Intelligent resource management in vehicular networks / / Haixia Peng, Qiang Ye, and Xuemin Shen |
Autore | Peng Haixia |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (163 pages) |
Disciplina | 388.312 |
Collana | Wireless Networks |
Soggetto topico |
Vehicular ad hoc networks (Computer networks) - Safety measures
Vehicular ad hoc networks (Computer networks) |
ISBN | 3-030-96507-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Contents -- Acronyms -- 1 Introduction -- 1.1 Overview of Vehicular Networks -- 1.1.1 Vehicular Network Applications -- 1.1.2 Vehicular Network Characteristics -- 1.1.3 Vehicular Network Classifications -- 1.1.4 Overview of Vehicular Communication Technologies -- 1.2 Challenges in Vehicular Networks -- 1.2.1 Vehicular Information Sharing -- 1.2.2 Task Computing -- 1.3 Resource Management in Vehicular Networks -- 1.3.1 Spectrum Resource Management -- 1.3.2 Computing Resource Management -- 1.3.3 Intelligent Multi-Resource Management -- 1.3.3.1 Methodology -- 1.4 Aim of the Monograph -- 1.5 Summary -- References -- 2 MEC-Assisted Vehicular Networking -- 2.1 MEC-Assisted ADVNET Architecture -- 2.1.1 Problem Statement -- 2.1.2 Architecture Design -- 2.2 SDN-Enabled Resource Management -- 2.2.1 Computing and Storage Resource Management -- 2.2.2 Spectrum Management -- 2.2.3 Open Research Issues -- 2.3 Aerial-Assisted Vehicular Network: Case Study -- 2.3.1 A Drone-Assisted MVNET Architecture -- 2.3.2 Intelligent Resource Management -- 2.3.3 Case Study -- 2.4 Summary -- References -- 3 Spectrum Slicing in MEC-Assisted ADVNETs -- 3.1 System Model -- 3.1.1 Dynamic Slicing Framework -- 3.1.2 Communication Model -- 3.2 Resource Management Scheme -- 3.2.1 Network-Level Spectrum Reservation -- 3.2.2 Vehicle-Level Spectrum Reservation -- 3.2.3 Transmit Power Control -- 3.3 Problem Analysis and Suboptimal Solution -- 3.3.1 Problem Analysis -- 3.3.2 Algorithm Design -- 3.4 Simulation Results -- 3.5 Summary -- References -- 4 Intelligent Multi-Dimensional Resource Allocation in MVNETs -- 4.1 System Model -- 4.1.1 Spectrum, Computing, and Caching Allocation -- 4.2 Problem Formulation and Transformation -- 4.2.1 Problem Formulation -- 4.2.2 Problem Transformation with DRL -- 4.3 DDPG Algorithm Based Solution -- 4.3.1 DDPG-Based Algorithm.
4.3.2 HDDPG-Based Algorithm -- 4.4 Simulation Results and Analysis -- 4.5 Summary -- References -- 5 Aerial-Assisted Intelligent Resource Allocation -- 5.1 System Model and Problem Formulation -- 5.1.1 UAV-Assisted MVNET -- 5.1.2 Resource Reservation Models -- 5.1.3 Problem Formulation -- 5.2 Centralized/Distributed Multi-Dimensional ResourceManagement -- 5.2.1 Problem Transformation -- 5.2.2 SADDPG/MADDPG-Based Solutions -- 5.3 Simulation Results -- 5.3.1 Performance Evaluation for the SADDPG-Based Scheme -- 5.3.2 Performance Evaluation for the MADDPG-BasedScheme -- 5.4 Summary -- References -- 6 Conclusions and Future Research Directions -- 6.1 Conclusions -- 6.2 Future Research Directions -- References -- Index. |
Record Nr. | UNISA-996464537403316 |
Peng Haixia | ||
Cham, Switzerland : , : Springer, , [2022] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. di Salerno | ||
|
Intelligent resource management in vehicular networks / / Haixia Peng, Qiang Ye, and Xuemin Shen |
Autore | Peng Haixia |
Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
Descrizione fisica | 1 online resource (163 pages) |
Disciplina | 388.312 |
Collana | Wireless Networks |
Soggetto topico |
Vehicular ad hoc networks (Computer networks) - Safety measures
Vehicular ad hoc networks (Computer networks) |
ISBN | 3-030-96507-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Contents -- Acronyms -- 1 Introduction -- 1.1 Overview of Vehicular Networks -- 1.1.1 Vehicular Network Applications -- 1.1.2 Vehicular Network Characteristics -- 1.1.3 Vehicular Network Classifications -- 1.1.4 Overview of Vehicular Communication Technologies -- 1.2 Challenges in Vehicular Networks -- 1.2.1 Vehicular Information Sharing -- 1.2.2 Task Computing -- 1.3 Resource Management in Vehicular Networks -- 1.3.1 Spectrum Resource Management -- 1.3.2 Computing Resource Management -- 1.3.3 Intelligent Multi-Resource Management -- 1.3.3.1 Methodology -- 1.4 Aim of the Monograph -- 1.5 Summary -- References -- 2 MEC-Assisted Vehicular Networking -- 2.1 MEC-Assisted ADVNET Architecture -- 2.1.1 Problem Statement -- 2.1.2 Architecture Design -- 2.2 SDN-Enabled Resource Management -- 2.2.1 Computing and Storage Resource Management -- 2.2.2 Spectrum Management -- 2.2.3 Open Research Issues -- 2.3 Aerial-Assisted Vehicular Network: Case Study -- 2.3.1 A Drone-Assisted MVNET Architecture -- 2.3.2 Intelligent Resource Management -- 2.3.3 Case Study -- 2.4 Summary -- References -- 3 Spectrum Slicing in MEC-Assisted ADVNETs -- 3.1 System Model -- 3.1.1 Dynamic Slicing Framework -- 3.1.2 Communication Model -- 3.2 Resource Management Scheme -- 3.2.1 Network-Level Spectrum Reservation -- 3.2.2 Vehicle-Level Spectrum Reservation -- 3.2.3 Transmit Power Control -- 3.3 Problem Analysis and Suboptimal Solution -- 3.3.1 Problem Analysis -- 3.3.2 Algorithm Design -- 3.4 Simulation Results -- 3.5 Summary -- References -- 4 Intelligent Multi-Dimensional Resource Allocation in MVNETs -- 4.1 System Model -- 4.1.1 Spectrum, Computing, and Caching Allocation -- 4.2 Problem Formulation and Transformation -- 4.2.1 Problem Formulation -- 4.2.2 Problem Transformation with DRL -- 4.3 DDPG Algorithm Based Solution -- 4.3.1 DDPG-Based Algorithm.
4.3.2 HDDPG-Based Algorithm -- 4.4 Simulation Results and Analysis -- 4.5 Summary -- References -- 5 Aerial-Assisted Intelligent Resource Allocation -- 5.1 System Model and Problem Formulation -- 5.1.1 UAV-Assisted MVNET -- 5.1.2 Resource Reservation Models -- 5.1.3 Problem Formulation -- 5.2 Centralized/Distributed Multi-Dimensional ResourceManagement -- 5.2.1 Problem Transformation -- 5.2.2 SADDPG/MADDPG-Based Solutions -- 5.3 Simulation Results -- 5.3.1 Performance Evaluation for the SADDPG-Based Scheme -- 5.3.2 Performance Evaluation for the MADDPG-BasedScheme -- 5.4 Summary -- References -- 6 Conclusions and Future Research Directions -- 6.1 Conclusions -- 6.2 Future Research Directions -- References -- Index. |
Record Nr. | UNINA-9910558496203321 |
Peng Haixia | ||
Cham, Switzerland : , : Springer, , [2022] | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
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