scholarly journals Improved Byzantine Fault-Tolerant Algorithm Based on Alliance Chain

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Wuqi Gao ◽  
Wubing Mu ◽  
Shanshan Huang ◽  
Man Wang ◽  
Xiaoyan Li
Keyword(s):  
Fault Tolerance ◽  
Fault Tolerant ◽  
Feedback Mechanism ◽  
Consensus Algorithm ◽  
Byzantine Fault Tolerance ◽  
Advantages And Disadvantages ◽  
Byzantine Fault ◽  
Credit Mechanism ◽  
Low Efficiency ◽  
System Nodes

Alliance chain is a typical multicenter block chain and is easily implemented, so it is supported by more and more enterprises and governments. This paper analyzes the advantages and disadvantages of the Practical Byzantine Fault Tolerance (PBFT) in the alliance chain application scene. Aiming at the low efficiency of multinode consensus of the PBFT algorithm, the C-Raft-PBFT consensus algorithm is proposed. By integrating the Raft algorithm and the PBFT algorithm with the credit mechanism, designing node credit evaluation and grading protocols, and increasing Byzantine node detection based on feedback mechanism and other methods, the system efficiency is improved. The experiment results show that the improved algorithm has better throughput and lower delay, and the system’s fault tolerance is also improved. Among them, the delay is reduced by 1.93 seconds on average; in the case of an increase in system nodes, the number of nodes in the experimental data is between 200 and 225, and the throughput is increased by 6.46% on average.

scholarly journals A Coordination Technique for Improving Scalability of Byzantine Fault-Tolerant Consensus

2020 ◽  
Vol 10 (21) ◽  
pp. 7609
Author(s):  
Jungwon Seo ◽  
Deokyoon Ko ◽  
Suntae Kim ◽  
Sooyong Park
Keyword(s):  
Fault Tolerance ◽  
Performance Improvement ◽  
Fault Tolerant ◽  
The Other ◽  
Consensus Algorithm ◽  
Byzantine Fault Tolerance ◽  
Consensus Process ◽  
Consensus Algorithms ◽  
Byzantine Fault ◽  
Research Questions

Among various consensus algorithms, the Byzantine Fault Tolerance (BFT)-based consensus algorithms are broadly used for private blockchain. However, as BFT-based consensus algorithms are structured for all participants to take part in a consensus process, a scalability issue becomes more noticeable. In this approach, we introduce a consensus coordinator to execute a conditionally BFT-based consensus algorithm by classifying transactions. Transactions are divided into equal and unequal transactions. Moreover, unequal transactions are divided again and classified as common and trouble transactions. After that, a consensus algorithm is only executed for trouble transactions, and BFT-based consensus algorithms can achieve scalability. For evaluating our approach, we carried out three experiments in response to three research questions. By applying our approach to PBFT, we obtained 4.75 times better performance than using only PBFT. In the other experiment, we applied our approach to IBFT of Hyperledger Besu, and our result shows a 61.81% performance improvement. In all experiments depending on the change of the number of blockchain nodes, we obtained the better performance than original BFT-based consensus algorithms; thus, we can conclude that our approach improved the scalability of original BFT-based consensus algorithms. We also showed a correlation between performance and trouble transactions associated with transaction issue intervals and the number of blockchain nodes.

scholarly journals Research on Dynamic PBFT Consensus Algorithm

2020 ◽  
Author(s):  
Cao Xiaopeng ◽  
Shi Linkai
Keyword(s):  
Fault Tolerance ◽  
Connected Graph ◽  
Fault Tolerant ◽  
Consensus Algorithm ◽  
Byzantine Fault Tolerance ◽  
Master Node ◽  
Practical Application ◽  
Network Bandwidth ◽  
Byzantine Fault

The practical Byzantine fault-tolerant algorithm does not add nodes dynamically. It is limited in practical application. In order to add nodes dynamically, Dynamic Practical Byzantine Fault Tolerance Algorithm (DPBFT) was proposed. Firstly, a new node sends request information to other nodes in the network. The nodes in the network decide their identities and requests. Then the nodes in the network reverse connect to the new node and send block information of the current network, the new node updates information. Finally, the new node participates in the next round of consensus, changes the view and selects the master node. This paper abstracts the decision of nodes into the undirected connected graph. The final consistency of the graph is used to prove that the proposed algorithm can adapt to the network dynamically. Compared with the PBFT algorithm, DPBFT has better fault tolerance and lower network bandwidth.

scholarly journals Blockchain Economical Models, Delegated Proof of Economic Value and Delegated Adaptive Byzantine Fault Tolerance and their implementation in Artificial Intelligence BlockCloud

2019 ◽  
Vol 12 (4) ◽  
pp. 177 ◽  
Author(s):  
Qi Deng
Keyword(s):  
Artificial Intelligence ◽  
Fault Tolerance ◽  
Large Scale ◽  
Economic Value ◽  
Economic Models ◽  
Consensus Algorithm ◽  
Economic Policies ◽  
Byzantine Fault Tolerance ◽  
Distributed Consensus ◽  
Byzantine Fault

The Artificial Intelligence BlockCloud (AIBC) is an artificial intelligence and blockchain technology based large-scale decentralized ecosystem that allows system-wide low-cost sharing of computing and storage resources. The AIBC consists of four layers: a fundamental layer, a resource layer, an application layer, and an ecosystem layer (the latter three are the collective “upper-layers”). The AIBC layers have distinguished responsibilities and thus performance and robustness requirements. The upper layers need to follow a set of economic policies strictly and run on a deterministic and robust protocol. While the fundamental layer needs to follow a protocol with high throughput without sacrificing robustness. As such, the AIBC implements a two-consensus scheme to enforce economic policies and achieve performance and robustness: Delegated Proof of Economic Value (DPoEV) incentive consensus on the upper layers, and Delegated Adaptive Byzantine Fault Tolerance (DABFT) distributed consensus on the fundamental layer. The DPoEV uses the knowledge map algorithm to accurately assess the economic value of digital assets. The DABFT uses deep learning techniques to predict and select the most suitable BFT algorithm in order to enforce the DPoEV, as well as to achieve the best balance of performance, robustness, and security. The DPoEV-DABFT dual-consensus architecture, by design, makes the AIBC attack-proof against risks such as double-spending, short-range and 51% attacks; it has a built-in dynamic sharding feature that allows scalability and eliminates the single-shard takeover. Our contribution is four-fold: that we develop a set of innovative economic models governing the monetary, trading and supply-demand policies in the AIBC; that we establish an upper-layer DPoEV incentive consensus algorithm that implements the economic policies; that we provide a fundamental layer DABFT distributed consensus algorithm that executes the DPoEV with adaptability; and that we prove the economic models can be effectively enforced by AIBC’s DPoEV-DABFT dual-consensus architecture.

Consistency Is Not Enough in Byzantine Fault Tolerance

2018 ◽  
pp. 1238-1247
Author(s):  
Wenbing Zhao
Keyword(s):  
Fault Tolerance ◽  
Fault Tolerant ◽  
Large Body ◽  
Random Numbers ◽  
Security Requirement ◽  
Critical Systems ◽  
Byzantine Fault Tolerance ◽  
Byzantine Fault ◽  
Mission Critical ◽  
Fault Tolerant Systems

The use of good random numbers is crucial to the security of many mission-critical systems. However, when such systems are replicated for Byzantine fault tolerance, a serious issue arises, i.e., how do we preserve the integrity of the systems while ensuring strong replica consistency? Despite the fact that there exists a large body of work on how to render replicas deterministic under the benign fault model, the solutions regarding the random number control are often overly simplistic without regard to the security requirement, and hence, they are not suitable for practical Byzantine fault tolerance. In this chapter, we present a novel integrity-preserving replica coordination algorithm for Byzantine fault tolerant systems. The central idea behind our CD-BFT algorithm is that all random numbers to be used by the replicas are collectively determined, based on the contributions made by a quorum of replicas, at least f+1 of which are not faulty.

T-PBFT: An EigenTrust-based practical Byzantine fault tolerance consensus algorithm

2019 ◽  
Vol 16 (12) ◽  
pp. 111-123 ◽  
Author(s):  
Sheng Gao ◽  
Tianyu Yu ◽  
Jianming Zhu ◽  
Wei Cai
Keyword(s):  
Fault Tolerance ◽  
Consensus Algorithm ◽  
Byzantine Fault Tolerance ◽  
Byzantine Fault

Consistency Is Not Enough in Byzantine Fault Tolerance

2019 ◽  
pp. 88-99
Author(s):  
Wenbing Zhao
Keyword(s):  
Fault Tolerance ◽  
Fault Tolerant ◽  
Large Body ◽  
Random Numbers ◽  
Security Requirement ◽  
Critical Systems ◽  
Byzantine Fault Tolerance ◽  
Byzantine Fault ◽  
Mission Critical ◽  
Fault Tolerant Systems

The use of good random numbers is crucial to the security of many mission-critical systems. However, when such systems are replicated for Byzantine fault tolerance, a serious issue arises (i.e., how do we preserve the integrity of the systems while ensuring strong replica consistency?). Despite the fact that there exists a large body of work on how to render replicas deterministic under the benign fault model, the solutions regarding the random number control are often overly simplistic without regard to the security requirement, and hence, they are not suitable for practical Byzantine fault tolerance. In this chapter, the authors present a novel integrity-preserving replica coordination algorithm for Byzantine fault tolerant systems. The central idea behind our CD-BFT algorithm is that all random numbers to be used by the replicas are collectively determined, based on the contributions made by a quorum of replicas, at least f+1 of which are not faulty.

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