Sandhya Avasthi & Suman Lata Tripathi 
Decentralized Systems and Distributed Computing [PDF ebook] 

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This book provides a comprehensive exploration of next-generation internet, distributed systems, and distributed computing, offering valuable insights into their impact on society and the future of technology.

The use of distributed systems is a big step forward in IT and computer science. As the number of tasks that depend on each other grows, a single machine can no longer handle all of them. Distributed computing is better than traditional computer settings in several ways. Distributed systems reduce the risks of a single point of failure, making them more reliable and able to handle mistakes. Most modern distributed systems are made to be scalable, which means that processing power can be added on the fly to improve performance. The internet of the future is meant to give us freedom and choices, encourage diversity and decentralization, and make it easier for people to be creative and do research. By making the internet more three-dimensional and immersive, the metaverse could introduce more ways to use it. Some people have expressed negative things about the metaverse, and there is much uncertainty regarding its future. Analysts in the field have pondered if the metaverse will differ much from our current digital experiences, and if so, whether people will be willing to spend hours per day exploring virtual space while wearing a headset. This book will look at the different aspects of the next-generation internet, distributed systems, distributed computing, and their effects on society as a whole.

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قائمة المحتويات

Preface xix

1 Introduction to Next-Generation Internet and Distributed Systems 1
Swapnil Gupta, Rajat Verma and Namrata Dhanda

1.1 Introduction 2

1.2 Traditional Network 4

1.3 Next-Generation Internet 5

1.4 Network Middleware 8

1.5 Software-Defined Network (SDN) 9

1.6 Edge Cloud-Based Next-Generation Internet 11

1.7 Network Architecture 13

1.8 Security and Safety 20

1.9 Distributed Systems 20

1.10 Distributed System Design 22

1.11 Distributed System Monitoring 23

1.12 Security in Distributed Systems 25

1.13 Blockchain and Distributed Systems 25

1.14 Blockchain-Based Distributed Control Systems 27

1.15 Blockchain for Distributed System Security 29

1.16 Conclusion and Future Scope 30

2 Decentralized System in Education and Research 35
Prashant Verma, Deepaks M. Ratnani, Shikha Verma and Sandhya Avasthi

2.1 Introduction 36

2.2 History of Decentralization in the Education System 38

2.3 Advantages and Challenges of Decentralization of the Education System 39

2.4 Impact of Decentralization in Education and Research 42

2.5 Current Approaches 44

2.6 Development Trend Towards Education and Research 46

2.7 Future Scope and Recommendations 47

2.8 Conclusion 48

3 Architecture of Blockchain-Enabled Decentralized Systems 53
Rohit Kumar, Sandhya Avasthi and Suman Lata Tripathi

3.1 Introduction 54

3.2 What is a Decentralized System? 54

3.3 Blockchain 57

3.4 Smart Contracts and Its Examples 59

3.5 Blockchain-Enabled Decentralized System 60

3.6 Architecture for the Blockchain-Enabled Decentralized System 64

3.7 Decentralized Todo App with Blockchain 67

3.8 Blockchain-Enabled Decentralized System Development and Challenges 71

3.9 Future of the Blockchain-Enabled Decentralized System 72

3.10 Conclusion 73

4 Mobile Edge Computing for Decentralized Systems 75
Swati Gupta and Puneet Garg

4.1 Introduction 76

4.2 Edge Computing 79

4.3 Benefits of Edge Computing 81

4.4 Classification of Attacks in a 5G Io T System 83

4.5 Decentralized Dynamic Computation Offloading Method 84

4.6 Conclusion 85

5 Blockchain in Education 89
Shahnaz Fatima and Guru Dev Singh

5.1 Introduction 89

5.2 Benefits of Blockchain in Education 91

5.3 Challenges of Blockchain in Education 99

5.4 Use Cases of Blockchain in Education 106

5.5 Conclusion 110

6 Pattern Recognition Applications in Distributed Systems and Distributed Machine Learning 117
Kalyani S., Swarup K. S., Sandhya Avasthi and Tanushree Sanwal

6.1 Introduction 118

6.2 Data Generation and Preprocessing 120

6.3 Feature Selection 121

6.4 Design of Classifier 130

6.5 Designing Machine Learning Models for Distributed Environment 138

6.6 Role of Distributed Computing in Pattern Recognition 139

6.7 Conclusion 141

7 Next-Generation Distributed Computing for Cancer Detection 145
Kapil Kumar Gupta, Namrata Dhanda and Neeraj Kumar

7.1 Introduction 146

7.2 Research Motivation 147

7.3 Cancer Statistics 148

7.4 Modern Cancer Diagnosis and Treatment Methods 149

7.5 Methodology 152

7.6 Technical Challenges 153

7.7 Future Directions 154

7.8 Conclusion 156

8 Benefits and Challenges of Decentralization in Education for Resource Optimization and Improved Performance 163
Ankita Singh, Shobhit Sinha, Satya Bhushan Verma and Bipin Kumar Singh

8.1 Introduction 164

8.2 The Centralization and Decentralization Concepts 167

8.3 Decentralized Systems in Education and Research: Policies and Practices 169

8.4 Building Capacity Across and Between Levels Within Education Systems 174

8.5 Developing Accountability Measures and Systems in Implementing a Decentralized Education Policy 175

8.6 Developing Local-Level Capacity Across All Education System Levels and Sectors 176

8.7 Education Policies in India to Achieve Decentralization in Education Systems 178

8.8 Research and Development Policies in India and Promoting Decentralization in R&D 180

9 Blockchain in Data Security and Transparency in Business Transactions 189
Rajat Verma and Namrata Dhanda

9.1 Introduction 190

9.2 Dimensions and Requirements of Data Security 191

9.3 Security Issues in Conventional Data Security 193

9.4 Diversity of Attacks in Conventional Data Security 195

9.5 Blockchain: The Complete Solution 196

9.6 The Decentralized and Immutable Approach 198

9.7 Comparison of ECC and RSA 199

9.8 Digital Signature Algorithm 200

9.9 Blockchain Technology Ensures Transparency 201

9.10 Blockchain Solutions for Traditional Data Security 201

9.11 Blockchain Types 203

9.12 Conclusion 205

10 A Comparative Study of Ad Hoc and Wireless Sensor Networks 215
Ankita Kumari and Ajita Pathak

10.1 Introduction 215

10.2 Ad Hoc Network 217

10.3 Wireless Sensor and Network 221

10.4 Challenges, Applications, and Limitations 225

10.5 Conclusion 226

11 Content Filtering-Based Movie Recommendation System Using Deep Learning 229
Atul Srivastava and Abhi Raj Singh

11.1 Introduction 230

11.2 Related Work 232

11.3 Method and Material 235

11.4 Experiments and Results 236

11.5 Possible Extension of Proposed Model into Distributed Environment 239

11.6 Conclusion 240

12 Mobile Edge Computing: A Paradigm Shift in Computing 243
Priti Kumari, Vandana Dubey, Parmeet Kaur and Sarika Shrivastava

12.1 Introduction 243

12.2 Why is MEC Important? 245

12.3 Background 246

12.4 Characteristics 247

12.5 Reference Architecture 248

12.6 Mobile Edge Computing Key Enablers 253

12.7 Advantages of Mobile Edge Computing 254

12.8 Potential Research Directions 255

12.9 Challenges and Issues 257

12.10 Conclusion 259

13 Descriptive Analysis of the Potential of 5G Technologies in Empowering Decentralized Systems 263
Megha Agarwal, Shahnawaz Alam, Dewansh, Avni Singh and Snehil Singh

13.1 Introduction 264

13.2 Building 5G Network 267

13.3 Blockchain on 5G Networks 268

13.4 Real-World Impact of 5G 269

13.5 Future of 5G 273

13.6 Limitations 274

14 Merging Blockchain and Deep Learning for Authentication and Security Architectures 277
Abhay Kumar Yadav and Satya Bhushan Verma

14.1 Introduction 278

14.2 Merger of Blockchain and DL 279

14.3 Application of Blockchain-Based DL Models 283

14.4 Study of Existing Integrated Models 286

14.5 Challenges and Issues 288

14.6 Conclusion 289

15 5G Embedded Decentralized Systems for Secure and Efficient Data Sharing 295
Asjad Suhail Akhtar, Garima Srivastava, Shikha Singh and Sachin Kumar

15.1 Overview of Decentralized Systems 295

15.2 5G Technology 300

15.3 5G for Decentralized Systems 305

15.4 Use Cases and Applications 310

15.5 Challenges and Opportunities 312

15.6 Conclusion 314

16 Artificial Intelligence in a Distributed System of the Future 317
Kadambri Agarwal, Ojasw Khare, Aastha Sharma, Ayushi Prakash and Abhishek Kumar Shukla

16.1 Introduction 318

16.2 AI in the Industrial Sector 319

16.3 AI in the Economic Sector 322

16.4 Environment Sector 324

16.5 Robotics Skill 325

16.6 Interaction Between the Human and the Machine 328

16.7 Recent Projects in AI 329

16.8 Terminologies Regarding AI for the Next Generation 330

16.9 Real-Time Project and Future Implementation 332

16.10 Conclusion 333

17 The Metaverse and Mental Health: The Future 337
Vandana Yadav and Namrata Dhanda

17.1 Introduction 338

17.2 How Has Technology and the Internet Already Impacted Mental Health? 339

17.3 Importance of Researching the Metaverse’s Effects on Mental Health 341

17.4 Potential Positive Mental Health Effects of the Metaverse 342

17.5 Possible Detrimental Effects of the Metaverse on Mental Health 345

17.6 Considerations for Designing the Metaverse with Mental Health in Mind 348

17.7 The Future of Mental Health and Metaverse 349

17.8 Conclusion 351

18 Decentralization in Education Governance: A Case Study of India 355
Mani Dublish and Anita Pati Mishra

18.1 Introduction 356

18.2 Central Organizations 357

18.3 Decentralized Systems 359

18.4 Distributed Systems 360

18.5 Use of a Distributed Database in the Education System 363

18.6 Decentralized Education and Contemporary Solution 364

18.7 Conclusion 368

References 369

Index 371

عن المؤلف

Sandhya Avasthi, Ph D, is an assistant professor in the Computer Science and Engineering Department at ABES Engineering College, Dr. Abdul Kalam Technical University, Ghaziabad, India. She has more than 17 years of teaching experience and is an active researcher in the field of machine learning and data mining. She has published numerous research articles in international journals, conference proceedings, and book chapters. She is associated as senior member the Institute of Electrical and Electronics Engineers and the Association for Computing Machinery and is continuously involved in different professional activities along with academic work.
Suman Lata Tripathi, Ph D, is a professor at Lovely Professional University with more than 17 years of experience in academics. She has published more than 89 research papers, as well as 13 Indian patents and 4 copyrights. She has organized several workshops, summer internships, and expert lectures for students and has worked as a session chair, conference steering committee member, editorial board member, and peer reviewer in national and international journals and conferences. She has edited and authored more than 14 books and one book series in different areas of electronics and electrical engineering.
Namrata Dhanda, Ph D, is a professor in the Department of Computer Science and Engineering at Amity University, Uttar Pradesh, Lucknow. She has over 21 years of experience teaching graduate and post-graduate students. Currently, she is guiding a large number of Ph D scholars working in the domains of machine learning, data science, and big data analytics. Additionally, she has more than 50 papers published in reputed journals, national and international conferences, and book chapters.
Satya Bhushan Verma, Ph D, is working as an associate professor and head of the Department of Computer Science and Engineering, Institute of Technology in Shri Ramswaroop Memorial University Lucknow-Deva Road, India. He has five years of teaching experience at the undergraduate and post graduate levels, as well as research experience. Additionally, he has been actively involved in a number of international committees as an abstract reviewer, workshop reviewer, and panel reviewer and has published several research papers in various journals, conferences, and symposia of national and international recognition.

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