This book provides an overview of concepts and challenges in intis investigated using structural equation modeling. The conveyed understanding of gaming QoE, empirical eraction quality in the domain of cloud gaming services. The author presents a unified evaluation approach by combining quantitative subjective assessment methods in a concise way. The author discusses a measurement tool, Gaming Input Quality Scale (GIPS), that assesses the interaction quality of such a service available. Furthermore, the author discusses a new framework to assess gaming Quality of Experience (QoE) using a crowdsourcing approach. Lastly, based on a large dataset including dominant network and encoding conditions, the evaluation method is investigated using structural equation modeling. The conveyed understanding of gaming QoE, empirical findings, and models presented in this book should be of particular interest to researchers working in the fields of quality and usability engineering, as well as service providers and network operators.
Author(s): Steven Schmidt
Series: T-Labs Series in Telecommunication Services
Publisher: Springer
Year: 2022
Language: English
Pages: 229
City: Cham
Preface
Acknowledgments
Contents
Acronyms
1 Introduction
1.1 Motivation
1.2 Scope
1.3 Structure
References
2 Quality Factors and Feature Space of Cloud Gaming Services
2.1 Quality of Experience Research
2.2 An Introduction to Cloud Gaming
2.2.1 Components of a Cloud Gaming System
2.2.2 Influencing Factors on Gaming QoE
2.3 Gaming QoE Taxonomy for Cloud Gaming Services
2.3.1 Game-related Quality Aspects
2.3.2 Player Experience Aspects
2.4 Summary
References
3 Methods for Assessing Gaming QoE
3.1 Overview of Assessment Methods
3.1.1 Classification of Assessment Methods
Behavioral Assessments
Psycho-Physiological Assessments
Subjective Assessments
Comparison of Classified Assessment Methods
3.1.2 Questionnaire-Based Assessment of Gaming QoE
3.1.3 Methods Considered for Research Objectives
3.2 Comparison of Interactive and Passive Test Paradigm (Study 3.2)
3.2.1 Applied Methodology to Investigate the Test Paradigms
Impact of Test Paradigm on Game-Related Quality Aspects
Impact of Test Paradigm on Player Experience Aspects
Impact of Player Performance during the Passive Test
Discussion About Findings
3.3 Designing Subjective Tests Measuring Gaming QoE
3.3.1 Standardization Activities
3.3.2 Test Design for ITU-T Rec. G.1072
Scaling Method and Rating Scale
Test Structure
Test Setup
Participant Requirements
Participant Instructions
Game Material Selection
Parameters Under Investigation—Independent Variables
Measured Quality Aspects—Dependent Variables
Pre-test Questionnaire
Post-game Questionnaire
Post-condition Questionnaire
3.4 Summary
References
4 Passive Video Quality Assessment Using Lab and Remote Testing
4.1 Passive Dataset for ITU-T Rec. G.1072
4.2 Video Quality Dataset Using Remote Testing
4.3 Comparison of Lab Studies and Remote Studies
4.4 Comparison of Different Stimulus Durations
4.5 Comparison Between Discrete and Continuous Rating Scales
4.6 Summary
References
5 Interactive Assessment of Gaming QoE Using Crowdsourcing
5.1 Development of Crowdgaming Framework
5.2 Testing the Crowdgaming Framework
5.2.1 Experimental Design
5.2.2 Demographic Information About Crowdworkers
5.2.3 Data Cleansing
5.2.4 Study Results
5.3 Test Environment Comparison
5.3.1 Data Collection
5.3.2 Analysis
5.3.3 Discussion
5.4 Summary
References
6 Development of the Gaming Input Quality Scale (GIPS)
6.1 Item Generation
6.2 Data Collection
6.3 Item Screening
6.4 Model Development
6.5 Validation of GIPS
6.6 Summary
References
7 Impact and Classification of the Game Content
7.1 Impact of Game Scenario (Study 7.1)
7.1.1 Method
7.1.2 Results
7.1.3 Discussion
7.2 Game Content Classification
7.2.1 Method
7.2.2 Encoding Complexity Classification
7.2.3 Delay Sensitivity Classification
7.2.4 Frame Loss Sensitivity Classification
7.2.5 Discussion
7.3 Summary
References
8 Empirical Investigation of the Cloud Gaming Taxonomy
8.1 Cloud Gaming Datasets
8.2 Measurement Model of Cloud Gaming QoE
8.3 Structural Model of Cloud Gaming QoE
8.4 Opinion Model Predicting Gaming QoE
8.5 Discussion
8.6 Summary
References
9 Conclusion and Outlook
9.1 Summary
9.2 Answers to Research Questions
9.3 Contribution of Research
9.4 Limitations and Future Work
References
A Additional Material Related to Empirical Studies or Related Work
B Measurement Instruments Used to Assess Gaming QoE
C Additional Material Related to the GIPS
D Information About Used Games in Research
References
Index
