A Group-Based Optimized Practical Byzantine Fault Tolerance Consensus Algorithm

2021 ◽  
pp. 95-115
Author(s):  
Zhenshan Bao ◽  
Yue Liu ◽  
Wenbo Zhang
Keyword(s):  
Fault Tolerance ◽  
Consensus Algorithm ◽  
Byzantine Fault Tolerance ◽  
Byzantine Fault

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.

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

scholarly journals Dynamic reputation–based consensus mechanism: Real-time transactions for energy blockchain

2020 ◽  
Vol 16 (3) ◽  
pp. 155014772090733
Author(s):  
Wenjun Cai ◽  
Wei Jiang ◽  
Ke Xie ◽  
Yan Zhu ◽  
Yingli Liu ◽  
...  
Keyword(s):  
Fault Tolerance ◽  
Power Systems ◽  
Real Time ◽  
Consensus Algorithm ◽  
Generation Process ◽  
Byzantine Fault Tolerance ◽  
Real Time Processing ◽  
Energy Field ◽  
Byzantine Fault ◽  
Application Requirements

The energy blockchain is a distributed Internet protocol for energy transactions between nodes in power systems. The consensus algorithm is the core component of the energy blockchain and has an essential impact on its application. At present, in the implementation of the energy blockchain, there are problems such as low transaction throughput (transactions per second) and high latency, which cannot meet the application requirements of real-time processing transactions in the energy field. To this end, according to the analysis of conventional blockchain consensus algorithm and traditional practical Byzantine fault tolerance algorithm, a dynamic-reputation practical Byzantine fault tolerance algorithm for the energy blockchain is proposed. The dynamic-reputation practical Byzantine fault tolerance algorithm adopts a credit-based consortium node consensus election method. The monitoring node divides the remaining nodes into two types of nodes according to the reputation value: the consensus node and the secondary node, which, respectively, participate in different stages of the block generation process, and dynamically update the consensus nodes with low reputation ratings. By constructing the experimental platform simulation, the test results verify the effectiveness of the dynamic-reputation practical Byzantine fault tolerance algorithm. Compared with the algorithm of the fabric platform, the dynamic-reputation practical Byzantine fault tolerance algorithm improves the transaction processing speed and is suitable for the blockchain application in the energy field.

scholarly journals Cryptospatial Coordinate using the RPCA Based on a Point in Polygon Test for Cultural Heritage Tourism

2020 ◽  
Vol 22 (4) ◽  
pp. 211-217
Author(s):  
Achmad Teguh Wibowo ◽  
MY Teguh Sulistyono ◽  
Mochamad Hariadi
Keyword(s):  
Fault Tolerance ◽  
Cultural Heritage ◽  
Mobile Device ◽  
Heritage Tourism ◽  
Test Method ◽  
Consensus Algorithm ◽  
Byzantine Fault Tolerance ◽  
Smart Contract ◽  
Byzantine Fault ◽  
Cultural Heritage Tourism

This research was aimed to enhance the cryptospatial with geospatial blockchain based on a point in polygon test. Ripple Protocol Consensus Algorithm (RPCA) was used for developing a blockchain. The steps taken include: (1) Data from the surveyors were entered using application connected to the transaction set; (2) The transaction set sent data to the transaction proposal; (3) The transaction proposal will distribute to every connected validating of nodes for executing the smart contract with the point in a polygon test method; (4) If the process succeeded with the maximum fault tolerance of 20%, then the node records a new chain to the ledger. This method is faster than Practical Byzantine Fault Tolerance (PBFT) blockchain for approximately 26% to add a new chain in the ledger and for 52% to decrypt the blockchain with a mobile device. The result of this process is a cryptospatial coordinate for the cultural heritage tourism.

Optimal Byzantine Fault Tolerance Consensus Algorithm for permissioned systems

2021 ◽  
Author(s):  
Lenuta Alboaie ◽  
Sinica Alboaie ◽  
Cristina Georgiana Calancea
Keyword(s):  
Fault Tolerance ◽  
Consensus Algorithm ◽  
Byzantine Fault Tolerance ◽  
Byzantine Fault

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.

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