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Connectivity and Edge Computing in IoT: Customized Designs and AI-based Solutions
Author
Title
Connectivity and Edge Computing in IoT: Customized Designs and AI-based Solutions [electronic resource] / by Jie Gao, Mushu Li, Weihua Zhuang.
ISBN
9783030887438
Edition
1st ed. 2021.
Publication
Cham : Springer International Publishing : Imprint: Springer, 2021.
Physical Description
1 online resource (XIV, 168 p.) 28 illus., 15 illus. in color.
Local Notes
Access is available to the Yale community.
Access and use
Access restricted by licensing agreement.
Summary
This book covers connectivity and edge computing solutions for representative Internet of Things (IoT) use cases, including industrial IoT, rural IoT, Internet of Vehicles (IoV), and mobile virtual reality (VR). Based on their unique characteristics and requirements, customized solutions are designed with targets such as supporting massive connections or seamless mobility and achieving low latency or high energy efficiency. Meanwhile, the book highlights the role of artificial intelligence (AI) in future IoT networks and showcases AI-based connectivity and edge computing solutions. The solutions presented in this book serve the overall purpose of facilitating an increasingly connected and intelligent world. The potential benefits of the solutions include increased productivity in factories, improved connectivity in rural areas, enhanced safety for vehicles, and enriched entertainment experiences for mobile users. Featuring state-of-the-art research in the IoT field, this book can help answer the question of how to connect billions of diverse devices and enable seamless data collection and processing in future IoT. The content also provides insights regarding the significance of customizing use case-specific solutions as well as approaches of using various AI methods to empower IoT. This book targets researchers and graduate students working in the areas of electrical engineering, computing engineering, and computer science as a secondary textbook or reference. Professionals in industry who work in the field of IoT will also find this book useful.
Variant and related titles
Springer ENIN.
Other formats
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Format
Books / Online
Language
English
Added to Catalog
November 30, 2021
Series
Wireless Networks,
Contents
Introduction
1.1 The Era of Internet of Things
1.2 Connectivity in IoT
1.3 Edge Computing in IoT
1.4 AI in IoT
1.5 Scope and Organization of This Book
References
2 Industrial Internet of Things: Smart Factory
2.1 Industrial IoT Networks
2.2 Connectivity Requirements of Smart Factory
2.2.1 Application-Specific Requirements
2.2.2 Related Standards
2.2.3 Potential Non-Link-Layer Solutions
2.2.4 Link-Layer Solutions: Recent Research Efforts
2.3 Protocol Design for Smart Factory
2.3.1 Networking Scenario
2.3.2 Mini-Slot based Carrier Sensing (MsCS)
2.3.3 Synchronization Sensing (SyncCS)
2.3.4 Di_erentiated Assignment Cycles
2.3.5 Superimposed Mini-slot Assignment (SMsA)
2.3.6 Downlink Control
2.4 Performance Analysis
2.4.1 Delay Performance with No Buaer
2.4.2 Delay Performance with Buaer
2.4.3 Slot Idle Probability
2.4.4 Impact of SyncCS
2.4.5 Impact of SMsA
2.5 Scheduling and AI-Assisted Protocol Parameter Selection
2.5.1 Background
2.5.2 The Considered Scheduling Problem
ix
x Contents
2.5.3 Device Assignment
2.5.4 AI-Assisted Protocol Parameter Selection
2.6 Numerical Results
2.6.1 Mini-Slot Delay with MsCS, SyncCS, and SMsA
2.6.2 Performance of the Device Assignment Algorithms
2.6.3 DNN-Assisted Scheduling
2.7 Summary
References
3 UAV-Assisted Edge Computing: Rural IoT Applications
3.1 Background on UAV-Assisted Edge Computing
3.2 Connectivity Requirements of UAV-assisted MEC for Rural
IoT
3.2.1 Network Constraints
3.2.2 State-of-the-Art Solutions
3.3 Multi-Resource Allocation for UAV-Assisted Edge Computing
3.3.1 Network Model
3.3.2 Communication Model
3.3.3 Computing Model
3.3.4 Energy Consumption Model
3.3.5 Problem Formulation
3.3.6 Optimization Algorithm for UAV-Assisted Edge
Computing
3.3.7 Proactive Trajectory Design based on Spatial
Distribution Estimation
3.4 Numerical Results
3.5 Summary
References
4 Collaborative Computing for Internet of Vehicles
4.1 Background on Internet of Vehicles
4.2 Connectivity Challenges for MEC
4.2.1 Server Selection for Computing Offoading
4.2.2 Service Migration
4.2.3 Cooperative Computing
4.3 Computing Task Partition and Scheduling for Edge Computing
4.3.1 Collaborative Edge Computing Framework
4.3.2 Service Delay
4.3.3 Service Failure Penalty
4.3.4 Problem Formulation
4.3.5 Task Partition and Scheduling
4.4 AI-Assisted Collaborative Computing Approach
4.5 Performance Evaluation
4.5.1 Task Partition and Scheduling Algorithm
4.5.2 AI-based Collaborative Computing Approach
Contents xi
4.6 Summary
References
5 Edge-assisted Mobile VR
5.1 Background on Mobile Virtual Reality
5.2 Caching and Computing Requirements of Mobile VR
5.2.1 Mobile VR Video Formats
5.2.2 Edge Caching for Mobile VR
5.2.3 Edge Computing for Mobile VR
5.3 Mobile VR Video Caching and Delivery Model
5.3.1 Network Model
5.3.2 Content Distribution Model
5.3.3 Content Popularity Model
5.3.4 Research Objective
5.4 Content Caching for Mobile VR
5.4.1 Adaptive Field-of-View Video Chunks
5.4.2 Content Placement on an Edge Cache
5.4.3 Placement Scheme for Video Chunks in a VS
5.4.4 Placement Scheme for Video Chunks of Multiple VSs
5.4.5 Numerical Results
5.5 AI-assisted Mobile VR Video Delivery
5.5.1 Content Distribution
5.5.2 Intelligent Content Distribution Framework
5.5.3 WI-based Delivery Scheduling
5.5.4 Reinforcement Learning Assisted Content Distribution
5.5.5 Neural Network Structure
5.5.6 Numerical Results
5.6 Summary
References
6 Conclusions
6.1 Summary of the Research
6.2 Discussion of Future Directions
Index.
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