Multimedia Streaming in SDN/NFV and 5G Networks Machine Learning for Managing Big Data Streaming

A comprehensive overview of Quality of Experience control and management of multimedia services in future networks

In Multimedia Streaming in SDN/NFV and 5G Networks, renowned researchers deliver a high-level exploration of Quality of Experience (QoE) control and management solutions for multimedia services in future softwarized and virtualized 5G networks. The book offers coverage of network softwarization and virtualization technologies, including SDN, NFV, MEC, and Fog/Cloud Computing, as critical elements for the management of multimedia services in future networks, like 5G and 6G networks and beyond.

Providing a fulsome examination of end-to-end QoE control and management solutions in softwarized and virtualized networks, the book concludes with discussions of probable future challenges and research directions in emerging multimedia services and applications, 5G network management and orchestration, network slicing and collaborative service management of multimedia services in softwarized networks, and QoE-oriented business models. The distinguished authors also explore:

• Thorough introductions to 5G networks, including definitions and requirements, as well as Quality of Experience management of multimedia streaming services
• Comprehensive explorations of multimedia streaming services over the internet and network softwarization and virtualization in future networks
• Practical discussions of QoE management using SDN and NFV in future networks, as well as QoE management of multimedia services in emerging architectures, including MEC, ICN, and Fog/Cloud Computing
• In-depth examinations of QoE in emerging applications, 5G network slicing architectures and implementations, and 5G network slicing orchestration and resource management

Perfect for researchers and engineers in multimedia services and telecoms, Multimedia Streaming in SDN/NFV and 5G Networks will also earn a place in the libraries of graduate and senior undergraduate students with interests in computer science, communication engineering, and telecommunication systems.

Alcardo Barakabitze, PhD, is an Irish Research Council funded and MSCA ELITE-S Fellow at Dublin City University. He is a reviewer for a variety of journals and serves on the technical program committees of leading conferences.

Andrew Hines, PhD, is Director of Research, Innovation and Impact for the School of Computer Science at University College Dublin. He is a committee member of the Audio Engineering Society (Ireland) and is a senior member of the IEEE.

Biography of Authors xi

Abstract xiii

List of Figures xv

List of Tables xix

Preface xxi

Acknowledgments xxv

List of Acronyms xxvii

1 5G Networks 1

1.1 History of Mobile Communication Systems 1

1.2 5G: Vision and Motivation 3

1.3 5G Service Quality and Business Requirements 6

1.3.1 High User Experienced Data Rate and Ultra-Low Latency 7

1.3.2 Transparency, Consistency, User’s QoE Personalization, and Service Differentiation 9

1.3.3 Enhanced Security, Mobility, and Services Availability 9

1.3.4 Seamless User Experience, Longer Battery Life, and Context Aware Networking 10

1.3.5 Energy and Cost Efficiency, Network Scalability, and Flexibility 10

1.4 5G Services, Applications, and Use Cases 11

1.5 5G Standardization Activities 12

1.6 Conclusion 14

Bibliography 14

2 5G Network Management for Big Data Streaming using Machine Learning 19

2.1 Machine Learning for Multimedia Networking 19

2.1.1 Data Collection 20

2.1.2 Feature Engineering 21

2.1.3 Ground Truth Quality Perception – Model Optimization and Training 22

2.1.4 Performance Metrics, Testing, and Model Validation 22

2.2 Machine Learning Paradigms 22

2.3 Multimedia Big Data Streaming 23

2.4 Deep Learning for IoT Big Data and Streaming Analytics 25

2.5 Intelligent QoE-based Big Data Strategies and Multimedia Streaming in Future Softwarized Networks 26

2.6 Optimization of Data Management with ML in Softwarized 5G Networks 27

2.6.1 A Multimodal Learning Framework for Video QoE Prediction 27

2.6.2 Supervised-Learning-based QoE Prediction of Video Streaming in Future Networks 28

2.6.3 OTT Service Providers 29

2.6.4 ISP/MNOs 29

2.6.5 Information Flow 29

2.7 Conclusion 30

Bibliography 31

3 Quality of Experience Management of Multimedia Streaming Services 35

3.1 Quality of Experience (QoE): Concepts and Definition 35

3.1.1 Quality of Experience Influence Factors 36

3.2 QoE Modeling and Assessment: Metrics and Models 38

3.2.1 Subjective Quality Models 38

3.2.2 Objective Quality Models 39

3.2.3 Data-driven Quality Models 41

3.3 QoE Measurement, Assessment, and Management 42

3.4 QoE Optimization and Control of Multimedia Streaming Services 43

3.4.1 Customer Experience Management and QoE Monitoring 47

3.5 Conclusion 51

Bibliography 51

4 Multimedia Streaming Services Over the Internet 57

4.1 Internet-Based Video Streaming: An Overview 57

4.1.1 A Brief History of Internet-Based Video Streaming 57

4.2 HTTP Adaptive Streaming (HAS) Framework 59

4.3 Server and Network-Assisted DASH (SAND) 63

4.4 Multimedia Delivery Chain and Service Management Issues 66

4.5 Conclusion 68

Bibliography 68

5 QoE Management of Multimedia Services Using Machine Learning in SDN/NFV 5G Networks 73

5.1 QoE-Centric Routing Mechanisms for Improving Video Quality 74

5.2 MPTCP/SR and QUIC Approaches for QoE Optimization 76

5.3 Server and Network-Assisted Optimization Approaches Using Sdn/nfv 80

5.4 QoE-Centric Fairness and Personalized QoE Control 84

5.4.1 QoE-driven Optimization Approaches for Video Streaming Using Machine Learning 86

5.5 Conclusion 89

Bibliography 89

6 Network Softwarization and Virtualization in Future Networks: The promise of SDN, NFV, MEC, and Fog/Cloud Computing 99

6.1 Network Softwarization: Concepts and Use Cases 99

6.2 Network Softwarization and Virtualization Technologies for Future Communication Platforms 100

6.2.1 Software-Defined Networking (SDN) 100

6.2.2 Standardization Activities of SDN 102

6.2.3 Traffic Management Applications for Stateful SDN Data Plane 103

6.2.4 Network Function Virtualization (NFV) 103

6.2.5 NFV Management and Orchestration (NFV MANO) Framework 106

6.2.6 NFV Use Cases, Application Scenarios, and Implementation 107

6.2.7 NFV Standardization Activities 107

6.2.8 Network Hypervisors, Containers, and Virtual Machines 108

6.2.9 Multiaccess Edge Computing (MEC): From Clouds to Edges 110

6.3 Conclusion 111

Bibliography 112

7 Management of Multimedia Services in Emerging Architectures Using Big Data Analytics: MEC, ICN, and Fog/Cloud computing 119

7.1 QoE-Aware/Driven Adaptive Streaming Over MEC Architectures 119

7.2 QoE-aware Self-Driving 3D Network Architecture 121

7.3 QoE-driven/aware Management Architecture Using ICN 124

7.4 QoE-aware Adaptive Streaming over Cloud/Fog Computing 126

7.5 Conclusion 127

Bibliography 127

8 Emerging Applications and Services in Future 5G Networks 133

8.1 QoE in Immersive AR/VR and Mulsemedia Applications 133

8.2 QoE in Cloud Gaming Video Streaming Applications 135

8.3 QoE in Light Field Applications 136

8.4 Holographic and Future Media Communications 137

8.5 Human-Centric Services and 3D Volumetric Video Streaming 137

8.6 New Video Compression Standards Toward 6G Networks 139

8.7 Conclusion 140

Bibliography 141

9 5G Network Slicing Management Architectures and Implementations for Multimedia 147

9.1 5G Network Slicing Architectures and Implementations 147

9.1.1 Collaborative 5G Network Slicing Research Projects 148

9.1.2 Open Source Orchestrators, Proof of Concepts, and Standardization Efforts 152

9.2 5G Network Slicing Orchestration and Management in Multi-domain 156

9.2.1 Reference Architecture for Data-Driven Network Management in 6G and Beyond Networks 158

9.3 Conclusion 161

Bibliography 162

10 QoE Management of Multimedia Service Challenges in 5G Networks 167

10.1 QoE Management and Orchestration in Future Networks 167

10.2 Immersive Media Experience in Future Softwarized and Beyond Networks 168

10.3 Development of New Subjective Assessment Methodologies for Emerging Services and Applications 170

10.4 QoE-aware Network Sharing and Slicing in Future Softwarized Networks 171

10.5 QoE Measurement, Modeling, and Testing Issues Over 6G Networks 172

10.6 QoE-Centric Business Models in Future Softwarized Network 172

10.7 Novel QoE-driven Virtualized Multimedia 3D Services Delivery Schemes Over 6G Networks 174

10.8 Novel 3D Cloud/Edge Models for Multimedia Applications and Elastic 3D Service Customization 174

10.9 Security, Privacy, Trust 176

10.10 Conclusion 177

Bibliography 178

11 Multimedia QoE-Driven Services Delivery Toward 6G and Beyond Network 185

11.1 The Roads Toward 6G and Beyond Networks 185

11.1.1 Holographic and Future Media Communications 189

11.1.2 Human-Centric Services and 3D Volumetric Video Streaming 190

11.1.3 Potential Features and Technologies in 6G Networks 191

11.2 6G Innovative Network Architectures: From Network Softwarization to Intelligentization 194

11.2.1 Network Management, Automation, and Orchestration 194

11.2.2 Pervasive AI, ML, and Big Data Analytics 196

11.2.3 New Protocol Stack and 3D Network Architectures 197

11.3 6G Standardization Activities 198

11.4 Conclusion 199

Bibliography 199

12 Multimedia Streaming Services Delivery in 2030 and Beyond Networks 203

12.1 The Future of the Video Streaming Industry: Market Growth and Trends Toward 2030 203

12.2 Future 2030 Communication Network and Computing Scenarios 204

12.3 New Paradigms of Internetworking for 2030 and Beyond Networks 206

12.3.1 Next-Generation Human–Machine Interaction Network: A Humancentric Hyper-real Experience 207

12.3.2 Multimedia Streaming Blockchain-enabled Resource Management and Sharing for 2030 and Beyond Networks 209

12.4 A General QoE Provisioning Ecosystem for 2030 and Beyond Networks 211

12.4.1 Customer QoE Quantification 213

12.4.2 QoE Analysis, Assessment, Measurement, and Visualization 213

12.4.3 5G Network Performance and QoE Optimization 214

12.4.4 Multistakeholders Collaboration for Video Content Delivery and Network Infrastructures 214

12.5 Conclusion 218

Bibliography 218

Index 221

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