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.