Mobile Edge Artificial Intelligence

With the availability of massive data sets, high performance computing platforms, as well as sophisticated algorithms and software toolkits, AI has achieved remarkable success in many application domains. AI tasks are computationally intensive and generally trained, developed, and deployed at data centers with specifically designed servers. With the fast-increasing number of intelligent devices, it is expected that many high-stake applications will be deployed at the edge of wireless networks soon. As such, the 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. Mobile Edge Artificial Intelligence: Opportunities and Challenges presents recent advances in wireless technologies and nonconvex optimization techniques for designing efficient edge AI systems, with a comprehensive coverage including modeling, algorithm design, and theoretical analysis. Through typical examples, the powerfulness of this set of systems and algorithms will be demonstrated, and their abilities in making low-latency, reliable and private intelligent decisions at network edge will be highlighted. Presents advanced key enabling techniques, including model compression, wireless MapReduce and wireless cooperative transmissionProvides advanced 6G wireless techniques, including over-the-air computation and reconfigurable intelligent surfaceBrings to the readers the principles of designing communication-efficient edge inference systems, communication-efficient training systems, and communication-efficient optimization algorithms for edge machine learning