Cluster-Based PBFT Blockchain Consensus Modelling with Jackson Open Queuing Network

Aiming at the problems of high cost of capital operation, complex and changeable financial operation process, opaque transaction information, tracing of settlement process and difficult information storage in the existing project settlement scenario, the Practical Byzantine Fault Tolerance (PBFT) consensus algorithm is improved. By combining the ideas of Dynamic Grouping Practical Byzantine Fault Tolerance algorithm and Evolution of Practical Byzantine Fault Tolerance, a Confidence Selection Practical Byzantine Fault Tolerance (CONS-PBFT) algorithm is proposed. By introducing a confidence mechanism, Byzantine Fault Tolerance algorithm optimizes the consensus process of the PBFT algorithm. The experiments show that the CONS-PBFT algorithm not only can significantly improve the consensus efficiency, but also can effectively solve various problems involved in the current engineering settlement tasks. Thus, a credible and cooperative, safe and transparent engineering settlement method can be realized.

Practical Byzantine Fault Tolerance (PBFT) algorithm is a popular solution for establishing consensus in blockchain systems. However, there are some issues in the PBFT algorithm, such as high energy consumption, low efficiency, and poor scalability. These problems are not solved even in some of its improved algorithms, such as Byzantine consensus algorithm based on Gossip protocol (GBC) and Credit Practical Byzantine Fault Tolerance (CBPFT) algorithms. To address these issues, this paper proposes a Byzantine Fault Tolerant algorithm based on Vote algorithm (vBFT). The nodes in the network are divided into three types of with different responsibilities by the vBFT algorithm, which are client, slave, and master nodes. The state between nodes could be dynamically adjusted at any time. As shown our simulations and analysis, the proposed algorithm has significantly improved performance in terms of dynamics, energy consumption, fault tolerance and low-latency compared with consensus algorithms such as PBFT, GBC and CBPFT algorithm.

Purpose Problems such as data security and trustworthy interactivity bring new challenges to the development and application of service ecosystems. As a decentralized ledger, blockchain has characteristics such as non-tamperability, unforgeability, traceability, global consistency, so that the integration between blockchain and service ecosystems can ensure data integrity and service availability. The purpose of this paper is to investigate problems of efficient consensus algorithm in service ecosystems alliance chain scenarios. Design/methodology/approach This method consists of two core modules: bubble sort and reputation mechanism. The bubble sort algorithm can reduce the number of consensus nodes, thereby reducing communication overhead and improving throughput. The reputation mechanism can improve the correctness of consensus nodes, thereby solving the problem of random selection of the primary in the PBFT algorithm and improving its security and efficiency. Findings Comparative experiments and analysis have been conducted between the practical Byzantine fault-tolerant algorithm combined with bubble sort and reputation mechanism (BR-PBFT) scheme proposed in this paper and existing similar PBFT algorithms in terms of communication complexity, transaction confirmation delay and throughput. The experimental results demonstrate that BR-PBFT maintains 1/3 fault tolerance of PBFT, effectively reduces communication overhead, lowers transaction confirmation delay and improves throughput. Originality/value The practical Byzantine fault tolerance (PBFT) algorithm used in the alliance chain still has the problems of high communication complexity and low throughput. Aiming at application scenarios of alliance chains in service ecosystems, an improved is proposed. It provides valuable insights into future research and practical applications in service ecosystems.

Because of its excellent properties of fault tolerance, efficiency and availability, the practical Byzantine fault tolerance (PBFT) algorithm has become the mainstream consensus algorithm in blockchain. However, current PBFT algorithms have problems such as inadequate security of primary node selection, high communication overhead and network delay in the process of consensus. To address these problems, we design a novel efficient Byzantine fault tolerance algorithm based on credit grouping, called CG-PBFT. First, we propose a new credit evaluation model to obtain nodes’ credit values and introduce an optimized three-way quick sorting algorithm to divide nodes into the master-node group, the consensus-node group and the observation-node group, which have different privileges. The nodes in the observation-node group are restricted from participating in consensus, which reduces the communication overhead and improves consensus efficiency. Second, we propose an optimized selection method for the primary node based on a voting mechanism whereby the consensus-node group and observation-node group vote to produce the primary node, which reduces the probability of malicious nodes acting as the primary node and improves the security of primary node selection. Finally, the identity conversion mechanism between node groups is designed, and the actual behavior of nodes within different groups is given credit rewards or punishment, so as to keep an incentive for nodes to participate in appropriate system behavior and improve the working enthusiasm of nodes. The experimental simulation results show that compared with existing PBFT algorithms, the CG-PBFT algorithm improves the average throughput by 51.3% and reduces the average delay by 64.5%; it greatly improves the operating efficiency of the system and can be more suitable for application in the consortium blockchain scenarios.

In traditional power networks, security protection models primarily rely on perimeter-based defenses, utilizing firewalls, virtual private networks (VPNs), and identity authentication to block external threats. However, once a node within the power system is compromised, attackers can exploit it as a pivot to launch lateral movement attacks from within the system, posing serious threats to the core operations of the power grid. To address the increasingly complex cybersecurity landscape, this paper proposes a security defense approach that integrates an improved trust evaluation model based on the Practical Byzantine Fault Tolerance (PBFT) algorithm with a zero-trust architecture, leveraging the structural and functional symmetry among network nodes. The PBFT algorithm’s fault tolerance and consensus mechanisms are leveraged to ensure dynamic trust scoring across multiple nodes. This approach guarantees that each node has an equal role in the system’s operations, maintaining fairness and security across the network. Furthermore, the primary node in the PBFT consensus process is redefined as the arbitration node in the zero-trust framework, and faulty nodes can be automatically replaced through the view change protocol, thereby mitigating the centralization risk inherent in traditional zero-trust models. Experimental results demonstrate that the proposed approach achieves high accuracy and robustness in defending against both internal and external attacks in power network scenarios, highlighting the role of symmetry in enhancing secure and balanced system operations.

Aiming at the challenges of low throughput, excessive consensus latency and high communication complexity in the Practical Byzantine Fault Tolerance (PBFT) algorithm in blockchain networks, its application in identity verification for distributed networking of a drone cluster is limited. Therefore, a lightweight blockchain-based identity authentication model for UAV swarms is designed, and a Credit-score and Grouping-mechanism Practical Byzantine Fault Tolerance (CG-PBFT) algorithm is proposed. CG-PBFT introduces a reputation score evaluation mechanism, classifies the reputation levels of nodes in the network, and optimizes the consensus process based on grouping consensus and BLS aggregate signature technology. Experimental results demonstrate that under identical experimental conditions, compared with the PBFT algorithm, CG-PBFT achieves a 250% increase in average throughput, a 70% reduction in average latency, and simultaneous enhancement in security, thus making it more suitable for UAV swarm networks.

Currently, in the blockchain-based distributed microgrid trading system, there are some problems, such as low throughput, high delay, and a high communication overhead. To this end, an improved Practical Byzantine Fault Tolerance (PBFT) algorithm (CE-PBFT) suitable for microgrid power trading is proposed. First, a node credit value calculation model is introduced, and nodes are divided into consensus, supervisory, and propagation nodes according to their credit values, forming a hierarchical network structure to ensure the efficiency and reliability of consensus. Secondly, the consensus process is optimized by adopting a segmented consensus mechanism. This approach calculates the consensus rounds for nodes and selects the methods for node-type switching and consensus based on these calculations, reaching dynamic changes in node states and credit values, effectively reducing the communication overhead of node consensus. Finally, the experiments show that compared with the IMPBFT and PBFT algorithms, the CE-PBFT algorithm has better performance in throughput, delay, and communication overhead, with a 22% higher average throughput and 15% lower average delay than the IMPBFT algorithm and a 118% higher average throughput and 87% lower average delay than the PBFT algorithm.

Nowadays Practical Byzantine Fault Tolerance (PBFT) algorithm has become the most extensive consensus algorithm in the alliance chain. However, the PBFT algorithm is usually only applicable to small networks due to high communication complexity and poor scalability. Although there have been many improved algorithms for PBFT in recent years, they ignore fault tolerance and democracy. Therefore, to meet the requirements of a high degree of decentralization and fault tolerance of blockchain-based scenarios. This paper proposes a high fault tolerance consensus algorithm NBFT, which follows the principle of decentralization and democratization of blockchain and ensures the improvement of performance in fault tolerance upper limit and scalability. First, we use the consistent hash algorithm to group the consensus nodes to avoid much communication between nodes, reduce the communication complexity of the network, and improve the scalability of the network. Second, to ensure the fault-tolerant ability of the grouping consensus, the nodal decision broadcast model and threshold vote-counting model are proposed first. Combined with the proposed two models, the joint fault analysis of nodes is carried out, and the fault tolerance upper limit is more than 1/3. Then, the Faulty Number Determined (FND) model is introduced to simulate the experiment, and the results are verified.

In service-transaction scenarios, blockchain technology is widely used as an effective tool for establishing trust between service providers and consumers. The consensus algorithm is the core technology of blockchain. However, existing consensus algorithms, such as the practical Byzantine fault tolerance (PBFT) algorithm, still suffer from high resource consumption and latency. To solve this problem, in this study, we propose an improved PBFT blockchain consensus algorithm based on quality of service (QoS)-aware trust service evaluation for secure and efficient service transactions. The proposed algorithm, called the QoS-aware trust practical Byzantine fault tolerance (QTPBFT) algorithm, efficiently achieves consensus, significantly reduces resource consumption, and enhances consensus efficiency. QTPBFT incorporates a QoS-aware trust service global evaluation mechanism that implements service reliability ranking by conducting a dynamic evaluation according to the real-time performance of the services. To reduce the traffic of the blockchain, it uses a mechanism that selects nodes with higher values to form a consensus group that votes for consensus according to the global evaluation result of the trust service. A practical protocol is also constructed for the proposed algorithm. The results of extensive simulations and comparison with other schemes verify the efficacy and efficiency of the proposed scheme.

The consensus mechanism is the core of the blockchain system, which plays an important role in the performance and security of the blockchain system . The Practical Byzantine Fault Tolerance (PBFT) algorithm is a widely used consensus algorithm, but the PBFT algorithm also suffers from high consensus latency, low throughput and performance. In this paper, we propose a grouped PBFT consensus algorithm (GPBFT) based on feature trust. First, the algorithm evaluates the trust degree of nodes in the transaction process through the EigenTrust trust model, and uses the trust degree of nodes as the basis for electing master nodes and proxy nodes. Then, the algorithm divides the nodes in the blockchain system into multiple groups, and the consensus within each independent group does not affect the other groups, which greatly reduces the communication overhead of the consensus process when the number of nodes in the system is large. Finally, we demonstrate through theoretical and experimental analysis that the GPBFT algorithm has a significant improvement in security and performance.

Voting-based consensus algorithms such as the Practical Byzantine Fault Tolerance (PBFT) algorithm and Raft algorithm are mainly used in consortium chains. PBFT algorithm is suitable for the Byzantine environment while Raft algorithm is suitable for the non-Byzantine environment. Although there are access mechanisms in the consortium chain, Byzantine nodes may pretend to be honest nodes. PBFT algorithm has high time complexity and poor performance when too many nodes participate in the consensus. Meanwhile, the Raft algorithm can be applied in practice due to its excellent performance and ease of understanding. To solve the performance as well as security problems of the consensus algorithm in consortium chain, this paper proposes the reputation-based Raft algorithm (rbRaft), which can get the honesty degree of the nodes by recording the reputation value of the nodes participating in the consensus. If a node is malicious, its reputation value will be reduced and the node has a low probability to become a leader. If the reputation value is less than 0.5, then it will be removed from the network and will not participate in the consensus. We also add digital signatures to the Raft consensus algorithm, which can guarantee the reliability of the data transmitted between nodes. This paper conducts simulation experiments to evaluate the performance and fault tolerance of the algorithm.

Due to the limited computing and storage capabilities of IoT devices, it is difficult to meet the computing needs of the Practical Byzantine Fault Tolerance (PBFT) algorithm. And the traditional PBFT algorithm is difficult to meet the throughput required by this system due to the prolonged consensus time. In order to solve the above problems, this paper proposes an improved PBFT algorithm, First, the node roles are divided, and only the consensus node role participates in the consensus, which reduces the communication overhead in the consensus process and makes enterprises of various strengths suitable for joining the system. Secondly, a scoring mechanism is added to improve the node selection and replacement method according to the points obtained by the nodes, and effectively eliminate Byzantine nodes, select a reliable node as the master node to the greatest extent, reduce the frequency of view change, and improve the speed of node change. Finally, the execution process of the consensus protocol is optimized, the communication complexity is reduced from O(N^2) to O(N), and the overall efficiency of the system is improved.

With the development of Intelligent Transportation Systems (ITS) and 5G communication technology, Vehicular Ad-Hoc Networks (VANETs) are playing an increasingly important role in enhancing road safety, improving traffic efficiency and providing online entertainment experience [1]. However, the information insecurity brought by the traditional centralized mode of VANETs is still a very challenging problem. To solve this problem, a 5G-enabled hierarchical network in VANETs is proposed through the research of blockchain and 5G technology. On this basis, a data sharing scheme based on Practical Byzantine Fault Tolerance (PBFT) algorithm is proposed, which realizes data storage and transmission effectively with its characteristics of data immutability and decentralization. The ideal expected result is that the scheme realizes data storage effectively and the security of data transmission and ensures the reliable transmission of data with lower computing time.

As the foundation of a blockchain, consensus algorithm significantly affects the blockchain system’s performance. To a consortium blockchain, Practical Byzantine Fault Tolerance (PBFT) has been widely believed as a good candidate consensus due to its many advantages. However, PBFT is not particularly designed for a consortium blockchain. Thus, there is still a large improvement space to implement the PBFT algorithm in a sharded blockchain. Based on network sharding, we aim to address the problems incurred by the traditional PBFT algorithm. Because when there are large number of nodes in a P2P network, PBFT can lead to a significant performance degradation. Even worse, Byzantine nodes cannot be found timely in a large-scale blockchain network where the PBFT algorithm is adopted. In this paper, we propose an adapted version of BFT consensus for the sharded blockchain. The proposed cross-shard BFT consensus mainly consists of a two-phase consensus mechanism after performing network sharding. In the first phase, Raft consensus is first adopted within each shard, in which a leader is elected. In the second phase, those leaders from all shards form a committee and perform a committee-wise PBFT consensus. Through introducing anchor nodes within each shard, the security of the proposed two-phase consensus is guaranteed. We analyze the security of the cross-shard BFT consensus based on a committee-wise monitoring framework. Through simulations, we find out that the proposed cross-shard BFT consensus yields a higher throughput, lower latency than the original PBFT. The fault-tolerance ability of the proposed consensus is around 1.5\(\times \) to 2\(\times \) of PBFT.KeywordsBlockchainConsensus algorithmPractical byzantine fault toleranceNetwork sharding

The consortium chain is the main form of application of blockchain technology in the actual industry, and its consensus mechanism mostly adopts the practical Byzantine fault tolerance (PBFT) algorithm. The traditional PBFT algorithm is only suitable for small-scale local area networks, but in large-scale wide-area network environments, its scalability bottleneck has a serious impact on the performance of the system. Therefore, in this paper, a scalable Byzantine fault tolerance algorithm based on a tree topology network is proposed (STBFT), which can take different steps to reach consensus according to the abnormal situation of the system. First, the STBFT algorithm divides the consensus nodes into different layers and groups based on the tree topology network structure, which transforms from global consensus to local consensus and drastically reduces communication consumption. Then, the division method of the group is based on a verifiable random function (VRF), with the purpose of preventing targeted attacks and colluding Byzantine nodes from affecting the normal consensus of the system. Finally, a feedback mechanism is proposed for the first time to reduce the influence of Byzantine failure on hierarchical network systems. The simulation results show that the proposed algorithm reduces the communication complexity and improves the fault tolerance of the system, and the scalability of the tree topology network structure can be better applied in large-scale scenarios such as IoT and health care.