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.
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.
Audience
Researchers, academics, engineers, system architects, technology developers, and policymakers specializing in IoT, wireless communications, and energy-efficient systems.
Table of Contents:
Preface xxvii
Part 1: Fundamentals and Architecture 1
1 Understanding the Energy-Efficiency Paradigm in Modern WSN-IoT Integration Fundamental Concepts 3
Urvashi Sugandh, Achin Jain, Sunita Yadav, Neha Sharma, Arvind Panwar and Vishal Jain
1.1 Introduction 4
1.2 Fundamental Concepts of WSN-IoT Integration 6
1.3 Energy Consumption Patterns 12
1.4 Core Challenges in Energy-Efficient WSN-IoT Systems 15
1.5 Modern Energy-Efficiency Techniques 18
1.6 Implementation Considerations 21
1.7 Future Directions and Emerging Solutions 23
1.8 Conclusion 26
2 Energy Efficient WSN in IoT: Introduction 33
Seema Malik, R.K. Yadav, Birendra Saraswat and Ambuj Kumar
2.1 Wireless Sensor Network 33
2.2 Various Types of WSN 36
2.3 Structure of WSN 38
2.4 Network Topologies of WSN 44
2.5 Routing in WSN 46
2.6 Clustering in WSN 50
2.7 Mobile Sink Based WSN 54
2.8 Coverage in WSN 55
2.9 QoS Parameters in WSN 57
2.10 Applications of WSN 57
2.11 Conclusion and Future Scopes 60
3 Energy-Efficient Architectures and Protocols in Internet of Things (IoT)-Based Wireless Sensor Networks 67
Ipseeta Satpathy, Arpita Nayak and Vishal Jain
3.1 Introduction 68
3.2 Research Questions 71
3.3 Research Objectives 71
3.4 Energy Efficient Protocols 72
3.5 Energy Harvesting Techniques for Wireless Sensor Network (WSN) 75
3.6 Optimizing Sensor Node Design for Energy Efficiency in Wireless Sensor Networks 79
3.7 The Ideal Data Handling for Energy Efficiency in Wireless Sensor Networks 83
4 Enhancing Energy Efficiency in IoT Via Cellular Network Integration 91
Manoj Singh Adhikari, Ritika Gupta, Dharm Raj, Anil Kumar Sagar, Danish Ather and Amrit Kumar Agrawal
4.1 Introduction 92
4.2 Cellular Network 93
4.3 Internet of Things 96
4.4 Integration of Cellular Network with IoT Technology 107
4.5 Security and Privacy in Cellular IoT 111
4.6 Recent Advancement 119
4.7 Future Direction 123
4.8 Conclusion 124
5 Green IoT Sustainable Energy Solutions for WSNs (Wireless Sensor Networks) 135
Sanchita Ghosh, Piyal Roy, Amitava Podder, Saptarshi Kumar Sarkar and Bitan Roy
5.1 Introduction 136
5.2 Overview of Wireless Sensor Networks (WSNs) 138
5.3 Green IoT: Concept and Principles 141
5.4 Sustainable Energy Solutions for WSNs 145
5.5 Integration of Green IoT and Sustainable Energy in WSNs 148
5.6 Challenges and Future Directions 150
5.7 Conclusion 153
6 A Comprehensive Review of Wireless Communication Standards for Smart Grid 157
L. Chhaya
6.1 Introduction 158
6.2 Wireless Communication Standards for Smart Grid 159
6.3 Comparison and Applications of Different Standards 181
6.4 Conclusions 184
Part 2: Energy-Efficient Protocols and Techniques 187
7 Edge Computing for Energy Efficient IoT 189
Sheetal Agarwal and Rupal Gupta
7.1 Introduction 189
7.2 IoT 192
7.3 Cloud Computing 203
7.4 Edge Computing 207
7.5 Challenges in Traditional IoT Architectures 210
7.6 Edge Computing for Energy Efficient IoT 211
7.7 Future Directions 212
7.8 Conclusion 213
8 Energy-Aware Routing Protocols in IoT-Based WSN 217
Shikha Verma and Vimal Dwivedi
8.1 Introduction 217
8.2 Characteristics and Challenges of Routing Protocols in IoT-Based WSN 219
8.3 Designing Challenges for WSNs Routing Protocols 219
8.4 Different Routing Protocols in IoT-Based WSN 221
8.5 Comparative Study of Four Prominent IoT-Based WSN Protocols 229
8.6 Conclusion 232
9 Energy Aware Routing Protocols in IoT Based Wireless Sensor Networks (WSN) 235
Sonia Singh and Neha Gupta
9.1 Introduction 236
9.2 Traditional Approaches of Energy-Aware Routing Protocols 237
9.3 Categories of Energy-Aware Routing Protocols 239
9.4 A Brief Comparison of Energy-Efficient Routing Protocols 251
9.5 Strategies for Optimizing Energy Utilization 256
9.6 Impact of IoT-Specific Characteristics 258
9.7 Challenges in IoT Deployments 260
9.8 Suitability for Diverse IoT Applications 262
9.9 Performance Metrics for Routing Protocols 264
9.10 Emerging Trends and Future Directions 266
9.11 Conclusion 267
9.12 Future Research Opportunities 268
10 Cross-Layer Optimization Employing Energy Efficient Routing Protocols in WSN 273
Lina Elmoiz Alatabani, Rashid A. Saeed and Elmustafa Sayed Ali
10.1 Introduction 274
10.2 Related Work 276
10.3 WSN Architecture and Constraints 278
10.4 Energy Efficient Routing Protocols 284
10.5 Cross-Layer Framework Application in WSN 290
10.6 Optimization Techniques for Energy Efficiency 296
10.7 Case Studies and Real-World Applications 302
10.8 Future Trends and Research Directions 312
10.9 Conclusion 314
11 Adaptive Blast Radius Optimization for Energy-Efficient Routing in Wireless Sensor Networks and IoT 319
J. Viji Gripsy, L. Sheeba, M. Sasikala and Bobby Lukose
11.1 Introduction 319
11.2 Literature Review 324
11.3 Proposed Methodology 327
11.4 Results and Discussion 332
11.5 Conclusion and Future Enhancement 335
12 An Energy-Efficient Load Distribution Clustering (EELDC) Algorithm Improves the Energy Efficiency of IoT‑Based Wireless Sensor Networks 341
G. Indra Navaroj, E. Golden Julie, S. Jerine Peter and A. Ananthakumari
12.1 Introduction 342
12.2 Related Works 344
12.3 Proposed Method 348
12.4 Results 355
12.5 Conclusion 356
13 Enhance the Security Protocols of Wireless Sensor Network Using an Ant-Based Approach 359
Renu Jangra and Ramesh Kait
13.1 Introduction 360
13.2 Literature Survey 361
13.3 Attacks in Wireless Sensor Network 364
13.4 Security Challenges 365
13.5 Securing Wireless Sensor Networks 366
13.6 Cryptography 367
13.7 Proposed Algorithm Flowchart 370
13.8 Experimental Results 371
13.9 Summary 375
Part 3: Applications and Integration 379
14 IoT Integrated Wireless Network in Medical and Healthcare Sectors 381
Rakesh Kumar Dhaka, Sampurna Panda, Babita Panda and Naeem Hannoon
14.1 Introduction 382
14.2 Why Use Wireless Networks in Healthcare Applications 383
14.3 Who Stands to Gain 383
14.4 Obstacles & Problems Along the Way 384
14.5 Utilized Wireless Networking Technologies 386
14.6 Standards 388
14.7 The Role of Applications in Research 389
14.8 Commercial Utilizations 392
14.9 LifeSync Wireless ECG System 392
14.10 Radio and Modules for Embedded Wireless Device Servers 392
14.11 Directions of the Future 394
14.12 Summarization 396
15 Integrating Big Data Analytics and IoT Technologies for Enhanced Industrial Efficiency: A Comprehensive Mapping Study 401
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 402
15.2 Literature Review 404
15.3 Research Method 414
15.4 Results and Discussion 415
15.5 Conclusion 425
16 Energy Efficient Internet of Things and Wireless Sensor Networks in Smart Agriculture 429
N. Suthanthira Vanitha, G. Sudha, J. Gowrishankar, K. Radhika, A. Kalaiyarasan and S. Grace Infantiya
16.1 Introduction 430
16.2 Architecture of WSN and IoT in Smart Agriculture 431
16.3 IoT-WSNs Technologies 435
16.4 WSN-IoT Communication Protocol Methods 439
16.5 Applications of IoT and WSNs in Smart Agriculture 440
16.6 Challenges of IoT-WSNs in Smart Agriculture 444
16.7 Future Prospects 446
16.8 Conclusion 446
17 Enhancing Energy-Efficient Wireless Sensor Network Techniques with Internet of Things (IoT) Using Artificial Intelligence 453
Dina Darwish and Kali Charan Rath
17.1 Introduction 454
17.2 IoT's Role in WSN 456
17.3 WSN's Challenges in the IoT 458
17.4 Energy Efficient Wireless Sensor Network Techniques with Internet of Things (IoT) 460
17.5 IoT and Associated Future Technology 465
17.6 Conclusion 468
18 Machine Learning for Energy Prediction in Wireless Sensor Networks (WSN) 473
Shilpi Gupta, R. Girija, Namita Kathpal, Savita Kumari and Vimlesh Singh
18.1 Introduction 474
18.2 About ML and Its Techniques 476
18.3 Methodology 485
18.4 Research Issues and Solutions 488
18.5 Conclusion and Future Scope 490
19 Integrated Machine Learning and Reinforcement Learning Framework for Optimizing Performance in Wireless Sensor Networks 497
J. Angel Ida Chellam, Harshini Manoharan, R. Shijitha and J. Mythili
19.1 Introduction 498
19.2 Literature Review 499
19.3 Machine Learning for Energy Prediction 501
19.4 Key Applications of RL in WSNs 510
19.5 Common RL Techniques in WSNs 513
19.6 Integrated Machine Learning and Reinforcement Learning Framework for Optimized Wireless Sensor Networks 515
19.7 Results and Discussion 517
19.8 Conclusion 523
20 Architectural Framework for Blockchain-Based Energy Management in Wireless Sensors Networks 527
Urvashi Sugandh, Achin Jain, Arvind Panwar, Sunita Yadav, Chandan Pal Singh and Kuldeep Singh Kaswan
20.1 Introduction 528
20.2 Background Concepts 530
20.3 Energy Management Challenges in WSNs 538
20.4 Blockchain Integration in WSN Architecture 541
20.5 Energy Management Framework 544
20.6 Future Directions and Challenges 547
20.7 Conclusion 549
Part 4: Challenges and Advanced Solutions 557
21 Analysis of Security Challenges in Next-Generation Wireless Networks 559
Vivek Yadav, Manju Khari, Kapil Kumar, Intekhab Alam and Ayush Verma
21.1 Introduction 560
21.2 Wireless Network Evolution 560
21.3 Literature Review 563
21.4 Architecture Analysis 565
21.5 Analysis of 4G Architecture 566
21.6 5G Architecture Analysis 568
21.7 Speculative Insights into 6G Architecture 569
21.8 Attack and Threats on 4G Networks 571
21.9 Attacks and Threats on 5G Networks 571
21.10 Speculative Insights into Attacks and Threats on 6G Networks 572
21.11 Application of 4G Wireless Network 577
21.12 Application of 5G Wireless Network 577
21.13 Speculative Application of 6G Wireless Network 578
21.14 Conclusive Outcomes of 4G, 5G, and 6G Network Technology 578
21.15 Conclusion 586
21.16 Future Scope 587
22 Energy Efficient Harvesting Technologies for Wireless Sensor Networks: An Overview 591
N. Suthanthira Vanitha, M. Shenbagapriya, A. Karthikeyan, S. Valarmathy, K. Radhika and D. Anbuselvi
22.1 Introduction 592
22.2 Energy Harvesting Sources 593
22.3 Energy Harvesting Techniques 594
22.4 Energy Storage Systems (ESS) 599
22.5 Architectures of Energy Harvesting 600
22.6 Challeges and Further Prospects 602
22.7 Conclusion 603
23 Energy Challenges in IoT-Based Wireless Sensor Network Deployment: Perspectives and Solutions 607
Neha Sharma, Arvind Panwar, Urvashi Sugandh, Rakesh Sharma and Chandan Pal Singh
23.1 Introduction 608
23.2 Energy Consumption Patterns in Sensor Nodes 609
23.3 Energy Harvesting Techniques 611
23.4 Energy-Efficient Communication Protocols 612
23.5 Cross-Layer Optimization for Energy Efficiency 615
23.6 Emerging Paradigms for Energy-Efficient WSN Deployment 616
23.7 Future Research Directions 619
23.8 Conclusion 621
24 Unveiling Energy Harvesting Solutions for Enhanced Wireless Sensor Network Efficiency 627
G. Gnana Priya, K. Balasubadra and K. Mumtaj Begam
24.1 Introduction 628
24.2 Overview of RF-EHNs 630
24.3 Applications of RF EH WSNs 647
24.4 Conclusion 648
25 Promoting Sustainability: Energy Harvesting Strategies That Enhance the Long-Term Viability of Internet-of-Things–Based Wireless Sensor Networks 653
Ankita Nayak, Ipseeta Satpathy and Vishal Jain
25.1 Introduction 654
25.2 Invigorating IoT: Sensor Networks' Use of Energy Harvesting Technologies 656
25.3 Combating Challenges and Capitalizing on Opportunities in IoT Energy Harvesting 659
25.4 Sustainable Sensor Networks: Essential Design Fundamentals for Energy Consuming Internet-of-Things Devices 660
25.5 Considering Efficiency: Advances in Energy Management for Internet-of-Things Networks 662
25.6 Obtaining Ecological and Financial Footprints: Examining the Effects of Sustainable Internet of Things and Standard Compliances 663
25.7 Determining the Trail for Future IoT Innovations 666
25.8 Conclusion 668
26 Security Considerations in Energy-Efficient Wireless Sensor Networks 673
Nikhil Kumar Goyal, Monika Dandotiya, Monika Kumari, Vinita Kushwah and A. Anushya
26.1 Introduction 674
26.2 Energy-Efficient Cryptographic Algorithms and Security in WSN 681
26.3 Detection System for WSNs 685
26.4 Authentication Protocol for Users in WSNs 687
26.5 Routing Protocols for Wireless Sensor Networks 690
26.6 Regulatory and Compliance Considerations in Wireless Sensor Network 693
26.7 Applications of Wireless Sensor Network 697
26.8 Conclusion 700
27 Energy Challenges in IoT-Based WSN Deployment 705
Sonal Laad, Hari Narayan Shukla, Tushar Chaurasia, Richa Patel, Akhilesh Panchal and Nasser S. Albalawi
27.1 Introduction 706
27.2 Literature Study of the Existing Research 708
27.3 Methodology of Bit-Mapping MAC for MWSN (BMMMWSN) and Contention-Based Hybrid MAC for MWSN (CBHM-MWSN) 714
27.4 Discussion 717
27.5 Conclusion 717
References 718
Index 731
About the Author :
Arvind Panwar, 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, 11 book chapters, edited two books, and 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.
