An Extensible Distributed Measurement Platform for Analyzing Quality-of-Experience (QoE) of Multimedia Applications over Wireless Networks

Author(s):  
Y. W. Wong ◽  
W. C. Lau ◽  
K. M. Chan ◽  
Y. Yang ◽  
C. Y. Tang ◽  
...  
Electronics ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 318
Author(s):  
Merima Kulin ◽  
Tarik Kazaz ◽  
Eli De Poorter ◽  
Ingrid Moerman

This paper presents a systematic and comprehensive survey that reviews the latest research efforts focused on machine learning (ML) based performance improvement of wireless networks, while considering all layers of the protocol stack: PHY, MAC and network. First, the related work and paper contributions are discussed, followed by providing the necessary background on data-driven approaches and machine learning to help non-machine learning experts understand all discussed techniques. Then, a comprehensive review is presented on works employing ML-based approaches to optimize the wireless communication parameters settings to achieve improved network quality-of-service (QoS) and quality-of-experience (QoE). We first categorize these works into: radio analysis, MAC analysis and network prediction approaches, followed by subcategories within each. Finally, open challenges and broader perspectives are discussed.


Author(s):  
Elahe Kani-Zabihi ◽  
Nadia Hussain ◽  
Gebremariam Mesfin ◽  
Alexandra Covaci ◽  
Gheorghita Ghinea

Abstract Quality of Experience (QoE) is inextricably linked to the human side of the multimedia experience. Whilst there has been a considerable amount of research undertaken to explore the various dimensions of QoE, one facet which been relatively unexplored is the role of individual differences in determining an individual’s QoE. Whereas this is certainly true of multimedia applications, when it comes to mulsemedia (multiple media engaging three or more human senses) this is even more so, given its emerging and novel nature. Accordingly, in this paper we report the results of a study which investigated the role that individual differences (such as age, gender, education, and smell sensitivity) have on QoE, when mulsemedia incorporating olfactory and haptic stimuli is experienced in cross-modal environments. Our results reveal that whilst users had a satisfying overall mulsemedia experience the specific use of cross modally matched odours did not result in significantly higher QoE levels than when a control scent (rosemary) was employed. However, aspects of QoE are impacted upon by all individual differences dimensions considered in our study.


2012 ◽  
Vol 61 (3) ◽  
pp. 697-701
Author(s):  
Mikołaj I. Leszczuk ◽  
Eduardo Cerqueira ◽  
Marília Curado ◽  
Andreas Mauthe ◽  
Sherali Zeadally

2020 ◽  
Vol 12 (7) ◽  
pp. 121 ◽  
Author(s):  
Chaminda Hewage ◽  
Erhan Ekmekcioglu

Quality of Experience (QoE) is becoming an important factor of User-Centred Design (UCD). The deployment of pure technical measures such as Quality of Service (QoS) parameters to assess the quality of multimedia applications is phasing out due to the failure of those methods to quantify true user satisfaction. Though significant research results and several deployments have occurred and been realized over the last few years, focusing on QoE-based multimedia technologies, several issues both of theoretical and practical importance remain open. Accordingly, the papers of this Special Issue are significant contribution samples within the general ecosystem highlighted above, ranging from QoE in the capture, processing and consumption of next-generation multimedia applications. In particular, a total of five excellent articles have been accepted, following a rigorous review process, which address many of the aforementioned challenges and beyond.


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