Description
Mobile Edge Artificial Intelligence: Opportunities and Challenges presents recent advances in wireless technologies and nonconvex optimization techniques for designing efficient edge AI systems. The book includes comprehensive coverage on modeling, algorithm design and theoretical analysis. Through typical examples, the powerfulness of this set of systems and algorithms is demonstrated, along with their abilities to make low-latency, reliable and private intelligent decisions at network edge. With the availability of massive datasets, high performance computing platforms, sophisticated algorithms and software toolkits, AI has achieved remarkable success in many application domains.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
Table of Contents
I. Introduction and Overview1. Primer on Artificial Intelligence2. Overview of Edge AI SystemsII. Edge Inference3. Model Compression for On-Device Inference4. Wireless MapReduce for Device Distributed Inference 5. Wireless Cooperative Transmission for Edge InferenceIII. Edge Training6. Over-the-Air Computation for Federated Learning7. Blind Over-the-Air Computation for Federated Learning8. Reconfigurable Intelligent Surface Aided Federated Learning SystemIV. Future Directions9. Communication-Efficient Algorithms for Edge AI10. Future Research Directions
