Edge AI : convergence of edge computing and artificial intelligence /: convergence of edge computing and artificial intelligence. ([2020])

• Record Type: Book
• Further Information: Note: Xiaofei Wang, Yiwen Han, Victor C. M. Leung, Dusit Niyato, Xueqiang Yan, Xu Chen.
• Authors: Wang, Xiaofei; Han, Yiwen; Leung, Victor C. M; Niyato, Dusit; Yan, Xueqiang; Chen, Xu
• Contents: Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- Part I Introduction and Fundamentals -- 1 Introduction -- 1.1 A Brief Introduction to Edge Computing -- 1.2 Trends in Edge Computing -- 1.3 Industrial Applications of Edge Computing -- 1.4 Intelligent Edge and Edge Intelligence -- References -- 2 Fundamentals of Edge Computing -- 2.1 Paradigms of Edge Computing -- 2.1.1 Cloudlet and Micro Data Centers -- 2.1.2 Fog Computing -- 2.1.3 Mobile and Multi-Access Edge Computing (MEC) -- 2.1.4 Definition of Edge Computing Terminologies -- 2.1.5 Collaborative End-Edge-Cloud Computing 2.2 Hardware for Edge Computing -- 2.2.1 AI Hardware for Edge Computing -- 2.2.2 Integrated Commodities Potentially for Edge Nodes -- 2.3 Edge Computing Frameworks -- 2.4 Virtualizing the Edge -- 2.4.1 Virtualization Techniques -- 2.4.2 Network Virtualization -- 2.4.3 Network Slicing -- 2.5 Value Scenarios for Edge Computing -- 2.5.1 Smart Parks -- 2.5.2 Video Surveillance -- 2.5.3 Industrial Internet of Things -- References -- 3 Fundamentals of Artificial Intelligence -- 3.1 Artificial Intelligence and Deep Learning -- 3.2 Neural Networks in Deep Learning 3.2.1 Fully Connected Neural Network (FCNN) -- 3.2.2 Auto-Encoder (AE) -- 3.2.3 Convolutional Neural Network (CNN) -- 3.2.4 Generative Adversarial Network (GAN) -- 3.2.5 Recurrent Neural Network (RNN) -- 3.2.6 Transfer Learning (TL) -- 3.3 Deep Reinforcement Learning (DRL) -- 3.3.1 Reinforcement Learning (RL) -- 3.3.2 Value-Based DRL -- 3.3.3 Policy-Gradient-Based DRL -- 3.4 Distributed DL Training -- 3.4.1 Data Parallelism -- 3.4.2 Model Parallelism -- 3.5 Potential DL Libraries for Edge -- References -- Part II Artificial Intelligence and Edge Computing 4 Artificial Intelligence Applications on Edge -- 4.1 Real-time Video Analytic -- 4.1.1 Machine Learning Solution -- 4.1.2 Deep Learning Solution -- 4.1.2.1 End Level -- 4.1.2.2 Edge Level -- 4.1.2.3 Cloud Level -- 4.2 Autonomous Internet of Vehicles (IoVs) -- 4.2.1 Machine Learning Solution -- 4.2.2 Deep Learning Solution -- 4.2.2.1 End Level -- 4.2.2.2 Edge Level -- 4.2.2.3 Cloud Level -- 4.3 Intelligent Manufacturing -- 4.3.1 Machine Learning Solution -- 4.3.2 Deep Learning Solution -- 4.3.2.1 End Level -- 4.3.2.2 Edge Level -- 4.3.2.3 Cloud Level -- 4.4 Smart Home and City 4.4.1 Machine Learning Solution -- 4.4.2 Deep Learning Solution -- 4.4.2.1 End Level -- 4.4.2.2 Edge Level -- 4.4.2.3 Cloud Level -- References -- 5 Artificial Intelligence Inference in Edge -- 5.1 Optimization of AI Models in Edge -- 5.1.1 General Methods for Model Optimization -- 5.1.2 Model Optimization for Edge Devices -- 5.2 Segmentation of AI Models -- 5.3 Early Exit of Inference (EEoI) -- 5.4 Sharing of AI Computation -- References -- 6 Artificial Intelligence Training at Edge -- 6.1 Distributed Training at Edge -- 6.2 Vanilla Federated Learning at Edge -- 6.3 Communication-Efficient FL
• Publisher Details: Singapore : Springer
• Publication Date: 2020
• Extent: 1 online resource
• Subjects: 006.3; Artificial intelligence; Edge computing; Artificial Intelligence; Computer Communication Networks; Computer Systems Organization and Communication Networks; Electronic books
• Languages: English
• ISBNs: 9789811561863; 9811561869
• Related ISBNs: 9811561850; 9789811561856
• Notes: Note: Includes bibliographical references.; Note: Description based on online resource; title from digital title page (viewed on October 05, 2020).
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• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.