Wow! eBook
Networks and Sustainability: Smart Grid, Data Science, and Smart Applications
Author(s): Andriy Luntovskyy (Editor), Mikhailo Klymash (Editor), Igor Melnyk (Editor), Mykola Beshley (Editor), Dietbert Gütter (Editor)
- Publisher: Springer
- Publication Date: October 2, 2025
- Language: English
- Print length: 852 pages
- ISBN-10: 3032022711
- ISBN-13: 9783032022714
Book Description
This book explores advanced networking topics, building on previous Springer books like “Intent-based Networking” (2022), “Emerging Networking in the Digital Transformation Age” (2023), and “Digital Ecosystems” (2024). It merges network technologies with sustainable development, energy efficiency, AI, and smart apps. Topics include LLMs, ML, large-scale distributed networks’ QoS, IoT with cloud and fog ecosystems, smart grids, and robotics. It emphasizes the synergy of smart apps, AI, and computational intelligence. The book shows how advanced networks support sustainability, energy efficiency, and inclusiveness focusing on data science, cybersecurity, user intentions, and cost reduction addressing key aspects like reliability, privacy, inclusiveness, and accessibility. Suitable for students, professors, and lecturers in networking, distributed systems, cybersecurity, data science, and AI, it also serves as a research base and source of inspiration for professionals seeking new challenges.
Editorial Reviews
From the Back Cover
This book explores advanced networking topics, building on previous Springer books like “Intent-based Networking” (2022), “Emerging Networking in the Digital Transformation Age” (2023), and “Digital Ecosystems” (2024). It merges network technologies with sustainable development, energy efficiency, AI, and smart apps. Topics include LLMs, ML, large-scale distributed networks’ QoS, IoT with cloud and fog ecosystems, smart grids, and robotics. It emphasizes the synergy of smart apps, AI, and computational intelligence. The book shows how advanced networks support sustainability, energy efficiency, and inclusiveness focusing on data science, cybersecurity, user intentions, and cost reduction addressing key aspects like reliability, privacy, inclusiveness, and accessibility. Suitable for students, professors, and lecturers in networking, distributed systems, cybersecurity, data science, and AI, it also serves as a research base and source of inspiration for professionals seeking new challenges.
