemes in wireless networking systems in order to increase the user´s satisfaction and optimize network resources. Operations based on Quality of Experience can be used as an indicator of how a networking environment meets the end-user’s needs and new assessment and packet control approaches are still important challenges. This chapter presents an overview of the most recent advances and challenges in assessment and traffic conditioner procedures for wireless multimedia streaming systems. In addition, an intelligent packet dropper mechanism for IEEE 802.11e systems is proposed and evaluated by using the Network Simulator 2, real video sequences and Evalvid tool. The benefit and the impact of the proposed solution is evaluated by using well-know objective and subjective Quality of Experience metrics, namely, Peak Signal-to-Noise Ratio, Video Quality Metric, Structural Similarity Index and Mean Option Score.

Quality of Experience: A New Paradigm for Resource Management in Wireless Multimedia Networks

2011 ◽  
Vol 4 (3) ◽  
pp. 177-187
Author(s):  
Kandaraj Piamrat ◽  
Adlen Ksentini ◽  
Cesar Viho ◽  
Jean-Marie Bonnin
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
Multimedia Networks ◽  
Wireless Multimedia ◽  
New Paradigm

Quality of Experience: A New Paradigm for Resource Management in Wireless Multimedia Networks

2011 ◽  
Vol 4 (3) ◽  
pp. 177-187
Author(s):  
Kandaraj Piamrat ◽  
Adlen Ksentini ◽  
Cesar Viho ◽  
Jean-Marie Bonnin
Keyword(s):  
Resource Management ◽  
Quality Of Experience ◽  
Multimedia Networks ◽  
Wireless Multimedia ◽  
New Paradigm

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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