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Automated Machine Learning (AutoML) for Zero-touch Network and Service Management (River Publishers Series in Automation, Control and Robotics)
Author(s): Prithi Samuel (Editor), Malathy Sathyamoorthy (Editor), Rajesh Kumar Dhanaraj (Editor), Balamurugan Balusamy (Editor)
- Publisher Finelybook 出版社: River Publishers
- Publication Date 出版日期: 21 Dec. 2026
- Edition 版本: 1st
- Language 语言: English
- Print length 页数: 440 pages
- ISBN-10: 8743810543
- ISBN-13: 9788743810544
Book Description
Automated Machine Learning (AutoML) for Zero-touch Network and Service Management provides a comprehensive examination of how AutoML techniques are transforming next-generation network operations. As modern communication networks continue to grow in scale, heterogeneity, and complexity, traditional manual configuration and management approaches have become increasingly impractical. Zero-touch network and service management (ZSM) has therefore emerged as a critical paradigm for enabling autonomous, self-configuring, self-optimizing, and self-healing networks.
This book bridges the gap between machine learning automation and intelligent network management by exploring the role of AutoML in the design, deployment, and operation of zero-touch networks. It presents fundamental concepts, system architectures, and enabling technologies, while addressing key practical challenges such as model selection, hyperparameter optimization, data scarcity, explainability, scalability, and the lifecycle management of machine learning models in real-world operational environments.
Through in-depth discussions, real-world use cases, and emerging research directions, the book offers valuable insights into applying AutoML across network domains, including software-defined networking, network function virtualization, 5G/6G systems, cloud-native services, and edge computing. It serves as both a research reference and a practical guide, it is an essential resource for researchers and practitioners seeking to build intelligent, autonomous, and resilient networked systems.
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About the Author
Dr. Prithi Samuelis an Assistant Professor in the Department of Computational Intelligence at SRM Institute of Science and Technology, Chennai. She holds a Ph.D. in information and communication engineering from Anna University and has over 15 years of teaching experience. Her research focuses on automata theory, machine learning, deep learning, computational intelligence, and IoT. She has published extensively in reputed journals, conferences, and leading publishers, and is an active member of IEEE, ACM, ISTE, and IAENG.
Dr. Malathy Sathyamoorthyis an Associate Professor in the Department of Information Technology at KPR Institute of Engineering and Technology, Coimbatore. She received her M.Eng. in computer science and engineering in 2012 and completed her Ph.D. in information and communication engineering from Anna University in 2023. She has published over 25 SCI/Scopus-indexed journal papers, 22 international conference papers, 2 patents, 1 book, and 8 book chapters. Her research interests include wireless sensor networks, networking, security, and machine learning. She is a senior member of IEEE, life member of ISTE and IAENG, a reviewer for Springer Wireless Networks, and serves on editorial and conference boards.
Dr. Rajesh Kumar Dhanarajis a distinguished Professor at Symbiosis International (Deemed University), Pune, with prior tenure at Galgotias University. He is recognized among the global top 2% scientists by Elsevier and Stanford University, he holds a B.Eng., M.Tech, and Ph.D. in computer science from Anna University. He has authored or edited over 50 books, published more than 100 research papers, and holds 21 patents. His research spans machine learning, cyber-physical systems, and wireless sensor networks. A senior IEEE member, he also contributes as an associate and guest editor to leading journals and serves on the Expert Advisory Panel of Texas Instruments.
Balamurugan Balusamyis a Professor and Chairperson in the School of Engineering and IT at Manipal University Dubai, and an Adjunct Professor at Taylor University, Malaysia. Previously, he served as Professor and Associate Dean (Academics) at Shiv Nadar Institution of Eminence, Delhi-NCR, and as Professor and Director (International Relations) at Galgotias University, India. He has been recognized among the top 2% of most-cited scientists worldwide (2023) by Stanford University in Data Science, AI, and ML. Prof. Balusamy has authored and edited 200+ books and published 200+ high-impact research papers with Springer, Elsevier, and IEEE. His expertise spans engineering education, blockchain, data science, and Industrial IoT, with extensive global academic and industry collaborations. An active academic leader, he has delivered 210+ invited talks and spearheaded 10+ IEEE and ACM international conferences across 15+ countries.
