Preface: Background and Overview
Chapter 1 ▪ The Development of Big Data
1.2 The Past and Present of Big Data
1.3 Technical Support of Big Data
1.3.1 Storage Device Capacity Is Increasing
1.3.2 Increasing Network Bandwidth
1.3.3 CPU Processing Capacity Increased Significantly
1.3.4 The Deepening of Machine Learning
1.4.1 Big Data Decision-Making Has Become a New Decision-Making Method
1.4.3 Big Data Development Promotes the Continuous Emergence of New Technologies and Applications
1.4.4 Big Data as a Strategic Resource
1.5 Key Technologies of Big Data
1.5.1 Big Data Acquisition Technology
1.5.2 Big Data Preprocessing Technology
1.5.3 Big Data Storage and Management Technology
1.5.4 Big Data Analysis and Mining Technology
1.5.5 Big Data Presentation Technology
Chapter 2 ▪ Blockchain Technology
2.1 Digital Currency and Bitcoin
2.2.2 Characteristics of Blockchain
2.2.2.2 Uniqueness Required to Express Value
2.2.2.4 Decentralised Self-Organisation
2.2.3 Classification of Blockchain
2.2.3.1 Public Blockchain: Everyone can Participate
2.2.3.2 Consortium Blockchain: Only Consortium Members can Participate
2.2.3.3 Private Blockchain: Only for Individuals or Companies
2.4 The Evolution of Blockchain Technology
2.4.1 The First Year of Blockchain History
Chapter 3 ▪ Evolution of Two Technologies
3.1 Development Trend of Big Data Technology
3.2 Key Technologies of Big Data
3.3 Development of Blockchain Technology
3.4 Taxonomy of Blockchain Systems
3.5 Scalability of Blockchain Technology
3.5.3 Off-Chain Payment Network
3.5.4.2 Side Chain/Relay Technology
3.5.4.4 Distributed Private Key Control Technology
3.6 Similarities between Big Data and Blockchain Technology
3.7 Differences between Big Data and Blockchain Technologies
Chapter 4 ▪ Convergence of Blockchain and Big Data
4.1 The Commercial Value of Blockchain
4.1.2 Smart Assets for the Society
4.1.4 Optimise the Social Structure
4.2 What Changes Can Blockchain Bring?
4.2.2 Credibility and Transparency
4.2.5 Protection of Data Sovereignty
4.3 Blockchain Technology Reconstructs Big Data Industry
4.3.1 Circulation Environment for Trusted Data Asset
4.4 Challenges in the Convergence of Blockchain and Big Data
4.4.2 Difficulty in Accurate Analysis
Chapter 5 ▪ Applications of Blockchain Technology
5.1 Changes in the Financial Industry
5.2.1 Documentation and Traceability of Sensor Data
5.2.2 Smart Meter-Based Energy Trading
5.2.3 Safe Communication and Group Intelligence for Drones
5.3.2 Drug Anti-Counterfeit Traceability
5.5 Management and Trading of Digital Assets
5.6 Application in Smart City Roadside Parking
5.7 Application in Traceability of Chinese Herbs
5.8.2 Specific Design of Blockchain
5.8.2.1 Double-Layer Blockchain Structure
5.8.2.2 Consensus Mechanism for Multi-Node Cooperate
5.8.2.3 Cutting Mechanism Based on Timestamp and Information Interaction
5.8.3 Specific Design of the System
5.8.3.1 Specific Process of vGuard
5.9 GeoAI-based Epidemic Control with Geo-Social Data Sharing on Blockchain
5.9.2.3 Data Analysis by GeoAI
5.9.3 The System Based on WeChat-GeoAI on the Blockchain
5.9.3.1 Proposed System and the Flow Chart
5.9.3.2 Initialisation and Registration Phase
5.9.3.3 To Initiate a Transaction Application for Confirmation of Suspected Patients
5.9.3.4 Distribution of Infectious Diseases under the GeoAI System
5.10.2 Blockchain File Storage and Sharing Advantages
5.10.3 Blockchain File Storage and Sharing System Solutions
5.10.4 Blockchain Distributed File Storage and Sharing System Case
6.1 Landing in Sharing Economy
6.1.1 Reduce Platform Operating Costs with Decentralised Architecture
6.1.2 Reduce Single Point of Failure through Distributed Storage Mechanisms
6.1.3 Rely on Asymmetric Encryption Algorithm to Protect Users’ Private Data
6.1.4 Use of Data-Storage Sharing Mechanisms to Increase Reuse of Information
6.1.5 Using Offline Digital Currency to Shorten the Length of the Money Transmission Chain
6.2 Combining with Cloud Computing
6.3 Expanding the Value of Artificial Intelligence
6.3.1 Intelligent Computing Power
6.3.2 Creating Diverse Data Sets
6.3.5 Trust in Artificial Intelligence Decision Making