Название: Machine Learning Empowered Intelligent Data Center Networking: Evolution, Challenges and Opportunities
Автор: Ting Wang, Bo Li, Mingsong Chen, Shui Yu
Издательство: Springer
Серия: SpringerBriefs in Computer Science
Год: 2023
Страниц: 123
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB
An Introduction to the Machine Learning Empowered Intelligent Data Center Networking. Fundamentals of Machine Learning in Data Center Networks. This book reviews the common learning paradigms that are widely used in data center networks, and offers an introduction to data collection and data processing in data centers. Additionally, it proposes a multi-dimensional and multi-perspective solution quality assessment system called REBEL-3S. The book offers readers a solid foundation for conducting research in the field of AI-assisted data center networks. Comprehensive Survey of AI-assisted Intelligent Data Center Networks. This book comprehensively investigates the peer-reviewed literature published in recent years. The wide range of Machine Learning techniques is fully reflected to allow fair comparisons. In addition, the book provides in-depth analysis and enlightening discussions on the effectiveness of AI in DCNs from various perspectives, covering flow prediction, flow classification, load balancing, resource management, energy management, routing optimization, congestion control, fault management, and network security. Machine Learning paradigms can be generally classified into three categories: supervised learning, unsupervised learning, and reinforcement learning. With the in-depth research and development of ML, some new learning paradigms such as deep learning and deep reinforcement learning have been derived for more complex scenarios.