Green Machine Learning Protocols for Future Communication Networks

The proposed book will cover new and novel lightweight and energy-efficient ML-based protocols for future communication networks, including ML for different communication networks and federated learning. It will also present a survey on ML-based energy-efficient protocols for future applications, highlight the requirements for energy-efficient and lightweight ML protocols, and present novel research opportunities and challenges for ML-based energy-efficient communication network applications.

Format: Hardback
Length: 200 pages
Publication date: 25 October 2023
Publisher: Taylor & Francis Ltd

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The proposed book aims to delve into the realm of machine learning (ML) and its applications in various communication networks, including federated learning. It seeks to provide a comprehensive understanding of the latest developments and advancements in the field.

The book will offer a fresh perspective on developing lightweight and energy-efficient ML-based protocols for diverse future communication networks. It will emphasize the importance of energy-efficient ML protocols in real-time communication network applications, highlighting their significance in meeting the growing demands of data transmission and processing.

The book will delve into the requirements and challenges of implementing energy-efficient and lightweight ML protocols in different communication networks. It will present a comprehensive survey on ML-based energy-efficient protocols for future applications, encompassing a wide range of topics such as wireless communication systems, cognitive radio networks, and Internet of Things (IoT) networks.

Furthermore, the book will explore physical layer protocols and schemes for ML and communication networks. It will provide novel research opportunities and challenges for ML-based energy-efficient communication network applications, fostering interdisciplinary collaboration and driving innovation in the field.

By offering a comprehensive and up-to-date exploration of ML and its applications in communication networks, the proposed book will serve as a valuable resource for researchers, practitioners, and students alike. It will contribute to the advancement of ML and its integration into communication networks, enabling the development of more efficient, sustainable, and resilient communication systems for the future.

Weight: 570g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032136851