This book focuses on conducting a comprehensive analysis of blockchain scalability serving large-scale application scenarios, from the “what, why, how” three perspectives, layer by layer. Gathering the latest state-of-the-art research advances in the area of key issues and technologies for blockchain scalability, it also presents some special and exciting insights on the existing and future blockchain scalability.
Despite blockchain’s merits of decentralization, immutability, non-repudiation, and traceability, the current blockchain has faced a serious scalability bottleneck. The scalability bottleneck problem is mainly manifested in two aspects: low-performance efficiency and difficulty in functional extension. First, the security and reliability of the blockchain system come from the fact that most nodes of the whole network participate in a distributed consensus to maintain the ledger. The high-cost consensus mechanism makes limited performance of blockchain, and there is a big gap between the actual large-scale application system. In addition, in order to ensure the security of a single blockchain system, data between different blockchain systems are relatively isolated, making it difficult for assets and data to interact.
This book explores the scalability of blockchain in depth, proposes meaningful approaches to the problems mentioned above, and builds an original theoretical system of blockchain scalability. It describes the root of blockchain scalability problems, mainstream blockchain performance, the classification of existing scalability problem solutions, and some exciting sharding-based approaches. It also includes open issues and future directions to scale blockchain for complex practical application scenarios. As such, this book will be a valuable resource for students, researchers, engineers, and policymakers working in various areas related to blockchain scalability, which is also of great significance for understanding and solving the bottleneck of blockchain scalability and realizing the practical large-scale commercial application of blockchain.
Author(s): Zibin Zheng, Wuhui Chen, Huawei Huang
Publisher: Springer
Year: 2023
Language: English
Pages: 242
City: Singapore
Preface
Acknowledgments
Contents
1 Blockchain Scalability Fundamentals
1.1 Overview
1.2 Preliminaries of Blockchains
1.2.1 Prime Blockchain Platforms
1.2.1.1 Bitcoin
1.2.1.2 Ethereum
1.2.1.3 Hyperledger Fabric
1.2.1.4 EOSIO
1.2.2 Consensus Mechanism
1.2.3 Scalability of Blockchains
1.2.3.1 Off-Chain Techniques
1.2.3.2 DAG
1.2.3.3 Sharding Technique
1.2.3.4 Cross-Shard Transactions
1.3 Theories to Improving the Performance of Blockchains
1.3.1 Latest Theories to Improving Blockchain Performance
1.3.1.1 Throughput and Latency
1.3.1.2 Storage Efficiency
1.3.1.3 Reliability of Blockchains
1.3.2 Scalability-Improving Solutions
1.3.2.1 Solutions to Sharding Blockchains
1.3.2.2 Multiple-Chain and Cross-Chain: Interoperability Amongst Multiple Blockchains
1.3.3 New Protocols and Infrastructures
1.3.3.1 New Protocols for Blockchains
1.3.3.2 New Infrastructures and Architectures for Blockchains
1.4 Various Modelings and Techniques for Better Understanding Blockchains
1.4.1 Graph-Based Theories
1.4.2 Stochastic Modelings
1.4.3 Queueing Theories for Blockchain Systems
1.4.4 Analytical Models for Blockchain Networks
1.4.5 Data Analytics for Cryptocurrency Blockchains
1.4.5.1 Market Risks Detection
1.4.5.2 Ponzi Schemes Detection
1.4.5.3 Money-Laundering Detection
1.4.5.4 Portrait of Cryptoeconomic Systems
1.5 Useful Measurements, Datasets and Experiment Tools for Blockchains
1.5.1 Performance Measurements and Datasets for Blockchains
1.5.2 Useful Evaluation Tools for Blockchains
1.6 Open Issues and Future Directions
1.6.1 Performance-Improving Issues
1.6.1.1 Scalability Issues
1.6.1.2 Resilient Mechanisms for Sharding Technique
1.6.1.3 Cross-Shard Performance
1.6.1.4 Cross-Chain Transaction Accelerating Mechanisms
1.6.1.5 Ordering Blocks for Multiple-Chain Protocols
1.6.1.6 Hardware-Assisted Accelerating Solutions for Blockchain Networks
1.6.1.7 Performance Optimization in Different Blockchain Network Layers
1.6.1.8 Blockchain-Assisted BigData Networks
1.6.2 Issues for Better Understanding Blockchains Further
1.6.3 Security Issues of Blockchains
1.6.3.1 Privacy-Preserving for Blockchains
1.6.3.2 Anti-cryptojacking Mechanisms for Malicious Miners
1.6.3.3 Security Issues of Cryptocurrency Blockchains
1.6.4 Powerful Experimental Platforms for Blockchains
1.7 Conclusion
References
2 Overview to Blockchain Scalability Challenges and Solutions
2.1 Overview
2.2 Scalability Issue of Blockchain
2.3 Taxonomy of the Approaches to Solving the Scalability of Blockchain
2.3.1 Layer1: On-Chain Solutions
2.3.1.1 Solutions Related to Block Data
2.3.1.2 Different Consensus Strategies
2.3.1.3 Sharding
2.3.1.4 DAG (Directed Acyclic Graph)
2.3.2 Layer2: Non On-Chain Solutions
2.3.2.1 Payment Channel
2.3.2.2 Sidechain
2.3.2.3 Off-Chain Computation
2.3.2.4 Cross-Chain Techniques
2.4 Future Directions and Open Issues
2.4.1 Layer-1
2.4.1.1 Block Data
2.4.1.2 Sharding Techniques
2.4.2 Layer-2
2.4.3 Layer-0
2.5 Conclusion
References
3 On-Chain and Off-Chain Scalability Techniques
3.1 Overview
3.2 Related Work
3.3 Two-Layer Scaling Sharing Framework Based on Large-Scale Wireless Networks
3.3.1 Framework Overview
3.3.2 Two-Layer Scaling Protocol
3.3.3 Automated Sharing Transaction Workflows
3.3.4 Advantages of Framework
3.3.4.1 Real-Time
3.3.4.2 Trusted Data Interaction
3.3.4.3 Fine-Grained Transaction Support
3.4 Case Study: ITS-Data-Sharing Economy
3.4.1 Proof of Concept Implementation
3.4.2 Performance Evaluation
3.5 Conclusion and Open Issues
References
4 Layered Sharding on Open Blockchain
4.1 Overview
4.2 System and Threat Model
4.2.1 System Model
4.2.2 Threat Model
4.3 System Design
4.3.1 Layered Sharding Formation
4.3.2 Cross-Shard Block Design
4.3.3 Layered Sharding Consensus
4.3.4 Design Refinements
4.4 Analysis
4.4.1 Security Analysis
4.4.2 Scalability Analysis
4.4.3 Performance Analysis
4.5 Evaluation
4.5.1 Implementation
4.5.2 Setup
4.5.3 Throughput
4.5.4 Confirmation Latency
4.5.5 Storage Overhead
4.5.6 Commit Ratio
4.6 Discussion
4.6.1 Comparison with Shard Overlapping in Complete Sharding
4.6.2 Heterogeneous Blockchain Node
4.6.3 Multi-Step Transactions
4.7 Conclusion
References
5 Sharding-Based Scalable Consortium Blockchain
5.1 Overview
5.2 System Model
5.2.1 Challenges (Goals)
5.2.2 Our Solution
5.3 Detailed Cross-Shard Solutions
5.3.1 Cross-Epoch and Cross-Call
5.3.2 Partial Cross-Call Merging Strategy
5.3.3 Replay-Epoch
5.3.4 Shadow Shard Based Recovery
5.4 Implementation and Evaluation
5.4.1 RQ1: Cross-Shard Efficiency
5.4.2 RQ2: Multi-State Dependency
5.4.3 RQ3: Consumption of Transaction Atomicity
5.4.4 RQ4: System Availability
5.5 Conclusion
References
6 State Sharding for Permissioned Blockchain
6.1 Overview
6.2 System Overview
6.3 Distributed Blockchain Transaction Structure
6.3.1 Shard Flag and Stage Flag
6.3.2 JUMP Operation
6.3.3 Atomicity
6.4 Distributed State Update Sharding
6.4.1 Sharding Strategy
6.4.2 Round-Based Distributed State Update
6.5 Evaluation
6.5.1 Implementation
6.5.2 Experimental Setup and Workloads
6.5.3 RQ1: Bottleneck of Current Blockchain
6.5.4 RQ2: Scalability of Aeolus
6.5.5 RQ3: Comparison with Other Systems
6.5.6 RQ4: Impact of Workload
6.6 Related Work
6.7 Discussion
6.8 Conclusion and Future Work
References
7 Elastic Resource Allocation in Sharding-Based Blockchains
7.1 Overview
7.2 Related Work
7.3 System Model and Problem Formulation
7.3.1 Sharding-Based Permissioned Blockchain
7.3.2 Blockchain Shards
7.3.3 Arrived Transactions in Each Network Shard
7.3.4 Threat Model of Bursty-TX Injection Attack
7.3.5 Problem Formulation
7.4 Dynamic Resource-Allocation Algorithm
7.4.1 Algorithm Design
7.4.2 Algorithm Analysis
7.4.2.1 Upper Bound of System Objective
7.4.2.2 Upper Bound of the Queue Length of Shards
7.5 Performance Evaluation
7.5.1 Basic Settings for Numerical Simulation
7.5.2 Metrics
7.5.3 Baselines
7.5.4 Performance Analysis
7.5.4.1 Effect of Tuning Parameter V
7.5.4.2 Performance Comparison with Baselines
7.5.4.3 Continued Bursty-TX Injection Attacks Against All Shards
7.5.4.4 Drastic Bursty-TX Injection Attack Against A Single Shard
7.6 Conclusion
References
8 Dynamic Sharding: A Trade-OFF Between Securityand Scalability
8.1 Overview
8.2 System Overview
8.2.1 System Model
8.2.2 Threat Model
8.2.3 DRL-Based Sharding Model
8.3 Adaptive Ledger Protocol
8.3.1 State Block
8.3.2 Ledgers Merging and Splitting
8.3.3 Shards Formation
8.4 Blockchain Sharding System Analysis
8.4.1 Definitions of Blockchain Sharding System
8.4.2 Performance Analysis
8.4.3 Security Analysis
8.4.4 Problem Formulation
8.5 DRL-Based Dynamic Sharding Framework
8.5.1 DRL Model Design
8.5.2 DRL Training Methodology
8.5.3 DRL Deployment Methodology
8.6 Evaluation
8.6.1 Convergence Analysis
8.6.2 Security and Latency Performance
8.6.3 Throughput Comparison with the Baselines
8.7 Conclusion
References
9 A Scalable and Secure Framework for 5G Networks Applications
9.1 Overview
9.2 Preliminaries of Distributed Machine Learning in 5G Networks
9.2.1 Consensus Protocols for Decentralized Learning in 5G
9.2.2 Configurations of Distributed Machine Learning
9.3 State-of-the-Art Studies of Byzantine-Resilient Machine Learning
9.3.1 Byzantine-Resilient Machine Learning
9.3.2 Byzantine Protection on Gradients
9.3.3 Risks of Decentralization
9.4 Our Proposal—PIRATE: A Machine Learning Framework Based on Sharding Technique
9.4.1 Overview of PIRATE
9.4.2 Permission Control
9.4.3 Sharding-Based Blockchain Protection Towards Decentralized Distributed-Learning
9.4.4 Intra-Committee Consensus
9.4.5 Committee-Wise Ring Allreduce
9.4.6 Security and Complexity Analysis
9.4.6.1 Security Analysis of Convergence Attack
9.4.6.2 Security Analysis of Take-Over Attack
9.4.6.3 Computation Overhead
9.4.7 Applications
9.4.7.1 Decentralized Federated Learning
9.4.7.2 Big Data Analysis for Consortium Blockchains
9.5 Case Study
9.5.1 Security
9.5.2 Performance Evaluation
9.6 Open Issues
9.7 Conclusion and Future Work
References
