Mobile Edge Artificial Intelligence: Opportunities and Challenges
Autor Yuanming Shi, Kai Yang, Zhanpeng Yang, Yong Zhouen Limba Engleză Paperback – 17 aug 2021
As such, intelligent wireless networks will be designed to leverage advanced wireless communications and mobile computing technologies to support AI-enabled applications at various edge mobile devices with limited communication, computation, hardware and energy resources.
- Presents advanced key enabling techniques, including model compression, wireless MapReduce and wireless cooperative transmission
- Provides advanced 6G wireless techniques, including over-the-air computation and reconfigurable intelligent surface
- Includes principles for designing communication-efficient edge inference systems, communication-efficient training systems, and communication-efficient optimization algorithms for edge machine learning
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Specificații
ISBN-13: 9780128238172
ISBN-10: 0128238178
Pagini: 206
Dimensiuni: 152 x 229 mm
Greutate: 0.28 kg
Editura: ELSEVIER SCIENCE
ISBN-10: 0128238178
Pagini: 206
Dimensiuni: 152 x 229 mm
Greutate: 0.28 kg
Editura: ELSEVIER SCIENCE
Public țintă
Scientists and researchers, postgraduates, undergraduates, practitioners and professionals in electronic engineering and computer scienceCuprins
I. Introduction and Overview
1. Primer on Artificial Intelligence
2. Overview of Edge AI Systems
II. Edge Inference
3. Model Compression for On-Device Inference
4. Wireless MapReduce for Device Distributed Inference
5. Wireless Cooperative Transmission for Edge Inference
III. Edge Training
6. Over-the-Air Computation for Federated Learning
7. Blind Over-the-Air Computation for Federated Learning
8. Reconfigurable Intelligent Surface Aided Federated Learning System
IV. Future Directions
9. Communication-Efficient Algorithms for Edge AI
10. Future Research Directions
1. Primer on Artificial Intelligence
2. Overview of Edge AI Systems
II. Edge Inference
3. Model Compression for On-Device Inference
4. Wireless MapReduce for Device Distributed Inference
5. Wireless Cooperative Transmission for Edge Inference
III. Edge Training
6. Over-the-Air Computation for Federated Learning
7. Blind Over-the-Air Computation for Federated Learning
8. Reconfigurable Intelligent Surface Aided Federated Learning System
IV. Future Directions
9. Communication-Efficient Algorithms for Edge AI
10. Future Research Directions