{ "item_title" : "Connectivity and Edge Computing in Iot", "item_author" : [" Jie Gao", "Mushu Li", "Weihua Zhuang "], "item_description" : "Introduction1.1 The Era of Internet of Things1.2 Connectivity in IoT1.3 Edge Computing in IoT1.4 AI in IoT1.5 Scope and Organization of This BookReferences2 Industrial Internet of Things: Smart Factory2.1 Industrial IoT Networks2.2 Connectivity Requirements of Smart Factory2.2.1 Application-Specific Requirements2.2.2 Related Standards2.2.3 Potential Non-Link-Layer Solutions2.2.4 Link-Layer Solutions: Recent Research Efforts2.3 Protocol Design for Smart Factory2.3.1 Networking Scenario2.3.2 Mini-Slot based Carrier Sensing (MsCS)2.3.3 Synchronization Sensing (SyncCS)2.3.4 Di_erentiated Assignment Cycles2.3.5 Superimposed Mini-slot Assignment (SMsA)2.3.6 Downlink Control2.4 Performance Analysis2.4.1 Delay Performance with No Buaer2.4.2 Delay Performance with Buaer2.4.3 Slot Idle Probability2.4.4 Impact of SyncCS2.4.5 Impact of SMsA2.5 Scheduling and AI-Assisted Protocol Parameter Selection2.5.1 Background2.5.2 The Considered Scheduling Problemixx Contents2.5.3 Device Assignment2.5.4 AI-Assisted Protocol Parameter Selection2.6 Numerical Results2.6.1 Mini-Slot Delay with MsCS, SyncCS, and SMsA2.6.2 Performance of the Device Assignment Algorithms2.6.3 DNN-Assisted Scheduling2.7 SummaryReferences3 UAV-Assisted Edge Computing: Rural IoT Applications3.1 Background on UAV-Assisted Edge Computing3.2 Connectivity Requirements of UAV-assisted MEC for RuralIoT3.2.1 Network Constraints3.2.2 State-of-the-Art Solutions3.3 Multi-Resource Allocation for UAV-Assisted Edge Computing3.3.1 Network Model3.3.2 Communication Model3.3.3 Computing Model3.3.4 Energy Consumption Model3.3.5 Problem Formulation3.3.6 Optimization Algorithm for UAV-Assisted EdgeComputing3.3.7 Proactive Trajectory Design based on SpatialDistribution Estimation3.4 Numerical Results3.5 SummaryReferences4 Collaborative Computing for Internet of Vehicles4.1 Background on Internet of Vehicles4.2 Connectivity Challenges for MEC4.2.1 Server Selection for Computing Offoading4.2.2 Service Migration4.2.3 Cooperative Computing4.3 Computing Task Partition and Scheduling for Edge Computing4.3.1 Collaborative Edge Computing Framework4.3.2 Service Delay4.3.3 Service Failure Penalty4.3.4 Problem Formulation4.3.5 Task Partition and Scheduling4.4 AI-Assisted Collaborative Computing Approach4.5 Performance Evaluation4.5.1 Task Partition and Scheduling Algorithm4.5.2 AI-based Collaborative Computing ApproachContents xi4.6 SummaryReferences5 Edge-assisted Mobile VR5.1 Background on Mobile Virtual Reality5.2 Caching and Computing Requirements of Mobile VR5.2.1 Mobile VR Video Formats5.2.2 Edge Caching for Mobile VR5.2.3 Edge Computing for Mobile VR5.3 Mobile VR Video Caching and Delivery Model5.3.1 Network Model5.3.2 Content Distribution Model5.3.3 Content Popularity Model5.3.4 Research Objective5.4 Content Caching for Mobile VR5.4.1 Adaptive Field-of-View Video Chunks5.4.2 Content Placement on an Edge Cache5.4.3 Placement Scheme for Video Chunks in a VS5.4.4 Placement Scheme for Video Chunks of Multiple VSs5.4.5 Numerical Results5.5 AI-assisted Mobile VR Video Delivery5.5.1 Content Distribution5.5.2 Intelligent Content Distribution Framewo", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/03/088/745/3030887456_b.jpg", "price_data" : { "retail_price" : "139.99", "online_price" : "139.99", "our_price" : "139.99", "club_price" : "139.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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