Search

Browse Subject Areas

For Authors

Submit a Proposal

Energy Efficient Internet of Things-Based Wireless Sensor Network

Edited by Arvind Panwar, Vishal Jain, Urvashi Sugandh and Vinay Kukreja
Copyright: 2025   |   Expected Pub Date:2025/8/30
ISBN: 9781394314720  |  Hardcover  |  
768 pages

One Line Description
Tackle the critical challenge of sustainability in modern technology with this essential book, which provides a comprehensive, expert-led exploration of energy-aware methodologies and machine learning strategies for optimizing IoT-based wireless sensor networks.

Audience
Researchers, academics, engineers, system architects, technology developers, and policymakers specializing in IoT, wireless communications, and energy-efficient systems.

Description
With the rapid expansion of IoT applications in diverse domains such as smart cities, agriculture, healthcare, and industry, energy constraints pose significant challenges to maintaining sustainable operations. This book addresses these challenges by presenting a comprehensive exploration of methodologies, technologies, and strategies aimed at optimizing energy usage in IoT-based wireless sensor networks. Authored by experts from academia and industry, the book covers topics such as energy-aware routing protocols, edge computing, energy harvesting technologies, machine learning applications, and blockchain-based energy management frameworks. Each chapter provides cutting-edge insights and practical approaches to fostering energy efficiency while ensuring robust and scalable IoT solutions. This book serves as a valuable resource for researchers, professionals, and policymakers, offering actionable knowledge to navigate the evolving landscape of IoT and wireless sensor network technologies.
Readers will find the volume:
• Explores the intersection of Internet of Things, wireless sensor networks, and energy efficiency across fundamental concepts, protocols, applications, and advanced solutions;
• Features chapters by leading researchers and industry professionals, providing authoritative perspectives;
• Offers actionable insights for implementing sustainable and energy-efficient IoT solutions in diverse fields like healthcare, agriculture, and smart cities;
• Highlights emerging trends, including AI, machine learning, and blockchain integration in wireless sensor networks.

Back to Top
Author / Editor Details
Arvind Pawar, PhD is an Associate Professor in the School of Computing Science and Engineering at Galgotias University, India with more than ten years of teaching experience. He has published more than 20 research papers in international journals and conferences and five Indian patents, one of which has been granted. His areas of interest include blockchain technology, distributed ledger technology, data science, machine learning, data mining, and network security.

Vishal Jain, PhD is a Professor in the Department of Computer Science and Engineering in the School of Engineering and Technology at Vivekananda Institute of Professional Studies’ Technical Campus, India. He has published more than 250 research papers in professional journals and conferences and more than 70 books and edited ten book series. His research areas include machine learning, information retrieval, semantic web, ontology engineering, data mining, ad hoc networks, sensor networks, and network security.

Urvashi Sugandh, PhD is an Assistant Professor at Galgotias University and a Professor at Chitkara University, India with more than 12 years of research and teaching experience. She has published seven journal articles, ten conference papers, and 11 book chapters, edited two books, and published 11 patents, six of which have been granted. Her expertise spans blockchain technology, cybersecurity, and Internet of Things applications.

Vinay Kukreja, PhD is a Professor and the Director of Research in the Office of Research Publications at Chitkara University, India with more than 18 years of experience. He has published more than 600 articles, three books, four edited volumes, and 50 patents. His research interests encompass machine learning, deep learning, agile software development, image processing, data analysis, and structural equation modeling.

Back to Top

Table of Contents
Preface
Part 1: Fundamentals and Architecture
1. Understanding the Energy-Efficiency Paradigm in Modern WSN-IoT Integration Fundamental Concepts
Urvashi Sugandh, Achin Jain, Sunita Yadav, Neha Sharma, Arvind Panwar and Vishal Jain
1.1 Introduction
1.1.1 Overview of WSN-IoT Integration
1.1.2 Importance of Energy Efficiency
1.1.3 Chapter Objectives and Organization
1.2 Fundamental Concepts of WSN-IoT Integration
1.2.1 Basic Architecture of WSN
1.2.2 IoT Framework and Components
1.2.3 Integration Points between WSN and IoT
1.2.4 Key Parameters and Metrics for Energy Efficiency
1.3 Energy Consumption Patterns
1.3.1 Sources of Energy Consumption
1.3.1.1 Sensing Operations
1.3.1.2 Data Processing
1.3.1.3 Communication Overhead
1.3.2 Energy Distribution in Different Network Components
1.3.3 Power Management States
1.4 Core Challenges in Energy-Efficient WSN-IoT Systems
1.4.1 Battery Life Limitations
1.4.2 Network Lifetime Optimization
1.4.3 Scalability Issues
1.4.4 Environmental Factors
1.4.5 Quality of Service (QoS) vs. Energy Efficiency
1.5 Modern Energy-Efficiency Techniques
1.5.1 Sleep/Wake Scheduling
1.5.2 Data Aggregation Methods
1.5.3 Clustering Approaches
1.5.4 Adaptive Power Management
1.5.5 Energy-Aware Routing Protocols
1.6 Implementation Considerations
1.6.1 Hardware Selection
1.6.2 Protocol Design
1.6.3 Network Topology Optimization
1.6.4 Cross-Layer Design Approaches
1.7 Future Directions and Emerging Solutions
1.7.1 Energy Harvesting Integration
1.7.2 Machine Learning Applications
1.7.3 Edge Computing Solutions
1.7.4 Green IoT Concepts
1.8 Conclusion
References
2. Energy Efficient WSN in IoT: Introduction
Seema Malik, R.K. Yadav, Birendra Saraswat and Ambuj Kumar
2.1 Wireless Sensor Network
2.1.1 System Introduction
2.2 Various Types of WSN
2.2.1 Underwater WSN
2.2.2 Underground WSN
2.2.3 Multimedia WSN
2.2.4 Terrestrials WSN
2.2.5 Mobile WSN
2.3 Structure of WSN
2.3.1 Structure of Sensor Nodes
2.3.2 Concept of Sink
2.3.3 Design Constrains of WSN
2.3.4 Network Energy Model
2.3.5 Steps to Overcome Power Consumption
2.4 Network Topologies of WSN
2.4.1 Bus Topology
2.4.2 Tree Topology
2.4.3 Star Topology
2.4.4 Ring Topology
2.4.5 Mesh Topology
2.4.6 Hybrid Topology
2.5 Routing in WSN
2.5.1 Protocols Based on Location
2.5.2 Protocols Focused on Data
2.5.3 Hierarchical Protocols
2.5.4 Mobility-Based Protocols
2.5.5 Multipath-Based Protocols
2.5.6 QoS-Based Protocols
2.5.7 Opportunistic Routing Protocols
2.5.8 Link Quality Based Protocol
2.6 Clustering in WSN
2.6.1 Grid Clustering
2.6.2 Grid Construction
2.7 Mobile Sink Based WSN
2.8 Coverage in WSN
2.8.1 Coverage Hole
2.9 QoS Parameters in WSN
2.10 Applications of WSN
2.10.1 Agriculture
2.10.2 Marine Environment
2.10.3 Forest Fire Detection
2.10.4 Military Applications
2.10.5 Robotics/Smart Homes
2.11 Conclusion and Future Scopes
References
3. Energy-Efficient Architectures and Protocols in Internet of Things (IoT)-Based Wireless Sensor Networks
Ipseeta Satpathy, Arpita Nayak and Vishal Jain
3.1 Introduction
3.2 Research Questions
3.3 Research Objectives
3.4 Energy Efficient Protocols
3.5 Energy Harvesting Techniques for Wireless Sensor Network (WSN)
3.6 Optimizing Sensor Node Design for Energy Efficiency in Wireless Sensor Networks
3.7 The Ideal Data Handling for Energy Efficiency in Wireless Sensor Networks
Conclusion
References
4. Enhancing Energy Efficiency in IoT Via Cellular Network Integration
Manoj Singh Adhikari, Ritika Gupta, Dharm Raj, Anil Kumar Sagar, Danish Ather and Amrit Kumar Agrawal
4.1 Introduction
4.2 Cellular Network
4.2.1 Evolution from 2G to 5G
4.2.2 Beyond 5G and 6G
4.2.3 Issues in Cellular Networks
4.3 Internet of Things
4.3.1 Architecture of IoT
4.3.1.1 Perception Layer
4.3.1.2 Gateways and Network Layer
4.3.1.3 Management Service Layer
4.3.1.4 Application Layer
4.3.2 Characteristic of IoT
4.3.2.1 Connectivity
4.3.2.2 Intelligence and Identify
4.3.2.3 Scalability
4.3.2.4 Interoperability
4.3.2.5 Autonomous Function
4.3.3 Technologies in IoT
4.3.3.1 Narrowband IoT
4.3.3.2 Massive IoT
4.3.3.3 Broadband IoT
4.3.3.4 Critical IoT
4.3.3.5 5G and B2G
4.4 Integration of Cellular Network with IoT Technology
4.4.1 Comparison with Non-Cellular IoT Technology (Wi-Fi, Zigee, LORAWAN)
4.4.2 Hybrid Approach (Cellular Wi-Fi Integration)
4.4.3 5G and IoT
4.4.3.1 Integration of 5G in IoT
4.4.3.2 Emerging Trend and Future Possibility
4.5 Security and Privacy in Cellular IoT
4.5.1 Threats and Vulnerabilities in IoT
4.5.1.1 Device Vulnerabilities
4.5.1.2 Lack of Standardization
4.5.1.3 Data Privacy
4.5.1.4 Network Vulnerabilities
4.5.1.5 DDOS Attacks
4.5.1.6 Physical Attacks
4.5.1.7 Supply Chain Attacks
4.5.1.8 Lack of Patch Management
4.5.1.9 Insider Threats
4.5.1.10 Regulatory Compliance
4.5.2 IoT Protocols
4.5.3 Securing IoT through Cellular Network
4.5.3.1 Common IoT Attacks and Vulnerabilities
4.5.3.2 Cellular Networks Can Address IoT Security
4.6 Recent Advancement
4.6.1 Edge Computing for IoT
4.6.2 Blockchain for IoT Security
4.6.3 Network Slicing in 5G Networks
4.6.4 Massive –Internet of Things (IoT)
4.6.5 An Energy Efficient IoT
4.7 Future Direction
4.8 Conclusion
References
5. Green IoT Sustainable Energy Solutions for WSNs (Wireless Sensor Networks)
Sanchita Ghosh, Piyal Roy, Amitava Podder, Saptarshi Kumar Sarkar and Bitan Roy
5.1 Introduction
5.1.1 Background
5.1.2 Motivation
5.1.3 Objectives
5.2 Overview of Wireless Sensor Networks (WSNs)
5.2.1 Architecture of WSNs
5.2.2 Applications of WSNs
5.2.3 Challenges in WSNs
5.3 Green IoT: Concept and Principles
5.3.1 What is Green IoT?
5.3.2 Principles of Green IoT
5.3.3 Green IoT Applications
5.4 Sustainable Energy Solutions for WSNs
5.4.1 Energy Harvesting Techniques
5.4.2 Low-Power Design Strategies
5.4.3 Battery and Storage Solutions
5.4.4 Energy-Aware Routing Protocols
5.5 Integration of Green IoT and Sustainable Energy in WSNs
5.5.1 Design Considerations
5.5.2 Optimization Techniques
5.5.3 Case Studies
5.6 Challenges and Future Directions
5.6.1 Current Challenges
5.6.2 Emerging Technologies
5.6.3 Future Research Directions
5.7 Conclusion
References
6. A Comprehensive Review of Wireless Communication Standards for Smart Grid
L. Chhaya
6.1 Introduction
6.2 Wireless Communication Standards for Smart Grid
6.2.1 Bluetooth
6.2.2 Wirelesshart
6.2.3 Zigbee
6.2.4 Wavenis
6.2.5 6LOWPAN
6.2.6 Wi-Fi/WLAN
6.2.7 Z Wave
6.2.8 WiMAX
6.2.9 Standards for Cellular Communication
6.2.10 Cognitive Radio-IEEE 802.22
6.3 Comparison and Applications of Different Standards
6.4 Conclusions
References
Part 2: Energy-Efficient Protocols and Techniques
7. Edge Computing for Energy Efficient IoT
Sheetal Agarwal and Rupal Gupta
7.1 Introduction
7.2 IoT
7.3 Cloud Computing
7.4 Edge Computing
7.5 Challenges in Traditional IoT Architectures
7.6 Edge Computing for Energy Efficient IoT
7.7 Future Directions
7.8 Conclusion
References
8. Energy-Aware Routing Protocols in IoT-Based WSN
Shikha Verma and Vimal Dwivedi
8.1 Introduction
8.2 Characteristics and Challenges of Routing Protocols in IoT-Based WSN
8.3 Designing Challenges for WSNs Routing Protocols
8.4 Different Routing Protocols in IoT-Based WSN
8.4.1 LEACH
8.4.2 RPL
8.4.3 AODV (Ad Hoc On-Demand Distance Vector)
8.5 Comparative Study of Four Prominent IoT-Based WSN Protocols
8.6 Conclusion
References
9. Energy Aware Routing Protocols in IoT Based Wireless Sensor Networks (WSN)
Sonia Singh and Neha Gupta
9.1 Introduction
9.1.1 Role of Energy-Aware Routing Protocols in WSNs
9.2 Traditional Approaches of Energy-Aware Routing Protocols
9.2.1 Clustering-Based Protocols
9.2.2 Multi-Hop Routing
9.2.3 Data Aggregation and Compression
9.2.4 Hierarchical Routing
9.2.5 Geographic and Location-Based Routing
9.3 Categories of Energy-Aware Routing Protocols
9.3.1 LEACH (Low-Energy Adaptive Clustering Hierarchy)
9.3.2 Threshold-Sensitive Energy Efficient Sensor Network Protocol (TEEN)
9.3.3 Adaptive Threshold-Sensitive Energy Efficient Sensor Network Protocol (APTEEN)
9.3.4 DEEC (Distributed Energy-Efficient Clustering)
9.3.5 Hybrid Energy-Efficient Distributed Clustering (HEED)
9.3.6 PEGASIS (Power-Efficient Gathering in Sensor Information Systems)
9.3.7 SEP (Stable Election Protocol)
9.3.8 EEUC (Energy Efficient Unequal Clustering)
9.3.9 EECDA (Energy Efficient Clustering and Data Aggregation)
9.3.10 MTE (Multihop Topology Control for Energy Efficiency)
9.4 A Brief Comparison of Energy-Efficient Routing Protocols
9.5 Strategies for Optimizing Energy Utilization
9.5.1 Data Aggregation
9.5.2 Clustering
9.5.3 Duty Cycling
9.6 Impact of IoT-Specific Characteristics
9.6.1 Heterogeneity
9.6.2 Mobility
9.6.3 Scalability
9.7 Challenges in IoT Deployments
9.7.1 Resource-Constrained Devices
9.7.2 Intermittent Connectivity
9.7.3 Dynamic Network Topologies
9.8 Suitability for Diverse IoT Applications
9.8.1 Environmental Monitoring
9.8.2 Smart Agriculture
9.8.3 Healthcare
9.8.4 Industrial Automation
9.9 Performance Metrics for Routing Protocols
9.9.1 Energy Efficiency
9.9.2 Packet Delivery Ratio
9.9.3 Latency
9.9.4 Scalability
9.10 Emerging Trends and Future Directions
9.10.1 Machine Learning-Based Optimization
9.10.2 Cross-Layer Design Approaches
9.10.3 Integration with Edge Computing Paradigms
9.11 Conclusion
9.12 Future Research Opportunities
References
10. Cross-Layer Optimization Employing Energy Efficient Routing Protocols in WSN
Lina Elmoiz Alatabani, Rashid A. Saeed and Elmustafa Sayed Ali
10.1 Introduction
10.1.1 Role of Cross-Layer Optimization
10.1.2 Scope of the Chapter
10.2 Related Work
10.3 WSN Architecture and Constraints
10.3.1 Network Architecture
10.3.2 Energy Constraints in WSN Issues
10.4 Energy Efficient Routing Protocols
10.4.1 Classification of Energy Effective Routing Protocols
10.4.1.1 Network Structure-Based Routing Protocols
10.4.1.2 Operation-Based Routing Protocols
10.4.1.3 Route Processing
10.4.2 Metrics for Routing Protocol Performance
10.5 Cross-Layer Framework Application in WSN
10.5.1 Concept of Cross-Layer Design
10.5.2 Benefits of Cross-Layer Optimization in WSN
10.5.3 Examples of Cross-Layer Design Approaches
10.5.3.1 Disaster Management and Military Applications
10.5.3.2 Web Base Cross-Layer Optimization for Energy Efficiency through Clustering
10.6 Optimization Techniques for Energy Efficiency
10.6.1 Swarm Algorithms
10.6.2 Application of Optimization in Routing Protocols
10.7 Case Studies and Real-World Applications
10.7.1 Urban Monitoring Using Optimized Routing Protocols
10.7.2 Evaluation and Discussion
10.7.2.1 Cross-Layer Clustering Algorithms Analysis
10.7.2.2 Optimization Algorithms Analysis – Urban Monitoring
10.8 Future Trends and Research Directions
10.8.1 Advances in Sensor Technology
10.8.2 Innovations in Cross-Layer Optimization Techniques
10.9 Conclusion
References
11. Adaptive Blast Radius Optimization for Energy-Efficient Routing in Wireless Sensor Networks and IoT
J. Viji Gripsy, L. Sheeba, M. Sasikala and Bobby Lukose
11.1 Introduction
11.1.1 Challenges of Clustering
11.1.2 Balanced Clusters
11.1.3 Intra-Cluster Distance
11.1.4 Problem Statement
11.2 Literature Review
11.3 Proposed Methodology
11.3.1 Cluster Head Selection
11.3.2 Optimal Routing
11.4 Results and Discussion
11.5 Conclusion and Future Enhancement
References
12. An Energy-Efficient Load Distribution Clustering (EELDC) Algorithm Improves the Energy Efficiency of IoT‑Based Wireless Sensor Networks
G. Indra Navaroj, E. Golden Julie, S. Jerine Peter and A. Ananthakumari
12.1 Introduction
12.2 Related Works
12.3 Proposed Method
12.3.1 Network Model
12.3.2 CH Selection Phase
12.3.3 Route Phase
12.4 Results
12.5 Conclusion
References
13. Enhance the Security Protocols of Wireless Sensor Network Using an Ant-Based Approach
Renu Jangra and Ramesh Kait
13.1 Introduction
13.2 Literature Survey
13.3 Attacks in Wireless Sensor Network
13.4 Security Challenges
13.5 Securing Wireless Sensor Networks
13.6 Cryptography
13.7 Proposed Algorithm Flowchart
13.8 Experimental Results
13.9 Summary
References
Part 3: Applications and Integration
14. IoT Integrated Wireless Network in Medical and Healthcare Sectors
Rakesh Kumar Dhaka, Sampurna Panda, Babita Panda and Naeem Hannoon
Introduction
Why Use Wireless Networks in Healthcare Applications
Who Stands to Gain
Obstacles & Problems Along the Way
Utilized Wireless Networking Technologies
Applications of Wireless Technology, Both Present and Historical
WBAN (Wireless Body Area Network)
RFID (Radio Frequency Identification)
WPAN (Wireless Personal Area Network)
Sensor Networks
GPRS/UMTS
Wireless LAN (802.11)
Standards
The Role of Applications in Research
CodeBlue
MobiHealth
Physiological Wireless Sensors for Wearable and Implantable Devices
Project Connect
Commercial Utilizations
LifeSync Wireless ECG System
Radio and Modules for Embedded Wireless Device Servers
ECG Anywhere
The Origin of Life End Result
A Health Care Transaction Laws Tracker
Directions of the Future
Patient Home Healthcare
iRevive
Summarization
References
15. Integrating Big Data Analytics and IoT Technologies for Enhanced Industrial Efficiency: A Comprehensive Mapping Study
Muhammad Younus, Halimah Abdul Manaf, Achmad Nurmandi, Dyah Mutiarin, Andi Luhur Prianto, Imron Sohsan, Bambang Irawan, Zuly Qodir, Rijal Ramdani, Bilveer Singh and Dimas Zulkarnain Rosadi
15.1 Introduction
15.2 Literature Review
15.2.1 Bibliometric Analysis
15.2.2 Big Data
15.2.3 Internet of Things
15.2.4 Industrial Internet of Things (IIoT)
15.3 Research Method
15.4 Results and Discussion
15.4.1 Year-by-Year Documents
15.4.2 Documents by Type
15.4.3 Subject Area of Publications
15.4.4 Affiliations of Publications
15.4.5 The Most Productive Authors
15.4.6 Countries Contributions
15.4.7 Sources of the Publications
15.4.8 Cluster Visualization Analysis
15.5 Conclusion
References
16. Energy Efficient Internet of Things and Wireless Sensor Networks in Smart Agriculture
N. Suthanthira Vanitha, G. Sudha, J. Gowrishankar, K. Radhika, A. Kalaiyarasan and S. Grace Infantiya
16.1 Introduction
16.2 Architecture of WSN and IoT in Smart Agriculture
16.2.1 Architecture of Wireless Sensor Networks
16.2.2 Architecture of Internet of Things
16.3 IoT-WSNs Technologies
16.3.1 Integration of Renewable Energy with IoT-WSNs
16.3.2 Artificial Intelligence in Agriculture
16.3.3 Machine Learning in Agriculture
16.3.4 Deep Learning in Agriculture
16.3.5 Drone Farming Technology
16.3.6 Robotics and Automation Technology
16.3.7 Blockchain Technology
16.3.8 Mechatronics System in Irrigation
16.4 WSN-IoT Communication Protocol Methods
16.5 Applications of IoT and WSNs in Smart Agriculture
16.5.1 Control of Crop Diseases and Pests
16.5.2 Irrigation System
16.5.3 Soil Moisture Monitoring
16.5.4 Energy and Power Consumption
16.5.5 Fertilizer Optimization and Control
16.6 Challenges of IoT-WSNs in Smart Agriculture
16.7 Future Prospects
16.8 Conclusion
References
17. Enhancing Energy-Efficient Wireless Sensor Network Techniques with Internet of Things (IoT) Using Artificial Intelligence
Dina Darwish and Kali Charan Rath
17.1 Introduction
17.1.1 Internet of Things Solutions
17.1.2 IoT Components
17.2 IoT’s Role in WSN
17.3 WSN’s Challenges in the IoT
17.3.1 Safety
17.3.2 Privacy and Security
17.3.3 Service Excellence
17.3.4 Accessible
17.3.5 Effective Time Management
17.3.6 Data Consistency
17.3.7 Keep Information Private
17.3.8 Setup
17.4 Energy Efficient Wireless Sensor Network Techniques with Internet of Things (IoT)
17.5 IoT and Associated Future Technology
17.5.1 Digital Twin
17.5.2 Blockchain and AI
17.6 Conclusion
References
18. Machine Learning for Energy Prediction in Wireless Sensor Networks (WSN)
Shilpi Gupta, R. Girija, Namita Kathpal, Savita Kumari and Vimlesh Singh
18.1 Introduction
18.2 About ML and Its Techniques
18.2.1 Development of Machine Learning Algorithms
18.2.1.1 Evolutionary Education
18.2.1.2 Semi- SL
18.2.1.3 Ensemble Learning
18.2.1.4 Artificial Neural Network
18.2.1.5 Ensemble Learning
18.3 Methodology
18.4 Research Issues and Solutions
18.5 Conclusion and Future Scope
References
19. Integrated Machine Learning and Reinforcement Learning Framework for Optimizing Performance in Wireless Sensor Networks
J. Angel Ida Chellam, Harshini Manoharan, R. Shijitha and J. Mythili
19.1 Introduction
19.2 Literature Review
19.2.1 Energy Prediction in WSNs
19.2.2 Anomaly Detection and Energy Optimization
19.2.3 Security and Privacy Considerations
19.2.4 Challenges and Future Directions
19.3 Machine Learning for Energy Prediction
19.3.1 Energy Prediction in Wireless Sensor Networks
19.3.2 Integration of Machine Learning in Wireless Sensor Networks
19.3.2.1 Data Processing and Analysis
19.3.2.2 Network Management and Optimization
19.3.2.3 Security and Privacy
19.3.3 Challenges in Applying Machine Learning to WSNs
19.3.4 How WSNs and Machine Learning Work Together
19.3.5 Applications of WSNs and Machine Learning
19.3.5.1 Supervised Learning
19.3.5.2 Unsupervised Learning
19.4 Key Applications of RL in WSNs
19.4.1 Energy-Efficient Routing
19.4.2 Duty Cycle Management
19.4.3 Adaptive Data Aggregation
19.4.4 Topology Control
19.4.5 Security Enhancement
19.5 Common RL Techniques in WSNs
19.5.1 Q-Learning
19.5.2 Deep Reinforcement Learning (DRL)
19.5.3 Multi-Agent Reinforcement Learning (MARL)
19.5.4 Challenges in Applying RL to WSNs
19.5.4.1 Energy Overhead of Learning
19.5.4.2 Exploration vs. Exploitation Trade-Off
19.5.4.3 Scalability
19.5.4.4 Dynamic Network Conditions
19.5.5 Future Trends
19.6 Integrated Machine Learning and Reinforcement Learning Framework for Optimized Wireless Sensor Networks
19.6.1 Data Collection and Preprocessing
19.6.2 Machine Learning Application
19.6.3 Reinforcement Learning Integration
19.6.4 Optimization and Adaptation
19.7 Results and Discussion
19.7.1 Comparison of Machine Learning Models
19.7.2 PCA Dimensionality Reduction Results
19.7.3 Reinforcement Learning Performance Metrics
19.7.4 Overall System Performance Comparison
19.8 Conclusion
References
20. Architectural Framework for Blockchain-Based Energy Management in Wireless Sensors Networks
Urvashi Sugandh, Achin Jain, Arvind Panwar, Sunita Yadav, Chandan Pal Singh and Kuldeep Singh Kaswan
20.1 Introduction
20.1.1 Background and Motivation
20.1.2 Problem Statement
20.1.3 Significance of Blockchain in WSN Energy Management
20.2 Background Concepts
20.2.1 Wireless Sensor Networks (WSNs)
20.2.1.1 Architecture and Components
20.2.1.2 Energy Consumption Patterns
20.2.1.3 Current Energy Management Challenges
20.2.2 Blockchain Technology
20.2.2.1 Fundamental Concepts
20.2.2.2 Working of Blockchain Framework
20.2.2.3 Consensus Mechanisms
20.2.2.4 Smart Contracts
20.3 Energy Management Challenges in WSNs
20.3.1 Energy Consumption Factors
20.3.2 Network Lifetime Issues
20.3.3 Security and Trust Concerns
20.3.4 Scalability Challenges
20.3.5 Current Solutions and Limitations
20.4 Blockchain Integration in WSN Architecture
20.4.1 Architectural Components
20.4.2 Integration Frameworks
20.4.2.1 Consensus Mechanism Selection
20.4.2.2 Smart Contract Design
20.4.2.3 Energy-Efficient Mining
20.4.2.4 Data Management
20.5 Energy Management Framework
20.5.1 Energy Monitoring and Analysis
20.5.2 Energy Distribution Mechanisms
20.5.3 Smart Contract-Based Energy Trading
20.5.4 Trust Management
20.6 Future Directions and Challenges
20.6.1 Technical Challenges
20.6.2 Future Trends
20.7 Conclusion
References
Part 4: Challenges and Advanced Solutions
21. Analysis of Security Challenges in Next-Generation Wireless Networks
Vivek Yadav, Manju Khari, Kapil Kumar, Intekhab Alam and Ayush Verma
21.1 Introduction
21.2 Wireless Network Evolution
21.3 Literature Review
21.4 Architecture Analysis
21.5 Analysis of 4G Architecture
21.6 5G Architecture Analysis
21.7 Speculative Insights into 6G Architecture
21.8 Attack and Threats on 4G Networks
21.9 Attacks and Threats on 5G Networks
21.10 Speculative Insights into Attacks and Threats on 6G Networks
21.11 Application of 4G Wireless Network
21.12 Application of 5G Wireless Network
21.13 Speculative Application of 6G Wireless Network
21.14 Conclusive Outcomes of 4G, 5G, and 6G Network Technology
21.15 Conclusion
21.16 Future Scope
References
22. Energy Efficient Harvesting Technologies for Wireless Sensor Networks: An Overview
N. Suthanthira Vanitha, M. Shenbagapriya, A. Karthikeyan, S. Valarmathy, K. Radhika and D. Anbuselvi
22.1 Introduction
22.2 Energy Harvesting Sources
22.3 Energy Harvesting Techniques
22.4 Energy Storage Systems (ESS)
22.5 Architectures of Energy Harvesting
22.6 Challeges and Further Prospects
22.7 Conclusion
References
23. Energy Challenges in IoT-Based Wireless Sensor Network Deployment: Perspectives and Solutions
Neha Sharma, Arvind Panwar, Urvashi Sugandh, Rakesh Sharma and Chandan Pal Singh
23.1 Introduction
23.2 Energy Consumption Patterns in Sensor Nodes
23.3 Energy Harvesting Techniques
23.4 Energy-Efficient Communication Protocols
23.4.1 Medium Access Control (MAC) Protocols
23.4.2 Routing Protocols
23.4.3 Cross-Layer Optimization
23.5 Cross-Layer Optimization for Energy Efficiency
23.6 Emerging Paradigms for Energy-Efficient WSN Deployment
23.6.1 Fog Computing and Mobile Edge Computing
23.6.2 Offloading Computationally Intensive Tasks
23.6.3 Energy-Aware Resource Management
23.6.4 Integrating WSNs with Fog/Edge Environments
23.7 Future Research Directions
23.7.1 Artificial Intelligence and Machine Learning for Energy Optimization
23.7.2 Energy-Efficient Hardware and Software Co-Design
23.7.3 Energy-Aware Security and Privacy Mechanisms
23.8 Conclusion
References
24. Unveiling Energy Harvesting Solutions for Enhanced Wireless Sensor Network Efficiency
G. Gnana Priya, K. Balasubadra and K. Mumtaj Begam
24.1 Introduction
24.2 Overview of RF-EHNs
24.2.1 RF EHN Architecture
24.2.2 RF EH Technique
24.2.3 RF Cognitive Radio Networks (RF CoRNs)
24.2.4 Single Hop Network with RF-EH
24.2.4.1 Multi-User Scheduling
24.2.4.2 Receiver Operation Strategy
24.2.5 Multi Antenna Network with RF-EH
24.2.5.1 SWIPT Beamforming without Secure Communication
24.2.5.2 SWIPT Beamforming for Secure Communication
24.2.5.3 Energy Beamforming
24.2.5.4 Information Feedback Mechanism
24.2.6 Relay Network with RF Energy Harvesting
24.2.6.1 Relay Operation Policy
24.2.6.2 Relay Selection
24.2.6.3 Power Allocation
24.2.7 Circuit Design
24.2.7.1 Antenna
24.2.7.2 Matching Network
24.2.7.3 Rectifier
24.2.7.4 Receiver Architecture
24.2.8 Communication Protocols
24.2.8.1 MAC Protocol
24.2.8.2 Routing Protocol
24.2.9 Real-World Challenges and Emerging Trends
24.2.9.1 RF Power Input
24.2.9.2 Antenna Design
24.2.9.3 Influence of Mobility
24.2.9.4 Commercialization
24.2.9.5 Emerging Trends
24.3 Applications of RF EH WSNs
24.4 Conclusion
Acknowledgement
References
25. Promoting Sustainability: Energy Harvesting Strategies That Enhance the Long-Term Viability of Internet-of-Things–Based Wireless Sensor Networks
Ankita Nayak, Ipseeta Satpathy and Vishal Jain
Introduction
Invigorating IoT: Sensor Networks’ Use of Energy Harvesting Technologies
Combating Challenges and Capitalizing on Opportunities in IoT Energy Harvesting
Sustainable Sensor Networks: Essential Design Fundamentals for Energy Consuming Internet-of-Things Devices
Considering Efficiency: Advances in Energy Management for Internet-of-Things Networks
Obtaining Ecological and Financial Footprints: Examining the Effects of Sustainable Internet of Things and Standard Compliances
Determining the Trail for Future IoT Innovations
Conclusion
References
26. Security Considerations in Energy-Efficient Wireless Sensor Networks
Nikhil Kumar Goyal, Monika Dandotiya, Monika Kumari, Vinita Kushwah and A. Anushya
26.1 Introduction
26.1.1 Structure of WSN
26.1.2 Sensor Node in WSN
26.1.2.1 Power Supply
26.1.2.2 Sensing Unit
26.1.2.3 Processing Unit
26.1.2.4 Communication Unit
26.1.2.5 Other Components
26.2 Energy-Efficient Cryptographic Algorithms and Security in WSN
26.2.1 Symetric Cryptography in Wireless Sensor Networks
26.3 Detection System for WSNs
26.4 Authentication Protocol for Users in WSNs
26.4.1 SLUA-WSN
26.4.2 Wsn-Slap
26.4.3 Mutual Authentication
26.4.4 Perfect Forward Secrecy
26.4.5 Laptas
26.4.6 Smartcard-Based Communication
26.5 Routing Protocols for Wireless Sensor Networks
26.5.1 Types of Routing Protocols
26.6 Regulatory and Compliance Considerations in Wireless Sensor Network
26.6.1 In Context of Industrial Purpose
26.6.2 Challenges in Terms of Setting Up Security
26.6.3 In Terms of Reliability
26.7 Applications of Wireless Sensor Network
26.7.1 Monitoring of Environment
26.7.2 In Case of Disaster Relief Operations
26.7.3 Applications in Military
26.7.4 In Field of Medical Sciences
26.8 Conclusion
References
27. Energy Challenges in IoT-Based WSN Deployment
Sonal Laad, Hari Narayan Shukla, Tushar Chaurasia, Richa Patel, Akhilesh Panchal and Nasser S. Albalawi
27.1 Introduction
27.2 Literature Study of the Existing Research
27.3 Methodology of Bit-Mapping MAC for MWSN (BMM-MWSN) and Contention-Based Hybrid MAC for MWSN (CBHM-MWSN)
27.4 Discussion
27.5 Conclusion
References
Index

Back to Top



Description
Author/Editor Details
Table of Contents
Bookmark this page