Distributed Computing to Blockchain : Architecture, Technology, and Applications

Distributed Computing to Blockchain: Architecture, Technology, and Applications provides researchers, computer scientists and data scientists with a comprehensive and applied reference covering the evolution of distributed systems computing into blockchain and associated systems such as consensus algorithms, distributed ledgers, DApps, byzantine fault tolerance, distributed databases and operating systems. Sections cover key concepts and technologies such as distributed systems and their architecture, distributed ledger and decentralized web, application and properties of crypto economics, blockchain crypto-analysis for distributed systems followed by DApps architecture. Other sections cover blockchain architecture and security, including smart contracts, tokens, and more.

The authors then review byzantine fault tolerance (BFT), distributed ledgers vs. blockchains, and blockchain protocols. The security issues of blockchain and how it aims to resolve trust problems is also covered, along with consensus algorithms used in blockchain. Throughout the book, the presentation of key concepts is supported by real-world tools, algorithms, programming languages and technology to support the implementation of distributed ledger and blockchain in a variety of fields, including healthcare, finance, legal and business applications.

• Provides readers with in-depth understanding of how to develop blockchain systems, architecture and applications in a variety of fields
• Includes the most complete platform for understanding the computer science and data science behind blockchain and related technologies such as distributed systems, distributed ledgers, consensus algorithms, DApps, distributed ledgers, decentralized web, and more
• Presents techniques for efficient and secure development of blockchains in a variety of domains such as healthcare, finance, legal and business applications
• Provides readers with complete example datasets associated with the methods and algorithms developed in the book

Dr. Rajiv Pandey is a Faculty member at Amity Institute of Information Technology, Amity University, Uttar Pradesh, Lucknow Campus, India. He possesses a diverse background experience of around 35 years to include 15 years in industry and 20 years of academic research and instruction. His research interests include blockchain and crypto currencies, information security, semantic web provenance, Cloud computing, Big Data, and Data Analytics. Dr. Pandey is a Senior Member of IEEE and has been a session chair and technical committee member for various IEEE conferences. He has been on the technical committees of various government and private universities, and is the editor of Quantum Computing: A Shift from Bits to Qubits from Springer, Data Modelling and Analytics for the Internet of Medical Things from CRC Press/Taylor & Francis, and Artificial Intelligence and Machine Learning for Edge Computing from AP/Elsevier.

Dr Sam Goundar is an established author, editor, and researcher in artificial intelligence, cyber security, data science, blockchain, digital transformation, and emerging technologies. He has written or edited numerous books on AI, digital innovation, and intelligent systems with leading publishers, reflecting a long-standing focus on the societal and technical dimensions of AI. He has a strong publication record in AI-related domains, including research on explainability, AI-enabled decision making, AI governance, intrusion detection, and applied machine learning. These publications show a sustained and credible research trajectory that directly aligns with the topics covered in this book. Dr. Goundar has published more than 150 peer-reviewed journal articles and book chapters, in addition to more than 20 authored and edited books. He also serves as Editor-in-Chief of multiple international journals and has overseen the review, curation, and publication of research in AI, ethics, digital systems, and technology policy. This long editorial experience ensures high standards of structure, clarity, and coherence across multi-author volumes. Dr. Goundar has taught artificial intelligence, machine learning, and digital ethics at universities across Asia, the Pacific, and Central Asia. His teaching integrates theory with real-world applications, giving him a practical understanding of how AI systems influence learning, governance, public administration, and daily life. This hands-on experience allows him to approach AI not only as a researcher but also as a practitioner who has seen the challenges of AI adoption in different cultural and institutional environments. His international collaborations with research networks, policy groups, and technology-focused organisations further strengthen his authority in areas such as AI governance, responsible innovation, cyber security, and digital transformation.

Dr. Shahnaz Fatima is a Faculty member in the Institute of Information Technology at Amity University, Lucknow, India. Her research interests are Human Computer Interaction, Data Mining, Deep Mining, Semantic Web, Edge Computing, and IoT. She is involved in supervising Doctorate Research Scholars and Post Graduate Students in the Institute of Information Technology. She is a member of the International Association of Computer Science and Information Technology (IACSIT).