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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Serie: Wiley - IEEE
- Sprache: Englisch
Multimedia Streaming in SDN/NFV and 5G Networks 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.
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Seitenzahl: 422
Veröffentlichungsjahr: 2022
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Table of Contents
Cover
Title Page
Copyright
Biography of Authors
Abstract
List of Figures
List of Tables
Preface
Acknowledgments
List of Acronyms
1 5G Networks
1.1 History of Mobile Communication Systems
1.2 5G: Vision and Motivation
1.3 5G Service Quality and Business Requirements
1.4 5G Services, Applications, and Use Cases
1.5 5G Standardization Activities
1.6 Conclusion
Bibliography
Note
2 5G Network Management for Big Data Streaming using Machine Learning
2.1 Machine Learning for Multimedia Networking
2.2 Machine Learning Paradigms
2.3 Multimedia Big Data Streaming
2.4 Deep Learning for IoT Big Data and Streaming Analytics
2.5 Intelligent QoE‐based Big Data Strategies and Multimedia Streaming in Future Softwarized Networks
2.6 Optimization of Data Management with ML in Softwarized 5G Networks
2.7 Conclusion
Bibliography
3 Quality of Experience Management of Multimedia Streaming Services
3.1 Quality of Experience (QoE): Concepts and Definition
3.2 QoE Modeling and Assessment: Metrics and Models
3.3 QoE Measurement, Assessment, and Management
3.4 QoE Optimization and Control of Multimedia Streaming Services
3.5 Conclusion
Bibliography
4 Multimedia Streaming Services Over the Internet
4.1 Internet‐Based Video Streaming: An Overview
4.2 HTTP Adaptive Streaming (HAS) Framework
4.3 Server and Network‐Assisted DASH (SAND)
4.4 Multimedia Delivery Chain and Service Management Issues
4.5 Conclusion
Bibliography
5 QoE Management of Multimedia Services Using Machine Learning in SDN/NFV 5G Networks
5.1 QoE‐Centric Routing Mechanisms for Improving Video Quality
5.2 MPTCP/SR and QUIC Approaches for QoE Optimization
5.3 Server and Network‐Assisted Optimization Approaches Using SDN/NFV
5.4 QoE‐Centric Fairness and Personalized QoE Control
5.5 Conclusion
Bibliography
Notes
6 Network Softwarization and Virtualization in Future Networks: The promise of SDN, NFV, MEC, and Fog/Cloud Computing
6.1 Network Softwarization: Concepts and Use Cases
6.2 Network Softwarization and Virtualization Technologies for Future Communication Platforms
6.3 Conclusion
Bibliography
7 Management of Multimedia Services in Emerging Architectures Using Big Data Analytics: MEC, ICN, and Fog/Cloud computing
7.1 QoE‐Aware/Driven Adaptive Streaming Over MEC Architectures
7.2 QoE‐aware Self‐Driving 3D Network Architecture
7.3 QoE‐driven/aware Management Architecture Using ICN
7.4 QoE‐aware Adaptive Streaming over Cloud/Fog Computing
7.5 Conclusion
Bibliography
8 Emerging Applications and Services in Future 5G Networks
8.1 QoE in Immersive AR/VR and Mulsemedia Applications
8.2 QoE in Cloud Gaming Video Streaming Applications
8.3 QoE in Light Field Applications
8.4 Holographic and Future Media Communications
8.5 Human‐Centric Services and 3D Volumetric Video Streaming
8.6 New Video Compression Standards Toward 6G Networks
8.7 Conclusion
Bibliography
Note
9 5G Network Slicing Management Architectures and Implementations for Multimedia
9.1 5G Network Slicing Architectures and Implementations
9.2 5G Network Slicing Orchestration and Management in Multi‐domain
9.3 Conclusion
Bibliography
Notes
10 QoE Management of Multimedia Service Challenges in 5G Networks
10.1 QoE Management and Orchestration in Future Networks
10.2 Immersive Media Experience in Future Softwarized and Beyond Networks
10.3 Development of New Subjective Assessment Methodologies for Emerging Services and Applications
10.4 QoE‐aware Network Sharing and Slicing in Future Softwarized Networks
10.5 QoE Measurement, Modeling, and Testing Issues Over 6G Networks
10.6 QoE‐Centric Business Models in Future Softwarized Network
10.7 Novel QoE‐driven Virtualized Multimedia 3D Services Delivery Schemes Over 6G Networks
10.8 Novel 3D Cloud/Edge Models for Multimedia Applications and Elastic 3D Service Customization
10.9 Security, Privacy, Trust
10.10 Conclusion
Bibliography
11 Multimedia QoE‐Driven Services Delivery Toward 6G and Beyond Network
11.1 The Roads Toward 6G and Beyond Networks
11.2 6G Innovative Network Architectures: From Network Softwarization to Intelligentization
11.3 6G Standardization Activities
11.4 Conclusion
Bibliography
Notes
12 Multimedia Streaming Services Delivery in 2030 and Beyond Networks
12.1 The Future of the Video Streaming Industry: Market Growth and Trends Toward 2030
12.2 Future 2030 Communication Network and Computing Scenarios
12.3 New Paradigms of Internetworking for 2030 and Beyond Networks
12.4 A General QoE Provisioning Ecosystem for 2030 and Beyond Networks
12.5 Conclusion
Bibliography
Index
End User License Agreement
List of Tables
Chapter 1
Table 1.1 A Summary of user experience requirements in 5G networks.
Table 1.2 A summary of standardization efforts from the academia and indust...
Chapter 3
Table 3.1 Some of the commonly used image and video quality assessment mode...
Chapter 4
Table 4.1 A comparison of HTTP adaptive streaming solutions.
Chapter 5
Table 5.1 A summary of QoE‐centric management strategies of multimedia stre...
Table 5.2 A summary of QoE optimization approaches in future networks using...
Chapter 6
Table 6.1 A summary of SDN open source platforms, standardization efforts, ...
Table 6.2 A summary of NFV open source platforms, projects, and implementat...
Chapter 7
Table 7.1 A summary of QoE‐centric management strategies in emerging archit...
Chapter 9
Table 9.1 A summary of academia/industry 5G projects and implementation bas...
Table 9.2 Summary of orchestration enabling technologies in 5G networks sli...
Chapter 10
Table 10.1 A summary of research directions and recommendations in future s...
Chapter 11
Table 11.1 A summary of applications, usage scenarios, and 6G networks char...
Table 11.2 Key performance indicators for 5G and 6G wireless networks.
List of Illustrations
Chapter 1
Figure 1.1 Network evolution toward 5G and beyond..
Figure 1.2 The 12 key enabling technologies in 5G networks.
Figure 1.3 Software network technologies in 5G architecture. A indicates RAN...
Figure 1.4 The NGMN 5G network slicing implementation.
Figure 1.5 5G service quality and business requirements.
Figure 1.6 Current and future 5G network capabilities to support various use...
Chapter 2
Figure 2.1 Problem categories that benefit from ML. Letters a, b, c, and d i...
Figure 2.2 Process flow diagram for ML solution in multimedia streaming serv...
Figure 2.3 Classification of ML algorithms.
Figure 2.4 Multimedia big data.
Figure 2.5 Deep learning models and IoT data creation at various levels to h...
Figure 2.6 ML algorithms.
Figure 2.7 Architectural components, implementation, and deployment options ...
Chapter 3
Figure 3.1 Illustration of the QoE concept.
Figure 3.2 QoE influence factors.
Figure 3.3 Multimedia streaming chain.
Figure 3.4 QoE optimization of multimedia services in access networks.
Figure 3.5 QoE in multimedia network. QoE is automatically managed using thr...
Figure 3.6 QoE‐based management in mobile cellular networks [55].
Figure 3.7 QoE monitoring for large traffic variations in business, resident...
Chapter 4
Figure 4.1 History of video streaming.
Figure 4.2 DASH architecture.
Figure 4.3 An overview of DASH players video streaming QoE.
Figure 4.4 Example of client‐centric HTTP adaptive streaming session.
Figure 4.5 MPEG‐SAND architecture. DANEs can communicate among each other an...
Figure 4.6 SAND/3 architecture.
Chapter 5
Figure 5.1 Scalable QoE‐aware path selection in large‐scale SDN‐based networ...
Figure 5.2 QoE ‐aware MPTCP/SR‐based architecture in softwarized 5G networks...
Figure 5.3 QoE‐driven management of multimedia services over softwarized 5G ...
Figure 5.4 QoE‐based network‐assisted approaches for adaptive video streamin...
Figure 5.5 Per‐cluster QoE policy structure and model abstraction.
Figure 5.6 QoE‐optimization and management using machine learning in softwar...
Chapter 6
Figure 6.1 Main layers of the SDN architecture.
Figure 6.2 ONF SDN network slicing architecture..
Figure 6.3 An integration of SDN controllers into the ETSI NFV reference arc...
Figure 6.4 A comparison between containers and virtual machines. (a) Virtual...
Figure 6.5 Cloud computing service models and their mapping to part of the N...
Figure 6.6 Multiaccess edge computing architecture and its mapping to NFV MA...
Chapter 7
Figure 7.1 Mobile edge virtualization with adaptive prefetching.
Figure 7.2 An overview of QoE‐aware control plane for adaptive streaming ser...
Figure 7.3 Hierarchical 3D network system architecture.
Chapter 8
Figure 8.1 mulsemedia experience delivery system over next generation wire...
Figure 8.2 Different application areas of VVC in 6G networks.
Chapter 9
Figure 9.1 5GEx network slicing conceptual architecture.
Figure 9.2 The main innovations of 5G NORMA concept.
Figure 9.3 Network slicing relevant industry groups and SDOs landscape.
Figure 9.4 A multi‐domain slicing architecture in 5G networks.
Figure 9.5 Reference architecture for data‐driven network management in 6G a...
Chapter 10
Figure 10.1 The challenge of immersive media experience in 6G and beyond net...
Figure 10.2 QoS, QoE, ELAs, and QoBiz relationship model for future communic...
Chapter 11
Figure 11.1 Future 6G communication services and applications.
Figure 11.2 Holographic streaming for 6G and beyond networks.
Figure 11.3 Key features and technologies for 6G and beyond networks.
Figure 11.4 Architectural innovations and mechanisms introduced in 6G networ...
Figure 11.5 The overall roadmap for 6G development toward 2030 networks.
Chapter 12
Figure 12.1 Future 2030 communication networks and computing scenarios.
Figure 12.2 New capabilities and services required for 2030 and beyond netwo...
Figure 12.3 Hyper‐real human–machine interaction experience.
Figure 12.4 Blockchain‐enabled multimedia streaming resource management fram...
Figure 12.5 The QoE ecosystem on 5G and beyond networks.
Figure 12.6 An expanded definition of QoE over 5G and beyond networks.
Figure 12.7 Multistakeholder value chain for video content distribution.
Figure 12.8 ISP–CDN collaboration and the elements of video delivery for 203...
Guide
Cover
Table of Contents
Title Page
Copyright
Biography of Authors
Abstract
List of Figures
List of Tables
Preface
Acknowledgments
List of Acronyms
Begin Reading
Index
End User License Agreement
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Multimedia Streaming in SDN/NFV and 5G Networks
Machine Learning for Managing Big Data Streaming
Alcardo Barakabitze and Andrew HinesUniversity College Dublin (UCD), Dublin, Ireland
Copyright © 2023 by The Institute of Electrical and Electronics Engineers, Inc. All rights reserved.
Published by John Wiley & Sons, Inc., Hoboken, New Jersey.Published simultaneously in Canada.
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Biography of Authors
Alcardo Barakabitze
Dr. Alcardo Barakabitze is a former MSCA Fellow in the School of Computing, Dublin City University, Ireland. Dr. Barakabitze completed his PhD in Computing and Communications from the School of Science and Engineering at the University of Plymouth, UK. His PhD thesis was titled “Quality of Experience (QoE) control and management of multimedia services in software defined and virtualized networks”. He received the degree in Computer Science with Honours from the University of Dar es Salaam, Tanzania in 2010 and Master Degree of Electronics and Communication Engineering with first class from Chongqing University, PR China, in May 2015. He has worked as Marie Curie Fellow (2015–2018) in MSCA ITN QoE‐Net project. He was also a Postdoctoral Research Fellow (2019–2020) at Qxlab in the School of Computer Science, University College Dublin under the Government of Ireland Postdoctoral Fellowship (Irish Research Council).
Dr. Barakabitze is recognised as the 2015 outstanding International Graduate Student of Chongqing University, China due to his excellent performance. He was a visiting researcher in the Department of Electrical and Electronics Engineering, University of Cagliari, Italy and the ITU‐T‐Standardization Department in 2016 and 2017 respectively. He is actively involved in both national and international projects from the EU Horizon 2020, and Horizon Europe – 2027 programme. He is an active member of the standardization activities of the ITU‐T Study Group 12 and 13 focusing on network performance, QoE and future 6G and 2030 networks. Dr. Barakabitze has more than 40 publications in peer‐reviewed conferences and journals with a total of 1041 Google Scholar citations and H‐index of 17. Barakabitze served as session chair of Future Internet and NGN Architectures during the IEEE Communication Conference in Kansas City, USA. He was also the Keynote and Panel Chairs at the International Young Researcher Summit on Quality of Experience in Emerging Multimedia Services (QEEMS 2017), which was held from May 29–30, 2017 in Erfurt, Germany. Dr. Barakabitze is a Reviewer for various journals including the IEEE Transactions in Network and Service Management, IEEE ACCESS, Computer Networks and many others. Dr. Barakabitze serves on technical program committees of leading conferences focusing on his research areas. His research interests are 5G, Quality of Experience (QoE), network management, video streaming services, SDN and NFV.
Andrew Hines
Andrew Hines is an Assistant Professor with the School of Computer Science, University College Dublin, Ireland where he served as the Director of Research, Impact and Innovation. He leads the QxLab research group with active research in multimedia signal processing as well as Quality of Experience for 5G, SDN and network management. He is an investigator in the Science Foundation Ireland Connect, Insight and Adapt research centres. He was awarded the US‐Ireland Research Innovation award in 2018 by the Royal Irish Academy and American Chamber of Commerce for work developing Multimedia Quality of Experience Models. He is a member of the 2022–2026 Royal Irish Academy Multidisciplinary Committee (Engineering and Computer Science). Dr Hines is a senior member of the IEEE and a member of the Audio Engineering Society. As a leading expert in Quality of Experience for media technology, he represented Ireland on the management committee of the European COST action expert group on Quality of Experience, Qualinet.
Abstract
The exponential growth of video streaming services (e.g. YouTube and Mobile TV) on smart devices has triggered and introduced new revenue potential for telecom operators and service providers. The future networks such as 5G and 6G are shifting toward the cloudification of the network resources via Software Defined Networks (SDNs), Network Function Virtualization (NFV), and Multi‐Access Edge/Cloud Computing, network hypervisors, virtual machines, and containers. This will equip Internet Service Providers (ISPs) with cutting‐edge technologies to provide service customization during service delivery and to offer Quality of Experience (QoE) which meets customers' needs via intelligent QoE control and management approaches. This book provides a high‐level description of QoE control and management solutions for multimedia services in future softwarized and virtualized 5G networks. The QoE control and management integrates QoE modeling, monitoring, and optimization at different points in the network. The book starts with an introduction to 5G networks along with 5G service quality and business requirements. The book provides a comprehensive description of HTTP2/3 Adaptive Streaming (HAS) solutions as the dominant technique for streaming high‐definition videos (4K/8K/3D) over the future Internet architecture. The book provides a description of network softwarization and virtualization technologies leveraging SDN, NFV, MEC, Fog/Cloud Computing as important elements for managing multimedia services in future networks such as 5G/6G. It also provides the past and ongoing key research projects, standardization activities, and use cases related to SDN, NFV, MEC, Fog/Cloud, and emerging applications (cloud video streaming gaming, immersive virtual reality [VR] and augmented reality [AR], mulsemedia, and 360° immersive video).
Moreover, the book provides the QoE control and management techniques using softwarized and virtualized networks. Furthermore, this book provides the 5G network slicing in future softwarized networks which is a key element for achieving QoE‐oriented sharing/slicing of resources. The book will provide different industrial initiatives and projects that are pushing forward the adoption of network softwarization and virtualization in accelerating 5G network slicing. A comparison of various 5G architectural approaches in terms of practical implementations, technology adoptions, and deployment strategies will be presented in the book. In addition, a discussion on various open‐source orchestrators and proof of concepts representing industrial contribution will be given in the book. This will go along with the management and orchestration of network slices in multi‐tenant or multi‐operators domains. In addition to that, the book provides a multimedia QoE‐driven services delivery toward 6G and 2030 networks. Some of the key technologies and services highlighted in this chapter include: holographic and future media communications, human‐centric services and 3D volumetric video streaming, innovative network architectures, pervasive AI, ML, and big data analytics, new protocol stack and 3D network architectures. The future of video streaming industry towards 2030 and new paradigms of internetworking for 2030 and beyond systems are also highlighted in the book. The last chapter provides future challenges for managing multimedia services focusing on the following important areas: emerging multimedia services, QoE‐oriented business models in future softwarized network, intelligent QoE‐based big data strategies in SDN/NFV, scalability, resilience, and optimization in SDN and NFV, multimedia communications in the Internet of Things AQ1 (IoTs), OTT‐ISP collaborative service management in softwarized networks. The chapter provides various opportunities that need extensive research from the academia and industry regarding QoE‐driven virtualized multimedia 3D services delivery schemes over 6G architecture, 3D cloud/edge models for multimedia services and elastic 3D service customization via network intelligentization and QoE management and orchestration challenges, over 6G networks.
List of Figures
Figure 1.1
Network evolution toward 5G and beyond.
Figure 1.2
The 12 key enabling technologies in 5G networks.
Figure 1.3
Software network technologies in 5G architecture. A indicates RAN; B = transport networks; C = core networks; and D represents the Internet.
Figure 1.4
The NGMN 5G network slicing implementation.
Figure 1.5
5G service quality and business requirements.
Figure 1.6
Current and future 5G network capabilities to support various use cases.
Figure 2.1
Problem categories that benefit from ML. Letters a, b, c, and d indicates clustering, classification, regression, and rule extraction, respectively.
Figure 2.2
Process flow diagram for ML solution in multimedia streaming service.
Figure 2.3
Classification of ML algorithms.
Figure 2.4
Multimedia big data.
Figure 2.5
Deep learning models and IoT data creation at various levels to handle knowledge abstraction.
Figure 2.6
ML algorithms.
Figure 2.7
Architectural components, implementation, and deployment options using ML.
Figure 3.1
Illustration of the QoE concept.
Figure 3.2
QoE influence factors.
Figure 3.3
Multimedia streaming chain.
Figure 3.4
QoE optimization of multimedia services in access networks.
Figure 3.5
QoE in multimedia network. QoE is automatically managed using three different axes, namely, (a) traffic‐flow adaptation, (b) admission control, and (c) video rate adaptation.
Figure 3.6
QoE‐based management in mobile cellular networks [55].
Figure 3.7
QoE monitoring for large traffic variations in business, residential, and public areas in 5G networks.
Figure 4.1
History of video streaming.
Figure 4.2
DASH architecture.
Figure 4.3
An overview of DASH players video streaming QoE.
Figure 4.4
Example of client‐centric HTTP adaptive streaming session.
Figure 4.5
MPEG‐SAND architecture. DANEs can communicate among each other and with the DASH clients to optimize the end‐to‐end video quality delivery.
Figure 4.6
SAND/3 architecture.
Figure 5.1
Scalable QoE‐aware path selection in large‐scale SDN‐based networks.
Figure 5.2
QoE ‐aware MPTCP/SR‐based architecture in softwarized 5G networks.
Figure 5.3
QoE‐driven management of multimedia services over softwarized 5G networks.
Figure 5.4
QoE‐based network‐assisted approaches for adaptive video streaming. (a) A specific bandwidth for each client is enforced by the network when bandwidth reservation is used, and (b) the network provides an explicit bitrate to the clients using bitrate guidance.
Figure 5.5
Per‐cluster QoE policy structure and model abstraction.
Figure 5.6
QoE‐optimization and management using machine learning in softwarized networks.
Figure 6.1
Main layers of the SDN architecture.
Figure 6.2
ONF SDN network slicing architecture.
Figure 6.3
An integration of SDN controllers into the ETSI NFV reference architecture at the two levels required to achieve network slicing.
Figure 6.4
A comparison between containers and virtual machines. (a) Virtual machines. (b) Containers.
Figure 6.5
Cloud computing service models and their mapping to part of the NFV reference architecture.
Figure 6.6
Multiaccess edge computing architecture and its mapping to NFV MANO.
Figure 7.1
Mobile edge virtualization with adaptive prefetching.
Figure 7.2
An overview of QoE‐aware control plane for adaptive streaming service in MEC.
Figure 7.3
Hierarchical 3D network system architecture.
Figure 8.1
mulsemedia experience delivery system over next generation wireless networks.
Figure 8.2
Different application areas of VVC in 6G networks.
Figure 9.1
5GEx network slicing conceptual architecture.
Figure 9.2
The main innovations of 5G NORMA concept.
Figure 9.3
Network slicing relevant industry groups and SDOs landscape.
Figure 9.4
A multi‐domain slicing architecture in 5G networks.
Figure 9.5
Reference architecture for data‐driven network management in 6G and beyond networks. Source: Benjamín Núñez González/Wikimedia Commons/CC BY‐SA 4.0; alan9187/Pixabay; PhotoMIX‐Company/Pixabay.
Figure 10.1
The challenge of immersive media experience in 6G and beyond networks.
Figure 10.2
QoS, QoE, ELAs, and QoBiz relationship model for future communication systems.
Figure 11.1
Future 6G communication services and applications.
Figure 11.2
Holographic streaming for 6G and beyond networks.
Figure 11.3
Key features and technologies for 6G and beyond networks.
Figure 11.4
Architectural innovations and mechanisms introduced in 6G networks.
Figure 11.5
The overall roadmap for 6G development toward 2030 networks.
Figure 12.1
Future 2030 communication networks and computing scenarios.
Figure 12.2
New capabilities and services required for 2030 and beyond networks.
Figure 12.3
Hyper‐real human–machine interaction experience.
Figure 12.4
Blockchain‐enabled multimedia streaming resource management framework in 2030 networks.
Figure 12.5
The QoE ecosystem on 5G and beyond networks.
Figure 12.6
An expanded definition of QoE over 5G and beyond networks.
Figure 12.7
Multistakeholder value chain for video content distribution.
Figure 12.8
ISP–CDN collaboration and the elements of video delivery for 2030 and beyond networks.
List of Tables
Table 1.1
A Summary of user experience requirements in 5G networks.
Table 1.2
A summary of standardization efforts from the academia and industry.
Table 3.1
Some of the commonly used image and video quality assessment models.
Table 4.1
A comparison of HTTP adaptive streaming solutions.
Table 5.1
A summary of QoE‐centric management strategies of multimedia streaming services in future networks.
Table 5.2
A summary of QoE optimization approaches in future networks using ML.
Table 6.1
A summary of SDN open source platforms, standardization efforts, projects, and implementations.
Table 6.2
A summary of NFV open source platforms, projects, and implementations.
Table 7.1
A summary of QoE‐centric management strategies in emerging architectures.
Table 9.1
A summary of academia/industry 5G projects and implementation based on SDN/NFV.
Table 9.2
Summary of orchestration enabling technologies in 5G networks slicing [23].
Table 10.1
A summary of research directions and recommendations in future softwarized networks.
Table 11.1
A summary of applications, usage scenarios, and 6G networks characteristics.
Table 11.2
Key performance indicators for 5G and 6G wireless networks.
Preface
This book expands on his published papers in the IEEE Communication Surveys and Tutorials and Elsevier Computer Networks journals. The transitional narrative of the material from these articles were added at the start of every chapter and section. The intention is to give a compact, highly motivated introduction to the central questions that arise in the study of QoE management of multimedia services in future 5G networks. The book provides a high‐level description of QoE control and management solutions for multimedia services in future softwarized and Virtualized 5G networks. The book covers network softwarization and virtualization technologies including SDN, NFV, Multi‐Access Edge Computing (MEC), Fog/Cloud Computing as important elements for managing multimedia services in future networks such as 5G/6G and beyond. The book further examines the end‐to‐end QoE control and management solutions in softwarized and virtualized networks including: (i) QoE‐aware/driven strategies using SDN or/and NFV, (ii) QoE‐aware/driven approaches for adaptive streaming over emerging architectures such as MEC, cloud/fog computing, and Information‐Centric Networking, and (iii) QoE measurements in new domains including AR/VR, mulsemedia and video gaming applications. The final part of this book discusses future challenges and research directions/recommendations in: (i) Emerging multimedia services and applications, (ii) 5G network management and orchestration, (iii) network slicing and collaborative service management of multimedia services in softwarized networks, and (iv) QoE‐oriented business models. The book is intended for researchers, engineers from academia and industry working in the area of multimedia services and telecommunication communications, networking and QoE optimization and control and management. The book is also intended for application scientists from the industry for gaining important knowledge of QoE management of multimedia services in future 5G and beyond networks using network softwarization technologies (SDN and NFV) and other emerging architectures (MEC, ICN, Cloud/Edge computing). In particular, the book will be beneficial to undergraduate students studying for a degree in computer science, communication engineering and telecommunication systems for both taught courses and their project work. In particular, the book will be also useful for postgraduate students for a PhD or master's degree in the above courses. I believe that, for undergraduate and postgraduate students, this book will be a valuable source of information for fundamental topics regarding video streaming QoE, multimedia services and applications, 5G networks, future Internet architecture, and softwarized and virtualized networks leveraging SDN and NFV. I also believe that the book will be used as a good vehicle for self‐learning and teaching text tools for application engineers, undergraduate and graduate students and university academics. Readers of this book are assumed to have some basic knowledge of computer networking, and an interest in SDN, NFV, cloud computing, multimedia services, video quality optimization, and QoE services delivery to end‐users. The book will also be a valuable resource for experts working in different fields such as patent attorneys and patent examiners.
Dr. Alcardo Barakabitze completed his PhD in Computing and Communications from the University of Plymouth, UK, in 2019. He received the degree in Computer Science with honors from the University of Dar es Salaam, Tanzania, in 2010 and master's degree of Electronics and Communication Engineering with first class from Chongqing University, PR China, in May 2015. He is a former MSCA Fellow (October 2020 – September 20228) in the School of Computing, Dublin City University, Ireland. In June 2020, Dr. Barakabitze delivered a commissioned four‐day training workshop on the topics in this book proposal for a group of patent examiners based in the European Patent Office, Geneva.
Since October 2019 to September 2020, he has served as a postdoctoral researcher in the QxLab research group, School of Computer Science, University College Dublin (UCD). He has worked as Marie Curie Fellow (October 2015–July 2019) in MSCA ITN QoE‐Net. Dr. Barakabitze was recognized as the 2015 outstanding International Graduate Student of Chongqing University, China, due to his excellent performance. He was awarded the BEST Male ICT Researcher of the Year 2021 by the ICT Commission of Tanzania. Dr. Barakabitze is also recognized as the BEST Young Researcher of the Year 2021, an award from the SUA Research and Innovation Competitions. He was a visiting researcher in the Department of Electrical and Electronics Engineering, University of Cagliari, Italy, and the ITU‐T‐Standardization Department in 2016 and 2017, respectively. Dr. Barakabitze has participated in the ITU‐T standardization process and made significant contributions since 2016 in the area of Software Defined Networking (SDN)/Network Function Virtualization (NFV), future network performance, Quality of Service (QoS), and Quality of Experience (QoE). Dr. Barakabitze has served as session chair of Future Internet and NGN Architectures during the 2018 IEEE Communication Conference (ICC) in Kansas City, USA. He was also the Keynote and Panel Chairs at the International Young Researcher Summit on Quality of Experience in Emerging Multimedia Services (QEEMS 2017), that was held from May 29 to 30, 2017 in Erfurt, Germany. He has numerous publications in international peer‐reviewed conferences and journals. He is a reviewer for various journals and serves on technical program committees of leading conferences focusing on his research areas. His research interests are 5G/6G, QoE, network management, video streaming services, SDN, and NFV.
Acknowledgments
Writing a book is harder than I thought and more rewarding than I could have ever imagined. This work is the culmination of a journey that started in October 2020. Completing this book has been a truly life‐changing experience for me, and it would not have been possible to do without the support and guidance that I received from many people. First and foremost, I would like to express my sincere gratitude to my supervisors of Postdoc (Prof. Andrew and Hines and Ray Walshe) for the continuous support, patience, motivation, and immense knowledge they gave to me since I started my Postdoc study at UCD and DCU. Their professional guidance helped me in all the time of research and writing of this book. I appreciate all the contributions of time, encouragement, and ideas to make the experience of writing this book productive and stimulating. The joy and enthusiasm they have for their research will remain to be contagious and motivational for me throughout the journey of my research career. It has been an enormous privilege to learn from their expertise and leadership, and I am also thankful for the excellent example they have provided to me of working very hard. My numerous quality chapters that I was able to publish during my two years of writing this book would not have been possible without them and for that I am truly grateful. I am also deeply in debt to my project managers, Mr. Paulo Soncini and Dr. Rob Brennan, who always had a door open when I needed someone to discuss and get feedback from. Their insights and comments have shaped this book. A very special thanks to them for their advice and support during my two years of doing my Postdocs. I have hugely benefited from the collaborations and discussions with them. I collectively thank my project supervisory team for inspirational guidance, support, and constructive discussions with me regarding the chapters. I am truly grateful to Dr. Andrew Hines for helping me in whatever way he could during this challenging period. I would also like to thank all the reviewers who reviewed my book. Without their constructive comments and suggestions, I would not have been able to raise the standard of the book chapters.
A particular mention also goes to all members of QxLab Research group at the University College Dublin (UCD), and the Department of Informatics and Information Technologies at Sokoine University of Agriculture (SUA), Tanzania, and Huawei Canada for any kind of help, support, and constructive discussions they gave to me through Zoom. It has been my great pleasure to have been working with these teams. I thank all of my fellow lab mates and coworkers from different universities, industry, and IT companies for the stimulating discussions and for all the fun moments we have had together in the last two years of completing this book. It has really been a privilege to be part of such an amazing team. I gratefully acknowledge the funding received toward my Postdoc from the European Union's Horizon 2020 Research and Innovation Fellowship under the Marie Skłodowska‐Curie‐Innovative Training Networks (MSCA ITN), ELITE‐S Fellowship Programme: A Marie Skłodowska‐Curie COFUND Action for intersectoral training, career development and mobility. Infinite thanks to my parents, Alex Barakabitze and Leonia Francis Nzika, my sisters and brothers, Josaphine, Alfred, Abely, and Bibiana, for all the support and unconditional love over the years. I would also like to thank my wife, Lilian Alcardo Barakabitze, for her encouragement, support, and unconditional love during this amazing journey of completing the book. Lastly, this book is dedicated to our beautiful three children, Alvin, Niah, and Doreen, for their motivation, support, endless love, and for bearing with me in my Postdocs journey. Not only have they given me the strength, stability, and motivation to finish this work, they have also made my life brighter and lighter with their love.
List of Acronyms
5G
Fifth Generation
ACTN
Abstraction and Control of Traffic Engineered Networks
B2B
Business‐to‐Business
B2C
Business‐to‐Customer
BSS
Business Support System
BSSO
Business Service Slice Orchestrator
CAPEX
Capital Expenditure
CC
Cloud Computing
CDNs
CDNs Content Distribution Networks
C‐RAN
Cloud RAN
D2D
Device‐to‐Device
DHCP
Dynamic Host Configuration Protocol
DSSO
Domain‐Specific Slice Orchestration
EC2
Elastic Compute Cloud
ELA
Experience Level Agreement
ETSI
European Telecommunication Standard Institute
FoC
Fog Computing
IRTF
Internet Research Task Force
ISPs
Internet Service Providers
ITU
International Telecommunication Union
KPR
Key Performance Requirements
KQIs
Key Quality Indicators
LAN
Local Area Network
LSDC
Lightweight Slice Defined Cloud
M2M
Machine‐to‐Machine
MANO
Management and Orchestration
MdO
Multi‐domain Orchestrator
MDSO
Multi‐Domain Slice Orchestrator
MEC
Multi‐Access Edge Computing
MIoTs
Massive Internet of Things
MO
Management and Orchestration
MTC
Machine Type Communications
MTCP
Mobile Transport and Computing Platform
NAT
Network Address Translation
NFs
Network Functions
NFV
Network Function Virtualization
NFVI‐PoP
NFVI Point of Presence
NFVO
Network Functions Virtualization Orchestrator
NGN
Next Generation Networks
ONF
Open Network Foundation
OPEX
OPerational EXpenditure
OSS
Operations Support Systems
PGW
Packet Data Network Gateway
PoP
Point of Presence
QoBiz
Quality of Business
RAN
Radio Access Network
RLC
Radio Link Control
RRM
Radio Resource Management
SaaS
Software as a Service
SDMC
Software‐Defined Mobile Network Control
SDMO
Software‐Defined Mobile network Orchestration
SFC
Service Function Chaining
SGW
Service Gateway
SLAs
Service Level Agreements
SRO
Slice Resource Orchestrator
SBS
Service Broker Stratum
SDO
Standard Developing Organizations
TN
Transport Networks
TOSCA
Topology and Orchestration Specification for Cloud Applications
USDL
Universal Service Definition Language
VMN
Virtual Mobile Networks
VMS
Virtual Machines
VNF‐FGs
VNF Forwarding Graphs
VNFs
Virtual Network Functions
VPN
Virtual Private Networks
VR/AR
Virtual/Augmented Reality
WWRF
Wireless World Research Forum
XCI
Xhaul Control Infrastructure
ZOOM
Zero‐time Orchestration, Operations and Management
15G Networks
From 1G to 4G, mobile communication has been for many years constantly changing our behavior, our communication experience in audio/video, and our lifestyle in general. With 5G arriving, our society will change radically through the realization of the Internet of Everything (IoE) where connected sensors will enable: connected robots for manufacturing and on Industry 4.0 revolution; connected sensors for smart city and connected smart homes. The requirements for ultra‐low latency and ultra‐high reliability in 5G networks is a game‐changer that is going to take the automotive industry from the assisted‐driving to connected cars. The 5G network is about enabling new services and applications, connecting new industries, and empowering new user experiences. 5G will connect people and things across a diverse set of other vertical segments including media and entertainment such as immersive and interactive media, collaborative video gaming andAugmented Reality (AR) or Virtual Reality (VR).
This chapter provides an introduction to 5G. It begins with some history of the progress through generations 1–5 of mobile network communications. Next it explains the motivations for 5G and the service and business drivers. It also discusses the emerging future services and applications that will require the capabilities of 5G and beyond to 6G. The chapter introduces a lot of network technology acronyms and terminology that is commonly used in the literature regarding 5G. For those familiar with 5G, there is also some discussion of the 5G standardization activities that are underway.
1.1 History of Mobile Communication Systems
Over the past decades, we have witnessed the tremendous growth of the fixed and wireless industry. Indeed, the mobile communication systems have evolved from a purely analog (1G), and limited to voice communications to 4G digital multimedia systems. The 2G mobile systems support full‐duplex communication and enable services such as picture messages, text messages, and Multimedia Messaging Service (MMS). Driven by the advancement in the Internet and IP network technology, 3G systems appeared in 2000 to fulfil users' ever increasing demands for data and service quality. 3G offers dedicated digital networks that are used for delivering broadband/multimedia services (e.g. TV streaming, mobile TV, phone calls, video conferencing, and 3D gaming) with an increased bandwidth and data transfer rates. 4G was necessary to meet the demands for multimedia services and applications (3D, HDTV content, Digital Video Broadcasting [DVB]) that require high bandwidth on sophisticated user platforms such as tablets and smartphones. 4G systems provide true wireless broadband services and deliver to its customer's multimedia services with good quality. However, many use cases and new applications with diverse requirements have emerged over the past years. These use cases and applications include: Internet of Things (IoTs); Internet of Vehicles (IoV); AR/VR; Device to Device (D2D) and Machine to Machine (M2M) communications and Financial Technology (FinTech), etc. Figure 1.1 shows the network evolution toward 5G systems and beyond.
It is unclear whether the current 4G LTE cellular systems can support the enormous rapid growth of data usage and device connectivity. For example, IoT and D2D/M2M communications in 5G systems would support tens of thousands of connected smart devices in a single cell while the current 4G LTE network can support up to 600 RCC‐connected users per cell. Both industry and academia are embracing 5G as the future network capable of supporting different verticals and use cases consisting of different service requirements.
Figure 1.1 Network evolution toward 5G and beyond.
Source: sarayut_sy/Adobe Stock
.
1.2 5G: Vision and Motivation
With the increasing number of new applications beyond personal communications, mobile devices, the exponential growth of mobile video services (e.g. YouTube and Mobile TV) on smart devices and the advances in the IoT have triggered global initiatives toward developing the 5G mobile/wireless communication systems [1–3]. The Cisco Visual Networking Index (VNI) Forecast [4] predicts that four‐fifths of the world's Internet traffic will be IP video traffic by 2023, a ninefold increase from 2018. Mobile video traffic alone will account for 78% of the global mobile data traffic. The traffic growth rates of TVs, tablets, smartphones, and M2M modules will be 21%, 29%, 49%, and 49%, respectively. The traffic for VR/AR will increase at a Compound Annual Growth Rate (CAGR) of 82% between 2018 and 2023. 5G devices and connections will be over 10% of global mobile devices and connections by 2023. Global mobile devices will grow from 8.8 billion in 2018 to 13.1 billion by 2023 – 1.4 billion of those will be 5G capable [4].
Moreover, three‐quarters of all devices connected to the mobile network will be smart devices by 2023, generating 99% of all mobile data traffic globally. 5G networks have been driven by the increasing number of smart devices (e.g. tablets and smartphones) and the growing number of bandwidth‐hungry mobile applications (e.g. live video streaming, online video gaming) which demand higher spectral efficiency than that of 4G LTE systems [4]. The increasing demand of high‐quality services by customers from service providers and mobile network operators and a well‐connected society context (e.g. smart grid and smart cities, critical infrastructure systems) are also among the factors that have triggered the development of 5G systems. The 5G market drivers that would enable the global economic output of trillion by 2035 include the needs for AR/VR, rich media services (e.g. real‐time video gaming, 4K/8K/12/3D video, video, live video broadcasting) and applications in smart cities, education, entertainment, industrial, and public safety [5] (Figure 1.2).
To support these new use cases, emerging multimedia services and applications, 5G and beyond systems should be able to support and deliver as much as 1000 times capacity compared with the current 4G LTE systems [2, 6]. The 5G Key Performance or Quality Indicators (KPIs/KQIs) include: 10–100 times higher user data rates, better, ubiquitous and almost 100% coverage for “anytime anywhere” connectivity and above 90% energy savings. In addition, 5G should also provide an End‐to‐End (E2E) latency of less than 1 ms, an aggregate service reliability and availability of 99.999%, and lowered electro‐magnetic field levels compared with 4G LTE [2, 7]. 5G has been recognized by industry and academia as the game‐changer that will enable new video streaming services and applications, connecting new vertical industries with a diverse set of performance and service requirements and empowering new user experiences. 5G will enable a connected society with massive devices connectivity and support intelligent transportation systems (e.g. autonomous and automated driving). Meeting performance targets such as higher data rate transmission, higher capacity, lower E2E latency, lower cost, and user satisfaction measured through Quality of Experience (QoE) for delivered services is key for the success of 5G. The 5G theme has attracted researchers and engineers for the past years. The debates, discussions and preliminary questions regarding the 2020 network and beyond include: (i) What the 5G network will be? [3], (ii) What are the requirements and future technological advancements for 5G networks? [2], (iii) What is the autonomic network architecture that can accommodate and support the emerging services and applications as well as various technologies to address the 5G challenges?, (iv) What are the novel solutions that can incorporate the 5G network driving principles (e.g. seamless mobility, programmability, flexibility): (v) How to implement the 5G vision of network/infrastructure/resource sharing/slicing and support dynamic multi‐service, multi‐tenancy across network softwarization technologies? (vi) How to perform dynamic control, orchestration of network resources as well as service customization of network slices (enabled by NFV principles) in 5G systems? (vii) How and to what extent can future 5G network management be automated to ensure that ISPs, MNOs, and OTT providers meet customer's service requirements and Experience Level Agreement (ELAs)1 in the cloud/fog/heterogeneous‐native supported softwarized networks [9]?
Figure 1.2 The 12 key enabling technologies in 5G networks.
Figure 1.3 Software network technologies in 5G architecture. A indicates RAN; B = transport networks; C = core networks; and D represents the Internet.
Different stakeholders from the research community have expressed their 5G vision for future 2020 communication systems and beyond as shown in Figure 1.3. One of the disruptive concepts that could provide answers to these questions and realize the 5G vision is network softwarization and slicing [10, 11]. For example, future multimedia services such as 4K/8K/12K will be managed and delivered with excellent QoE to end‐users in 5G using a new paradigm of network softwarization and virtualization that leverages cutting‐edge technologies such as Software‐Defined Networking (SDN), Network Function Virtualization (NFV), Multi‐Access Edge Computing (MEC), and Cloud/Fog computing [4]. Network softwarization [10, 12] in 5G networks is intended to deliver future services and applications with greater agility and cost‐effectiveness by employing software programming in the design, implementation, deployment, and management of network equipment/components/services [12, 13]. The E2E service QoE management and 5G network requirements (e.g. programmability, flexibility, and adaptability) are to be realized by network softwarization [4, 14]. Network softwarization and virtualization technologies are set to offer capabilities to developers and operators to build network‐aware applications and application‐aware networks. This would enable them to match their end‐users' business demands in 5G and the beyond networks. However, new design and implementation is needed in different 5G network segments (e.g. RAN, transport networks, core networks, mobile‐edge networks and network clouds) in order to achieve network softwarization goals. This is because each network segment needs a different softwarization level and set of technical characteristics [15]. Figure 1.3 indicates software network technologies at different network segments in 5G systems.
Figure 1.4 The NGMN 5G network slicing implementation.
For example, softwarization in mobile edge networks should be implemented using virtualized platforms based on SDN, NFV, and Information Centric Networking (ICN) [16, 17]. The design of most core networks and service plane functions in 5G networks have to be designed and implemented as Virtual Network Functions (VNFs) based on the envisaged SDN/NFV architectural principles. This approach would enable them to run on Virtual Machines (VMs), potentially over standard servers on Fog/Cloud Computing (CC) environments [18, 19]. That way, different network slices (smart cars) can use core networks and service VNFs based on the required latency and storage capacity of the requested service. In order to easily implement resource discovery and optimization mechanisms in the 5G control plane, the design of softwarized transport network can be done using appropriate interfaces in SDN/NFV infrastructures. This would allow various user applications and network‐based services to be accommodated in 5G systems (Figure 1.4).
1.3 5G Service Quality and Business Requirements
5G networks promise to be more reliable on smart devices and facilitate ultra‐fast video downloads. Different domains such as D2D/M2M, health (e.g. e‐health, telemedicine), industrial 4.0, entertainment, intelligent transportation are to be facilitated with various 5G applications and services. Different requirements for these 5G applications will be required in order to enhance their performance. For 5G to meet these performance requirements, new ways with intelligent network traffic management, caching, mobility and offload schemes, as well as enhanced capacity (e.g. small cells deployment) will have to be developed. Some of the 5G vision is to provide an increase of network bandwidth, coverage, and Internet connectivity, a massive reduction in energy consumption on smart devices and lower latency. With lower latency in 5G, downloading a large video file on a customer's device will be achieved within a few seconds. Some of the identified requirements of 5G networks as illustrated in Figure 1.5
