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Cognitive computing using green technologies : modeling techniques and applications /

"Cognitive Computing is a new topic which aims to simulate human thought processes using computers that self-learn through data mining, pattern recognition, and natural language processing. This book focuses on the applications of Cognitive Computing in areas like Robotics, Blockchain, Deep Lea...

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Bibliographic Details
Corporate Author: Taylor & Francis
Other Authors: Tripathy, Asis Kumar (Editor), Chowdhary, Chiranji Lal, 1975- (Editor), Sarkar, Mahasweta (Editor), Panda, Sanjaya Kumar (Editor)
Format: eBook
Language:English
Published: Boca Raton, FL : CRC Press, 2021.
Edition:First edition.
Series:Green energy and technology : concepts and applications
Subjects:
Soft computing.
Machine learning.
Energy conservation > Data processing.
Electronic digital computers > Energy conservation.
Informatique douce.
Apprentissage automatique.
Économies d'énergie > Informatique.
Ordinateurs > Économies d'énergie.
COMPUTERS / Machine Theory
COMPUTERS / Computer Science
TECHNOLOGY / Industrial Health & Safety
Energy conservation > Data processing
Machine learning
Soft computing
Electronic books.
Online Access:Connect to the full text of this electronic book
Table of Contents:
  • Intro
  • Half Title
  • Title Page
  • Copyright Page
  • Table of Contents
  • Preface
  • Contributors
  • About the Book
  • Green Engineering and Technology: Concepts and Applications
  • Part I: Introduction
  • 1. Green Communication Technology, IOT, VR, AR in Smart Environment
  • 1. Introduction
  • 2. Associated Work
  • 3. Technical Technology
  • 3.1. Strategies Based on Program Acquisition
  • 3.2. Irregularity Grounded Interruption Recognition
  • 3.3. IDSs: Presentation Assessment
  • 4. Keen Metropolitan Tenders
  • 4.1. Smart Transportation
  • 4.2. Ambient Abetted Existing
  • 4.3. Corruption Deterrence and Public Security Documentation of Convicts
  • 4.4. Ascendency
  • 4.5. Disruption of Nursing and Maintenance of Replacement
  • 4.6. Disaster and Backup Organization
  • 4.7. Ecological Monitoring
  • 4.8. Waste and Equipment Administration
  • 4.9. Canny Is Taken Home
  • 4.10. Smart Energy
  • 5. Conclusion
  • References
  • 2. Green Computing
  • Uses and Design
  • 1. Introduction
  • 2. Origin of Green Computing
  • 3. Related Works
  • 4. Need for Green Computing
  • 5. Challenges in Green Computing
  • 5.1. Return of Investment
  • 5.2. Disposal of Electronic Wastes
  • 5.3. Perspective with Respect to Indian Scenario
  • 5.4. Energy Efficiency and Miniaturization Board Level Witnessing the R&amp
  • D Capabilities
  • 6. Paradigms of Green Computing in IT
  • 7. Application of Green Computing
  • 7.1. In Distributed and Cloud Environments
  • Server rooms
  • 7.2. In Smart Portable Devices
  • 7.3. In IoT
  • 7.4. In Parallel Computing of Big Data Systems
  • 8. Pros and Cons of Green Computing
  • 9. Measures to be Taken in Developing IT Products as a Move Towards Green Computing
  • 10. Conclusion
  • References
  • Part II: Analysis
  • 3. Statistical Methods for Reproducible Data Analysis
  • 1. Introduction
  • 2. Overview Hierarchy.
  • 3. Introduction to Descriptive Statistics
  • 4. Introduction to Inferential Statistics
  • 5. Introduction to Predictive Modelling
  • 6. Conclusion
  • References
  • 4. An Approach for Energy-Efficient Task Scheduling in Cloud Environment
  • 1. Introduction
  • 2. Literature Survey
  • 3. Proposed Model
  • 4. Problem Formulation
  • 5. Proposed Algorithm
  • 6. Simulation and Experimental Result
  • 7. Conclusion and Future Work
  • References
  • 5. Solar-Powered Cloud Data Center for Sustainable Green Computing
  • 1. Introduction
  • 2. Background
  • 3. Energy Consumption Analysis
  • 4 . Methodology
  • 4.1. Cloud Data Centers Solar PV Model
  • 4.2. Small Scale Routing Algorithm
  • Detection of Route
  • 4.3. MRR Analysis
  • 5 . Results and Discussions
  • 6. Conclusions
  • References
  • 6. State-of-the-Art Energy Grid with Cognitive Behavior and Blockchain Techniques
  • 1. Introduction
  • 1.1. Renewable Energy's Unreliable Nature
  • 1.2. Distributed Architecture Benefits
  • 1.3. Renewable Energy Resources
  • 1.4. Need for Effective Utilization
  • 2. Related Works
  • 2.1. Existing Systems
  • 2.2. Problems with Existing System
  • 3. Proposed Grid Design
  • 3.1. Architecture
  • 3.2. Smart Energy Distribution
  • 3.3. Storage Automation
  • 3.4. Data Analysis
  • 4. Grid Modules
  • 4.1. Energy Storage Pool
  • 4.2. Energy Flow Controller
  • 4.3. Data Storage
  • 4.4. Communication
  • 5. Experimental Setup
  • 6. Techniques Incorporated
  • 6.1. BC Network
  • 6.2. IoT Data Transmission
  • 6.3. Smart Contracts
  • 6.4. Distributed Storage Structure
  • 6.5. Cognitive Character
  • 7. Challenges and Issues
  • 8. Results
  • 8.1. SARIMAX Load Forecasting
  • 8.2. Spectral Clustering
  • 8.3. Distributed Storage
  • 8.4. P2P Energy Trade with Reservations
  • 9. Conclusion
  • References.
  • 7. Optimized Channel Selection Scheme Using Cognitive Radio Controller for Health Monitoring and Post-Disaster Management Applications
  • 1. Introduction
  • 1.1. Cognitive Radio Network
  • 1.2. Dynamic Spectrum Access
  • 2. Problem Identification
  • 3. System Model
  • 3.1. Channel Identification
  • 3.2. Channel Assignment
  • 3.3. Channel Mobility
  • 4. Scheduling and Routing Process
  • 4.1. Transmission Power
  • 4.2. Minimizing Overhead Problem (MOP)
  • 4.3. Overhead
  • 5. Experimental Setup and Results
  • 6. Application of DSA in Health Monitoring System
  • 6.1. Data Extraction Using CRC (Tier 1)
  • 6.2. Channel Selection Layer (Tier 2)
  • 6.2.1 WBAN Controller
  • 6.2.2 Cognitive Radio Controller
  • 6.3. Application Layer (Tier 3)
  • 7. Application of DSA in Post Disaster Management Applications
  • 8. Conclusion
  • References
  • 8. TB-PAD: A Novel Trust-Based Platooning Attack Detection in Cognitive Software-Defined Vehicular Network (CSDVN)
  • 1. Introduction
  • 2. TB-PAD Proposed Methodology
  • 3. Related Works
  • 3.1. Network Model
  • 3.2. Misbehavior Model
  • 3.3. Proposed Methodology for TB-PAD
  • 4. Simulation and Results
  • 5. Conclusion
  • References
  • 9. Analysis of Security Issues in IoT System
  • 1. Introduction
  • 2. IoT Architecture
  • 2.1. Perception Layer
  • 2.2. Network Layer
  • 2.3. Processing Layer
  • 2.4. Application Layer
  • 3. Some Important Technologies
  • 3.1. Radio Frequency Identification
  • 3.2. Wireless Sensor Network
  • 3.3. Green IoT
  • 4. Applications of IoT
  • 4.1. IoT in Healthcare
  • 4.2. IoT in Transport
  • 4.3. IoT in Smart Houses
  • 4.4. IoT in Agriculture
  • 4.5. IoT in Industries
  • 4.6. IoT in Education
  • 4.7. IoT in Smart Cities
  • 5. Security and Authenticity of Data in IoT
  • 5.1. Data Confidentiality
  • 5.2. Date Integrity
  • 5.3. Data Access Control
  • 5.4. Data Availability
  • 5.5. Data Encryption.
  • 6. Layered Analysis of Attacks and Countermeasures
  • 6.1. Perception Layer Attacks and Countermeasures
  • 6.1.1 Some Attacks on Perception Layer
  • a Fake Node Insertion
  • b Malicious Code Insertion
  • c Side Channel Attack
  • d Sinkhole Attack
  • e Device Tampering
  • f Social Engineering Attack
  • g Node Capture Attacks
  • h Sleep Deprivation Attack (SDA)
  • 6.1.2 Some Countermeasures to Protect Perception Layer
  • a Authentication
  • b Data Integrity Schemes
  • c IPSec (Internet Protocol Security)
  • d Secure Physical Designing
  • e Safe Booting
  • 6.2. Network Layer Attacks and Countermeasures
  • 6.2.1 Some Attacks on Network Layer
  • a Traffic Analysis Attack
  • b Man in the Middle Attack (MIMA)
  • c Denial of Service Attack (DoS)
  • d Sybil Attack
  • e False Data Injection Attack (FDIA)
  • f Black Hole Attack (BHA)
  • g Worm Hole Attack
  • h Routing Table Overflow Attack
  • i Distributed Denial-of-Service Attack
  • 6.2.2 Some Countermeasures to Protect Network Layer
  • a Routing Security
  • b Protection against Denial of Service Attacks
  • c Sybil Attack Countermeasure
  • d False Data Injection Attack Countermeasures
  • 6.3. Processing Layer Attacks and Countermeasures
  • 6.3.1 Processing Layer Attacks
  • a Session Hijacking
  • b XML Signature Wrapping Attack
  • c SaaS Security Threats
  • d SQL Injection
  • e Flooding Attack
  • 6.3.2 Processing Layer Countermeasures
  • a Homomorphic Encryption
  • b End-to-End Encryption
  • 6.4. Application Layer Attacks and Countermeasures
  • 6.4.1 Some Attacks on Application Layer
  • a Data Modification Attack
  • b Reprogramming Attack
  • c Phishing Attack
  • 6.4.2 Some Countermeasures to Protect Application Layer
  • a Firewall
  • b User Authentication
  • c Sniffing Attack Countermeasure
  • 7. Conclusion
  • References
  • 10. Resource Optimization of Cloud Services with Bi-layered Blockchain.
  • 1. Introduction
  • 2. Literature Review
  • 3. Problem Statement
  • 4. Bi-layering of Blockchain
  • 5. Smart Contracts
  • 6. Solidity
  • 7. System Design
  • 8. Implementation
  • 9. Consensus Algorithm
  • 9.1. Mathematical Analysis on Modified PoW
  • 10. Application of Proposed Solution on AWS S3
  • 11. Signing and Authenticating Rest Request
  • 12. Results
  • 13. Conclusion
  • References
  • 11. Trust-Based GPS Faking Attack Detection in Cognitive Software-Defined Vehicular Network (CSDVN)
  • 1. Introduction
  • 2. Related Works
  • 3. Trust-Based GPS Faking Attack Detection Methodology for CSDVN
  • 3.1. Network Model
  • 3.2. Misbehavior Model
  • 3.3. Proposed Methodology for GPS Faking Attack Detection
  • 4. Simulation and Results
  • 5. Conclusion
  • References
  • Part III: Applications
  • 12. Cognitive Intelligence-Based Framework for Financial Forecasting
  • 1. Introduction
  • 2. Artificial Neural Network
  • 3. ANN Training Methods
  • 3.1. Gradient Descent-Based Method
  • 3.2. Evolutionary Optimization-Based Method
  • 3.2.1 FWA
  • 3.2.5 MBO
  • 3.2.6 MVO
  • 4. Financial Time Series Data
  • 5. ANN-Based Financial Prediction
  • 6. Simulation Studies and Results Analysis
  • 7. Conclusions
  • References
  • 13. Benefits of IoT in Monitoring and Regulation of Power Sector
  • 1. Introduction
  • 1.1. Indian Power Distribution Reforms Scenario
  • 1.2. Emergence of Internet of Things (IoT)
  • 1.3. IoT in Renewable Energy Sources
  • 2. IoT in Power Sector
  • 3. IoT Architecture and Basic Blocks
  • 3.1. Device Management
  • 3.2. User Management
  • 3.3. Security Monitoring
  • 4. IoT Based Grid
  • 4.1. Applications in Real-Time Systems
  • 5. Comparison of Conventional Power Grid and Smart Grid
  • 6. Application of IoT in the Electrical Power Industry
  • 6.1. IoT SCADA
  • 6.2. Smart Metering
  • 6.3. Building Automation
  • 6.4. Connected Public Lighting.