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Biblioteca

MARC Lista (tabellare)
Edge Computing : Technology, Management and Integration / / Sam Goundar
Edge Computing : Technology, Management and Integration / / Sam Goundar
Autore Goundar Sam
Pubbl/distr/stampa London : , : IntechOpen, , 2023
Descrizione fisica 1 Online-Ressource (258 pages)
Disciplina 005.758
Soggetto topico Edge computing
Distributed databases
ISBN 1-83768-862-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910741318703321
Goundar Sam  
London : , : IntechOpen, , 2023
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Edge computing - EDGE 2021 : 5th international conference held as part of the Services Conference Federation, SCF 2021 virtual event, December 10-14, 2021 : proceedings / / edited by Liang-Jie Zhang
Edge computing - EDGE 2021 : 5th international conference held as part of the Services Conference Federation, SCF 2021 virtual event, December 10-14, 2021 : proceedings / / edited by Liang-Jie Zhang
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (105 pages)
Disciplina 005.758
Collana Lecture Notes in Computer Science
Soggetto topico Edge computing
ISBN 9783030965044
9783030965037
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996464450603316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Edge computing - EDGE 2021 : 5th international conference held as part of the Services Conference Federation, SCF 2021 virtual event, December 10-14, 2021 : proceedings / / edited by Liang-Jie Zhang
Edge computing - EDGE 2021 : 5th international conference held as part of the Services Conference Federation, SCF 2021 virtual event, December 10-14, 2021 : proceedings / / edited by Liang-Jie Zhang
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (105 pages)
Disciplina 005.758
Collana Lecture Notes in Computer Science
Soggetto topico Edge computing
ISBN 9783030965044
9783030965037
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910553099203321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Edge computing and IoT : systems, management and security : Second EAI International Conference, ICECI 2021, virtual event, December 22-23, 2021, proceedings / / Kaishun Wu, Lu Wang and Yanjiao Chen (editors)
Edge computing and IoT : systems, management and security : Second EAI International Conference, ICECI 2021, virtual event, December 22-23, 2021, proceedings / / Kaishun Wu, Lu Wang and Yanjiao Chen (editors)
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (143 pages)
Disciplina 005.758
Collana Lecture notes of the Institute for Computer Sciences, Social Informatics, and Telecommunications Engineering
Soggetto topico Edge computing
Internet of things
Machine learning
ISBN 3-031-04231-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996475766003316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Edge computing and IoT : systems, management and security : Second EAI International Conference, ICECI 2021, virtual event, December 22-23, 2021, proceedings / / Kaishun Wu, Lu Wang and Yanjiao Chen (editors)
Edge computing and IoT : systems, management and security : Second EAI International Conference, ICECI 2021, virtual event, December 22-23, 2021, proceedings / / Kaishun Wu, Lu Wang and Yanjiao Chen (editors)
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (143 pages)
Disciplina 005.758
Collana Lecture notes of the Institute for Computer Sciences, Social Informatics, and Telecommunications Engineering
Soggetto topico Edge computing
Internet of things
Machine learning
ISBN 3-031-04231-X
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910568298903321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Edge intelligence : from theory to practice / / Javid Taheri [and three others]
Edge intelligence : from theory to practice / / Javid Taheri [and three others]
Autore Taheri Javid
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2023]
Descrizione fisica 1 online resource (254 pages)
Disciplina 060
Soggetto topico Artificial intelligence
Edge computing
ISBN 9783031221552
9783031221545
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910725080803321
Taheri Javid  
Cham, Switzerland : , : Springer, , [2023]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Edge intelligence : from theory to practice / / Javid Taheri [and three others]
Edge intelligence : from theory to practice / / Javid Taheri [and three others]
Autore Taheri Javid
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2023]
Descrizione fisica 1 online resource (254 pages)
Disciplina 060
Soggetto topico Artificial intelligence
Edge computing
ISBN 9783031221552
9783031221545
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNISA-996547952603316
Taheri Javid  
Cham, Switzerland : , : Springer, , [2023]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
EdgeAI for algorithmic government / / Rajan? Gupta, Sanjana Das, and Saibal Kumar Pal
EdgeAI for algorithmic government / / Rajan? Gupta, Sanjana Das, and Saibal Kumar Pal
Autore Gupta Rajan <1953->
Edizione [1st ed. 2023.]
Pubbl/distr/stampa Singapore : , : Palgrave Macmillan, , [2023]
Descrizione fisica 1 online resource (109 pages)
Disciplina 060
Soggetto topico Artificial intelligence
Edge computing
Internet in public administration
ISBN 9789811997983
9789811997976
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Chapter 1: Algorithmic Government -- Chapter 2: Edge Computing -- Chapter 3: EdgeAI -- Chapter 4: EdgeAI Cases for Algorithmic Government -- Chapter 5: Design Challenges & Future Scope.
Record Nr. UNINA-9910683354903321
Gupta Rajan <1953->  
Singapore : , : Palgrave Macmillan, , [2023]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Energy efficient computation offloading in mobile edge computing / / Ying Chen [and three others]
Energy efficient computation offloading in mobile edge computing / / Ying Chen [and three others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (167 pages)
Disciplina 004
Collana Wireless Networks
Soggetto topico Mobile computing
Edge computing
ISBN 3-031-16822-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 Introduction -- 1.1 Background -- 1.1.1 Mobile Cloud Computing -- 1.1.1.1 Architecture of Mobile Cloud Computing -- 1.1.1.2 Characteristics of Mobile Cloud Computing -- 1.1.1.3 Cloudlet -- 1.1.1.4 Fog Computing -- 1.1.1.5 Data Security and Privacy Protection -- 1.1.1.6 Challenges of Mobile Cloud Computing -- 1.1.2 Mobile Edge Computing -- 1.1.2.1 Definition of Mobile Edge Computing -- 1.1.2.2 Architecture of Mobile Edge Computing -- 1.1.2.3 Advantages of Mobile Edge Computing -- 1.1.2.4 Applications of Mobile Edge Computing -- 1.1.2.5 Challenges of Mobile Edge Computing -- 1.1.3 Computation Offloading -- 1.1.3.1 Minimize Latency -- 1.1.3.2 Minimize Energy Consumption -- 1.1.3.3 Weighted Sum of Latency and Energy Consumption -- 1.2 Challenges -- 1.3 Contributions -- 1.4 Book Outline -- References -- 2 Dynamic Computation Offloading for Energy Efficiency in Mobile Edge Computing -- 2.1 System Model and Problem Statement -- 2.1.1 Network Model -- 2.1.2 Task Offloading Model -- 2.1.3 Task Queuing Model -- 2.1.4 Energy Consumption Model -- 2.1.5 Problem Statement -- 2.2 EEDCO: Energy Efficient Dynamic Computing Offloading for Mobile Edge Computing -- 2.2.1 Joint Optimization of Energy and Queue -- 2.2.2 Dynamic Computation Offloading for Mobile Edge Computing -- 2.2.3 Trade-Off Between Queue Backlog and Energy Efficiency -- 2.2.4 Convergence and Complexity Analysis -- 2.3 Performance Evaluation -- 2.3.1 Impacts of Parameters -- 2.3.1.1 Effect of Tradeoff Parameter -- 2.3.1.2 Effect of Arrival Rate -- 2.3.1.3 Effect of Transmit Power -- 2.3.1.4 Effect of Channel Power Gain -- 2.3.1.5 Effect of Number of IoT Devices -- 2.3.2 Performance Comparison with EA and QW Schemes -- 2.4 Literature Review -- 2.5 Summary -- References.
3 Energy Efficient Offloading and Frequency Scaling for Internet of Things Devices -- 3.1 System Model and Problem Formulation -- 3.1.1 Network Model -- 3.1.2 Task Model -- 3.1.3 Queuing Model -- 3.1.4 Energy Consumption Model -- 3.1.5 Problem Formulation -- 3.2 COFSEE: Computation Offloading and Frequency Scaling for Energy Efficiency of Internet of Things Devices -- 3.2.1 Problem Transformation -- 3.2.2 Optimal Frequency Scaling -- 3.2.3 Local Computation Allocation -- 3.2.4 MEC Computation Allocation -- 3.2.5 Theoretical Analysis -- 3.3 Performance Evaluation -- 3.3.1 Impacts of System Parameters -- 3.3.1.1 Effect of Tradeoff Parameter V -- 3.3.1.2 Effect of Arrival Rate -- 3.3.1.3 Effect of Slot Length -- 3.3.2 Performance Comparison with RLE, RME and TSSchemes -- 3.4 Literature Review -- 3.5 Summary -- References -- 4 Deep Reinforcement Learning for Delay-Aware and Energy-Efficient Computation Offloading -- 4.1 System Model and Problem Formulation -- 4.1.1 System Model -- 4.1.2 Problem Formulation -- 4.2 Proposed DRL Method -- 4.2.1 Data Prepossessing -- 4.2.2 DRL Model -- 4.2.2.1 Reinforcement Learning Framework -- 4.2.2.2 Deep Reinforcement Learning Model -- 4.2.3 Training -- 4.2.3.1 Initialization -- 4.2.3.2 Exploration and Data Acquisition -- 4.2.3.3 Replay Experience Buffer -- 4.2.3.4 Learning -- 4.2.3.5 Reward Clipping -- 4.3 Performance Evaluation -- 4.4 Literature Review -- 4.5 Summary -- References -- 5 Energy-Efficient Multi-Task Multi-Access Computation Offloading via NOMA -- 5.1 System Model and Problem Formulation -- 5.1.1 Motivation -- 5.1.2 System Model -- 5.1.3 Problem Formulation -- 5.2 LEEMMO: Layered Energy-Efficient Multi-Task Multi-Access Algorithm -- 5.2.1 Layered Decomposition of Joint Optimization Problem -- 5.2.2 Proposed Subroutine for Solving Problem (TEM-E-Sub).
5.2.3 A Layered Algorithm for Solving Problem (TEM-E-Top) -- 5.2.4 DRL-Based Online Algorithm -- 5.3 Performance Evaluation -- 5.3.1 Impacts of Parameters -- 5.3.2 Performance Comparison with FDMA Based Offloading Schemes -- 5.4 Literature Review -- 5.5 Summary -- References -- 6 Conclusion -- 6.1 Concluding Remarks -- 6.2 Future Directions -- References.
Record Nr. UNINA-9910624378303321
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Energy efficient computation offloading in mobile edge computing / / Ying Chen [and three others]
Energy efficient computation offloading in mobile edge computing / / Ying Chen [and three others]
Pubbl/distr/stampa Cham, Switzerland : , : Springer, , [2022]
Descrizione fisica 1 online resource (167 pages)
Disciplina 004
Collana Wireless Networks
Soggetto topico Mobile computing
Edge computing
ISBN 3-031-16822-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Acknowledgements -- Contents -- Acronyms -- 1 Introduction -- 1.1 Background -- 1.1.1 Mobile Cloud Computing -- 1.1.1.1 Architecture of Mobile Cloud Computing -- 1.1.1.2 Characteristics of Mobile Cloud Computing -- 1.1.1.3 Cloudlet -- 1.1.1.4 Fog Computing -- 1.1.1.5 Data Security and Privacy Protection -- 1.1.1.6 Challenges of Mobile Cloud Computing -- 1.1.2 Mobile Edge Computing -- 1.1.2.1 Definition of Mobile Edge Computing -- 1.1.2.2 Architecture of Mobile Edge Computing -- 1.1.2.3 Advantages of Mobile Edge Computing -- 1.1.2.4 Applications of Mobile Edge Computing -- 1.1.2.5 Challenges of Mobile Edge Computing -- 1.1.3 Computation Offloading -- 1.1.3.1 Minimize Latency -- 1.1.3.2 Minimize Energy Consumption -- 1.1.3.3 Weighted Sum of Latency and Energy Consumption -- 1.2 Challenges -- 1.3 Contributions -- 1.4 Book Outline -- References -- 2 Dynamic Computation Offloading for Energy Efficiency in Mobile Edge Computing -- 2.1 System Model and Problem Statement -- 2.1.1 Network Model -- 2.1.2 Task Offloading Model -- 2.1.3 Task Queuing Model -- 2.1.4 Energy Consumption Model -- 2.1.5 Problem Statement -- 2.2 EEDCO: Energy Efficient Dynamic Computing Offloading for Mobile Edge Computing -- 2.2.1 Joint Optimization of Energy and Queue -- 2.2.2 Dynamic Computation Offloading for Mobile Edge Computing -- 2.2.3 Trade-Off Between Queue Backlog and Energy Efficiency -- 2.2.4 Convergence and Complexity Analysis -- 2.3 Performance Evaluation -- 2.3.1 Impacts of Parameters -- 2.3.1.1 Effect of Tradeoff Parameter -- 2.3.1.2 Effect of Arrival Rate -- 2.3.1.3 Effect of Transmit Power -- 2.3.1.4 Effect of Channel Power Gain -- 2.3.1.5 Effect of Number of IoT Devices -- 2.3.2 Performance Comparison with EA and QW Schemes -- 2.4 Literature Review -- 2.5 Summary -- References.
3 Energy Efficient Offloading and Frequency Scaling for Internet of Things Devices -- 3.1 System Model and Problem Formulation -- 3.1.1 Network Model -- 3.1.2 Task Model -- 3.1.3 Queuing Model -- 3.1.4 Energy Consumption Model -- 3.1.5 Problem Formulation -- 3.2 COFSEE: Computation Offloading and Frequency Scaling for Energy Efficiency of Internet of Things Devices -- 3.2.1 Problem Transformation -- 3.2.2 Optimal Frequency Scaling -- 3.2.3 Local Computation Allocation -- 3.2.4 MEC Computation Allocation -- 3.2.5 Theoretical Analysis -- 3.3 Performance Evaluation -- 3.3.1 Impacts of System Parameters -- 3.3.1.1 Effect of Tradeoff Parameter V -- 3.3.1.2 Effect of Arrival Rate -- 3.3.1.3 Effect of Slot Length -- 3.3.2 Performance Comparison with RLE, RME and TSSchemes -- 3.4 Literature Review -- 3.5 Summary -- References -- 4 Deep Reinforcement Learning for Delay-Aware and Energy-Efficient Computation Offloading -- 4.1 System Model and Problem Formulation -- 4.1.1 System Model -- 4.1.2 Problem Formulation -- 4.2 Proposed DRL Method -- 4.2.1 Data Prepossessing -- 4.2.2 DRL Model -- 4.2.2.1 Reinforcement Learning Framework -- 4.2.2.2 Deep Reinforcement Learning Model -- 4.2.3 Training -- 4.2.3.1 Initialization -- 4.2.3.2 Exploration and Data Acquisition -- 4.2.3.3 Replay Experience Buffer -- 4.2.3.4 Learning -- 4.2.3.5 Reward Clipping -- 4.3 Performance Evaluation -- 4.4 Literature Review -- 4.5 Summary -- References -- 5 Energy-Efficient Multi-Task Multi-Access Computation Offloading via NOMA -- 5.1 System Model and Problem Formulation -- 5.1.1 Motivation -- 5.1.2 System Model -- 5.1.3 Problem Formulation -- 5.2 LEEMMO: Layered Energy-Efficient Multi-Task Multi-Access Algorithm -- 5.2.1 Layered Decomposition of Joint Optimization Problem -- 5.2.2 Proposed Subroutine for Solving Problem (TEM-E-Sub).
5.2.3 A Layered Algorithm for Solving Problem (TEM-E-Top) -- 5.2.4 DRL-Based Online Algorithm -- 5.3 Performance Evaluation -- 5.3.1 Impacts of Parameters -- 5.3.2 Performance Comparison with FDMA Based Offloading Schemes -- 5.4 Literature Review -- 5.5 Summary -- References -- 6 Conclusion -- 6.1 Concluding Remarks -- 6.2 Future Directions -- References.
Record Nr. UNISA-996495560003316
Cham, Switzerland : , : Springer, , [2022]
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui