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Autore: | Chakraborty Rajdeep |
Titolo: | Smart Edge Computing : An Operation Research Perspective |
Pubblicazione: | Newark : , : John Wiley & Sons, Incorporated, , 2024 |
©2024 | |
Edizione: | 1st ed. |
Descrizione fisica: | 1 online resource (275 pages) |
Altri autori: | GhoshAnupam MandalJyotsna Kumar ChoudhuryTanupriya ChatterjeePrasenjit |
Nota di contenuto: | Cover -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgments -- Chapter 1. Introduction to Operations Research Methodologies -- 1.1. Introduction -- 1.2. Decision-making framework/models for operations research -- 1.3. Operations research in IoT, IIoT, edge and smart edge computing, sensor data -- 1.4. Paradigms and procedures -- 1.5. Conclusion -- 1.6. References -- Chapter 2. Edge Computing: The Foundation, Emergence and Growing Applications -- 2.1. Introduction -- 2.2. Objective of the work -- 2.3. Methods adopted -- 2.4. Edge computing and edge cloud: basics -- 2.5. Edge computing and edge devices -- 2.6. Edge computing: working fashions, buying and deploying and 5G -- 2.7. Functions and features of edge computing -- 2.7.1. Privacy and security -- 2.7.2. Scalability -- 2.7.3. Reliability -- 2.7.4. Speed -- 2.7.5. Efficiency -- 2.7.6. Latency and bandwidth -- 2.7.7. Reduction in congestion -- 2.8. Edge computing: applications and examples -- 2.8.1. Self-managed and automated cars/vehicles -- 2.8.2. Fleet management -- 2.8.3. Predictive maintenance -- 2.8.4. Voice assisting systems -- 2.8.5. Smart cities and town planning -- 2.8.6. Manufacturing and core sector -- 2.8.7. Healthcare and medical segment -- 2.8.8. Edge computing and augmented reality -- 2.9. Drawbacks, obstacles and issues in edge computing -- 2.10. Edge computing, cloud computing and Internet of Things: some concerns -- 2.11. Future and emergence of edge computing -- 2.12. Conclusion -- 2.13. Acknowledgment -- 2.14. References -- Chapter 3. Utilization of Edge Computing in Digital Education: Conceptual Overview -- 3.1. Introduction -- 3.2. Objectives -- 3.3. Methodology used -- 3.4. Digital education -- 3.4.1. Emerging technologies in digital education -- 3.5. Education and information science -- 3.6. Edge computing. |
3.6.1. Edge computing promotes education and information science -- 3.6.2. Conceptual overview of edge computing in education -- 3.6.3. Conceptual diagram of edge computing in education -- 3.6.4. Concept of communication between different layers of edge computing in education -- 3.6.5. Diagram of communication between different layers of edge computing in education -- 3.6.6. Stakeholder of edge computing in digital education -- 3.6.7. Advantages of edge computing in digital education -- 3.6.8. Challenges of edge computing in digital education -- 3.7. Conclusion -- 3.8. Acknowledgment -- 3.9. References -- Chapter 4. Edge Computing with Operations Research Using IoT Devices in Healthcare: Concepts, Tools, Techniques and Use Cases -- 4.1. Overview -- 4.2. The smartness of edge across artificial intelligence with the IoT -- 4.2.1. Operations research in edge computing -- 4.2.2. Artificial intelligence and its innovative strategy -- 4.2.3. Machine learning and its potential application -- 4.2.4. Deep learning and its significance -- 4.2.5. Generative adversarial network and healthcare records -- 4.2.6. Natural language processing and its driving factors -- 4.2.7. Cloud-based intelligent edge computing infrastructure -- 4.2.8. Handling security and privacy issues -- 4.3. Promising approaches in edge healthcare system -- 4.3.1. Software adaptable network -- 4.3.2. Self-learning healthcare IoT -- 4.3.3. Towards Big Data in healthcare IoT -- 4.4. Impact of smartphones on edge computing -- 4.4.1. Use in clinical practice -- 4.4.2. Application for healthcare professionals -- 4.4.3. Edge computing in cutting edge devices -- 4.4.4. Robust smartphone using deep learning -- 4.4.5. Smartphone towards healthcare IoT -- 4.5. Tools, techniques and use cases -- 4.5.1. Smart self-monitoring healthcare system -- 4.5.2. Healthcare development tools. | |
4.5.3. Simple use cases -- 4.6. Significant forthcomings of edge healthcare IoT -- 4.7. Software and hardware companies developing healthcare tools -- 4.8. Summary -- 4.9. References -- Chapter 5. Performance Measures in Edge Computing Using the Queuing Model -- 5.1. Introduction -- 5.2. Methodology -- 5.2.1. Queuing theory on edge computing -- 5.2.2. Result -- 5.3. Conclusion -- 5.4. Future scope -- 5.5. References -- Chapter 6. A Smart Payment Transaction Procedure by Smart Edge Computing -- 6.1. Introduction -- 6.2. Related works -- 6.3. Ethereum -- 6.3.1. Ethereum's four stages of development -- 6.4. Ethereum's components -- 6.4.1. P2P network -- 6.4.2. Consensus rules -- 6.4.3. Transactions -- 6.4.4. State machine -- 6.4.5. Data structures -- 6.4.6. Consensus algorithm -- 6.4.7. Economic security -- 6.4.8. Clients -- 6.5. General-purpose blockchains to decentralized applications (DApps) -- 6.6. Ether currency units -- 6.7. Ethereum wallet -- 6.7.1. MetaMask -- 6.7.2. Jaxx -- 6.7.3. MyEtherWallet (MEW) -- 6.7.4. Emerald Wallet -- 6.8. A simple contract: a test Ether faucet -- 6.9. Ethereum clients -- 6.9.1. Hardware requirements for a full node -- 6.9.2. Advantages and disadvantages of full node -- 6.9.3. The advantages and disadvantages of public testnet -- 6.10. Conclusion -- 6.11. References -- Chapter 7. Statistical Learning Approach for the Detection of Abnormalities in Cancer Cells for Finding Indication of Metastasis -- 7.1. Introduction -- 7.2. Edge computation: a new era -- 7.3. Impact of edge computation in cancer treatment -- 7.4. Assessment parameters operational methodologies -- 7.5. Shape descriptor analysis: statistical approach -- 7.6. Results and discussion -- 7.7. Conclusion -- 7.8. References -- Chapter 8. Overcoming the Stigma of Alzheimer's Disease by Means of Natural Language Processing as well as Blockchain Technologies. | |
8.1. Introduction -- 8.2. Alzheimer's disease -- 8.3. Alzheimer's disease types -- 8.4. NLP in chat-bots/AI companions -- 8.5. Proposed methodologies for reduction of stigma -- 8.5.1. Proposed methodology using NLP -- 8.5.2. Model objective function of Alzheimer's disease -- 8.6. Blockchain technology for securing all medical data -- 8.6.1. Blockchain strategies for data privacy in healthcare -- 8.6.2. Application of blockchain technologies -- 8.6.3. Blockchain application intended for EHR data management -- 8.6.4. Issues with blockchain security and privacy -- 8.6.5. Challenges faced by blockchain applications -- 8.7. Conclusion -- 8.8. Future scope -- 8.9. Acknowledgments -- 8.10. References -- Chapter 9. Computer Vision-based Edge Computing System to Detect Health Informatics for Oral Pre-Cancer -- 9.1. Introduction -- 9.2. Related works -- 9.3. Materials and methods -- 9.3.1. Microscopic imaging -- 9.3.2. Proposed methodology -- 9.3.3. RGB color segmentation -- 9.4. Results -- 9.5. Conclusion -- 9.6. References -- Chapter 10. A Study of Ultra-lightweight Ciphers and Security Protocol for Edge Computing -- 10.1. Introduction -- 10.1.1. Evolution of the IoT -- 10.1.2. Content of the review work -- 10.2. Ultra-lightweight ciphers -- 10.2.1. SLIM -- 10.2.2. Piccolo -- 10.2.3. Hummingbird -- 10.2.4. Comparison between SLIM, Piccolo and Hummingbird ciphers -- 10.3. Ultra-lightweight security protocols -- 10.3.1. Lightweight extensible authentication protocol (LEAP) -- 10.3.2. MIFARE -- 10.3.3. Remote frame buffer (RFB) -- 10.3.4. Comparison between LEAP, MIFARE and RFB protocols -- 10.4. Conclusion -- 10.5. References -- Chapter 11. A Study on Security Protocols, Threats and Probable Solutions for Internet of Things Using Blockchain -- 11.1. Introduction -- 11.2. IoT architecture and security challenges -- 11.3. Security threat classifications. | |
11.3.1. Low-level security threats -- 11.3.2. Intermediate-level security threats -- 11.3.3. High-level security threats -- 11.4. Security solutions for IoT -- 11.4.1. Low-level security solutions -- 11.4.2. Intermediate-level security solutions -- 11.4.3. High-level security solutions -- 11.5. Blockchain-based IoT paradigm: security and privacy issues -- 11.5.1. Lack of IoT-centric agreement mechanisms -- 11.5.2. IoT device incorporation -- 11.5.3. Software update -- 11.5.4. Data scalability and organization -- 11.5.5. Interoperability with the varied IoT devices organized lying on blockchain network -- 11.5.6. Perception layer -- 11.5.7. Network layer -- 11.5.8. Processing layer -- 11.5.9. Application layer -- 11.6. IoT Messaging Protocols -- 11.6.1. Hyper Text Transfer Protocol (HTTP) -- 11.6.2. Message Queue Telemetry Protocols (MQTT) -- 11.6.3. Secure MQTT (SMQTT) -- 11.6.4. Advanced Message Queuing Protocol (AMQP) -- 11.6.5. Constrained Application Protocol (CoAP) -- 11.6.6. Extensible Messaging and Presence Protocol (XMPP) -- 11.6.7. Relative study of different messaging protocols of IoT environments -- 11.7. Advantages of edge computing -- 11.8. Conclusion -- 11.9. References -- List of Authors -- Index -- EULA. | |
ISBN: | 1-394-27759-8 |
1-394-27757-1 | |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 9910835065703321 |
Lo trovi qui: | Univ. Federico II |
Opac: | Controlla la disponibilità qui |