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Submit a ProposalDecentralized Systems and Distributed Computing
 | Edited by Sandhya Avasthi, Suman Lata Tripathi, Namrata Dhanda, and Satya Bhushan Verma Series: Decentralized Systems and Next-Generation Internet Copyright: 2024 | Status: Published ISBN: 978139420436 | Hardcover | 394 pages Price: $225 USD  |
One Line Description
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.
Audience
Researchers, Professors, and IT experts working in internet technology, distributed systems and computing, metaverse, and Internet of Things
Researchers, Professors, and IT experts working in internet technology, distributed systems and computing, metaverse, and Internet of Things
Description
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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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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Author / Editor Details
Sandhya Avasthi, PhD, 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.
Sandhya Avasthi, PhD, 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, PhD, 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, PhD 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 PhD 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, PhD 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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Table of Contents
Preface
1. Introduction to Next-Generation Internet and Distributed Systems
Swapnil Gupta, Rajat Verma and Namrata Dhanda
1.1 Introduction
1.2 Traditional Network
1.3 Next-Generation Internet
1.3.1 Next-Generation Internet Protocol
1.3.1.1 IPv6
1.3.1.2 Tunneling
1.3.2 Quality of Service (QoS)
1.4 Network Middleware
1.5 Software-Defined Network (SDN)
1.5.1 Necessity of Software-Defined Network
1.6 Edge Cloud-Based Next-Generation Internet
1.6.1 Edge Cloud
1.6.2 Content Distribution Networks (CDNs)
1.7 Network Architecture
1.7.1 Some Proposed Architectures
1.7.1.1 Security Architecture for Networked Enterprises (SANE)
1.7.1.2 Swarming Architecture
1.7.1.3 Flexible Internet Architecture (FlexNGIA)
1.7.1.4 Architecture for Mobility Support
1.7.1.5 The Data-Oriented Network Architecture (DONA)
1.7.1.6 MILSA (Mobility and Multihoming Supporting Identifier‑Locator Split
Architecture)
1.7.1.7 Delay/Disruption Tolerant Networks (DTN) and Related Architectures
1.7.2 Challenges for Architecture
1.7.2.1 Network Services
1.7.2.2 Network Management
1.7.2.3 Network Performance
1.7.2.4 Diversity and Change
1.8 Security and Safety
1.9 Distributed Systems
1.9.1 Concept of Distributed System
1.9.2 Terminologies
1.9.2.1 Grouping of Autonomous Computer Components
1.9.2.2 Single Coherent System
1.10 Distributed System Design
1.10.1 Significance of a Certain Design
1.10.2 Scale and Scalability
1.10.2.1 Definition of Scale
1.10.2.2 Scalability Analysis
1.11 Distributed System Monitoring
1.11.1 Idea of Monitoring System
1.12 Security in Distributed Systems
1.12.1 Reasons for Not Using Encryption
1.12.2 Authorization
1.13 Blockchain and Distributed Systems
1.13.1 Decentralization
1.13.2 Peer-to-Peer Networks (P2P)
1.14 Blockchain-Based Distributed Control Systems
1.14.1 Control System
1.14.1.1 To Handle Complicated Processes
1.14.1.2 Pre-Defined Function Blocks
1.14.1.3 Scalable Platform
1.15 Blockchain for Distributed System Security
1.15.1 Fault-Tolerant Consensus in a Distributed System
1.15.2 Complications while Using Blockchain for Distributed Computing
1.16 Conclusion and Future Scope
References
2. Decentralized System in Education and Research
Prashant Verma, Deepaks M. Ratnani, Shikha Verma and Sandhya Avasthi
2.1 Introduction
2.2 History of Decentralization in the Education System
2.3 Advantages and Challenges of Decentralization of the Education System
2.3.1 Advantages
2.3.2 Challenges
2.4 Impact of Decentralization in Education and Research
2.5 Current Approaches
2.5.1 World Scenario
2.5.1.1 Finland Education System
2.5.1.2 Brazil, Federal Universities
2.5.1.3 The United States, National Science Foundation
2.5.1.4 Mexico, CONACYT
2.5.2 Indian Scenario
2.5.2.1 Kerala Model of Decentralization Implementation in Education and Research
2.6 Development Trend Towards Education and Research
2.7 Future Scope and Recommendations
2.8 Conclusion
References
3. Architecture of Blockchain-Enabled Decentralized Systems
Rohit Kumar, Sandhya Avasthi and Suman Lata Tripathi
3.1 Introduction
3.2 What is a Decentralized System?
3.2.1 Centralized System vs. Decentralized System
3.2.2 Merits and Demerits of a Decentralized System
3.3 Blockchain
3.3.1 What is Blockchain?
3.3.2 Structure of Blockchain
3.3.3 Requirements of Blockchain
3.3.4 Merits and Demerits of Blockchain
3.4 Smart Contracts and Its Examples
3.5 Blockchain-Enabled Decentralized System
3.5.1 Role of Blockchain
3.5.2 Types of Decentralization in Blockchain
3.5.3 Types of Blockchain Architecture
3.5.4 Requirements
3.5.5 Pros and Cons
3.6 Architecture for the Blockchain-Enabled Decentralized System
3.6.1 The Network
3.6.2 The Consensus Protocol
3.6.3 The Data Structure
3.7 Decentralized Todo App with Blockchain
3.8 Blockchain-Enabled Decentralized System Development and Challenges
3.9 Future of the Blockchain-Enabled Decentralized System
3.10 Conclusion
References
4. Mobile Edge Computing for Decentralized Systems
Swati Gupta and Puneet Garg
4.1 Introduction
4.2 Edge Computing
4.3 Benefits of Edge Computing
4.4 Classification of Attacks in a 5G IoT System
4.5 Decentralized Dynamic Computation Offloading Method
4.6 Conclusion
References
5. Blockchain in Education
Shahnaz Fatima and Guru Dev Singh
5.1 Introduction
5.2 Benefits of Blockchain in Education
5.2.1 Blockchain Can Enhance Learner Data Privacy and Security, Allowing Learners to Maintain Control over Their Personal Information
5.2.2 Blockchain Can Enable Lifelong Learning Tracking, Creating a Comprehensive and Immutable Record of a Learner’s Achievements and Skills
5.2.2.1 Blockchain as a Distributed and Immutable Record-Keeping System
5.2.2.2 Benefits of Blockchain-Enabled Lifelong Learning Tracking
5.3 Challenges of Blockchain in Education
5.3.1 Concerns Related to Data Privacy, Security, and Compliance with Data Protection Regulations
5.3.1.1 Data Privacy Concern
5.3.1.2 Compliance with Data Protection Regulations
5.3.1.3 Security Concerns
5.3.1.4 Collaboration with Industry Experts and Auditors
5.3.2 Potential Resistance to Change and Adoption Barriers in the Education Sector
5.4 Use Cases of Blockchain in Education
5.5 Conclusion
References
6. Pattern Recognition Applications in Distributed Systems and Distributed Machine Learning
Kalyani S., Swarup K. S., Sandhya Avasthi and Tanushree Sanwal
6.1 Introduction
6.1.1 What is Pattern Recognition?
6.1.2 Distributed Computing Environment
6.1.3 Basic Model of the Pattern Recognition System
6.2 Data Generation and Preprocessing
6.3 Feature Selection
6.3.1 What is Feature Selection?
6.3.2 Filter Models of Feature Selection
6.3.3 Wrapper Models of Feature Selection
6.4 Design of Classifier
6.4.1 Conventional Classifiers in Distributed Environment
6.4.2 Neural Network Classifiers in a Distributed Environment
6.5 Designing Machine Learning Models for Distributed Environment
6.6 Role of Distributed Computing in Pattern Recognition
6.7 Conclusion
References
7. Next-Generation Distributed Computing for Cancer Detection
Kapil Kumar Gupta, Namrata Dhanda and Neeraj Kumar
7.1 Introduction
7.2 Research Motivation
7.3 Cancer Statistics
7.4 Modern Cancer Diagnosis and Treatment Methods
7.5 Methodology
7.6 Technical Challenges
7.7 Future Directions
7.8 Conclusion
References
8. Benefits and Challenges of Decentralization in Education for Resource Optimization and Improved Performance
Ankita Singh, Shobhit Sinha, Satya Bhushan Verma
and Bipin Kumar Singh
8.1 Introduction
8.1.1 Decentralized Systems in Education and Research
8.1.2 Connect Between Democracy and Education
8.2 The Centralization and Decentralization Concepts
8.3 Decentralized Systems in Education and Research: Policies and Practices
8.3.1 Open Educational Resources (OER) Policy
8.3.2 Collaborative Research Networks
8.3.3 Self-Directed Learning
8.3.4 Peer Review
8.3.5 Open Data
8.3.6 Equity and Inclusion
8.3.7 Quality Assurance
8.4 Building Capacity Across and Between Levels Within Education Systems
8.5 Developing Accountability Measures and Systems in Implementing a Decentralized Education Policy
8.5.1 Establish Clear and Quantifiable Policy Objectives
8.5.2 Create Performance Indicators and Benchmarks
8.5.3 Assign Roles and Responsibilities
8.5.4 Build Effective Monitoring and Evaluation Systems
8.5.5 Encourage Transparency and Involvement
8.5.6 Establish Redressal Mechanisms
8.6 Developing Local-Level Capacity Across All Education System Levels and Sectors
8.7 Education Policies in India to Achieve Decentralization in Education Systems
8.7.1 National Education Policy (NEP) 2020
8.7.2 Rashtriya Madhyamik Shiksha Abhiyan (RMSA)
8.7.3 RUSA (Rashtriya Uchchatar Shiksha Abhiyan)
8.8 Research and Development Policies in India and Promoting Decentralization in R&D
8.8.1 Atal Innovation Mission (AIM)
8.8.2 The National Initiative for Developing and Harnessing Innovations (NIDHI)
8.8.3 National Science, Technology, and Innovation Policy (STI) 2020
8.8.4 Council of Scientific and Industrial Research (CSIR)
8.8.5 Department of Science and Technology (DST)
References
9. Blockchain in Data Security and Transparency in Business Transactions
Rajat Verma and Namrata Dhanda
9.1 Introduction
9.2 Dimensions and Requirements of Data Security
9.3 Security Issues in Conventional Data Security
9.4 Diversity of Attacks in Conventional Data Security
9.5 Blockchain: The Complete Solution
9.6 The Decentralized and Immutable Approach
9.7 Comparison of ECC and RSA
9.8 Digital Signature Algorithm
9.9 Blockchain Technology Ensures Transparency
9.10 Blockchain Solutions for Traditional Data Security
9.11 Blockchain Types
9.12 Conclusion
References
10. A Comparative Study of Ad Hoc and Wireless Sensor Networks
Ankita Kumari and Ajita Pathak
10.1 Introduction
10.2 Ad Hoc Network
10.2.1 Ad Hoc Network Types
10.2.2 Ad Hoc Routing Protocol
10.2.3 Ad Hoc Security Attack
10.3 Wireless Sensor and Network
10.3.1 Types of Wireless Network
10.3.2 Mobility in WSN
10.3.3 Routing Protocol
10.4 Challenges, Applications, and Limitations
10.5 Conclusion
References
11. Content Filtering-Based Movie Recommendation System Using Deep Learning
Atul Srivastava and Abhi Raj Singh
11.1 Introduction
11.2 Related Work
11.2.1 “Collaborative Filtering for Movie Recommendations” by George Karypis et al. (2001)
11.2.2 “Item-Based Collaborative Filtering Recommendation Algorithms” by Badrul Sarwar et al. (2001)
11.2.3 “Netflix Prize” by Netflix (2006)
11.2.4 “Collaborative Filtering Recommender Systems” by Robin Burke (2007)
11.2.5 “Movie Recommendation Using Personal Preferences” by Alok Singh et al. (2012)
11.2.6 “A Comparative Study of Collaborative Filtering Algorithms for Movie Recommendation” by Gopal Krishna Shyam et al. (2015)
11.2.7 “Movie Recommendation System Using Collaborative Filtering Algorithm”
by Shashank Gupta et al. (2016)
11.2.8 “Movie Recommendation System Using K-Nearest Neighbors Algorithm” by L. Dhivya et al. (2017)
11.2.9 “Movie Recommendation System Based on User’s Personal Preferences” by Bhavesh Parikh et al. (2018)
11.2.10 “A Review of Movie Recommendation Systems” by Muhammad Usman et al. (2020)
11.3 Method and Material
11.4 Experiments and Results
11.4.1 Data Pre-Processing
11.4.2 Evaluation Metrics
11.4.3 Recommendation Generation
11.4.4 Results
11.4.5 Comparison with Previous Works
11.5 Possible Extension of Proposed Model into Distributed Environment
11.6 Conclusion
References
12. Mobile Edge Computing: A Paradigm Shift in Computing
Priti Kumari, Vandana Dubey, Parmeet Kaur and Sarika Shrivastava
12.1 Introduction
12.2 Why Is MEC Important?
12.3 Background
12.4 Characteristics
12.5 Reference Architecture
12.6 Mobile Edge Computing Key Enablers
12.7 Advantages of Mobile Edge Computing
12.8 Potential Research Directions
12.9 Challenges and Issues
12.10 Conclusion
References
13. Descriptive Analysis of the Potential of 5G Technologies in Empowering Decentralized Systems
Megha Agarwal, Shahnawaz Alam, Dewansh, Avni Singh and Snehil Singh
13.1 Introduction
13.1.1 Evolution of 5G Networks
13.1.2 Generations of 5G
13.1.3 Phases of 5G
13.2 Building 5G Network
13.3 Blockchain on 5G Networks
13.4 Real-World Impact of 5G
13.4.1 Impact on Business
13.4.1.1 Impact on Business After and Before 5G
13.4.2 Impact on Infrastructure
13.4.3 Impact on Humans as Well as on Nature by the 5G Network
13.4.3.1 Impact on Humans
13.4.3.2 Impact on Nature
13.5 Future of 5G
13.6 Limitations
References
14. Merging Blockchain and Deep Learning for Authentication and Security Architectures
Abhay Kumar Yadav and Satya Bhushan Verma
14.1 Introduction
14.1.1 Motivation and Structure
14.2 Merger of Blockchain and DL
14.2.1 Limitations of DL and Blockchain
14.2.1.1 Limited Utility of Blockchain Nodes
14.2.1.2 High Dependency on Energy
14.2.1.3 Providing Guarantee
14.2.1.4 Computational Scalability
14.2.1.5 Neural Networks
14.2.1.6 DL Classification Framework
14.3 Application of Blockchain-Based DL Models
14.3.1 Smart Contract-Based Security Analysis
14.3.2 Cybersecurity
14.3.3 Healthcare Sector
14.3.4 Cloud Storage
14.3.5 Banking and FinTech Segments
14.3.6 IoT in Data Analytics
14.3.7 Internet of Vehicles (IoV)
14.3.8 Law Enforcement and Associated Things
14.4 Study of Existing Integrated Models
14.4.1 Arrhythmia Classification
14.4.2 Blockchain-Based DL Model in IoT
14.4.3 Currency Supervision
14.4.4 Ovarian Cancer Detection
14.5 Challenges and Issues
14.6 Conclusion
References
15. 5G Embedded Decentralized Systems for Secure and Efficient Data Sharing
Asjad Suhail Akhtar, Garima Srivastava, Shikha Singh and Sachin Kumar
15.1 Overview of Decentralized Systems
15.1.1 Peer-to-Peer (P2P) Network
15.1.2 Distributed Databases
15.1.3 Blockchain
15.2 5G Technology
15.2.1 Key Futures of 5G Technology
15.2.2 5G Architecture
15.2.3 5G Advantages Over Previous Generations
15.3 5G for Decentralized Systems
15.3.1 Scalability
15.3.2 Security
15.3.3 Interoperability
15.3.4 Internet of Things (IoT)
15.3.5 Low Latency
15.3.6 Edge Computing
15.4 Use Cases and Applications
15.4.1 Current Use Case
15.4.2 Future Use Case
15.5 Challenges and Opportunities
15.6 Conclusion
References
16. Artificial Intelligence in a Distributed System of the Future
Kadambri Agarwal, Ojasw Khare, Aastha Sharma, Ayushi Prakash and Abhishek Kumar Shukla
16.1 Introduction
16.2 AI in the Industrial Sector
16.2.1 Applications
16.2.2 AI in the United States
16.2.3 AI in India
16.3 AI in the Economic Sector
16.3.1 Applications
16.4 Environment Sector
16.5 Robotics Skill
16.5.1 Applications
16.6 Interaction Between the Human and the Machine
16.6.1 Applications
16.7 Recent Projects in AI
16.8 Terminologies Regarding AI for the Next Generation
16.9 Real-Time Project and Future Implementation
16.10 Conclusion
References
17. The Metaverse and Mental Health: The Future
Vandana Yadav and Namrata Dhanda
17.1 Introduction
17.2 How Has Technology and the Internet Already Impacted Mental Health?
17.2.1 These Concerns May Be Exacerbated by the Metaverse
17.3 Importance of Researching the Metaverse’s Effects on Mental Health
17.4 Potential Positive Mental Health Effects of the Metaverse
17.4.1 Access to Virtual Mental Health Services
17.4.2 Reduction of Stigma Surrounding Health
17.4.3 Opportunities for Social Connection and Support
17.4.4 The Potential for Immersive Therapy
17.5 Possible Detrimental Effects of the Metaverse on Mental Health
17.5.1 Risk of Addiction and Compulsive Behavior
17.5.2 Impact on Physical Health
17.5.3 Concerns Regarding the Morality of Data Privacy and Mental Health Diagnoses
17.6 Considerations for Designing the Metaverse with Mental Health in Mind
17.7 The Future of Mental Health and Metaverse
17.7.1 Innovation and Advancement Opportunities in Mental Health Care
17.7.2 Challenges and Potential Pitfalls to Consider
17.7.3 The Influence of Interdisciplinarity on the Development of Mental Health and the Metaverse
17.8 Conclusion
References
18. Decentralization in Education Governance: A Case Study of India
Mani Dublish and Anita Pati Mishra
18.1 Introduction
18.2 Central Organizations
18.3 Decentralized Systems
18.3.1 Features of a Decentralized System
18.3.2 Architecture of a Decentralized System
18.4 Distributed Systems
18.4.1 Features of a Distributed System
18.4.2 The Architecture of a Distributed System
18.4.3 Limitations of a Distributed System
18.4.4 Difference Between a Centralized Database and a Distributed Database
18.5 Use of a Distributed Database in the Education System
18.5.1 Functions of a Distributed Database System
18.6 Decentralized Education and Contemporary Solution
18.6.1 Rebuilding Education through Decentralization
18.6.2 Education Scenario in India
18.6.3 Education Tools
18.7 Conclusion
References
Index
Back to Top
Preface
1. Introduction to Next-Generation Internet and Distributed Systems
Swapnil Gupta, Rajat Verma and Namrata Dhanda
1.1 Introduction
1.2 Traditional Network
1.3 Next-Generation Internet
1.3.1 Next-Generation Internet Protocol
1.3.1.1 IPv6
1.3.1.2 Tunneling
1.3.2 Quality of Service (QoS)
1.4 Network Middleware
1.5 Software-Defined Network (SDN)
1.5.1 Necessity of Software-Defined Network
1.6 Edge Cloud-Based Next-Generation Internet
1.6.1 Edge Cloud
1.6.2 Content Distribution Networks (CDNs)
1.7 Network Architecture
1.7.1 Some Proposed Architectures
1.7.1.1 Security Architecture for Networked Enterprises (SANE)
1.7.1.2 Swarming Architecture
1.7.1.3 Flexible Internet Architecture (FlexNGIA)
1.7.1.4 Architecture for Mobility Support
1.7.1.5 The Data-Oriented Network Architecture (DONA)
1.7.1.6 MILSA (Mobility and Multihoming Supporting Identifier‑Locator Split
Architecture)
1.7.1.7 Delay/Disruption Tolerant Networks (DTN) and Related Architectures
1.7.2 Challenges for Architecture
1.7.2.1 Network Services
1.7.2.2 Network Management
1.7.2.3 Network Performance
1.7.2.4 Diversity and Change
1.8 Security and Safety
1.9 Distributed Systems
1.9.1 Concept of Distributed System
1.9.2 Terminologies
1.9.2.1 Grouping of Autonomous Computer Components
1.9.2.2 Single Coherent System
1.10 Distributed System Design
1.10.1 Significance of a Certain Design
1.10.2 Scale and Scalability
1.10.2.1 Definition of Scale
1.10.2.2 Scalability Analysis
1.11 Distributed System Monitoring
1.11.1 Idea of Monitoring System
1.12 Security in Distributed Systems
1.12.1 Reasons for Not Using Encryption
1.12.2 Authorization
1.13 Blockchain and Distributed Systems
1.13.1 Decentralization
1.13.2 Peer-to-Peer Networks (P2P)
1.14 Blockchain-Based Distributed Control Systems
1.14.1 Control System
1.14.1.1 To Handle Complicated Processes
1.14.1.2 Pre-Defined Function Blocks
1.14.1.3 Scalable Platform
1.15 Blockchain for Distributed System Security
1.15.1 Fault-Tolerant Consensus in a Distributed System
1.15.2 Complications while Using Blockchain for Distributed Computing
1.16 Conclusion and Future Scope
References
2. Decentralized System in Education and Research
Prashant Verma, Deepaks M. Ratnani, Shikha Verma and Sandhya Avasthi
2.1 Introduction
2.2 History of Decentralization in the Education System
2.3 Advantages and Challenges of Decentralization of the Education System
2.3.1 Advantages
2.3.2 Challenges
2.4 Impact of Decentralization in Education and Research
2.5 Current Approaches
2.5.1 World Scenario
2.5.1.1 Finland Education System
2.5.1.2 Brazil, Federal Universities
2.5.1.3 The United States, National Science Foundation
2.5.1.4 Mexico, CONACYT
2.5.2 Indian Scenario
2.5.2.1 Kerala Model of Decentralization Implementation in Education and Research
2.6 Development Trend Towards Education and Research
2.7 Future Scope and Recommendations
2.8 Conclusion
References
3. Architecture of Blockchain-Enabled Decentralized Systems
Rohit Kumar, Sandhya Avasthi and Suman Lata Tripathi
3.1 Introduction
3.2 What is a Decentralized System?
3.2.1 Centralized System vs. Decentralized System
3.2.2 Merits and Demerits of a Decentralized System
3.3 Blockchain
3.3.1 What is Blockchain?
3.3.2 Structure of Blockchain
3.3.3 Requirements of Blockchain
3.3.4 Merits and Demerits of Blockchain
3.4 Smart Contracts and Its Examples
3.5 Blockchain-Enabled Decentralized System
3.5.1 Role of Blockchain
3.5.2 Types of Decentralization in Blockchain
3.5.3 Types of Blockchain Architecture
3.5.4 Requirements
3.5.5 Pros and Cons
3.6 Architecture for the Blockchain-Enabled Decentralized System
3.6.1 The Network
3.6.2 The Consensus Protocol
3.6.3 The Data Structure
3.7 Decentralized Todo App with Blockchain
3.8 Blockchain-Enabled Decentralized System Development and Challenges
3.9 Future of the Blockchain-Enabled Decentralized System
3.10 Conclusion
References
4. Mobile Edge Computing for Decentralized Systems
Swati Gupta and Puneet Garg
4.1 Introduction
4.2 Edge Computing
4.3 Benefits of Edge Computing
4.4 Classification of Attacks in a 5G IoT System
4.5 Decentralized Dynamic Computation Offloading Method
4.6 Conclusion
References
5. Blockchain in Education
Shahnaz Fatima and Guru Dev Singh
5.1 Introduction
5.2 Benefits of Blockchain in Education
5.2.1 Blockchain Can Enhance Learner Data Privacy and Security, Allowing Learners to Maintain Control over Their Personal Information
5.2.2 Blockchain Can Enable Lifelong Learning Tracking, Creating a Comprehensive and Immutable Record of a Learner’s Achievements and Skills
5.2.2.1 Blockchain as a Distributed and Immutable Record-Keeping System
5.2.2.2 Benefits of Blockchain-Enabled Lifelong Learning Tracking
5.3 Challenges of Blockchain in Education
5.3.1 Concerns Related to Data Privacy, Security, and Compliance with Data Protection Regulations
5.3.1.1 Data Privacy Concern
5.3.1.2 Compliance with Data Protection Regulations
5.3.1.3 Security Concerns
5.3.1.4 Collaboration with Industry Experts and Auditors
5.3.2 Potential Resistance to Change and Adoption Barriers in the Education Sector
5.4 Use Cases of Blockchain in Education
5.5 Conclusion
References
6. Pattern Recognition Applications in Distributed Systems and Distributed Machine Learning
Kalyani S., Swarup K. S., Sandhya Avasthi and Tanushree Sanwal
6.1 Introduction
6.1.1 What is Pattern Recognition?
6.1.2 Distributed Computing Environment
6.1.3 Basic Model of the Pattern Recognition System
6.2 Data Generation and Preprocessing
6.3 Feature Selection
6.3.1 What is Feature Selection?
6.3.2 Filter Models of Feature Selection
6.3.3 Wrapper Models of Feature Selection
6.4 Design of Classifier
6.4.1 Conventional Classifiers in Distributed Environment
6.4.2 Neural Network Classifiers in a Distributed Environment
6.5 Designing Machine Learning Models for Distributed Environment
6.6 Role of Distributed Computing in Pattern Recognition
6.7 Conclusion
References
7. Next-Generation Distributed Computing for Cancer Detection
Kapil Kumar Gupta, Namrata Dhanda and Neeraj Kumar
7.1 Introduction
7.2 Research Motivation
7.3 Cancer Statistics
7.4 Modern Cancer Diagnosis and Treatment Methods
7.5 Methodology
7.6 Technical Challenges
7.7 Future Directions
7.8 Conclusion
References
8. Benefits and Challenges of Decentralization in Education for Resource Optimization and Improved Performance
Ankita Singh, Shobhit Sinha, Satya Bhushan Verma
and Bipin Kumar Singh
8.1 Introduction
8.1.1 Decentralized Systems in Education and Research
8.1.2 Connect Between Democracy and Education
8.2 The Centralization and Decentralization Concepts
8.3 Decentralized Systems in Education and Research: Policies and Practices
8.3.1 Open Educational Resources (OER) Policy
8.3.2 Collaborative Research Networks
8.3.3 Self-Directed Learning
8.3.4 Peer Review
8.3.5 Open Data
8.3.6 Equity and Inclusion
8.3.7 Quality Assurance
8.4 Building Capacity Across and Between Levels Within Education Systems
8.5 Developing Accountability Measures and Systems in Implementing a Decentralized Education Policy
8.5.1 Establish Clear and Quantifiable Policy Objectives
8.5.2 Create Performance Indicators and Benchmarks
8.5.3 Assign Roles and Responsibilities
8.5.4 Build Effective Monitoring and Evaluation Systems
8.5.5 Encourage Transparency and Involvement
8.5.6 Establish Redressal Mechanisms
8.6 Developing Local-Level Capacity Across All Education System Levels and Sectors
8.7 Education Policies in India to Achieve Decentralization in Education Systems
8.7.1 National Education Policy (NEP) 2020
8.7.2 Rashtriya Madhyamik Shiksha Abhiyan (RMSA)
8.7.3 RUSA (Rashtriya Uchchatar Shiksha Abhiyan)
8.8 Research and Development Policies in India and Promoting Decentralization in R&D
8.8.1 Atal Innovation Mission (AIM)
8.8.2 The National Initiative for Developing and Harnessing Innovations (NIDHI)
8.8.3 National Science, Technology, and Innovation Policy (STI) 2020
8.8.4 Council of Scientific and Industrial Research (CSIR)
8.8.5 Department of Science and Technology (DST)
References
9. Blockchain in Data Security and Transparency in Business Transactions
Rajat Verma and Namrata Dhanda
9.1 Introduction
9.2 Dimensions and Requirements of Data Security
9.3 Security Issues in Conventional Data Security
9.4 Diversity of Attacks in Conventional Data Security
9.5 Blockchain: The Complete Solution
9.6 The Decentralized and Immutable Approach
9.7 Comparison of ECC and RSA
9.8 Digital Signature Algorithm
9.9 Blockchain Technology Ensures Transparency
9.10 Blockchain Solutions for Traditional Data Security
9.11 Blockchain Types
9.12 Conclusion
References
10. A Comparative Study of Ad Hoc and Wireless Sensor Networks
Ankita Kumari and Ajita Pathak
10.1 Introduction
10.2 Ad Hoc Network
10.2.1 Ad Hoc Network Types
10.2.2 Ad Hoc Routing Protocol
10.2.3 Ad Hoc Security Attack
10.3 Wireless Sensor and Network
10.3.1 Types of Wireless Network
10.3.2 Mobility in WSN
10.3.3 Routing Protocol
10.4 Challenges, Applications, and Limitations
10.5 Conclusion
References
11. Content Filtering-Based Movie Recommendation System Using Deep Learning
Atul Srivastava and Abhi Raj Singh
11.1 Introduction
11.2 Related Work
11.2.1 “Collaborative Filtering for Movie Recommendations” by George Karypis et al. (2001)
11.2.2 “Item-Based Collaborative Filtering Recommendation Algorithms” by Badrul Sarwar et al. (2001)
11.2.3 “Netflix Prize” by Netflix (2006)
11.2.4 “Collaborative Filtering Recommender Systems” by Robin Burke (2007)
11.2.5 “Movie Recommendation Using Personal Preferences” by Alok Singh et al. (2012)
11.2.6 “A Comparative Study of Collaborative Filtering Algorithms for Movie Recommendation” by Gopal Krishna Shyam et al. (2015)
11.2.7 “Movie Recommendation System Using Collaborative Filtering Algorithm”
by Shashank Gupta et al. (2016)
11.2.8 “Movie Recommendation System Using K-Nearest Neighbors Algorithm” by L. Dhivya et al. (2017)
11.2.9 “Movie Recommendation System Based on User’s Personal Preferences” by Bhavesh Parikh et al. (2018)
11.2.10 “A Review of Movie Recommendation Systems” by Muhammad Usman et al. (2020)
11.3 Method and Material
11.4 Experiments and Results
11.4.1 Data Pre-Processing
11.4.2 Evaluation Metrics
11.4.3 Recommendation Generation
11.4.4 Results
11.4.5 Comparison with Previous Works
11.5 Possible Extension of Proposed Model into Distributed Environment
11.6 Conclusion
References
12. Mobile Edge Computing: A Paradigm Shift in Computing
Priti Kumari, Vandana Dubey, Parmeet Kaur and Sarika Shrivastava
12.1 Introduction
12.2 Why Is MEC Important?
12.3 Background
12.4 Characteristics
12.5 Reference Architecture
12.6 Mobile Edge Computing Key Enablers
12.7 Advantages of Mobile Edge Computing
12.8 Potential Research Directions
12.9 Challenges and Issues
12.10 Conclusion
References
13. Descriptive Analysis of the Potential of 5G Technologies in Empowering Decentralized Systems
Megha Agarwal, Shahnawaz Alam, Dewansh, Avni Singh and Snehil Singh
13.1 Introduction
13.1.1 Evolution of 5G Networks
13.1.2 Generations of 5G
13.1.3 Phases of 5G
13.2 Building 5G Network
13.3 Blockchain on 5G Networks
13.4 Real-World Impact of 5G
13.4.1 Impact on Business
13.4.1.1 Impact on Business After and Before 5G
13.4.2 Impact on Infrastructure
13.4.3 Impact on Humans as Well as on Nature by the 5G Network
13.4.3.1 Impact on Humans
13.4.3.2 Impact on Nature
13.5 Future of 5G
13.6 Limitations
References
14. Merging Blockchain and Deep Learning for Authentication and Security Architectures
Abhay Kumar Yadav and Satya Bhushan Verma
14.1 Introduction
14.1.1 Motivation and Structure
14.2 Merger of Blockchain and DL
14.2.1 Limitations of DL and Blockchain
14.2.1.1 Limited Utility of Blockchain Nodes
14.2.1.2 High Dependency on Energy
14.2.1.3 Providing Guarantee
14.2.1.4 Computational Scalability
14.2.1.5 Neural Networks
14.2.1.6 DL Classification Framework
14.3 Application of Blockchain-Based DL Models
14.3.1 Smart Contract-Based Security Analysis
14.3.2 Cybersecurity
14.3.3 Healthcare Sector
14.3.4 Cloud Storage
14.3.5 Banking and FinTech Segments
14.3.6 IoT in Data Analytics
14.3.7 Internet of Vehicles (IoV)
14.3.8 Law Enforcement and Associated Things
14.4 Study of Existing Integrated Models
14.4.1 Arrhythmia Classification
14.4.2 Blockchain-Based DL Model in IoT
14.4.3 Currency Supervision
14.4.4 Ovarian Cancer Detection
14.5 Challenges and Issues
14.6 Conclusion
References
15. 5G Embedded Decentralized Systems for Secure and Efficient Data Sharing
Asjad Suhail Akhtar, Garima Srivastava, Shikha Singh and Sachin Kumar
15.1 Overview of Decentralized Systems
15.1.1 Peer-to-Peer (P2P) Network
15.1.2 Distributed Databases
15.1.3 Blockchain
15.2 5G Technology
15.2.1 Key Futures of 5G Technology
15.2.2 5G Architecture
15.2.3 5G Advantages Over Previous Generations
15.3 5G for Decentralized Systems
15.3.1 Scalability
15.3.2 Security
15.3.3 Interoperability
15.3.4 Internet of Things (IoT)
15.3.5 Low Latency
15.3.6 Edge Computing
15.4 Use Cases and Applications
15.4.1 Current Use Case
15.4.2 Future Use Case
15.5 Challenges and Opportunities
15.6 Conclusion
References
16. Artificial Intelligence in a Distributed System of the Future
Kadambri Agarwal, Ojasw Khare, Aastha Sharma, Ayushi Prakash and Abhishek Kumar Shukla
16.1 Introduction
16.2 AI in the Industrial Sector
16.2.1 Applications
16.2.2 AI in the United States
16.2.3 AI in India
16.3 AI in the Economic Sector
16.3.1 Applications
16.4 Environment Sector
16.5 Robotics Skill
16.5.1 Applications
16.6 Interaction Between the Human and the Machine
16.6.1 Applications
16.7 Recent Projects in AI
16.8 Terminologies Regarding AI for the Next Generation
16.9 Real-Time Project and Future Implementation
16.10 Conclusion
References
17. The Metaverse and Mental Health: The Future
Vandana Yadav and Namrata Dhanda
17.1 Introduction
17.2 How Has Technology and the Internet Already Impacted Mental Health?
17.2.1 These Concerns May Be Exacerbated by the Metaverse
17.3 Importance of Researching the Metaverse’s Effects on Mental Health
17.4 Potential Positive Mental Health Effects of the Metaverse
17.4.1 Access to Virtual Mental Health Services
17.4.2 Reduction of Stigma Surrounding Health
17.4.3 Opportunities for Social Connection and Support
17.4.4 The Potential for Immersive Therapy
17.5 Possible Detrimental Effects of the Metaverse on Mental Health
17.5.1 Risk of Addiction and Compulsive Behavior
17.5.2 Impact on Physical Health
17.5.3 Concerns Regarding the Morality of Data Privacy and Mental Health Diagnoses
17.6 Considerations for Designing the Metaverse with Mental Health in Mind
17.7 The Future of Mental Health and Metaverse
17.7.1 Innovation and Advancement Opportunities in Mental Health Care
17.7.2 Challenges and Potential Pitfalls to Consider
17.7.3 The Influence of Interdisciplinarity on the Development of Mental Health and the Metaverse
17.8 Conclusion
References
18. Decentralization in Education Governance: A Case Study of India
Mani Dublish and Anita Pati Mishra
18.1 Introduction
18.2 Central Organizations
18.3 Decentralized Systems
18.3.1 Features of a Decentralized System
18.3.2 Architecture of a Decentralized System
18.4 Distributed Systems
18.4.1 Features of a Distributed System
18.4.2 The Architecture of a Distributed System
18.4.3 Limitations of a Distributed System
18.4.4 Difference Between a Centralized Database and a Distributed Database
18.5 Use of a Distributed Database in the Education System
18.5.1 Functions of a Distributed Database System
18.6 Decentralized Education and Contemporary Solution
18.6.1 Rebuilding Education through Decentralization
18.6.2 Education Scenario in India
18.6.3 Education Tools
18.7 Conclusion
References
Index
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