Fault Tolerance Consensus Algorithm Research Articles

A data sharing scheme based on blockchain for privacy protection certification of Internet of Vehicles

With the vigorous development of Internet of Vehicles (IoV) technology, modern cars equipped with advanced on-board systems are continuously generating massive amounts of data. Utilizing this data can improve driving safety and achieve better service quality in smart transportation systems. Therefore, ensuring the efficiency and security of data sharing is an important issue. Integrating IoV and blockchain technology can provide solutions to the data sharing security problems. This paper researches on IoV data sharing based on blockchain technology. In view of the problem that Internet of Vehicles data is susceptible to denial of service attacks, central failures and privacy leaks, we propose a data sharing scheme based on blockchain for privacy protection certification of Internet of Vehicles. Firstly, a decentralized privacy protection authentication framework is proposed is based on blockchain. Authenticated communication is performed between vehicle nodes and roadside units (as trusted authorities) by using authentication and access authentication schemes. Secondly, the trusted cluster head selected through the weight indicator is responsible for forwarding the information to the Trust Authority (TA), which then forwards the data to cloud storage and records the certificate and hash value on the distributed blockchain, along with other related information. In addition, the solution also uses a practical Byzantine fault-tolerant consensus algorithm to ensure the security and reliability of the blockchain, as well as the efficiency and decentralization of cloud storage. Finally, the TA revokes the certificate of the malicious vehicle node and clears it from the blockchain. Security analysis experiments show that our solution can effectively resist various threats such as counterfeiting, replay attacks, forgery and data tampering, thereby ensuring the security of Internet of Vehicles data sharing. Compared to the proposed solution, our performance has improved by 50.12%, 41.62%, 6.01%, and 29.11%, respectively.

Dynamic Byzantine Fault-Tolerant Consensus Algorithm with Supervised Feedback Mechanisms

Among the existing consensus algorithms, there are very few low-latency consensus algorithms that can simultaneously take into account node dynamics, fault tolerance, and scalability, and which are applicable to large-scale open scenarios where low latency is required. Therefore, this paper proposes a low-latency scalable dynamic consensus algorithm with high fault tolerance utilizing a combination of layered and threshold signature technologies, known briefly as LTSBFT. Firstly, LTSBFT achieves linear communication complexity through the utilization of threshold signature technology and a two-layer structure. Secondly, the mutual supervision feedback mechanism among nodes enables the attainment of linear complexity for reaching consensus on the faulty upper-layer nodes during the view-change. Lastly, a node dynamic protocol was proposed for the first time to support dynamic changes in the number of nodes during the consensus process. That is to say, consensus can still be reached when the number of nodes dynamically changes without interrupting the client’s request for consensus in the network. The experimental results indicate that LTSBFT exhibits lower communication latency and higher throughput compared to the classic HotStuff and PBFT algorithms. Furthermore, in comparison to double-layer PBFT, the LTSBFT has been demonstrated to have improved fault tolerance.

Fault-Tolerant Optimal Consensus Control for Heterogeneous Multi-Agent Systems

This study explores fault-tolerant consensus in leader–following heterogeneous multi-agent systems, focusing on actuator failures in uncrewed aerial vehicles (UAVs) and uncrewed ground vehicles (UGVs). An optimization-based fault-tolerant consensus algorithm is proposed. The algorithm utilizes the Euler–Lagrange formula to ensure system consistency under actuator failures, with the Lyapunov stability theory proving the asymptotic stability of the consistency error. The algorithm is applied to heterogeneous multi-agent systems of UAVs and UGVs to derive optimal fault-tolerant consensus control laws for each vehicle type. Simulation experiments give evidence for the feasibility of the proposed control strategy.

Lightweight adaptive Byzantine fault tolerant consensus algorithm for distributed energy trading

With the rapid development of smart grid, constructing distributed energy trading market (DETM) based on blockchain to coordinate distributed energy resources (DER) has become a future direction. However, existing consensus algorithms of blockchain face many challenges in large-scale energy trading scenarios, such as high resource overhead, slow transaction procedure. To solve the above crucial problems for wide deployment of distributed energy trading, this study proposes a novel consensus algorithm named Lightweight adaptive Byzantine fault tolerant consensus (LA-BFT), and a reputation calculation method based on behavioral characteristics for selection of consensus nodes. The LA-BFT consists of two parts: (i) weak consensus for normal cases. By introducing threshold signature mechanism, weak consensus simplifies the consensus process to achieve linear communication complexity O(n). (ii) byzantine node detection scheme is enable for malicious cases. With consensus committee, the detection scheme can detect the potential byzantine nodes by cross-validation, which ensures transaction safety. The reputation calculation method is presented to cooperate with LA-BFT to elect leaders and candidates for consensus procedure. Once a round of consensus is completed, the reputation of each node needs to be updated, only nodes with high reputation are eligible to become leaders or committee nodes in the next round. With the reputation calculation method, honest nodes and byzantine nodes can be effectively identified, ensuring the security of the consensus process. Numerical results indicate that LA-BFT exhibits superior performance on communication overhead and bandwidth occupancy in large-scale concurrent energy trading scenarios. When the number of nodes is 50, under normal scenarios, LA-BFT’s communication overhead is notably lower, constituting a mere 6.02% of PBFT and 24.26% of SHBFT, while bandwidth occupancy amounts to merely 5.55% of PBFT and 9.76% of SHBFT.

A Parallel Multi-Party Privacy-Preserving Record Linkage Method Based on a Consortium Blockchain

Privacy-preserving record linkage (PPRL) is the process of linking records from various data sources, ensuring that matching records for the same entity are shared among parties while not disclosing other sensitive data. However, most existing PPRL approaches currently rely on third parties for linking, posing risks of malicious tampering and privacy breaches, making it difficult to ensure the security of the linkage. Therefore, we propose a parallel multi-party PPRL method based on consortium blockchain technology which can effectively address the issue of semi-trusted third-party validation, auditing all parties involved in the PPRL process for potential malicious tampering or attacks. To improve the efficiency and security of consensus within a consortium blockchain, we propose a practical Byzantine fault tolerance consensus algorithm based on matching efficiency. Additionally, we have incorporated homomorphic encryption into Bloom filter encoding to enhance its security. To optimize computational efficiency, we have adopted the MapReduce model for parallel encryption and utilized a binary storage tree as the data structure for similarity computation. The experimental results show that our method can effectively ensure data security while also exhibiting relatively high linkage quality and scalability.

RaBFT: an improved Byzantine fault tolerance consensus algorithm based on raft

RaBFT: an improved Byzantine fault tolerance consensus algorithm based on raft

Exploring Fault Tolerance Consensus for Wireless Sensor Networks: A Comprehensive Detailed Study

The integration of wireless networks into modern communication systems has revolutionized information exchange across various applications. However, achieving reliable agreement in these networks is significantly impeded by their unique properties, such as blurring, interruption, and transparency. A fundamental component of distributed systems, fault-tolerant consensus ensures that nodes in the network can agree on a consistent value even in the presence of malfunctioning or corrupted elements. This study explores both non-Byzantine and Byzantine fault-tolerant consensus approaches, with a focus on achieving agreement in the presence of benign faults. The importance of fault-tolerant consensus in wireless connections is underscored, particularly in applications like wireless blockchain, IoT, and vehicular networks. The research delves into wireless network-specific fault-tolerant consensus algorithms to address the specific challenges posed by networking environments. Furthermore, a comparative analysis of Byzantine Fault Tolerance mechanisms in distributed systems is provided to shed light on their features and benefits. It highlights the importance of ensuring system reliability and consistency in wireless networks to maintain seamless communication and data integrity. Moreover, the paper emphasizes the critical role of fault-tolerant consensus in enhancing system resilience and performance. It underscores the need for robust algorithms and protocols to detect and mitigate errors, ensuring reliable communication and coordination despite potential node failures. By providing insights into fault-tolerant consensus mechanisms tailored to dynamic conditions, the study aims to optimize system adaptation and effectively mitigate both Byzantine and non-Byzantine failures in wireless network environments.

Research on evolutionary game of digital twin data information sharing based on blockchain technology

Due to the significant characteristics of decentralization and tamper resistance of blockchain technology, it helps to solve the problems of timeliness and slow permission control in traditional information sharing. However, most researchers are committed to exploring how to improve the efficiency, reliability, and privacy security of digital twin data. There is a lack of research on issues such as blockchain participants free-riding and not actively participating in information sharing, and how to promote information sharing through incentives. Therefore, this paper designs a distance grouping based practical byzantine fault tolerance consensus algorithm to address the credibility issue of transmitted data, thereby improving the efficiency of negotiation. The feasibility of the algorithm is verified through cases analysis. In addition, for the problem of low subjective willingness of information sharing, this paper designs an information sharing incentive strategy based on blockchain intelligent contracts, establishes digital twin data sharing evolutionary game models with reputation incentives and non-reputation incentives, so as to explore the impact of reputation incentive on evolutionary stability strategies. Finally, simulation analysis is conducted on the evolutionary game model of digital twin data sharing. The impact of several key indicators such as data complementarity, trust, positive incentive coefficient, and data sharing cost on the evolution process of information sharing are considered, and corresponding management insights are obtained.

Improvement of Practical Byzantine Fault Tolerance Consensus Algorithm Based on DIANA in Intellectual Property Environment Transactions

In response to the shortcomings of the consensus algorithm for intellectual property transactions, such as high communication overhead, random primary node selection, and prolonged consensus time, a Practical Byzantine Fault Tolerance (PBFT) improvement algorithm based on Divisive Analysis (DIANA) D-PBFT algorithm is proposed. Firstly, the algorithm adopts the hierarchical clustering mechanism of DIANA to cluster nodes based on similarity, enhancing node partition accuracy and reducing the number of participating consensus nodes. Secondly, it designs a reward and punishment system based on node ranking, to achieve consistency between node status and permissions, timely evaluation, and feedback on node behaviours, thereby enhancing node enthusiasm. Then, the election method of the primary node is improved by constructing proxy and alternate nodes and adopting a majority voting strategy to achieve the selection and reliability of the primary node. Finally, the consistency protocol is optimised to perform consensus once within the cluster and once between all primary nodes, to ensure the accuracy of the consensus results. Experimental results demonstrate that the D-PBFT algorithm shows a better performance, in terms of communication complexity, throughput, and latency.

Trapdoor proof of work.

Consensus algorithms play a crucial role in facilitating decision-making among a group of entities. In certain scenarios, some entities may attempt to hinder the consensus process, necessitating the use of Byzantine fault-tolerant consensus algorithms. Conversely, in scenarios where entities trust each other, more efficient crash fault-tolerant consensus algorithms can be employed. This study proposes an efficient consensus algorithm for an intermediate scenario that is both frequent and underexplored, involving a combination of non-trusting entities and a trusted entity. In particular, this study introduces a novel mining algorithm, based on chameleon hash functions, for the Nakamoto consensus. The resulting algorithm enables the trusted entity to generate tens of thousands blocks per second even on devices with low energy consumption, like personal laptops. This algorithm holds promise for use in centralized systems that require temporary decentralization, such as the creation of central bank digital currencies where service availability is of utmost importance.

Advances in Consortium Chain Scalability: A Review of the Practical Byzantine Fault Tolerance Consensus Algorithm

Advances in Consortium Chain Scalability: A Review of the Practical Byzantine Fault Tolerance Consensus Algorithm

An Efficient and Secure Blockchain Consensus Protocol for Internet of Vehicles

Conventional blockchain consensus protocols tailored for the Internet of Vehicles (IoV) usually face low transaction throughput, high latency, and elevated communication overhead issues. To address these issues, in this paper, we propose ESBCP, an efficient and secure blockchain consensus protocol for the IoV environment. Firstly, considering the significant performance differences among nodes in the IoV, we designed a blockchain consensus model for the IoV. Roadside units execute a trust evaluation mechanism to select high-quality vehicle nodes for the consensus process, thereby reducing the likelihood of malicious nodes in the consensus cluster. Secondly, we designed a node partition strategy to adapt to the dynamic feature of the IoV. Finally, addressing the mobility of nodes in the IoV, we introduced a dynamic unique node list. Vehicle nodes can promptly select nodes with high reliability from the list of communicable nodes to join their unique node list, while also promptly removing nodes with low reliability from their unique node list. Combining these strategies, we propose DK-PBFT, an improved Practical Byzantine Fault Tolerance consensus algorithm. The algorithm meets the efficiency and mobility requirements of vehicular networks. Through theoretical analysis, ESBCP could prevent external and internal security risks while reducing communication overhead. Experimental verification demonstrated that ESBCP effectively reduces consensus latency and improves transaction throughput. Our proposed ESBCP can be used in other application scenarios that require high consensus efficiency.

BW-PBFT: Practical byzantine fault tolerance consensus algorithm based on credit bidirectionally waning

BW-PBFT: Practical byzantine fault tolerance consensus algorithm based on credit bidirectionally waning

Byzantine Fault-Tolerant Consensus Algorithms: A Survey

The emergence of numerous consensus algorithms for distributed systems has resulted from the swift advancement of blockchain and its related technologies. Consensus algorithms play a key role in decentralized distributed systems, because all nodes in the system need to reach a consensus on requests or commands through consensus algorithms. In a distributed system where nodes work together to reach consensus, there may be Byzantine nodes present. The emergence of Byzantine nodes will affect the consensus of nodes in the distributed system. Therefore, tolerating Byzantine nodes in a distributed system and then reaching a consensus is an essential function of a consensus algorithm. So far, many Byzantine fault-tolerant (BFT) consensus algorithms have emerged, and there are correspondingly many methods to improve the performance of these algorithms. In order to allow researchers to have a clearer understanding of the existing methods, this paper systematically investigated and studied the research progress of the current Byzantine fault-tolerant consensus algorithm. The scope of the research ranged from the classic Byzantine consensus algorithm to some of the latest Byzantine consensus algorithms. The articles were classified according to the methods used to improve the Byzantine consensus algorithm. Through classification and centralized analysis and discussion, we achieved a clearer understanding of the development of Byzantine consensus algorithms and, at the same time, clarified the advantages and disadvantages of this type of method and the latest research progress using this method. At the end of this article, an in-depth discussion and analysis is also presented. By analyzing the impact of the use of these methods on the performance of the BFT consensus algorithm, it is proposed that future research can be improved.

Improvement of Hierarchical Byzantine Fault Tolerance Algorithm in RAFT Consensus Algorithm Election

Currently, blockchain technology is not only gaining momentum in the financial industry but also showing promising developments in other sectors. Due to its suitability for various societal needs, an increasing number of non-financial institutions are expanding the scope of blockchain services beyond finance to areas such as healthcare service management and enterprise governance. The core of a blockchain system lies in consensus, which plays a crucial role in its performance and security. The PBFT algorithm is a widely used fault-tolerant consensus algorithm. However, it suffers from issues like high consensus latency, low throughput, and poor performance. In recent years, the HBFT algorithm has addressed these concerns. This paper proposes an improved HBFT blockchain consensus algorithm tailored for large enterprises and non-financial institutions with multiple independent functions. The goal is to achieve more efficient data management and election strategies that are both more secure than PBFT and more efficient than HBFT. Leveraging the enhanced HBFT consensus algorithm ensures stability and efficiency in the consensus and verification processes between organizations. Additionally, it enables the efficient management of data and value creation in the application context.

An improved PBFT consensus algorithm based on grouping and credit grading

To improve the blockchain consensus algorithm practical Byzantine fault tolerance (PBFT) with random master node selection, which has high communication overhead and a small supported network size, this paper proposes a Byzantine fault tolerant consensus algorithm based on credit (CBFT) enhanced with a grouping and credit model. The CBFT algorithm divides the network nodes according to the speed of their response to the management nodes, resulting in different consensus sets, and achieves consensus within and outside the group separately to reduce communication overhead and increase system security. Second, the nodes are divided into different types according to the credit model, each with different responsibilities to reduce the probability that the master node is a malicious node. Experimental results show that the throughput of the CBFT algorithm is 3.1 times that of PBFT and 1.5 times that of GPBFT when the number of nodes is 52. Our scheme has latency that is 7.4% that of PBFT and 38.8% that of GPBFT; CBFT has communication overhead that is 6.4% that of PBFT and 87.3% that of GPBFT. The number of nodes is 300, and the Byzantine fault tolerance is improved by 59.3%. These improvements are clearer with the increase in the number of nodes.

Multi‐stage energy‐risk adjustments using practical Byzantine fault tolerance consensus for blockchain‐powered peer‐to‐peer transactive markets

AbstractThe energy risk associated with distributed energy resources is inevitable in peer‐to‐peer (P2P) transactive energy markets owing to mismatches between energy commitments and metered measurements. However, adjusting these possible mismatches by progressive revision of the energy commitments in the rolling time horizon mitigates the energy risk, and thereby mitigates the financial risk for prosumers. In this study, the conditional value at risk (CVaR) is used to estimate the risk value for each prosumer. The energy offers that are riskier than CVaR‐based threshold values are reduced in an ‘adjustment bid’. A new pricing mechanism for these adjustment bids is introduced, which varies with historical deviations of a prosumer from energy commitments. This market framework and pricing mechanism are simulated through a blockchain network hosted on a Python Django server using the practical Byzantine fault tolerance consensus algorithm to guarantee network immutability and data privacy. Efforts to mitigate such mismatches between ex ante and ex post energy values incentivise risk‐aware participation in P2P markets. In addition, the welfare of both prosumers and consumers improves with their participation in the proposed market framework. Furthermore, implementing a network using blockchain technology guarantees the privacy of bidding data and provides a secure transaction platform.

FP‐BFT: A fast pipeline Byzantine consensus algorithm

AbstractThe Byzantine Fault Tolerant (BFT) consensus algorithms have been widely applied in the blockchain systems because of their fault tolerance capability to determine system consistency in the presence of malicious nodes. However, the BFT consensus algorithms are confronted with low efficiency and scalability problems caused by multiple rounds of handshake communication. In this paper, a pipeline‐based Fast Pipeline Byzantine Fault Tolerance consensus algorithm (FP‐BFT) is proposed, which adopts a non‐leader pipeline framework to process different rounds of transactions in parallel. By means of randomly selecting 2f+1 nodes to form a committee for one round of transactions, consensus agreement can be reached within the committee via nodes broadcasting and voting. Committee nodes participating in the consensus are chosen by chance to avoid the monopoly of which becomes the block producer. Consensus efficiency and the system throughput can be significantly improved with the pipeline framework. Comparison experiments are conducted to verify the superiority of the FP‐BFT algorithm, and the theoretical proof is given to guarantee the Byzantine fault‐tolerant security. Experimental results show that FP‐BFT has improved the consensus efficiency by decreasing communication overhead to make it better applied both in public blockchain and consortium blockchain systems.

Contract-Theory-Based Secure Spectrum Sharing Framework in Internet of Vehicles

Internet of vehicles (IoV) enables a large number of applications for consumers by integrating massive electronics, which aggravates the spectrum scarcity and data security, and degrades the quality of services (QoS) and experiences of consumers obviously. Focusing on enhancing the security and improving spectrum utilization, this article proposes a contract-theory-based secure spectrum sharing framework, which adopts the consortium blockchain to guarantee security of spectrum sharing and utilizes the practical Byzantine fault tolerant consensus algorithm to achieve consensus in IoV. Smart contracts are then formed based on insurance contracts to promote primary users to share their idle spectrum resources. A preference-based spectrum allocation algorithm is designed to maximize the total utility of secondary users (SUs). Simulation results show that, compared with the existing schemes, the proposed scheme achieves better performance in terms of the utility of SUs and the spectrum utilization greatly, which provides more access opportunities to consumers in IoV.

Improvement of the PBFT Algorithm Based on Grouping and Reputation Value Voting

An improved practical Byzantine fault tolerance (Practical Byzantine Fault Tolerant consensus algorithm based on reputation, RPBFT) algorithm based on grouping and reputation value voting is proposed for the problems of high communication complexity, poor scalability, and random selection of master nodes of the practical Byzantine fault tolerance (PBFT) consensus algorithm of the consortium chain. First, the consistency process is optimized to take the response speed of nodes to each group leader as the basis of grouping, and the intragroup consensus is performed. The group leader then takes the result of intragroup consensus and participates in extra-group consensus to reduce the frequency and time of internode communication. Second, the reputation model and voting mechanism are proposed, and the group leader is generated by node reputation value voting, which enhances the initiative and reliability of trusted nodes and reduces the abnormal nodes as group leader. Finally, a simulation and performance testing system based on this improved scheme is built to prove the effectiveness as well as the usability of the scheme through simulation experiments. The experimental results show that when the number of network nodes is 36, the throughput of the RPBFT algorithm is six times that of PBFT. Therefore, the consensus delay is reduced by 91.7%, and the communication overhead is reduced by 37.8%.