Optimising IoT Networks
Energy-Efficient Resource Management through Machine Learning
- Publisher's listprice GBP 79.99
-
38 215 Ft (36 395 Ft + 5% VAT)
The price is estimated because at the time of ordering we do not know what conversion rates will apply to HUF / product currency when the book arrives. In case HUF is weaker, the price increases slightly, in case HUF is stronger, the price goes lower slightly.
- Discount 20% (cc. 7 643 Ft off)
- Discounted price 30 572 Ft (29 116 Ft + 5% VAT)
Subcribe now and take benefit of a favourable price.
Subscribe
38 215 Ft
Availability
Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
Not in stock at Prospero.
Why don't you give exact delivery time?
Delivery time is estimated on our previous experiences. We give estimations only, because we order from outside Hungary, and the delivery time mainly depends on how quickly the publisher supplies the book. Faster or slower deliveries both happen, but we do our best to supply as quickly as possible.
Product details:
- Edition number 1
- Publisher Chapman and Hall
- Date of Publication 23 June 2025
- ISBN 9781032997971
- Binding Hardback
- No. of pages280 pages
- Size 234x156 mm
- Weight 680 g
- Language English
- Illustrations 98 Illustrations, black & white; 7 Halftones, black & white; 91 Line drawings, black & white; 27 Tables, black & white 673
Categories
Short description:
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.
More
Long 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.
MoreTable of 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
More
Optimising IoT Networks: Energy-Efficient Resource Management through Machine Learning
Number Concepts and Operations in the Middle Grades: the Research Agenda for Mathematics Education, Volume 2
19 105 HUF
17 194 HUF
