Edge Computing for Internet of Things |
Autore | Lee Kevin |
Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
Descrizione fisica | 1 electronic resource (186 p.) |
Soggetto topico |
Technology: general issues
History of engineering & technology Energy industries & utilities |
Soggetto non controllato |
hierarchical edge computing
WSN rapid response strategy edge node fog access points cache memory convolutional neural network proactive caching fog computing Internet of Things service placement fog service orchestration spectral classification portable optical fiber spectrometers dew computing edge computing smartphone job scheduling scheduling heuristics mobile edge computing mobile edge server placement multiagent RL edge security offloading computation distributed collaboration data processing dynamic offloading IoT gateways Internet of Things (IoT) failure recovery FP-Growth algorithm association rules frequency pattern analysis computational offloading orchestration functional programming |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910576879503321 |
Lee Kevin
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Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
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Lo trovi qui: Univ. Federico II | ||
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Energy-Efficient Computing and Communication |
Autore | Pack Sangheon |
Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
Descrizione fisica | 1 electronic resource (116 p.) |
Soggetto topico | History of engineering & technology |
Soggetto non controllato |
UAV
relay cooperative communications buffer power control energy efficiency energy-neutral operation wireless powered sensor network simultaneous wireless information and power transfer energy harvesting clustering offloading Internet of Things (IoT) energy constraint Markov decision process (CMDP) optimization computation offloading mobile edge computing lyapunov optimization 1-bit unit cell coding metasurface adaptive beam focusing wireless power transfer UAV network topology control space division |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910557476803321 |
Pack Sangheon
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Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
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Lo trovi qui: Univ. Federico II | ||
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Green, Energy-Efficient and Sustainable Networks |
Autore | Lorincz Josip |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
Descrizione fisica | 1 electronic resource (382 p.) |
Soggetto non controllato |
node speed
linear recovery resource block allocation social awareness internet-of-things scheduling algorithm renewables neural network battery capacity energy awareness measurement structure optimization energy efficiency charging efficiency random structural matrices SDN water filling algorithm ONOS energy harvesting malware detection node density HetNets sustainability cooperative smart community adversarial samples spatial modulation NOMA 5G light-weight authentication green networking Device-to-Device (D2D) lightweight cipher mobile edge computing wireless power transfer adaptive link rate successive interference cancellation (SIC) directional charging vehicle self-interference cancellation proportional rate constraint inter-meeting time sustainable RWSN channel state information stochastic geometry networks green internet of things (IoT) PHY-layer IoT Markov chain traffic engineering QoS energy-efficient Ethernet power lightweight authentication energy aware routing authentication wired access amplify-and-forward software defined networking (SDN) image compressive sensing (CS) green edge computing LTE-A opportunistic networks RF Fingerprinting data centre multiple-input multiple-output Internet of Things machine learning peer discovery full-duplex industrial carbon footprint WSN imperfect CSI data center symbol error probability physical-layer authentication interference coordination clustering control and data plane wireless ICT bisection based optimal power allocation energy-efficiency consumer preferences real-time traffic |
ISBN | 3-03928-039-2 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910372783803321 |
Lorincz Josip
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MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
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Lo trovi qui: Univ. Federico II | ||
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Mobile Edge Computing [[electronic resource]] |
Autore | Zhang Yan |
Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
Descrizione fisica | 1 online resource (123 p.) |
Collana | Simula SpringerBriefs on Computing |
Soggetto topico |
Mobile & handheld device programming / Apps programming
WAP (wireless) technology Electrical engineering Computing & information technology |
Soggetto non controllato |
Open Access
mobile edge computing 5G beyond 6G edge caching Internet of Things UAV |
ISBN | 3-030-83944-3 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 Introduction -- 1.1 Mobile Cloud Computing (MCC) -- 1.2 Overview of MEC -- 1.3 Book Organization -- 2 Mobile Edge Computing -- 2.1 A Hierarchical Architecture of Mobile Edge Computing (MEC) -- 2.2 Computation Model -- 2.2.1 Computation Model of Local Execution -- 2.2.2 Computation Model of Full Offloading -- 2.2.3 A Computation Model for Partial Offloading -- 2.3 Offloading Policy -- 2.3.1 Binary Offloading -- 2.3.2 Partial Offloading -- 2.4 Challenges and Future Directions -- 3 Mobile Edge Caching -- 3.1 Introduction
3.2 The Architecture of Mobile Edge Caching -- 3.3 Caching Performance Metrics -- 3.3.1 Hit Rate Ratio -- 3.3.2 Content Acquisition Latency -- 3.3.3 Quality of Experience (QoE) -- 3.3.4 Caching System Utility -- 3.4 Caching Service Design and Data Scheduling Mechanisms -- 3.4.1 Edge Caching Based on Network Infrastructure Services -- 3.4.2 Edge Caching Based on D2D Services -- 3.4.3 Hybrid Service-Enabled Edge Caching -- 3.5 Case Study: Deep Reinforcement Learning-Empowered … -- 3.5.1 System Model -- 3.5.2 Problem Formulation and a DDPG-Based Optimal Content Dispatch Scheme 3.5.3 Numerical Results -- 4 Mobile Edge Computing for Beyond 5G/6G -- 4.1 Fundamental Characteristics of 6G -- 4.2 Integrating Mobile Edge Computing (MEC) … -- 4.2.1 Use Cases of Integrating MEC into 6G -- 4.2.2 Applications of Integrating MEC into 6G -- 4.2.3 Challenges of Integrating MEC into 6G -- 4.3 Case Study: MEC-Empowered Edge Model Sharing for 6G -- 4.3.1 Sharing at the Edge: From Data to Model -- 4.3.2 Architecture of Edge Model Sharing -- 4.3.3 Processes of Edge Model Sharing -- 5 Mobile Edge Computing for the Internet of Vehicles -- 5.1 Introduction -- 5.2 Challenges in VEC 5.3 Architecture of VEC -- 5.4 Key Techniques of VEC -- 5.4.1 Task Offloading -- 5.4.2 Heterogeneous Edge Server Cooperation -- 5.4.3 AI-Empowered VEC -- 5.5 A Case Study -- 5.5.1 Predictive Task Offloading for Fast-Moving Vehicles -- 5.5.2 Deep Q-Learning for Vehicular Computation Offloading -- 6 Mobile Edge Computing for UAVs -- 6.1 Unmanned Aerial Vehicle-Assisted Mobile Edge Computing (MEC) Networks -- 6.2 Joint Trajectory and Resource Optimization in UAV-Assisted MEC Networks -- 6.2.1 Resource Allocation and Optimization in the Scenario of a UAV Exploiting MEC Computing Capabilities 6.2.2 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Computing Server -- 6.2.3 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Relay for Computation Offloading -- 6.3 Case Study: UAV Deployment and Resource Optimization for MEC at a Wind Farm -- 6.3.1 UAV Deployment for MEC at a Wind Farm -- 6.3.2 Joint Trajectory and Resource Optimization of UAV-Aided MEC at a Wind Farm -- 6.4 Conclusions -- 7 The Future of Mobile Edge Computing -- 7.1 The Integration of Blockchain and Mobile Edge Computing (MEC) -- 7.1.1 The Blockchain Structure 7.1.2 Blockchain Classification |
Record Nr. | UNISA-996464547003316 |
Zhang Yan
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Cham, : Springer International Publishing AG, 2021 | ||
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Lo trovi qui: Univ. di Salerno | ||
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Mobile Edge Computing |
Autore | Zhang Yan |
Pubbl/distr/stampa | Cham, : Springer International Publishing AG, 2021 |
Descrizione fisica | 1 online resource (123 p.) |
Collana | Simula SpringerBriefs on Computing |
Soggetto topico |
Mobile & handheld device programming / Apps programming
WAP (wireless) technology Electrical engineering Computing & information technology |
Soggetto non controllato |
Open Access
mobile edge computing 5G beyond 6G edge caching Internet of Things UAV |
ISBN | 3-030-83944-3 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 Introduction -- 1.1 Mobile Cloud Computing (MCC) -- 1.2 Overview of MEC -- 1.3 Book Organization -- 2 Mobile Edge Computing -- 2.1 A Hierarchical Architecture of Mobile Edge Computing (MEC) -- 2.2 Computation Model -- 2.2.1 Computation Model of Local Execution -- 2.2.2 Computation Model of Full Offloading -- 2.2.3 A Computation Model for Partial Offloading -- 2.3 Offloading Policy -- 2.3.1 Binary Offloading -- 2.3.2 Partial Offloading -- 2.4 Challenges and Future Directions -- 3 Mobile Edge Caching -- 3.1 Introduction
3.2 The Architecture of Mobile Edge Caching -- 3.3 Caching Performance Metrics -- 3.3.1 Hit Rate Ratio -- 3.3.2 Content Acquisition Latency -- 3.3.3 Quality of Experience (QoE) -- 3.3.4 Caching System Utility -- 3.4 Caching Service Design and Data Scheduling Mechanisms -- 3.4.1 Edge Caching Based on Network Infrastructure Services -- 3.4.2 Edge Caching Based on D2D Services -- 3.4.3 Hybrid Service-Enabled Edge Caching -- 3.5 Case Study: Deep Reinforcement Learning-Empowered … -- 3.5.1 System Model -- 3.5.2 Problem Formulation and a DDPG-Based Optimal Content Dispatch Scheme 3.5.3 Numerical Results -- 4 Mobile Edge Computing for Beyond 5G/6G -- 4.1 Fundamental Characteristics of 6G -- 4.2 Integrating Mobile Edge Computing (MEC) … -- 4.2.1 Use Cases of Integrating MEC into 6G -- 4.2.2 Applications of Integrating MEC into 6G -- 4.2.3 Challenges of Integrating MEC into 6G -- 4.3 Case Study: MEC-Empowered Edge Model Sharing for 6G -- 4.3.1 Sharing at the Edge: From Data to Model -- 4.3.2 Architecture of Edge Model Sharing -- 4.3.3 Processes of Edge Model Sharing -- 5 Mobile Edge Computing for the Internet of Vehicles -- 5.1 Introduction -- 5.2 Challenges in VEC 5.3 Architecture of VEC -- 5.4 Key Techniques of VEC -- 5.4.1 Task Offloading -- 5.4.2 Heterogeneous Edge Server Cooperation -- 5.4.3 AI-Empowered VEC -- 5.5 A Case Study -- 5.5.1 Predictive Task Offloading for Fast-Moving Vehicles -- 5.5.2 Deep Q-Learning for Vehicular Computation Offloading -- 6 Mobile Edge Computing for UAVs -- 6.1 Unmanned Aerial Vehicle-Assisted Mobile Edge Computing (MEC) Networks -- 6.2 Joint Trajectory and Resource Optimization in UAV-Assisted MEC Networks -- 6.2.1 Resource Allocation and Optimization in the Scenario of a UAV Exploiting MEC Computing Capabilities 6.2.2 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Computing Server -- 6.2.3 Resource Allocation and Optimization in the Scenario of a UAV Serving as a Relay for Computation Offloading -- 6.3 Case Study: UAV Deployment and Resource Optimization for MEC at a Wind Farm -- 6.3.1 UAV Deployment for MEC at a Wind Farm -- 6.3.2 Joint Trajectory and Resource Optimization of UAV-Aided MEC at a Wind Farm -- 6.4 Conclusions -- 7 The Future of Mobile Edge Computing -- 7.1 The Integration of Blockchain and Mobile Edge Computing (MEC) -- 7.1.1 The Blockchain Structure 7.1.2 Blockchain Classification |
Record Nr. | UNINA-9910502647303321 |
Zhang Yan
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Cham, : Springer International Publishing AG, 2021 | ||
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Lo trovi qui: Univ. Federico II | ||
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