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Biblioteca

MARC Lista (tabellare)
Cloud computing solutions : architecture, data storage, implementation and security / / Souvik Pal, Dac-Nhuong Le and Prasant Kumar Pattnai
Cloud computing solutions : architecture, data storage, implementation and security / / Souvik Pal, Dac-Nhuong Le and Prasant Kumar Pattnai
Autore Pal Souvik
Pubbl/distr/stampa Beverly, Massachusetts ; ; Hoboken, New Jersey : , : Scrivener Publishing : , : Wiley, , [2022]
Descrizione fisica 1 online resource (403 pages)
Disciplina 004.6782
Soggetto topico Cloud computing
Information retrieval
Data protection
ISBN 1-119-68231-2
1-119-68202-9
1-119-68215-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910573093403321
Pal Souvik  
Beverly, Massachusetts ; ; Hoboken, New Jersey : , : Scrivener Publishing : , : Wiley, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Cloud computing solutions : architecture, data storage, implementation and security / / Souvik Pal, Dac-Nhuong Le and Prasant Kumar Pattnai
Cloud computing solutions : architecture, data storage, implementation and security / / Souvik Pal, Dac-Nhuong Le and Prasant Kumar Pattnai
Autore Pal Souvik
Pubbl/distr/stampa Beverly, Massachusetts ; ; Hoboken, New Jersey : , : Scrivener Publishing : , : Wiley, , [2022]
Descrizione fisica 1 online resource (403 pages)
Disciplina 004.6782
Soggetto topico Cloud computing
Information retrieval
Data protection
ISBN 1-119-68231-2
1-119-68202-9
1-119-68215-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910830874803321
Pal Souvik  
Beverly, Massachusetts ; ; Hoboken, New Jersey : , : Scrivener Publishing : , : Wiley, , [2022]
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
IoT Edge Intelligence
IoT Edge Intelligence
Autore Pal Souvik
Edizione [1st ed.]
Pubbl/distr/stampa Cham : , : Springer International Publishing AG, , 2024
Descrizione fisica 1 online resource (392 pages)
Altri autori (Persone) SavaglioClaudio
MinervaRoberto
DelicatoFlávia C
Collana Internet of Things Series
ISBN 9783031583889
9783031583872
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Intro -- Preface -- Key Features -- Contents -- About the Editors -- Part I Architecture, Systems, and Services -- Modeling, Simulating, and Evaluating Complex End-to-End Edge Intelligence Systems -- 1 Introduction -- 2 Components of Edge Intelligence Systems -- 2.1 Infrastructure Components -- 2.2 Functional Components -- 3 Performance Metrics -- 3.1 Component Metrics -- 3.2 Systemwide Considerations and Trade-Offs -- 4 Simulation and Evaluation Tools -- 4.1 Using ML/AI Libraries and Packages -- 4.2 Network Simulation, Emulation, and Evaluation -- 4.3 Runtime Environments -- 5 End-to-End and Integrated Solutions for Simulation -- 6 Conclusion -- References -- Exploring Edge AI Inference in Heterogeneous Environments: Requirements, Challenges, and Solutions -- 1 Introduction -- 2 Understanding Edge Intelligence: An In-depth Look -- 2.1 What Is Edge Intelligence -- 2.2 Manifestations of Edge Intelligence -- 2.3 From Edge Intelligence to Edge AI -- 3 Heterogeneous Edge AI Inference: Benefits, Requirements, and Challenges -- 3.1 Potential and Benefits of Heterogeneous Edge AI Inference -- 3.2 Hardware and Software Heterogeneity in Edge AI Inference -- 3.3 Requirements and Challenges for Heterogeneous Edge AI Inference -- 3.4 Practical Scenarios for Heterogeneous Edge AI Inference -- 4 A Framework for Inference Provisioning in Heterogeneous Edge AI -- 4.1 Service Networking for Edge AI Inference Provisioning -- 4.2 Framework Architecture -- 4.3 Test Bed and Experimental Setup -- 4.4 DNS-Based Edge AI Inference Discovery -- 4.5 System Health Assurance for Reliable AI Inference Provisioning -- 4.6 Orchestration of Single-Model Edge AI Inference -- 4.7 Orchestration of Multi-model Edge AI Inference Pipelines -- 4.8 Addressing Requirements and Challenges -- 5 Conclusion and Future Directions -- References.
Artificial Intelligence-Enabled Edge Computing: Necessity of Next Generation Future Computing System -- 1 Introduction -- 1.1 Edge Computing -- 1.2 Edge Computing vs Fog vs Cloud Computing -- 1.2.1 Cloud Computing -- 1.2.2 Edge Computing -- 1.2.3 Fog Computing -- 1.2.4 AI Based Edge Computing -- 1.2.5 AI Based Edge Computing for Next Generation Computing Systems -- 1.2.6 Features and Characteristics -- 1.2.7 Benefit and Limitations -- 2 Literature Review -- 3 Motivation -- 4 Popular Applications Used AI Based Edge Computing Systems in This Smart Era -- 5 Current Stage of AI Based Edge Computing System -- 6 Recent Trends in AI Based Edge Computing System -- 7 Future Research Opportunities with AI Based Edge Computing Systems -- 7.1 AI-IoT Based Edge Computing Systems -- 7.2 AI-Blockchain Based Edge Computing Systems -- 7.3 AI-Blockchain-IoT Based Edge Computing Systems -- 8 Open Issues Toward AI Based Edge Computing Systems -- 8.1 Security Issues Toward AI Based Edge Computing Systems -- 8.2 Privacy Issues Toward AI Based Edge Computing Systems -- 8.3 Scalability Issues Toward AI Based Edge Computing Systems -- 8.4 Trust Issues Toward AI Based Edge Computing Systems -- 8.5 Legal Issues Toward AI Based Edge Computing Systems -- 9 Critical Challenges Toward AI Based Edge Computing Systems -- 9.1 Technical Challenges Toward AI Based Edge Computing Systems -- 9.2 Non-technical Challenges Toward AI Based Edge Computing Systems -- 9.3 Research Challenges Toward AI Based Edge Computing Systems -- 10 Lesson Learned for AI Based Edge Computing Systems for Next Generation Computing Environment -- 11 Conclusion -- References -- Artificial Intelligence-Based IoT-Edge Environment for Industry 5.0 -- 1 Introduction -- 1.1 Framework for IoT-Edge Environment -- 1.2 Edge Computing in IoT -- 2 Industry 5.0 -- 2.1 Key Enablers of Industry 5.0.
2.2 Challenges and Limitations of Industry 5.0 -- 2.3 Edge AI and Its Transition into Industry 5.0 -- 3 Existing Works: An Extensive Survey -- 4 AI-Based Trustworthiness in Edge Systems -- 5 Applications of AI in Edge Computing -- 6 Open Research Challenges for Edge Computing -- 7 Conclusions -- References -- Service Provisioning at the Edge: An AI Approach Based on Policies -- 1 Introduction -- 2 Background -- 2.1 Cloud and Edge Computing -- 2.2 Open Digital Rights Language -- 2.3 Case Study -- 3 Roles of Edges in Service Provisioning -- 3.1 Edges' Prescribed Roles -- 3.2 Services Across all Roles -- 3.3 Service Adjustment Per Role -- 3.4 Discussions -- 3.5 Implementation -- 4 Conclusion -- References -- Unsupervised Time Series Anomaly Detection for Edge Computing Applications: A Review -- 1 Introduction -- 2 Anomaly Detection -- 2.1 Machine Learning Methods -- 2.1.1 Proximity-Based -- 2.1.2 Clustering-Based -- 2.1.3 Predictive-Based -- 2.1.4 Regression -- 2.2 Statistical Methods -- 2.2.1 Parametric Methods -- 2.2.2 Non-parametric Methods -- 2.3 Deep Learning Methods -- 3 Concept Drift Detection -- 3.1 Data Distribution-Based Methods -- 3.2 Performance-Based Methods -- 4 Discussions and Future Research Directions -- 5 Conclusion -- References -- Part II Security and Privacy Paradigm -- Secure, Trusted, Privacy-Protected Data Exchange in an Edge-Cloud Continuum Environment -- 1 Introduction -- 2 Motivations and Related Work -- 2.1 Edge-Cloud Continuum -- 2.2 Interoperability and Data Processing -- 2.3 Data Storage -- 3 Data Exchange -- 3.1 Data Spaces -- 3.2 Data as a Service -- 4 Modern Data Management Frameworks -- 4.1 Data Fabric -- 4.2 Data as a Product -- 4.3 Data Mesh -- 4.4 Synergies Between Modern Data Management Approaches -- 5 Use Case: RE4DY Project -- 5.1 Technical Approach -- 5.2 Pilots -- 6 Conclusions and Future Work -- References.
Security, Privacy, Trust, and Provenance Issues in Internet of Things -Based Edge Environment -- 1 Introduction -- 2 Related Work -- 3 IoT-Based Edge Environment Applications -- 4 Available Simulation Tools to Implement Internet of Things-Based Edge Environment -- 5 Open Issues in Internet of Things-Based Edge Environment -- 5.1 Security Issues in IoT-Based Edge Environment -- 5.2 Privacy Issues in IoT-Based Edge Environment -- 5.3 Trust Issues in IoT-Based Edge Environment -- 5.4 Provenance Issues in IoT-Based Edge Environment -- 5.5 Scalability Issues in IoT-Based Edge Environment -- 5.6 Legal Issues in IoT-Based Edge Environment -- 6 Critical Challenges Toward IoT-Based Edge Environment -- 6.1 Technical Challenges in IoT-Based Edge Environment -- 6.2 Non-technical Challenges in IoT-Based Edge Environment -- 6.3 Research Challenges in IoT-Based Edge Environment -- 7 Future Research Opportunities with IoT-Based Edge Environment -- 7.1 AI-IoT-Based Edge Environment -- 7.2 Blockchain-IoT-Based Edge Environment -- 7.3 AI-blockchain-IoT-Based Edge Environment -- 8 Research Statements for Security, Privacy, Trust, and Provenance Issues in IoT-Based Edge Environments -- 9 Conclusion -- References -- Secure Neural Network Inference for Edge Intelligence: Implications of Bandwidth and Energy Constraints -- 1 Introduction -- 2 Preliminaries -- 2.1 Neural Networks -- 2.2 Secure Neural Network Inference -- 2.3 CrypTFlow2/SCIHE/SCIOT -- 2.4 Cheetah -- 2.5 Benchmark Neural Networks -- 3 Design of Experiments -- 3.1 Logical Design of the Experiments -- 3.2 Evaluation Metrics -- 3.3 Technical Setup -- 4 Experimental Results -- 4.1 Initial Measurements -- 4.2 Power and Energy Comparison -- 4.3 Timeseries Analysis -- 4.4 Impact of the Bandwidth -- 5 Discussion -- 5.1 Lessons Learned -- 5.2 Consequences for Future Research -- 5.3 Threats to Validity -- 6 Related Work.
7 Conclusion -- References -- Part III Applications -- Internet of Things in Intelligent Transportation Systems -- 1 Introduction -- 2 Usefulness of Edge Computing in ITS -- 3 Internet of Things -- 3.1 Definition -- 3.2 General Components of IoT -- 3.3 General Architecture of IoT -- 4 Intelligence Transportation Systems -- 4.1 Components of ITS -- 5 Internet of Things in Intelligent Transportation Systems -- 5.1 IoT for Smart Monitor Traffic System -- 5.2 IoT in Smart Roads -- 5.3 IoT for Smart Parking -- 6 -4pt -- References -- IoT-Driven Analytics and Edge Intelligence in Autonomous Navigation Systems -- 1 Introduction -- 2 Methodology -- 2.1 Data Identification -- 2.2 Data Mining -- 2.3 Data Analysis and Result Reporting -- 3 Internet of Things (IoT) and Edge Intelligence -- 3.1 IoT Characteristics -- 3.2 IoT Architecture -- 3.3 Challenges of IoT -- 3.4 IoT Analytics -- 3.5 IoT and Edge Intelligence -- 4 Autonomous Navigation Systems -- 5 IoT and Edge Intelligence (EAI) Integration in Autonomous Navigation System -- 6 Conclusion -- 7 Future Direction -- References -- Edge-AI for Monitoring Air Pollution from Urban Waste Incineration: A Survey -- 1 Introduction -- 2 Background and Impacts of Air Pollution from Urban Landfills -- 2.1 Urban Landfills Management in Africa -- 2.2 Impact of Air Pollution on Health and Environment -- 3 IoT Technologies for Air Quality Monitoring -- 3.1 IoT Basic Architecture for Air Quality Monitoring -- 3.2 Sensors for Air Quality Monitoring -- 3.3 Microcontroller Market -- 3.4 Data Transmission Technologies -- 4 IoT Deployment Techniques -- 4.1 Classical Deployment Techniques -- 4.2 Heuristic Deployment Techniques -- 5 New Trends Technologies: Edge-AI for Air Pollution Monitoring -- 5.1 Limitations and Challenges of Classical IoT Networks for Air Pollution Monitoring -- 5.2 Edge-AI Fundamentals.
5.3 Machine Learning Framework for Air Quality/Pollution Prediction.
Record Nr. UNINA-9910865235903321
Pal Souvik  
Cham : , : Springer International Publishing AG, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui