Optimizing IoT Networks：Energy-Efficient Resource Management through Machine Learning

The book examines the application of machine learning to enhance resource allocation in IoT networks, with a specific focus on energy efficiency. It discusses various algorithms, including neural networks and reinforcement learning, to optimize resource use and improve network performance. It addresses challenges such as the dynamic behaviour of IoT devices and the need for real-time decision-making. It discusses optimization methods used alongside machine learning to enhance resource allocation efficiency.

• Provides a foundational understanding of IoT network architecture and the importance of efficient resource allocation

• Discusses complexities in resource allocation due to dynamic device behavior and varying data traffic patterns

• Covers key machine learning concepts and algorithms relevant to optimizing resource allocation in IoT networks

• Emphasizes the significance of energy efficiency in IoT networks and its impact on resource allocation strategies

• Explores algorithms such as clustering, regression, and reinforcement learning for effective resource allocation

The book is designed for researchers, practitioners, and scholars in computer science and technology who are interested in or actively working on optimizing IoT networks.