Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Advanced Techniques for IoT Applications : Proceedings of EAIT 2020
| Advanced Techniques for IoT Applications : Proceedings of EAIT 2020 |
| Autore | Mandal Jyotsna Kumar |
| Pubbl/distr/stampa | Singapore : , : Springer Singapore Pte. Limited, , 2021 |
| Descrizione fisica | 1 online resource (626 pages) |
| Altri autori (Persone) | DeDebashis |
| Collana | Lecture Notes in Networks and Systems Ser. |
| Soggetto genere / forma | Electronic books. |
| ISBN | 981-16-4435-7 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Advanced Techniques for IoT Applications |
| Record Nr. | UNINA-9910497099003321 |
Mandal Jyotsna Kumar
|
||
| Singapore : , : Springer Singapore Pte. Limited, , 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Advanced techniques for IoT applications : proceedings of EAIT 2020 ; Kalyani, India, November 2020 / / editors, Jyotsna Kumar Mandal, Debashis De
| Advanced techniques for IoT applications : proceedings of EAIT 2020 ; Kalyani, India, November 2020 / / editors, Jyotsna Kumar Mandal, Debashis De |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (626 pages) : illustrations (some color) |
| Disciplina | 004 |
| Collana | Lecture Notes in Networks and Systems |
| Soggetto topico |
Internet of things
Electronic data processing |
| ISBN |
981-16-4435-7
981-16-4434-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910743265503321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence-based Internet of Things Systems / / Souvik Pal, Debashis De, Rajkumar Buyya, editors
| Artificial Intelligence-based Internet of Things Systems / / Souvik Pal, Debashis De, Rajkumar Buyya, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (512 pages) |
| Disciplina | 006.22 |
| Collana | Internet of Things, Technology, Communications and Computing |
| Soggetto topico | Cooperating objects (Computer systems) |
| ISBN | 3-030-87059-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910523799903321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Artificial Intelligence-based Internet of Things Systems / / Souvik Pal, Debashis De, Rajkumar Buyya, editors
| Artificial Intelligence-based Internet of Things Systems / / Souvik Pal, Debashis De, Rajkumar Buyya, editors |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (512 pages) |
| Disciplina | 006.22 |
| Collana | Internet of Things, Technology, Communications and Computing |
| Soggetto topico | Cooperating objects (Computer systems) |
| ISBN | 3-030-87059-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNISA-996464536303316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Blockchain based Internet of things / / Debashis De, Siddhartha Bhattacharyya, Joel J. P. C. Rodrigues, editors
| Blockchain based Internet of things / / Debashis De, Siddhartha Bhattacharyya, Joel J. P. C. Rodrigues, editors |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (313 pages) |
| Disciplina | 005.74 |
| Collana | Lecture notes on data engineering and communications technologies |
| Soggetto topico |
Blockchains (Databases)
Internet of things |
| ISBN |
981-16-9260-2
981-16-9259-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Preface -- Contents -- Editors and Contributors -- BCoT: Introduction to Blockchain-Based Internet of Things for Industry 5.0 -- 1 Introduction -- 1.1 Objectives -- 1.2 Contributions -- 1.3 Organization of the Paper -- 2 Background on Blockchain Technology -- 2.1 Link List Structured Block -- 2.2 Merkle Tree Structure -- 3 Internet of Things Overview -- 3.1 Architecture of IoT -- 3.2 IoT Integrated Technologies -- 4 Challenges in IoT -- 5 Basic Architecture of Blockchain for IoT -- 5.1 Blockchain in the Gateway of IoT Devices -- 5.2 Blockchain in Management Hub for IoT -- 5.3 Ownership of IoT Devices Using Dew-Block Architecture -- 6 Tools and Techniques for Blockchain of Things -- 7 Challenges of Blockchain of Things -- 8 Limitation of Blockchain of Things -- 9 Conclusion -- References -- Blockchain-Based Internet of Things: Challenges and Opportunities -- 1 Introduction -- 2 Concept of Blockchain Technology -- 2.1 Structure of a Block -- 2.2 Structure of Blockchain -- 2.3 Decentralized Ledger -- 2.4 Proof-of-Work -- 2.5 Peer-to-Peer -- 2.6 Miners -- 3 Benefits of Using Blockchain -- 4 Types of Blockchains -- 4.1 Public Blockchain -- 4.2 Private Blockchain -- 4.3 Consortium Blockchain -- 4.4 Hybrid Blockchain -- 5 Opportunities for Blockchain Technology in IoT -- 5.1 In Banking Sector -- 5.2 In Financial Services -- 5.3 In Healthcare -- 5.4 In Identity Management -- 5.5 In Insurance Sector -- 5.6 In Music Industry -- 5.7 In Real Estate -- 5.8 In Supply Chain -- 5.9 In Voting -- 6 Risk and Challenges of Blockchain in IoT -- 6.1 Decentralization -- 6.2 Energy Consumption -- 6.3 Image Problem -- 6.4 Interoperability -- 6.5 Lack of Regulatory Clarity and Good Governance -- 6.6 Lack of Standardization -- 6.7 Lack of Talent -- 6.8 Organizational Challenges -- 6.9 Scalability -- 6.10 Security and Privacy Challenges -- 6.11 Technical Challenges.
6.12 The Ecosystem -- 6.13 The Vested Interest of Incumbent Parties -- 7 Summary -- References -- Challenges and Issues in Blockchain-Based IoT Services -- 1 Introduction -- 2 Blockchain (BC) -- 2.1 A Synopsis of Blockchain -- 2.2 Sections of Blockchain -- 2.3 Structures of BC -- 3 Internet of Things Using BC -- 4 IoT with BC Architecture -- 5 Execution of BC Using IoT -- 5.1 Ethereum -- 5.2 Hyperledger -- 5.3 Cargo Transportation -- 5.4 Segment Following and Consistence -- 5.5 Log Operational Support Information -- 6 Advantages -- 7 Blockchain IoT Stages -- 7.1 Hdac -- 7.2 VeChain -- 7.3 Walton-Chain -- 7.4 Streamr -- 8 Shortcomings with BC -- 9 Challenges and Issues -- 9.1 Slow Processing -- 9.2 Energy and Cost -- 9.3 Scalability -- 9.4 Interoperability -- 9.5 Independent Ventures -- 9.6 Integration -- 9.7 Complexity -- 9.8 Regulations -- 9.9 Productivity Paradox -- 9.10 Unavailability of Skills -- 9.11 Reputation -- 9.12 Security and Protection Challenges -- 10 Ongoing Projects -- 10.1 HELIUM -- 10.2 Chronicled -- 10.3 ArcTouch -- 10.4 Fiber -- 10.5 NetObjex -- 10.6 HYPR -- 10.7 Xage Security -- 10.8 Grid+ -- 11 Future Research Directions -- 11.1 Security -- 11.2 Flexibility -- 11.3 Data Storage -- 11.4 Legal Issues -- 11.5 Restricted Resources -- 12 Conclusion -- References -- Blockchain for IoT-Based Cyber-Physical Systems (CPS): Applications and Challenges -- 1 Introduction -- 2 The Cyber-Physical Systems Revolution -- 3 Multi-paradigm Modeling of Cyber-Physical Systems -- 4 Design of CPS Based on System of Systems (CPSoS) -- 5 Cyber-Physical System Architecture for IoT -- 6 Blockchain-Enabled Cyber-Physical Systems -- 7 Blockchain for IoT-Based CPS Framework -- 8 Blockchain IoT-Based CPS Applications -- 8.1 Blockchain in Healthcare Applications -- 8.2 Blockchain Applications in Industrial Control Systems (ICS). 8.3 Blockchain for Transportation Applications -- 8.4 Blockchain in Smart Grid -- 9 Challenges of Blockchain IoT-Based CPS Integration -- 9.1 Performance Requirements -- 9.2 Shortcomings of Blockchain Implementations -- 9.3 Security Issues -- 9.4 Limitation of Public-Key Infrastructure -- 10 Effective Adoption Barriers of Blockchain IoT-Based CPS Technology -- 11 Conclusions -- References -- Blockchain in IoT and Beyond: Case Studies on Interoperability and Privacy -- 1 Introduction -- 2 Survey on Blockchain in IoT and IIoT -- 2.1 IoT and Industrial IoT -- 2.2 Survey of Recent Works and Proof of Concepts of Distributed Ledger Technology -- 3 Blockchain and Identity: Concepts and Case Study -- 3.1 Role of Identity Management on Distributed Ledger Technology in Internet of Things -- 3.2 Concepts Relating to Identity Management -- 3.3 Hyperledger Indy -- 3.4 Active Use Cases of Hyperledger Indy -- 4 Blockchain and Interoperability: Case Study of Polkadot and Contemporary Survey -- 4.1 Role of Blockchain Interoperability in IoT -- 4.2 Case Study on Polkadot Protocol -- 4.3 Survey of Contemporary Interoperability Engines and Platforms -- 5 Open Challenges and Discussions -- 6 Conclusion -- References -- Hybrid Blockchain-Enabled Security in Cloud Storage Infrastructure Using ECC and AES Algorithms -- 1 Introduction -- 2 Basic Concepts -- 2.1 IoT Architecture -- 2.2 Cloud Computing Architecture -- 2.3 Definition of Security and Privacy -- 2.4 Definition of Cloud Security -- 2.5 Cloud Security Items "CIA" and Requirements -- 2.6 Security in the SPI Model -- 2.7 Cloud Storage -- 2.8 Cryptography -- 2.9 Hashing -- 3 Related Work -- 4 Methodology -- 5 Result and Decision -- 6 Conclusion -- References -- An Efficient Blockchain-Based IoT System Using Improved KNN Machine Learning Classifier -- 1 Introduction -- 2 Material and Method -- 2.1 Datasets. 2.2 Proposed System -- 2.3 Classification Evaluation -- 3 Findings and Discussion -- 3.1 Findings -- 4 Discussion -- 5 Conclusion -- References -- Leveraging Blockchain Technology for Internet of Things Powered Banking Sector -- 1 Introduction -- 2 Application of IoT in Financial Services Sector -- 2.1 Banking Sector -- 2.2 Insurance -- 3 Blockchain and IoT for Banking -- 4 Status of Blockchain Technology Implementation by Commercial Banks in India -- 4.1 Know Your Customer (KYC) -- 4.2 Trade Finance -- 4.3 Financial Market Infrastructure (Payment, Clearing, and Settlement) -- 4.4 Peer to Peer (P2P) Bank Transfers and Cross Border Payments -- 4.5 Credit Reporting -- 4.6 Reduction of Fraud -- 4.7 Loan Process -- 4.8 Syndicated Lending -- 5 SWOC (Strength Weakness Opportunities and Challenges) Analysis on Blockchain Technology in Banking -- 6 Conclusion -- References -- Identity Management in Internet of Things with Blockchain -- 1 Introduction -- 1.1 What is Identity Management -- 1.2 Related Concepts and Terminology-IAM -- 1.3 Related Concepts and Terminology-Blockchain -- 1.4 The Benefits of Blockchain-Enhanced IAM -- 2 Identity and Access Management (IAM) -- 2.1 Different IAM Models -- 2.2 Responsibilities of IAM -- 2.3 The Four Principles of Managing Identities and Access -- 3 Decentralized Identity and Access Management -- 3.1 New Concepts and Components -- 3.2 The Self-sovereign Identity Model -- 3.3 SSI Implementations for IoT -- 3.4 The State of the SSI -- 4 Cryptography: The Key to Privacy and Security -- 4.1 Zero-Knowledge Proofs (ZKP) -- 4.2 Decentralized Public Key Infrastructure -- 5 Conclusions and Further Research -- References -- An Efficient Hash-Selection-Based Blockchain Architecture for Industrial IoT (IIoT) -- 1 Introduction -- 2 Motivations -- 3 Background and Related Work -- 4 Proposed Model -- 5 Methodology -- 6 Implementation. 7 Result Analysis -- 8 Performance Comparison -- 9 Future Research Direction -- 10 Conclusion -- References -- Quantum Aware Distributed Ledger Technology for Blockchain-Based IoT Network -- 1 Introduction -- 2 Related Work -- 2.1 Distributed Ledger-Based Internet of Things Network -- 2.2 SHA384 Hash-Based STS Technique -- 2.3 IoT-Related Emerging Trends In Research -- 3 Discussion on System Model -- 3.1 Basic Elements in System Model -- 4 STS Scheme -- 4.1 Key Generation -- 4.2 Signature Creation -- 4.3 Verification of Signature -- 4.4 Key Compression -- 5 Discussion on Post-quantum Distributed Ledger for IoT -- 5.1 Accepting and Verification of Transaction -- 5.2 Differentiate Between Trusted and Malicious Peers -- 5.3 Ledger Pruning -- 5.4 Working Architecture of Blockchain-for-IoT -- 6 Security Analysis for Distributed Ledger STS -- 7 Blockchain-STS Performance Analysis -- 7.1 Blockchain-STS Compactness Assessment -- 7.2 Power and Energy Efficiency of Blockchain STS -- 8 Conclusion -- References -- BCoT: Concluding Remarks -- 1 Introduction -- 2 Key Takeaways -- References -- Index. |
| Record Nr. | UNINA-9910743241503321 |
| Singapore : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Confluence of artificial intelligence and robotic process automation / / edited by Siddhartha Bhattacharyya, Jyoti Sekhar Banerjee, and Debashis De
| Confluence of artificial intelligence and robotic process automation / / edited by Siddhartha Bhattacharyya, Jyoti Sekhar Banerjee, and Debashis De |
| Edizione | [1st ed. 2023.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (417 pages) |
| Disciplina | 006.3 |
| Collana | Smart Innovation, Systems and Technologies |
| Soggetto topico | Artificial intelligence - Industrial applications |
| ISBN | 981-19-8296-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Chapter 1. Intelligent Automation Framework using AI and RPA: An Introduction -- Chapter 2. Role of RPA in Intelligent Auditing -- Chapter 3. Impact of AI and RPA in Banking -- Chapter 4. Robotic Process Automation: The key to Reviving the Supply Chain Processes -- Chapter 5. Intelligent Document Processing in end-to-end RPA contexts: a systematic literature review -- Chapter 6. Challenges in Banking and Solving them using RPA -- Chapter 7. Robotic Process Automation in Healthcare -- Chapter 8. Intellectual Property Management in Healthcare Using Robotic Process Automation during Covid-19 -- Chapter 9. RPA Revolution in the Healthcare Industry during COVID-19 -- Chapter 10. Importance of Artificial Intelligence (AI) and Robotic process automation (RPA) in the Banking Industry: A study from an Indian perspective -- Chapter 11. Integration of RPA and AI in Industry 4.0 -- Chapter 12. A Comprehensive Review on Artificial Intelligence (AI) and Robotic Process Automation (RPA) for the development of Smart Cities -- Chapter 13. The Existing IT Functions and Robotics Process Automation -- Chapter 14. RPA Adoption in Healthcare Application -- Chapter 15. Cognitive IoT meets Robotic Process Automation: The Unique Convergence revolutionizing Digital Transformation in the Industry 4.0 era -- Chapter 16. Confluence of Artificial Intelligence and Robotic Process Automation: Concluding Remarks. . |
| Record Nr. | UNINA-9910682590403321 |
| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Dew Computing [[electronic resource] ] : The Sustainable IoT Perspectives / / edited by Debashis De, Samarjit Roy
| Dew Computing [[electronic resource] ] : The Sustainable IoT Perspectives / / edited by Debashis De, Samarjit Roy |
| Edizione | [1st ed. 2024.] |
| Pubbl/distr/stampa | Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
| Descrizione fisica | 1 online resource (347 pages) |
| Disciplina | 004.678 |
| Collana | Internet of Things, Technology, Communications and Computing |
| Soggetto topico |
Telecommunication
Internet of things Electronic circuits Cooperating objects (Computer systems) Communications Engineering, Networks Internet of Things Electronic Circuits and Systems Cyber-Physical Systems |
| ISBN | 981-9945-90-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Fundamentals of Dew Computing -- Foundation of system architectures in Dew computing paradigm -- IoT Convergence paradigm: Cloud, Edge, Fog, and Dew Computing -- Statistical and computational frameworks in Dew-based IoT ecosystems -- Intrusion Detection Systems and analysis in Intelligent Dew-based IoT systems. |
| Record Nr. | UNINA-9910760260403321 |
| Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Frontiers of ICT in Healthcare : Proceedings of EAIT 2022 / / Jyotsna Kumar Mandal and Debashis De, editors
| Frontiers of ICT in Healthcare : Proceedings of EAIT 2022 / / Jyotsna Kumar Mandal and Debashis De, editors |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Singapore : , : Springer, , [2023] |
| Descrizione fisica | 1 online resource (700 pages) |
| Disciplina | 004 |
| Collana | Lecture Notes in Networks and Systems Series |
| Soggetto topico |
Internet of things
Medical informatics |
| ISBN |
9789811951916
9789811951909 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | A method of genome sequence comparison based on a new form of fuzzy polynucleotide space -- Similarity Study of Spike Protein of Corona Virus by PCA Using Physical Properties of Amino Acids -- Identification of Humans by using Machine LearningModels on Gait Features -- Analysis of spread of COVID-19 based on Socio Economic Factors: A Comparison of Prediction Models -- Efficient Heart Disease Prediction using Modified Hybrid Classifier -- Continuous Speech Recognition in Hindi for Healthcare using Deep Learning -- Improving Mental Health through Multimodal Emotion Detection from Speech and Text Data using Long-Short Term Memory -- An unstructured mammogram analysis for feasible classification and detection of breast cancer using a convolutional approach -- MediFi : An IoT Based Health Monitoring Device -- Emotion Recognition from EEG Data Using Hybrid Deep Learning Approach. |
| Record Nr. | UNINA-9910717428103321 |
| Singapore : , : Springer, , [2023] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Green mobile cloud computing / / edited by Debashis De, Anwesha Mukherjee, and Rajkumar Buyya
| Green mobile cloud computing / / edited by Debashis De, Anwesha Mukherjee, and Rajkumar Buyya |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (316 pages) |
| Disciplina | 004.6782 |
| Soggetto topico |
Mobile computing
Cloud computing |
| ISBN | 3-031-08038-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- Part I Mobile Cloud Computing -- Green Mobile Cloud Computing for Industry 5.0 -- 1 Introduction -- 2 Architecture of MCC -- 2.1 Service-Oriented Architecture -- 2.2 Agent - Client Architecture -- 2.3 Collaborative Architecture -- 2.4 Fog-Edge Architecture -- 3 Applications of MCC -- 3.1 Mobile Learning -- 3.2 Mobile Commerce -- 3.3 Mobile Healthcare -- 3.4 Mobile Game -- 4 Simulators of MCC -- 5 Research Challenges of MCC -- 5.1 Mobility Management -- 5.2 Offloading Method -- 5.3 Security and Privacy -- 5.4 Cost and Business Model -- 5.5 Deployment of Agents -- 5.6 Context-Aware Service Provisioning -- 5.7 Mobile Data Management -- 5.8 Energy-Efficiency -- 5.9 Resource Management -- 5.10 Integration of MCC with IoT -- 6 Green Mobile Cloud Computing -- 7 Summary and Conclusions -- References -- Optimization of Green Mobile Cloud Computing -- 1 Introduction -- 1.1 MCC Definition -- 1.2 Edge, Fog Computing and Cloudlet -- 2 Energy-Aware Algorithms in MCC -- 2.1 Content Caching -- 2.2 Computational Offloading -- 2.2.1 Energy-Aware Offloading Modeling -- 2.2.2 Green Offloading Algorithms -- 3 Energy-Aware Key Technologies in MCC -- 3.1 Energy-Aware NFV Deployment -- 3.2 Energy-Aware SDN-Enabled MCC -- 4 Renewable Energy Based MCC -- 4.1 Renewable Energy-Based MCC Risk Issues -- 4.2 Renewable Energy and MCC Functionalities -- 4.2.1 Computing (Task Scheduling and Offloading) -- 4.2.2 Content Caching -- 5 Energy-Aware Algorithms for Devices -- 6 Green AI-Based Algorithms -- 6.1 Traditional ML and Heuristic Algorithms -- 6.2 Deep Learning-Based Algorithms -- 6.3 Advanced ML Algorithms -- 7 Challenges and Future Works -- 8 Conclusion -- References -- Part II Green Mobile Cloud Computing -- Energy Efficient Virtualization and Consolidation in Mobile Cloud Computing -- 1 Introduction -- 2 Motivation -- 3 Basics MCC.
3.1 Architecture of MCC -- 3.2 Characteristics of MCC -- 3.3 Advantages of MCC -- 3.4 Applications of MCC -- 4 Energy Efficient Techniques -- 4.1 Energy Efficiency of Mobile Devices -- 4.2 Limited Battery Lifetime of Mobile Devices -- 4.3 Resource Scheduling -- 4.4 Task Offloading -- 4.5 Load Balancing -- 4.6 Resource Provisioning -- 5 Research Challenges -- 6 Future Research -- 7 Conclusion -- References -- Multi-criterial Offloading Decision Making in Green Mobile Cloud Computing -- 1 Introduction -- 2 Aspects of Decision-Making Regarding Offloading -- 3 Decision Making Regarding Offloading: When, What, Where and How to Offload -- 3.1 When to Offload -- 3.2 What to Offload -- 3.3 Where to Offload -- 3.4 How to Offload -- 4 Multi Criteria Decision Making (MCDM) -- 4.1 Analytical Hieratical Process (AHP) -- 4.2 Analytical Network Process (ANP) -- 4.3 Technique for Order of Preferences by Similarity to Ideal Solution (TOPSIS) -- 4.4 VIekriterijumsko KOmpromisno Rangiranje (VIKOR) -- 4.5 Tomada de decisaointerativa e multicritévio (TODIM) -- 4.6 Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) -- 4.7 ELimination Et Choix Traduisant la REalit´e (ELECTRE) -- 4.8 Grey Relational Analysis (GRA) -- 5 Use of MCDM in Offloading -- 6 Conclusion -- References -- 5G Green Mobile Cloud Computing Using Game Theory -- 1 Introduction -- 2 Advantages of Mobile Cloud Computing -- 3 The Use of Game Theory in Mobile Data Offloading -- 4 Utility Function and Game Table for Mobile Task Offloading -- 5 The Use of Game Theory in 5G Wireless Networks -- 6 Utility Function and Game Table for 5G Wireless Networks in Spectrum Allocation -- 7 The Use of Game Theory in Cloud Resource Allocation -- 8 Utility Function and Game Table for Non-Cooperative Game used in Cloud Resource Allocation -- 9 Mathematical Model -- 9.1 Delay -- 9.2 Power Consumption. 10 Result and Discussions -- 10.1 Delay -- 10.2 Power Consumption -- 11 Summary of Games and Mobile Cloud Computing -- 11.1 Games for Task Offloading -- 11.2 Games for 5G Wireless Networks -- 11.3 Games for MCC Resource Allocation -- 12 Future Scope -- 13 Conclusion -- References -- Security Frameworks for Green Mobile Cloud Computing -- 1 Introduction -- 2 Existing Frameworks -- 2.1 Data Security Framework -- 2.1.1 Data Security Framework Proposed by Patel et al. [19] -- 2.1.2 Data Security Framework Proposed by Zhou and Huang [23] -- 2.2 Access Control Framework -- 2.2.1 System Architecture of Li et al.'s Dynamic Attributes Based Conventional Access Control -- 2.2.2 Static and Dynamic Attribute-Based Access Control Strategy for Collective Attribute Authorities -- 2.3 Communication Framework -- 2.3.1 Benefits of GMCC Communication Framework -- 2.3.2 Some Issues in GMCC Communication Framework -- 3 Security Challenges in Green Mobile Cloud Computing (GMCC) Frameworks -- 3.1 Data Security Challenges -- 3.2 Virtualization Security Challenges -- 3.3 Mobile Cloud Applications Security Challenges -- 3.4 Privacy Challenges -- 3.5 Partitioning and Offloading Security Challenges -- 4 Conclusion -- References -- Part III Applications and Future Research Directions of Green Mobile Cloud Computing -- Sustainable Energy Management System Using Green Smart Grid in Mobile Cloud Computing Environment -- 1 Introduction -- 2 Mobile Cloud Computing and Smart Grid Overview -- 2.1 Mobile Cloud Computing -- 2.2 Smart Grid -- 2.3 Smart Metering -- 2.4 Micro Grid -- 3 Mobile Cloud Computing Key Requirements for Energy Efficiency -- 4 Architecture of Mobile Cloud Computing -- 5 MCC Advantages for Green Smart Grid -- 6 Integration of MCC in Green Smart Grid -- 7 Security Prospects of Green Energy Management -- 8 Future Scope -- 9 Conclusion -- References. Geospatial Green Mobile Edge Computing: Challenges, Solutions and Future Directions -- 1 Introduction -- 2 Mobile Computing Paradigms -- 3 Existing Geospatial Applications on Mobile Edge Computing -- 3.1 Smart City Services -- 3.1.1 Traffic Prediction and Road Safety -- 3.1.2 Health Care Service -- 3.1.3 Environment Monitoring -- 3.2 Disease Monitoring -- 3.3 Disaster Monitoring -- 3.4 Tourism Monitoring -- 3.5 Geospatial Data Collection and Query Processing -- 4 Existing Energy Efficient Methods in Mobile Edge Computing -- 5 Challenges in Geospatial Mobile Edge Computing -- 6 Future Directions -- 7 Summary -- References -- Dynamic Voltage and Frequency Scaling Approach for Processing Spatio-Temporal Queries in Mobile Environment -- 1 Introduction -- 2 Related Work -- 3 Spatio-Temporal Query Processing and Experimentation on Two Dataset -- 4 Energy and Power-Aware Spatio-Temporal Query Processing -- 5 Conclusion and Future Directions -- References -- Green Cloud Computing for IoT Based Smart Applications -- 1 Introduction -- 1.1 Motivation -- 1.2 Contribution -- 2 Related Works -- 3 Mobile Computing -- 4 Green Cloud Computing -- 5 Approaches for Green Computing -- 6 Towards Green Fog Computing -- 7 Virtualization -- 8 Fog Serves a more Green Purpose -- 9 IoT Use Cases in Green Computing -- 9.1 Green IoT Outdoor Lights -- 10 Scope for Future Research -- 11 Conclusion -- References -- Green Internet of Things Using Mobile Cloud Computing: Architecture, Applications, and Future Directions -- 1 Introduction -- 2 Architecture of MCC -- 3 Delay and Power Consumption of IoT-MCC Based Network -- 4 Contribution of IoT- MCC Convergence -- 5 Applications of IoT- MCC -- 6 Enabling Technologies for Green IoT-MCC -- 7 Energy Harvesting Techniques for Green IoT -- 8 Future Research Directions of IoT-MCC -- 9 Conclusion -- References. Predictive Analysis of Biomass with Green Mobile Cloud Computing for Environment Sustainability -- 1 Introduction -- 2 Mobile Cloud -- 3 Green Cloud Computing -- 4 Biomass and Their Composition -- 4.1 Wood and Agriculture Products -- 4.2 Solid Wastes -- 4.3 Landfill Gas and Biogas -- 4.4 Alcohol Fuels -- 5 Procedure -- 5.1 Data Mining/Collecting -- 5.2 Data Cleaning and Preprocessing -- 5.3 Exploratory Data Analysis (EDA) -- 5.4 Data Splitting -- 5.5 Selection & -- Application of Suitable Algorithm -- 5.6 Obtaining Result and Model Evaluation -- 5.7 Model Creation and Deployment into Cloud -- 5.8 Testing the Overall Process -- 6 Software Required -- 7 Cloud Server -- 8 Data Analysis Using Python -- 8.1 Gross Residue Potential -- 8.2 Bioenergy Potential -- 9 Algorithm -- 10 Deployment of the Model -- 10.1 File Upload Algorithm -- 10.2 File Download Algorithm -- 11 Dataset Used -- 12 Exploratory Data Analysis (EDA) -- 13 Advantage -- 14 Conclusion -- 15 Future Scope -- References -- 6G Based Green Mobile Edge Computing for Internet of Things (IoT) -- 1 Introduction -- 2 5G and Beyond 5G for Internet of Things -- 2.1 Protocols for Green IoT -- 2.2 MQTT Protocol -- 2.3 gRPC Protocol for Edge, Cloud Microservices -- 2.4 IoT Application Development -- 2.4.1 Edge Level Buffer -- 2.4.2 Dew Level Buffering -- 2.5 Green IoT Challenges -- 2.6 Network Slicing Under 6G Mobile Edge -- 3 Sustainable Green Sensing -- 3.1 WSNs Application Perspective -- 3.2 Energy Efficient Sensor Networks Integrating 5G & -- 6G -- 4 Federated Learning for 6G Mobile Network -- 4.1 FL Based Mobile Edge Computing in the 6G Era Has the Following Benefits -- 4.2 Artificial Intelligence of Things for Edge Enabled Mobile Computing -- 5 Conclusion -- References -- Resource Management for Future Green Mobile Cloud Computing -- 1 Introduction. 2 Architectures and Resource Management Challenges in GMCC. |
| Record Nr. | UNISA-996495564303316 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. di Salerno | ||
| ||
Green mobile cloud computing / / edited by Debashis De, Anwesha Mukherjee, and Rajkumar Buyya
| Green mobile cloud computing / / edited by Debashis De, Anwesha Mukherjee, and Rajkumar Buyya |
| Pubbl/distr/stampa | Cham, Switzerland : , : Springer, , [2022] |
| Descrizione fisica | 1 online resource (316 pages) |
| Disciplina | 004.6782 |
| Soggetto topico |
Mobile computing
Cloud computing |
| ISBN | 3-031-08038-6 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Intro -- Contents -- Part I Mobile Cloud Computing -- Green Mobile Cloud Computing for Industry 5.0 -- 1 Introduction -- 2 Architecture of MCC -- 2.1 Service-Oriented Architecture -- 2.2 Agent - Client Architecture -- 2.3 Collaborative Architecture -- 2.4 Fog-Edge Architecture -- 3 Applications of MCC -- 3.1 Mobile Learning -- 3.2 Mobile Commerce -- 3.3 Mobile Healthcare -- 3.4 Mobile Game -- 4 Simulators of MCC -- 5 Research Challenges of MCC -- 5.1 Mobility Management -- 5.2 Offloading Method -- 5.3 Security and Privacy -- 5.4 Cost and Business Model -- 5.5 Deployment of Agents -- 5.6 Context-Aware Service Provisioning -- 5.7 Mobile Data Management -- 5.8 Energy-Efficiency -- 5.9 Resource Management -- 5.10 Integration of MCC with IoT -- 6 Green Mobile Cloud Computing -- 7 Summary and Conclusions -- References -- Optimization of Green Mobile Cloud Computing -- 1 Introduction -- 1.1 MCC Definition -- 1.2 Edge, Fog Computing and Cloudlet -- 2 Energy-Aware Algorithms in MCC -- 2.1 Content Caching -- 2.2 Computational Offloading -- 2.2.1 Energy-Aware Offloading Modeling -- 2.2.2 Green Offloading Algorithms -- 3 Energy-Aware Key Technologies in MCC -- 3.1 Energy-Aware NFV Deployment -- 3.2 Energy-Aware SDN-Enabled MCC -- 4 Renewable Energy Based MCC -- 4.1 Renewable Energy-Based MCC Risk Issues -- 4.2 Renewable Energy and MCC Functionalities -- 4.2.1 Computing (Task Scheduling and Offloading) -- 4.2.2 Content Caching -- 5 Energy-Aware Algorithms for Devices -- 6 Green AI-Based Algorithms -- 6.1 Traditional ML and Heuristic Algorithms -- 6.2 Deep Learning-Based Algorithms -- 6.3 Advanced ML Algorithms -- 7 Challenges and Future Works -- 8 Conclusion -- References -- Part II Green Mobile Cloud Computing -- Energy Efficient Virtualization and Consolidation in Mobile Cloud Computing -- 1 Introduction -- 2 Motivation -- 3 Basics MCC.
3.1 Architecture of MCC -- 3.2 Characteristics of MCC -- 3.3 Advantages of MCC -- 3.4 Applications of MCC -- 4 Energy Efficient Techniques -- 4.1 Energy Efficiency of Mobile Devices -- 4.2 Limited Battery Lifetime of Mobile Devices -- 4.3 Resource Scheduling -- 4.4 Task Offloading -- 4.5 Load Balancing -- 4.6 Resource Provisioning -- 5 Research Challenges -- 6 Future Research -- 7 Conclusion -- References -- Multi-criterial Offloading Decision Making in Green Mobile Cloud Computing -- 1 Introduction -- 2 Aspects of Decision-Making Regarding Offloading -- 3 Decision Making Regarding Offloading: When, What, Where and How to Offload -- 3.1 When to Offload -- 3.2 What to Offload -- 3.3 Where to Offload -- 3.4 How to Offload -- 4 Multi Criteria Decision Making (MCDM) -- 4.1 Analytical Hieratical Process (AHP) -- 4.2 Analytical Network Process (ANP) -- 4.3 Technique for Order of Preferences by Similarity to Ideal Solution (TOPSIS) -- 4.4 VIekriterijumsko KOmpromisno Rangiranje (VIKOR) -- 4.5 Tomada de decisaointerativa e multicritévio (TODIM) -- 4.6 Multi Objective Optimization on the Basis of Ratio Analysis (MOORA) -- 4.7 ELimination Et Choix Traduisant la REalit´e (ELECTRE) -- 4.8 Grey Relational Analysis (GRA) -- 5 Use of MCDM in Offloading -- 6 Conclusion -- References -- 5G Green Mobile Cloud Computing Using Game Theory -- 1 Introduction -- 2 Advantages of Mobile Cloud Computing -- 3 The Use of Game Theory in Mobile Data Offloading -- 4 Utility Function and Game Table for Mobile Task Offloading -- 5 The Use of Game Theory in 5G Wireless Networks -- 6 Utility Function and Game Table for 5G Wireless Networks in Spectrum Allocation -- 7 The Use of Game Theory in Cloud Resource Allocation -- 8 Utility Function and Game Table for Non-Cooperative Game used in Cloud Resource Allocation -- 9 Mathematical Model -- 9.1 Delay -- 9.2 Power Consumption. 10 Result and Discussions -- 10.1 Delay -- 10.2 Power Consumption -- 11 Summary of Games and Mobile Cloud Computing -- 11.1 Games for Task Offloading -- 11.2 Games for 5G Wireless Networks -- 11.3 Games for MCC Resource Allocation -- 12 Future Scope -- 13 Conclusion -- References -- Security Frameworks for Green Mobile Cloud Computing -- 1 Introduction -- 2 Existing Frameworks -- 2.1 Data Security Framework -- 2.1.1 Data Security Framework Proposed by Patel et al. [19] -- 2.1.2 Data Security Framework Proposed by Zhou and Huang [23] -- 2.2 Access Control Framework -- 2.2.1 System Architecture of Li et al.'s Dynamic Attributes Based Conventional Access Control -- 2.2.2 Static and Dynamic Attribute-Based Access Control Strategy for Collective Attribute Authorities -- 2.3 Communication Framework -- 2.3.1 Benefits of GMCC Communication Framework -- 2.3.2 Some Issues in GMCC Communication Framework -- 3 Security Challenges in Green Mobile Cloud Computing (GMCC) Frameworks -- 3.1 Data Security Challenges -- 3.2 Virtualization Security Challenges -- 3.3 Mobile Cloud Applications Security Challenges -- 3.4 Privacy Challenges -- 3.5 Partitioning and Offloading Security Challenges -- 4 Conclusion -- References -- Part III Applications and Future Research Directions of Green Mobile Cloud Computing -- Sustainable Energy Management System Using Green Smart Grid in Mobile Cloud Computing Environment -- 1 Introduction -- 2 Mobile Cloud Computing and Smart Grid Overview -- 2.1 Mobile Cloud Computing -- 2.2 Smart Grid -- 2.3 Smart Metering -- 2.4 Micro Grid -- 3 Mobile Cloud Computing Key Requirements for Energy Efficiency -- 4 Architecture of Mobile Cloud Computing -- 5 MCC Advantages for Green Smart Grid -- 6 Integration of MCC in Green Smart Grid -- 7 Security Prospects of Green Energy Management -- 8 Future Scope -- 9 Conclusion -- References. Geospatial Green Mobile Edge Computing: Challenges, Solutions and Future Directions -- 1 Introduction -- 2 Mobile Computing Paradigms -- 3 Existing Geospatial Applications on Mobile Edge Computing -- 3.1 Smart City Services -- 3.1.1 Traffic Prediction and Road Safety -- 3.1.2 Health Care Service -- 3.1.3 Environment Monitoring -- 3.2 Disease Monitoring -- 3.3 Disaster Monitoring -- 3.4 Tourism Monitoring -- 3.5 Geospatial Data Collection and Query Processing -- 4 Existing Energy Efficient Methods in Mobile Edge Computing -- 5 Challenges in Geospatial Mobile Edge Computing -- 6 Future Directions -- 7 Summary -- References -- Dynamic Voltage and Frequency Scaling Approach for Processing Spatio-Temporal Queries in Mobile Environment -- 1 Introduction -- 2 Related Work -- 3 Spatio-Temporal Query Processing and Experimentation on Two Dataset -- 4 Energy and Power-Aware Spatio-Temporal Query Processing -- 5 Conclusion and Future Directions -- References -- Green Cloud Computing for IoT Based Smart Applications -- 1 Introduction -- 1.1 Motivation -- 1.2 Contribution -- 2 Related Works -- 3 Mobile Computing -- 4 Green Cloud Computing -- 5 Approaches for Green Computing -- 6 Towards Green Fog Computing -- 7 Virtualization -- 8 Fog Serves a more Green Purpose -- 9 IoT Use Cases in Green Computing -- 9.1 Green IoT Outdoor Lights -- 10 Scope for Future Research -- 11 Conclusion -- References -- Green Internet of Things Using Mobile Cloud Computing: Architecture, Applications, and Future Directions -- 1 Introduction -- 2 Architecture of MCC -- 3 Delay and Power Consumption of IoT-MCC Based Network -- 4 Contribution of IoT- MCC Convergence -- 5 Applications of IoT- MCC -- 6 Enabling Technologies for Green IoT-MCC -- 7 Energy Harvesting Techniques for Green IoT -- 8 Future Research Directions of IoT-MCC -- 9 Conclusion -- References. Predictive Analysis of Biomass with Green Mobile Cloud Computing for Environment Sustainability -- 1 Introduction -- 2 Mobile Cloud -- 3 Green Cloud Computing -- 4 Biomass and Their Composition -- 4.1 Wood and Agriculture Products -- 4.2 Solid Wastes -- 4.3 Landfill Gas and Biogas -- 4.4 Alcohol Fuels -- 5 Procedure -- 5.1 Data Mining/Collecting -- 5.2 Data Cleaning and Preprocessing -- 5.3 Exploratory Data Analysis (EDA) -- 5.4 Data Splitting -- 5.5 Selection & -- Application of Suitable Algorithm -- 5.6 Obtaining Result and Model Evaluation -- 5.7 Model Creation and Deployment into Cloud -- 5.8 Testing the Overall Process -- 6 Software Required -- 7 Cloud Server -- 8 Data Analysis Using Python -- 8.1 Gross Residue Potential -- 8.2 Bioenergy Potential -- 9 Algorithm -- 10 Deployment of the Model -- 10.1 File Upload Algorithm -- 10.2 File Download Algorithm -- 11 Dataset Used -- 12 Exploratory Data Analysis (EDA) -- 13 Advantage -- 14 Conclusion -- 15 Future Scope -- References -- 6G Based Green Mobile Edge Computing for Internet of Things (IoT) -- 1 Introduction -- 2 5G and Beyond 5G for Internet of Things -- 2.1 Protocols for Green IoT -- 2.2 MQTT Protocol -- 2.3 gRPC Protocol for Edge, Cloud Microservices -- 2.4 IoT Application Development -- 2.4.1 Edge Level Buffer -- 2.4.2 Dew Level Buffering -- 2.5 Green IoT Challenges -- 2.6 Network Slicing Under 6G Mobile Edge -- 3 Sustainable Green Sensing -- 3.1 WSNs Application Perspective -- 3.2 Energy Efficient Sensor Networks Integrating 5G & -- 6G -- 4 Federated Learning for 6G Mobile Network -- 4.1 FL Based Mobile Edge Computing in the 6G Era Has the Following Benefits -- 4.2 Artificial Intelligence of Things for Edge Enabled Mobile Computing -- 5 Conclusion -- References -- Resource Management for Future Green Mobile Cloud Computing -- 1 Introduction. 2 Architectures and Resource Management Challenges in GMCC. |
| Record Nr. | UNINA-9910616371303321 |
| Cham, Switzerland : , : Springer, , [2022] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
