QoS-Aware Virtual Network Embedding
Autor Chunxiao Jiang, Peiying Zhangen Limba Engleză Hardback – 4 dec 2021
At present, a distinctive feature of the Internet environment is that the quality of service (QoS) requirements of users are differentiated. Different regions, different times, and different users have different network function requirements. Therefore, network resources need to be reasonably allocated according to users' QoS requirements to avoid the waste of network resources.
In this book, based on the analysis of the principle of VNE algorithm, we provide a VNE scheme for users with differentiated QoS requirements. We summarize the common user requirements into four categories: security awareness, service awareness, energy awareness, and load balance, and then introduce the specific implementation methods of various differentiated QoS algorithms. This book provides a variety of VNE solutions, including VNE algorithms for single physical domain, VNE algorithms for across multiple physical domains, VNE algorithms based on heuristic method, and VNE algorithms based on machine learning method.
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Specificații
ISBN-13: 9789811652202
ISBN-10: 9811652201
Pagini: 412
Ilustrații: X, 401 p. 1 illus.
Dimensiuni: 160 x 241 x 28 mm
Greutate: 0.73 kg
Ediția:1st ed. 2021
Editura: Springer
Locul publicării:Singapore, Singapore
ISBN-10: 9811652201
Pagini: 412
Ilustrații: X, 401 p. 1 illus.
Dimensiuni: 160 x 241 x 28 mm
Greutate: 0.73 kg
Ediția:1st ed. 2021
Editura: Springer
Locul publicării:Singapore, Singapore
Cuprins
Chapter 1. Introduction.- Chapter 2. Introduction of security requirements in VNE.- Chapter 3. Security Aware Virtual Network Embedding Algorithm using Information Entropy TOPSIS.- Chapter 4. Security-Aware Virtual Network Embedding Algorithm based on Reinforcement Learning.- Chapter 5. VNE Solution for Network Differentiated QoS
and Security Requirements From the Perspective of Deep Reinforcement Learning.- Chapter 6. Resource Management and Security Scheme of ICPSs and IoT Based on VNE Algorithm.- Chapter 7. Description of service-aware requirements in VNE.- Chapter 8. Virtual Network Embedding based on Modified Genetic Algorithm.- Chapter 9. VNE-HPSO Virtual Network Embedding Algorithm based On Hybrid Particle Swarm Optimization.- Chapter 10. Topology based Reliable Virtual Network Embedding from a QoE Perspective.- Chapter 11. "DSCD Delay Sensitive Cross-Domain Virtual Network Embedding Algorithm".- Chapter 12."A Multi-Domain Virtual Network Embedding Algorithm with Delay Prediction".- Chapter 13. "Description of energy consumption requirements in VNE".- Chapter 14. A"Multi-objective Enhanced Particle Swarm Optimization in Virtual Network Embedding".- Chapter 15. "Incorporating Energy and Load Balance into Virtual Network Embedding Process".- Chapter 16. "IoV Scenario Implementation of a Bandwidth Aware Algorithm in Wireless Network Communication Mode".- Chapter 17. Description of load balance in VNE.- Chapter 18."A Multi-Domain VNE Algorithm based on Load Balancing in the IoT Networks".- Chapter 19."Virtual Network Embedding based on Computing, Network and Storage Resource Constraints".- Chapter 20. Virtual Network Embedding using Node Multiple Metrics based on Simplified ELECTRE Method.- Chapter 21."VNE Strategy based on Chaotic Hybrid Flower Pollination Algorithm Considering Multi-criteria Decision Making".- Chapter 22. Conclusion.
Notă biografică
Jingjing Wang (S'14-M'19-SM'21) is currently an associate professor in School of Cyber Science and Technology, Beihang University. He received his B.S. degree in Electronic Information Engineering from Dalian University of Technology, Liaoning, China in 2014 and the Ph.D. degree in Information and Communication Engineering from Tsinghua University, Beijing, China in 2019, both with the highest honors. From 2017 to 2018, he visited the Next Generation Wireless Group chaired by Prof. Lajos Hanzo, University of Southampton, UK. Dr. Wang His research interests include AI enhanced next-generation wireless networks, swarm intelligence and confrontation. He has published over 100 IEEE Journal/Conference papers. Dr. Wang has served as an Editor of IEEE Open Journal of the Communications Society, and also served as a member of the technical program committee for a number of international conferences. Dr. Wang was the recipient of the Best Journal Paper Award of IEEE ComSoc Technical Committee on Green Communications & Computing in 2018, the Best Paper Award of IEEE ICC and IWCMC in 2019. Chunxiao Jiang (S'09-M'13-SM'15) is an associate professor in School of Information Science and Technology, Tsinghua University. He received the B.S. degree in information engineering from Beihang University, Beijing in 2008 and the Ph.D. degree in electronic engineering from Tsinghua University, Beijing in 2013, both with the highest honors. From 2011 to 2012 (as a Joint Ph.D) and 2013 to 2016 (as a Postdoc), he was in the Department of Electrical and Computer Engineering at University of Maryland College Park under the supervision of Prof. K. J. Ray Liu. His research interests include application of game theory, optimization, and statistical theories to communication, networking, and resource allocation problems, in particular space networks and heterogeneous networks. Dr. Jiang has served as an Editor of IEEE Transactions on Communications, IEEE Internet of Things Journal, IEEE Wireless Communications, IEEE Network, IEEE Communications Letters, and a Guest Editor of IEEE Communications Magazine, IEEE Transactions on Network Science and Engineering and IEEE Transactions on Cognitive Communications and Networking. He has also served as a member of the technical program committee as well as the Symposium Chair for a number of international conferences, including IEEE Globecom 2021 Symposium Chair, IEEE CNS 2020 Publication Chair, IEEE WCSP 2019 Symposium Chair, IEEE ICC 2018 Symposium Co-Chair, IWCMC 2020/19/18 Symposium Chair, WiMob 2018 Publicity Chair, ICCC 2018 Workshop Co-Chair, and IEEE ICC 2017 Workshop Co-Chair. Dr. Jiang is the recipient of the Best Paper Award from IEEE GLOBECOM in 2013, the Best Student Paper Award from IEEE GlobalSIP in 2015, IEEE Communications Society Young Author Best Paper Award in 2017, the Best Paper Award IWCMC in 2017, IEEE ComSoc TC Best Journal Paper Award of the IEEE ComSoc TC on Green Communications & Computing 2018, IEEE ComSoc TC Best Journal Paper Award of the IEEE ComSoc TC on Communications Systems Integration and Modeling 2018, the Best Paper Award from ICC 2019, IEEE VTS Early Career Award 2020, IEEE ComSoc Asia-Pacific Best Young Researcher Award 2020, and IEEE VTS Distinguished Lecturer 2021. He received the Chinese National Second Prize in Technical Inventions Award in 2018 and Natural Science Foundation of China Excellent Young Scientists Fund Award in 2019. He is a Senior Member of IEEE and a Fellow of IET.
Textul de pe ultima copertă
As an important future network architecture, virtual network architecture has received extensive attention. Virtual network embedding (VNE) is one of the core services of network virtualization (NV). It provides solutions for various network applications from the perspective of virtual network resource allocation. The Internet aims to provide global users with comprehensive coverage. The network function requests of hundreds of millions of end users have brought great pressure to the underlying network architecture. VNE algorithm can provide effective support for the reasonable and efficient allocation of network resources, so as to alleviate the pressure off the Internet.
At present, a distinctive feature of the Internet environment is that the quality of service (QoS) requirements of users are differentiated. Different regions, different times, and different users have different network function requirements. Therefore, network resources need to be reasonably allocated according to users' QoS requirements to avoid the waste of network resources.
In this book, based on the analysis of the principle of VNE algorithm, we provide a VNE scheme for users with differentiated QoS requirements. We summarize the common user requirements into four categories: security awareness, service awareness, energy awareness, and load balance, and then introduce the specific implementation methods of various differentiated QoS algorithms. This book provides a variety of VNE solutions, including VNE algorithms for single physical domain, VNE algorithms for across multiple physical domains, VNE algorithms based on heuristic method, and VNE algorithms based on machine learning method.
At present, a distinctive feature of the Internet environment is that the quality of service (QoS) requirements of users are differentiated. Different regions, different times, and different users have different network function requirements. Therefore, network resources need to be reasonably allocated according to users' QoS requirements to avoid the waste of network resources.
In this book, based on the analysis of the principle of VNE algorithm, we provide a VNE scheme for users with differentiated QoS requirements. We summarize the common user requirements into four categories: security awareness, service awareness, energy awareness, and load balance, and then introduce the specific implementation methods of various differentiated QoS algorithms. This book provides a variety of VNE solutions, including VNE algorithms for single physical domain, VNE algorithms for across multiple physical domains, VNE algorithms based on heuristic method, and VNE algorithms based on machine learning method.
Caracteristici
Is the first book that introduces virtual network embedded algorithms for differentiated QoS requirements Introduces a variety of virtual network embedding algorithms suitable for different network ranges Provides comprehensive and detailed virtual network embedding theory