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Full Description
With a specific focus on energy efficiency, Optimizing IoT Networks examines the application of machine learning to enhance resource allocations in IoT networks.It discusses various algorithms, including neural networks and reinforcement learning, to optimise 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 optimisation 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 behaviour and varying data traffic patterns
• Covers key machine learning concepts and algorithms relevant to optimising resource allocation in IoT networks
• Emphasises 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 optimising IoT networks.
Contents
1. IoT Network 2. Research Issues and Performance Analysis in IoT network 3. Distance Aware Gateway Placement in IoT Network 4. Machine Learning Traffic Prediction for Link Selection 5. Fairness-Driven Resource Allocation Optimisation in IoT Network 6. Delay Aware Link Scheduling in IoT network 7. Energy Consumption Optimisation in IoT network 8. Future Directions and Trends in IoT Network 9. Practical Applications and Case Studies: Realising the Potential of IoT Resource Allocation
