On Quality of Experience in Remote Visualization on Mobile Devices

2012 ◽  
pp. 1-19
Author(s):  
Gianluca Paravati ◽  
Andrea Sanna ◽  
Fabrizio Lamberti ◽  
Luigi Ciminiera
Keyword(s):  
Mobile Devices ◽  
User Satisfaction ◽  
Quality Of Experience ◽  
Experimental Tests ◽  
Frame Rate ◽  
Remote Visualization ◽  
Server Side ◽  
Compressed Images ◽  
Novel Approach

Quality of Experience (QoE) is a relatively new concept which represents a way of measuring user satisfaction in the use of a certain kind of service. This work investigates issues related to the QoE in manipulating 3D scenes on mobile devices, by focusing on scenarios based on the remote visualization paradigm where a remote server is in charge of computing a flow of compressed images to be delivered to client devices. A novel approach able to dynamically set the encoding parameters at the server side is presented; the considered parameters are frame resolution, frame rate and image quality. The proposed solution is able to tune the above parameters according to both user preferences and network performance. Experimental tests are exploited to assess the relationship between the involved parameters and the QoE. Results obtained by considering low resource hardware (e.g. mobile devices) and unreliable connections (e.g. wireless networks) are presented. User feedback proves the effectiveness of the proposed approach.

On Quality of Experience in Remote Visualization on Mobile Devices

2010 ◽  
Vol 2 (1) ◽  
pp. 1-20 ◽  
Author(s):  
Gianluca Paravati ◽  
Andrea Sanna ◽  
Fabrizio Lamberti ◽  
Luigi Ciminiera
Keyword(s):  
Mobile Devices ◽  
User Satisfaction ◽  
Network Performance ◽  
Quality Of Experience ◽  
Experimental Tests ◽  
User Preferences ◽  
Frame Rate ◽  
Remote Visualization ◽  
Server Side

Quality of Experience (QoE) is a relatively new concept which represents a way of measuring user satisfaction in the use of a certain kind of service. This work investigates issues related to the QoE in manipulating 3D scenes on mobile devices, by focusing on scenarios based on the remote visualization paradigm where a remote server is in charge of computing a flow of compressed images to be delivered to client devices. A novel approach able to dynamically set the encoding parameters at the server side is presented; the considered parameters are frame resolution, frame rate and image quality. The proposed solution is able to tune the above parameters according to both user preferences and network performance. Experimental tests are exploited to assess the relationship between the involved parameters and the QoE. Results obtained by considering low resource hardware (e.g. mobile devices) and unreliable connections (e.g. wireless networks) are presented. User feedback proves the effectiveness of the proposed approach.

End-User Quality of Experience-Aware Personalized E-Learning

2011 ◽  
pp. 281-301
Author(s):  
Cristina Hava Muntean ◽  
Gabriel-Miro Muntean
Keyword(s):  
Learning Process ◽  
User Satisfaction ◽  
Quality Of Experience ◽  
Learning System ◽  
Learning Performance ◽  
End User ◽  
Delivery Performance ◽  
E Learning ◽  
Result Analysis

Lately, user quality of experience (QoE) during their interaction with a system is a significant factor in the assessment of most systems. However, user QoE is dependent not only on the content served to the users, but also on the performance of the service provided. This chapter describes a novel QoE layer that extends the features of classic adaptive e-learning systems in order to consider delivery performance in the adaptation process and help in providing good user perceived QoE during the learning process. An experimental study compared a classic adaptive e-learning system with one enhanced with the proposed QoE layer. The result analysis compares learner outcome, learning performance, visual quality and usability of the two systems and shows how the QoE layer brings significant benefits to user satisfaction improving the overall learning process.

Multimedia Quality of Experience

2016 ◽  
pp. 250-284
Author(s):  
Jeevan Pokhrel ◽  
Natalia Kushik ◽  
Bachar Wehbi ◽  
Nina Yevtushenko ◽  
Ana Rosa Cavalli
Keyword(s):  
User Satisfaction ◽  
Quality Of Experience ◽  
Learning Algorithms ◽  
Estimation Methods ◽  
The Internet ◽  
Successful Transmission ◽  
Methods And Techniques ◽  
Future Challenges ◽  
The Media

This chapter introduces the overall concept of multimedia Quality of Experience (QoE) over the Internet. It presents all the elements of multimedia QoE ecosystem and emphasizes their roles in determining the user satisfaction. The chapter also presents different multimedia transmission components and how these components contribute to successful transmission of the media content. In addition, some key performance indicators relevant to the multimedia QoE are presented with more emphasis on network and application level indicators. Furthermore, different QoE estimation methods and techniques along with QoS/QoE learning algorithms are presented. Finally, the chapter includes some of the future challenges and issues related to multimedia QoE.

A Generic Adaptation Framework for Mobile Communication

2011 ◽  
Vol 2 (1) ◽  
pp. 46-57
Author(s):  
Hong Sun ◽  
Ning Gui ◽  
Chris Blondia
Keyword(s):  
Quality Of Service ◽  
Mobile Devices ◽  
Mobile Communication ◽  
Quality Of Experience ◽  
Adaptation Strategies ◽  
Easy Access ◽  
Mobile Terminals ◽  
System Resources ◽  
New Applications

Today, technologies are providing mobile terminals with much more powerful computational abilities. Such improvement has made it possible to run many complex applications on mobile devices. However, many of these new applications are also resource demanding. Lacking sufficient resources would cause performance failures and impact negatively on the users’ quality of experience. In order to improve this, it is important to provide the users with an easy access to specifying their requirements. It is also crucial to monitor the system resources and make corresponding adaptation immediately according to the user’s specifications. In this paper, the authors propose adaptation strategies that flexibly combine the process of monitoring and adaptation, which provides an easy way to specify user’s requirements. By tuning the quality of service, the applications’ demand on system resources is reduced, thus decreasing the chances of performance failures and improving the users’ quality of experience.

scholarly journals Multimedia Quality of Experience (QoE): Current Status and Future Direction

2020 ◽  
Vol 12 (7) ◽  
pp. 121 ◽  
Author(s):  
Chaminda Hewage ◽  
Erhan Ekmekcioglu
Keyword(s):  
User Satisfaction ◽  
Quality Of Experience ◽  
Practical Importance ◽  
Multimedia Applications ◽  
Current Status ◽  
Significant Research ◽  
Multimedia Technologies ◽  
Future Direction ◽  
Technical Measures

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.

scholarly journals Subjective Evaluation of User Quality of Experience for Omnidirectional Video Streaming

2020 ◽  
Vol 32 (3) ◽  
pp. 409-421
Author(s):  
Štefica Mrvelj ◽  
Marko Matulin ◽  
Sergo Martirosov
Keyword(s):  
Quality Of Experience ◽  
Subjective Evaluation ◽  
The Other ◽  
Frame Rate ◽  
Dynamic Scenes ◽  
Head Mounted Display ◽  
Subjective Testing ◽  
Perception Of Quality ◽  
The Impact

This paper reports on the results of subjective testing of user Quality of Experience (QoE) for omnidirectional video (ODV) streaming quality. The test was conducted among 20 test subjects who watched three ODVs using a Head Mounted Display (HMD) system. The length of the videos was between two and three minutes. The first video was used for training purposes and contained no quality degradations. The quality of the other two ODVs was degraded by manipulating the resolution or by introducing different frame drop patterns. While watching the pre-prepared videos the subjects indicated if they noticed the changes in the quality and then rated it. After watching each video, the subjects completed a separate questionnaire, which evaluated their level of enjoyment and discomfort with the video. The results showed that the degradation of both objective parameters (video resolution and frame rate) impacted the subjects’ perception of quality; however, the impact was somewhat alleviated in ODV which contained dynamic scenes and fast camera movements.

A Generic Adaptation Framework for Mobile Communication

2012 ◽  
pp. 196-207
Author(s):  
Hong Sun ◽  
Ning Gui ◽  
Chris Blondia
Keyword(s):  
Quality Of Service ◽  
Mobile Devices ◽  
Mobile Communication ◽  
Quality Of Experience ◽  
Adaptation Strategies ◽  
Easy Access ◽  
Mobile Terminals ◽  
System Resources ◽  
New Applications

Today, technologies are providing mobile terminals with much more powerful computational abilities. Such improvement has made it possible to run many complex applications on mobile devices. However, many of these new applications are also resource demanding. Lacking sufficient resources would cause performance failures and impact negatively on the users’ quality of experience. In order to improve this, it is important to provide the users with an easy access to specifying their requirements. It is also crucial to monitor the system resources and make corresponding adaptation immediately according to the user’s specifications. In this paper, the authors propose adaptation strategies that flexibly combine the process of monitoring and adaptation, which provides an easy way to specify user’s requirements. By tuning the quality of service, the applications’ demand on system resources is reduced, thus decreasing the chances of performance failures and improving the users’ quality of experience.

Quality of Experience (QOE) Aware Video Attributes Determination for Mobile Streaming Using Hybrid Profiling

2017 ◽  
Vol 8 (3) ◽  
pp. 597
Author(s):  
Muhamad Hanif Jofri ◽  
Mohd Farhan Md Fudzee ◽  
Mohd Norasri Ismail ◽  
SHAHREEN KASIM ◽  
Jemal Abawajy
Keyword(s):  
Energy Consumption ◽  
Quality Of Experience ◽  
Energy Use ◽  
Video Quality ◽  
Frame Rate ◽  
Online Video ◽  
Energy Aware ◽  
Hybrid Energy ◽  
Set Up

<p>Today, consumers use a smartphone device to display the media contents for work and entertainment purposes, as well as watching online video. Online video streaming is the main cause that consume smartphone’s energy quickly. To overcome this problem, smartphone’s energy management is crucial. Thus, a hybrid energy-aware profiler is proposed. Basically, a profiler will monitor and manage the energy consumption in the smartphone devices. The hybrid energy-aware profiler will set up a protocol preference of both the user and the device. Then, it will estimates the energy consumption in smartphone. However, saving energy alone can contribute to the Quality of Experience (QoE) neglection, thus the proposed solution takes into account the client QoE. Even though there are several existing energy-aware profilers that have been developed to manage energy use in smartphones however, most energy-aware profilers does not consider QoE at the same time. The proposed solution consider both, the performance of the hybrid energy-aware profiler is compared with the baseline energy models against a variation of content adaptation according to the pre-defined variables. Three types of variables were determined; resolution, frame rate and energy consumption in smartphone devices. In this area, QoE subjective methods based on MOS (Mean Opinion Score) are the most commonly used approaches for defining and quantifying real video quality. Nevertheless, although these approaches have been established to consistently quantify users’ amounts of approval, they do not adequately realize which are the criteria of video attribute that important. In this paper, we conducted an experiment with a certain devices to measures user’s QoE and energy usage of video attribute in smartphone devices. Our results demonstrate that the list of possible solution is a relevant and useful video attribute that satify the users.</p>

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