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Connectivity and edge computing in IoT : customized designs and AI-based solutions / / Jie Gao, Mushu Li, Weihua Zhuang
| Connectivity and edge computing in IoT : customized designs and AI-based solutions / / Jie Gao, Mushu Li, Weihua Zhuang |
| Autore | Gao Jie <1985-> |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (177 pages) |
| Disciplina | 004.678 |
| Collana | Wireless networks (Springer (Firm)) |
| Soggetto topico |
Internet of things
Edge computing |
| ISBN | 3-030-88743-X |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 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 Differentiated 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 Buffer -- 2.4.2 Delay Performance with Buffer -- 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 -- 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 EdgeComputing -- 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 Offloading -- 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 -- 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 -- 5.4.1.1 Extended FoV -- 5.4.1.2 Content Types -- 5.4.1.3 Rules for Content Distribution -- 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. |
| Record Nr. | UNISA-996464418803316 |
Gao Jie <1985->
|
||
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Connectivity and edge computing in IoT : customized designs and AI-based solutions / / Jie Gao, Mushu Li, Weihua Zhuang
| Connectivity and edge computing in IoT : customized designs and AI-based solutions / / Jie Gao, Mushu Li, Weihua Zhuang |
| Autore | Gao Jie <1985-> |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2021] |
| Descrizione fisica | 1 online resource (177 pages) |
| Disciplina | 004.678 |
| Collana | Wireless networks (Springer (Firm)) |
| Soggetto topico |
Internet of things
Edge computing |
| ISBN | 3-030-88743-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 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 Differentiated 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 Buffer -- 2.4.2 Delay Performance with Buffer -- 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 -- 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 EdgeComputing -- 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 Offloading -- 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 -- 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 -- 5.4.1.1 Extended FoV -- 5.4.1.2 Content Types -- 5.4.1.3 Rules for Content Distribution -- 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. |
| Record Nr. | UNINA-9910510534803321 |
|
Gao Jie <1985->
|
||
| Cham, Switzerland : , : Springer, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent computing and communication for the internet of vehicles / / Mushu Li [and three others]
| Intelligent computing and communication for the internet of vehicles / / Mushu Li [and three others] |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (90 pages) |
| Disciplina | 004.678 |
| Collana | SpringerBriefs in Computer Science |
| Soggetto topico |
Internet of things
Vehicular ad hoc networks (Computer networks) |
| ISBN | 3-031-22860-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Introduction -- 1.1 Internet of Vehicles (IoV) -- 1.2 IoV Use Cases -- 1.3 Network Characteristics in IoV -- 1.4 Outline of the Monograph -- References -- 2 Overview of Communication and Computing in IoV -- 2.1 Communication and Computing in IoV -- 2.2 V2X Communication Protocols -- 2.3 Vehicular Computing Resource Scheduling -- References -- 3 Protocol Design for Safety Message Broadcast -- 3.1 Communication in Safety Message Broadcast -- 3.2 Network Scenario -- 3.2.1 Basic Settings -- 3.2.2 Features of Safety Message Broadcast -- 3.2.3 Assumptions -- 3.3 CIDC: A Distributed and Adaptive MAC Design -- 3.3.1 Messaging Mechanism Design -- 3.3.2 Contention Intensity Estimation Method -- 3.3.3 Channel Access Mechanism Design -- 3.4 CIDC: Network-Perspective Modeling -- 3.5 CIDC: Performance Analysis -- 3.5.1 Basic Features -- 3.5.2 Packet-to-Slot Ratio -- 3.5.3 Contention Intensity and Contention Delay -- 3.5.4 Collision Conditions and Probability -- 3.6 Performance Evaluation -- vii -- viii Contents -- 3.6.1 Performance with Accurate Contention Intensity -- Estimation -- 3.6.2 A Comparison of Analytical and Numerical Results -- 3.6.3 Performance under Contention Intensity Estimation -- Errors -- 3.7 Summary -- References -- 4 Computing Scheduling for Autonomous Driving -- 4.1 Computing in Autonomous Driving -- 4.2 System Model -- 4.2.1 Network Model -- 4.2.2 Computing Scheduling Scenarios -- 4.2.3 Age of Computing Results -- 4.3 Adaptive Computing Resource Scheduling -- 4.3.1 Restless Multi-armed Bandit Formulation -- 4.3.2 Indexability and Index Policy -- 4.4 Machine Learning-based Scheduling Policy -- 4.4.1 DRL-assisted Scheduling -- 4.4.2 Scheduling Scheme for Asynchronous Offloading -- 4.5 Performance Evaluation -- 4.5.1 Numerical Results -- 4.5.2 Simulation in a Real Dataset -- 4.6 Summary -- References -- 5 Conclusions -- 5.1 Conclusions on Intelligent Computing and Communication -- in IoV -- 5.2 Open Research Problems. |
| Record Nr. | UNINA-9910640384403321 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Intelligent computing and communication for the internet of vehicles / / Mushu Li [and three others]
| Intelligent computing and communication for the internet of vehicles / / Mushu Li [and three others] |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (90 pages) |
| Disciplina | 004.678 |
| Collana | SpringerBriefs in Computer Science |
| Soggetto topico |
Internet of things
Vehicular ad hoc networks (Computer networks) |
| ISBN | 3-031-22860-X |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | 1 Introduction -- 1.1 Internet of Vehicles (IoV) -- 1.2 IoV Use Cases -- 1.3 Network Characteristics in IoV -- 1.4 Outline of the Monograph -- References -- 2 Overview of Communication and Computing in IoV -- 2.1 Communication and Computing in IoV -- 2.2 V2X Communication Protocols -- 2.3 Vehicular Computing Resource Scheduling -- References -- 3 Protocol Design for Safety Message Broadcast -- 3.1 Communication in Safety Message Broadcast -- 3.2 Network Scenario -- 3.2.1 Basic Settings -- 3.2.2 Features of Safety Message Broadcast -- 3.2.3 Assumptions -- 3.3 CIDC: A Distributed and Adaptive MAC Design -- 3.3.1 Messaging Mechanism Design -- 3.3.2 Contention Intensity Estimation Method -- 3.3.3 Channel Access Mechanism Design -- 3.4 CIDC: Network-Perspective Modeling -- 3.5 CIDC: Performance Analysis -- 3.5.1 Basic Features -- 3.5.2 Packet-to-Slot Ratio -- 3.5.3 Contention Intensity and Contention Delay -- 3.5.4 Collision Conditions and Probability -- 3.6 Performance Evaluation -- vii -- viii Contents -- 3.6.1 Performance with Accurate Contention Intensity -- Estimation -- 3.6.2 A Comparison of Analytical and Numerical Results -- 3.6.3 Performance under Contention Intensity Estimation -- Errors -- 3.7 Summary -- References -- 4 Computing Scheduling for Autonomous Driving -- 4.1 Computing in Autonomous Driving -- 4.2 System Model -- 4.2.1 Network Model -- 4.2.2 Computing Scheduling Scenarios -- 4.2.3 Age of Computing Results -- 4.3 Adaptive Computing Resource Scheduling -- 4.3.1 Restless Multi-armed Bandit Formulation -- 4.3.2 Indexability and Index Policy -- 4.4 Machine Learning-based Scheduling Policy -- 4.4.1 DRL-assisted Scheduling -- 4.4.2 Scheduling Scheme for Asynchronous Offloading -- 4.5 Performance Evaluation -- 4.5.1 Numerical Results -- 4.5.2 Simulation in a Real Dataset -- 4.6 Summary -- References -- 5 Conclusions -- 5.1 Conclusions on Intelligent Computing and Communication -- in IoV -- 5.2 Open Research Problems. |
| Record Nr. | UNISA-996547968003316 |
| Cham, Switzerland : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||