Existing Consensus Algorithms Research Articles

An improved practical Byzantine fault tolerance algorithm for aggregating node preferences

Consensus algorithms play a critical role in maintaining the consistency of blockchain data, directly affecting the system’s security and stability, and are used to determine the binary consensus of whether proposals are correct. With the development of blockchain-related technologies, social choice issues such as Bitcoin scaling and main chain forks, as well as the proliferation of decentralized autonomous organization (DAO) applications based on blockchain technology, require consensus algorithms to reach consensus on a specific proposal among multiple proposals based on node preferences, thereby addressing the multi-value consensus problem. However, existing consensus algorithms, including Practical Byzantine Fault Tolerance (PBFT), do not support nodes expressing preferences. Instead, the proposal to reach consensus is directly decided by specific nodes, with other nodes merely verifying the proposal’s validity, which can easily result in monopolistic or dictatorial outcomes. In response, we proposed the Aggregating Preferences with Practical Byzantine Fault Tolerance (AP-PBFT) consensus algorithm, which allows nodes to express preferences for multiple proposals. AP-PBFT ensures the validity of consensus results through a consensus output protocol, and incentivizes nodes to act honestly during the consensus process by incentive mechanism. First, AP-PBFT leverages Verifiable Random Function to select both consensus nodes and a primary node from the candidates. The primary node gathers proposals, assembles them into a proposal package, and broadcasts it to other consensus nodes. The consensus nodes independently vote to express their preferences for different proposals in the package, execute the consensus output protocol to reach local consensus, and the primary node aggregates these results to form the global consensus. Once the global consensus is finalized, AP-PBFT evaluates node behavior based on the consensus output protocol, penalizes nodes that acted maliciously, and rewards those that adhered to the protocol. Additionally, nodes can interact and adopt different strategies while executing the consensus output protocol, which can influence the consensus outcome. Therefore, we established an evolutionary game model based on hypergraph to analyze these interactions. Theoretical analysis shows that the incentive mechanism in AP-PBFT effectively encourages nodes to honestly follow the consensus output protocol, ensuring that AP-PBFT satisfies the properties of consistency, validity, and termination. Finally, the simulation results demonstrate that the AP-PBFT algorithm possesses good scalability and the capability to handle dynamic changes in nodes, surpassing some mainstream consensus algorithms in terms of transaction throughput and consensus achievement time. Moreover, AP-PBFT can incentivize honest behavior among consensus nodes, thereby enhancing the reliability of consensus and strengthening the security of the network.

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.

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.

Erdos: A Novel Blockchain Consensus Algorithm with Equitable Node Selection and Deterministic Block Finalization

The introduction of blockchain technology has brought about significant transformation in the realm of digital transactions, providing a secure and transparent platform for peer-to-peer interactions that cannot be tampered with. The decentralised and distributed nature of blockchains guarantees the integrity and authenticity of the data, eliminating the need for intermediaries. The applications of this technology are not limited to the financial sector, but extend to various areas, such as supply chain management, identity verification, and governance. At the core of these blockchains is the consensus mechanism, which plays a crucial role in ensuring the reliability and integrity of a system. Consensus mechanisms are essential for achieving an agreement amongst network participants regarding the validity of transactions and the order in which they are recorded on the blockchain. By incorporating consensus mechanisms, blockchains ensure that all honest nodes in the network reach a consensus on whether to accept or reject a block, based on predefined rules and criteria. The aim of this study is to introduce a novel consensus mechanism named Erdos, which seeks to address the shortcomings of existing consensus algorithms, such as the Proof of Work and Proof of Stake. Erdos emphasises security, decentralisation, and fairness. One notable feature of this mechanism is its equitable node-selection algorithm, which ensures equal opportunities for all nodes to engage in block creation and validation. In addition, Erdos implements a deterministic block finalisation process that guarantees the integrity and authenticity of the blockchain. The main contribution of this research lies in its innovative approach to deterministic block finalisation, which effectively mitigates the various security risks associated with blockchain systems.

A novel fully distributed discrete-time min–max consensus seeking algorithm with high convergence speed

Abstract In this paper, we propose a novel discrete-time consensus algorithm based on the new min–max criterion for the discrete-time second-order linear agents. To boost the convergence speed, the proposed algorithm allocates three different operating modes to the network agents. Unlike most of the existing consensus algorithms in which the links of the communication graph have specific weights and these weights are required to have positive lower bounds to achieve asymptotic convergence, the communication graph in this paper has unspecific link weights. Accordingly, because of data transmission errors and faults, the weights of the communication links can even go from a positive to a negative value. Thus, the proposed algorithm can bring the agents to consensus under more general conditions. To demonstrate the efficacy of the proposed algorithm, numerical simulations are performed, and their results are compared with those of the minimum consensus algorithm, which shows a significantly faster convergence speed.

DEVELOPMENT OF DAG BLOCKCHAIN MODEL

In this study the authors present an innovative approach to resolving scalability and efficiency challenges in blockchain technology through the integration of Directed Acyclic Graphs (DAGs). This approach helps to overcome the limitations of traditional blockchain systems, particularly in transaction processing. The classic blockchain has some problems as slow transaction processing and poor scalability. The authors offer Directed Acyclic Graph (DAG) as a scalable and energy-efficient alternative. The paper outlines the development of a DAG-based blockchain model, utilizing Python and Flask alongside the Ed25519 cryptographic curve. It conducts a comparative analysis of DAG with traditional consensus mechanisms like Proof of Work and Proof of Stake, underscoring the efficiency and security benefits of employment of DAG. The research methodology includes an extensive literature review and the construction of a practical model to demonstrate DAG's applicability in blockchain networks. Particularly notable is the exploration of DAG's potential in Internet of Things (IoT) ecosystems, addressing critical issues such as energy inefficiency and network communication challenges in existing consensus algorithms. The authors calculated the performance of the model and compared it with similar models on several evaluation criteria. The simulation results of our proposed model show an improvement in performance and security by minimizing end-to-end delay, time cost, energy consumption, and throughput. The model eliminates the limitations of classic blockchain systems, such as high latency and low scalability. It structures transactions and blocks as a DAG, which provides fast validation and high scalability without compromising security. The research demonstrates the transformative implications of DAG for advancing blockchain technology.

MuSelect Chain: trusted decentralized mutual selection through blockchain

Mutual selection (the process of two types of objects choosing each other) often occurs in practical applications, such as those concerning financial credit. Considering the increasing demands for credibility, traditional artificial methods often cannot satisfy the corresponding requirements for security and transparency. Blockchain technology has the characteristics of decentralization, traceability, transparency, and being tamper-resistant, making it a potential method for solving the abovementioned problems. However, the existing consensus algorithms have some shortcomings in terms of efficiency, fault tolerance, security, and other relevant aspects, rendering them unsuitable for direct implementation in a mutual selection scenario. In this study, a system for mutual selection operations, denoted as “MuSelect Chain," is established. First, the institution information initialization method on blockchain is developed via a smart contract, ensuring the authenticity of information stored on the chain. Second, a mutual selection relationship confirmation algorithm is designed to ensure a reliable automated mutual selection process. Next, considering the characteristics of nodes participating in the network, a consensus algorithm called “Proof-of-Leadership” is proposed to ensure consistency of information stored by different nodes on the chain. Subsequently, an incentive mechanism is established with the focus on improving MuSelect Chain efficiency. Finally, a MuSelect Chain prototype is built. Simulation results prove that the proposed MuSelect Chain is secure with strong fault tolerance.

Trochoidal patterns generation using generalized consensus strategy for double-integrator dynamic agents

This article studies a distributed consensus law to achieve a coordinated trochoidal formation among a team of mobile agents. The mobile agents are modeled as double integrators. We generalize an existing consensus algorithm for double-integrator dynamics (1) to achieve trochoidal patterns under a general network topology and (2) to extend the pattern formation in a 3-D plane. Since the trochoidal patterns are 2-D curves, the proposed control law allows us to specify the 2-D plane in the 3-D space on which the patterns will be formed. We modify the standard consensus protocol and manipulate the gains to create trochoidal motion through local information exchange by appropriately placing the eigenvalues of the system. Trochoids have been used in multifaceted robotic applications such as area coverage, hurricane sampling, and orbit designs for satellites, apart from their aesthetic appeal. Computer simulations and multi-robot experiments are presented to validate the theoretical findings.

Performance Analysis of Reputation based Proof of Credibility Consensus Mechanism for Blockchain based Applications

Blockchain is a decentralized transaction and data management technology first developed for the Bitcoin cryptocurrency. Blockchain technology is gaining popularity due to its core attributes which provides security, anonymity and data integrity without any involvement of third party. Consensus mechanism is a procedure by which all peers in the blockchain network agrees to a common agreement on the current state of the distributed ledger. It plays vital role in increasing efficiency of any blockchain environment. Though we have many consensus mechanisms working currently in different areas but they still lack in parameters like status of validators, latency, node failure etc. In Our proposed algorithm Proof of credibility, we have tried to incorporate all above factors in it. We have also implemented two or more factors of proposed algorithm and have evaluated and compared with existing consensus algorithm. In future research we aim to implement RPoC in any blockchain network and then we will evaluate it in terms of different evaluation parameters such as performance, security, scalability.

P-Raft: An Efficient and Robust Consensus Mechanism for Consortium Blockchains

With the rise in blockchain technology, consortium blockchains have garnered increasing attention in practical applications due to their decentralization and immutability. However, the performance of current consortium blockchains remains a significant obstacle to large-scale commercial adoption. The consensus algorithm, as a fundamental component of blockchain technology, plays a critical role in ensuring both security and efficiency. Unfortunately, most existing consensus algorithms for consortium blockchains are vote-based consensus algorithms, and the performance of vote-based consensus algorithms is largely limited by the performance of the leader node. Therefore, we present P-Raft: a high-performance consensus algorithm that builds upon the Raft algorithm and leverages node server performance evaluations. The primary objectives of this article included enhancing the efficiency of Leader processing, promoting the utilization of the consortium blockchain, and ensuring the robustness of Leader election. Specifically designed to meet the service requirements of consortium blockchain’s consensus mechanism, the P-Raft incorporated the Yasa model, which evaluated the instant machine performance of each node. The performance of each node is then associated with the election timeout, ensuring that nodes with superior performance are more likely to be chosen as Leaders. Additionally, we implemented a leader verification mechanism based on the Bohen-Lynn-Shacham (BLS) signature, which prevented malicious Byzantine nodes from becoming Leaders without receiving enough votes. Empirical findings show that the P-Raft can swiftly designate high-performing nodes as Leaders, thereby greatly improving service efficiency in the consensus process and the overall performance of the consensus mechanism. Ultimately, P-Raft is better equipped to meet the demands of consortium blockchain applications for large-scale transactions.

An Internet of Things Access Control Scheme Based on Permissioned Blockchain and Edge Computing

In the IoT (Internet of Things) environment, the existing access control schemes for device resources have some problems, such as poor scalability, high latency, security, and dynamics. Combining the advantages of the permissioned blockchain and edge computing, an access control scheme for the Internet of Things based on the permissioned blockchain and edge computing is proposed. By authenticating the user’s identity at the edge, the user’s identity is reliable and the response time is improved. In the ABAC (Attribute Based Access Control) model, the blockchain is regarded as a trusted entity, and the access control policy is written into a smart contract and deployed on the blockchain for calling. Most of the existing consensus algorithms have the problems of low throughput and scalability. A Kraft (Kademlia–Raft) consensus algorithm is introduced to solve the above issues. Security analysis and experimental results show that the scheme can achieve fine-grained, dynamic access control, has high throughput and low latency, and ensures security and reliability.

A Taxonomic Hierarchy of Blockchain Consensus Algorithms: An Evolutionary Phylogeny Approach

Countless endeavors have been undertaken to address the Byzantine Generals Problem, a generalization of the Two Generals Problem. The emergence of proof of work (PoW) for Bitcoin has led to various consensus algorithms diverging, and comparable existing consensus algorithms are being gradually utilized interchangeably, or only developed for each specific application domain. Our approach employs an evolutionary phylogeny method to classify blockchain consensus algorithms based on their historical development and current usage. To demonstrate the relatedness and lineage of distinct algorithms, as well as to support the recapitulation theory, which posits that the evolutionary history of its mainnets is mirrored in the development of an individual consensus algorithm, we present a taxonomy. We have created a comprehensive classification of past and present consensus algorithms that serves to organize this swift consensus algorithm evolution period. By recognizing similarities, we have compiled a list of different verified consensus algorithms and performed clustering on over 38 of these. Our new taxonomic tree presents five taxonomic ranks, including the evolutionary process and decision-making method, as a technique for analyzing correlation. Through the examination of the evolution and utilization of these algorithms, we have developed a systematic and hierarchical taxonomy that enables the grouping of consensus algorithms into distinct categories. The proposed method classifies various consensus algorithms according to taxonomic ranks and aims to reveal the direction of research on the application of blockchain consensus algorithms for each domain.

A Trust-Based Hierarchical Consensus Mechanism for Consortium Blockchain in Smart Grid

As the smart grid develops rapidly, abundant connected devices offer various trading data. This raises higher requirements for secure and effective data storage. Traditional centralized data management does not meet the above requirements. Currently, smart grid with conventional consortium blockchain can solve the above issues. However, in the face of a large number of nodes, existing consensus algorithms often perform poorly in terms of efficiency and throughput. In this paper, we propose a trust-based hierarchical consensus mechanism (THCM) to solve this problem. Firstly, we design a hierarchical mechanism to improve the efficiency and throughput. Then, intra-layer nodes use an improved Raft consensus algorithm and inter-layer nodes use the Byzantine Fault Tolerance algorithm. Thirdly, we propose a trust evaluation method to improve the election process of Raft. Finally, we implement a prototype system to evaluate the performance of THCM. The results demonstrate that the consensus efficiency is improved by 19.8%, the throughput is improved by 12.34%, and the storage is reduced by 37.9%.

PBFT optimization algorithm based on community contributions.

Community governance is the basic unit of social governance, and it is also an important direction for building a social governance pattern of co-construction, co-governance and sharing. Previous studies have solved the problems of data security, information traceability and participant enthusiasm in the process of community digital governance by building a community governance system based on blockchain technology and incentive mechanisms. The application of blockchain technology can solve the problems of low data security, difficulty in sharing and tracing and low enthusiasm on the part of multiple subjects regarding participation in community governance. The process of community governance involves the cooperation of multiple government departments and multiple social subjects. Under the blockchain architecture, the number of alliance chain nodes will reach 1000 with the expansion of community governance. The existing consensus algorithms for coalition chains are difficult to meet the high concurrent processing requirements under such large-scale nodes. An optimization algorithm has improved the consensus performance to a certain extent, but the existing systems still cannot meet the data needs of the community and are not suitable for community governance scenarios. Since the community governance process only involves the participation of relevant departments in users, all nodes in the network are not required to participate in the consensus under the blockchain architecture. Therefore, a practical Byzantine fault tolerance (PBFT) optimization algorithm based on community contribution (CSPBFT) is proposed here. First, consensus nodes are set according to different roles of participants in community activities, and participants are given different consensus permissions. Second, the consensus process is divided into different stages, and the amount of data processed by each consensus step is reduced. Finally, a two-level consensus network is designed to perform different consensus tasks, and reduce unnecessary communication between nodes to reduce the communication complexity of consensus among nodes. Compared with the PBFT algorithm, CSPBFT reduces the communication complexity from O(N2) to O(N2/C3). Finally, the simulation results show that, through rights management, network level setting and consensus phase division, when the number of nodes in the CSPBFT network is 100-400, the consensus throughput can reach 2000 TPS. When the node in the network is 1000, the instantaneous concurrency is guaranteed to be above 1000 TPS, which can meet the concurrent needs of the community governance scenario.

Preferential Delegated Proof of Stake (PDPoS)—Modified DPoS with Two Layers towards Scalability and Higher TPS

Security and a decentralized system are identical unique features of Blockchain. In recent times, blockchain-based cryptocurrency has become mainstream, but the growth and value of transactions and application services remain volatile. Among all these applications, finding a fast consensus in a large-scale blockchain network frequently requires extreme energy for huge computations and storing the complete blockchain for verification. These problems prevent further commercialization. Here, we present a solution to this problem. In this paper, we introduce a revised blockchain consensus algorithm, PDPoS, to address the scalability and transaction efficiency limitations. The symmetry in between Proof of Stake (PoS) and Delegated Proof of Stake (DPoS) is PoS. However, their ways of working are dissimilar. Here, we review the existing consensus algorithms, such as Proof of work (PoW), PoS and DPoS, as they are directly relating to our proposed work: PDPoS. We highligh Delegated Proof of Stake (DPoS)–based crypto-currencies, as they have much higher transactions per second (TPS) than PoW-based currencies. Then, we describe our proposed works and the working steps of the proposed PDPoS. Simulation results of the proposed PDPoS with two layers result in improved efficiency. We used TPS as the evolution criteria for showing that the proposed PDPoS is more efficient than DPoS. This makes the proposed work more relevant to the large-scale blockchain network as it is more efficient and requires less energy consumption.

AnonymousFox: An Efficient and Scalable Blockchain Consensus Algorithm

Blockchain is an innovative application of distributed storage, consensus algorithm, encryption algorithm, and other computer technologies. The consensus algorithm is the key to keep consistent among blockchain nodes. In most existing consensus algorithms, the leader node is responsible for proposing new block and communicating with other nodes. The leader node is easy to be the target of malicious attackers. With the increase of the number of nodes, the throughput and scalability of the blockchain system are also unsatisfactory. To address such issues, we propose the AnonymousFox consensus algorithm, which is suitable for the consortium blockchain and private blockchain. First, we design an anonymous leader node sorting algorithm, which hides the identity of the leader node through a variety of encryption algorithms. It periodically changes the ordered leader list to hide the target of malicious attackers. In addition, we design a consensus algorithm based on the anonymous identity of the leader node. Through one-to-many message communication, the amount of messages is greatly reduced. The complexity of the algorithm is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$O(n)$ </tex-math></inline-formula> . It solves the problem of ordered replication of state machines when the leader node is anonymous. We analyze the algorithm, it ensures safety and liveness when the fault nodes are less than one-third of the total. We evaluate the throughput, latency, scalability, resource consumption, exception processing, smart contract, and blockchain network through experiments. The throughput of the proposed algorithm is 49.3% higher than that of the practical Byzantine fault tolerance (PBFT) algorithm. The experimental results show that the proposed algorithm has high performance and scalability.

Novel Consensus Algorithm for Blockchain Using Proof-of-Majority (PoM)

The popularity of Blockchain is rising on account of its far-reaching applications in diverse industries. However, recently, blockchain has seen a rise of energy extensive mining pools which is leading to centralization, contradicting the basic blockchain tenet of decentralization. This letter proposes a novel consensus algorithm using Proof of Majority (PoM), to increase decentralization and to eliminate resource-intensive tasks leading to a reduced carbon footprint. We have evaluated the proposed algorithm in terms of latency and throughput. The proposed consensus algorithm outperforms popular existing consensus algorithms.

IoT-Chain and Monitoring-Chain Using Multilevel Blockchain for IoT Security.

In general, the Internet of Things (IoT) relies on centralized servers due to limited computing power and storage capacity. These server-based architectures have vulnerabilities such as DDoS attacks, single-point errors, and data forgery, and cannot guarantee stability and reliability. Blockchain technology can guarantee reliability and stability with a P2P network-based consensus algorithm and distributed ledger technology. However, it requires the high storage capacity of the existing blockchain and the computational power of the consensus algorithm. Therefore, blockchain nodes for IoT data management are maintained through an external cloud, an edge node. As a result, the vulnerability of the existing centralized structure cannot be guaranteed, and reliability cannot be guaranteed in the process of storing IoT data on the blockchain. In this paper, we propose a multi-level blockchain structure and consensus algorithm to solve the vulnerability. A multi-level blockchain operates on IoT devices, and there is an IoT chain layer that stores sensor data to ensure reliability. In addition, there is a hyperledger fabric-based monitoring chain layer that operates the access control for the metadata and data of the IoT chain to lighten the weight. We propose an export consensus method between the two blockchains, the Schnorr signature method, and a random-based lightweight consensus algorithm within the IoT-Chain. Experiments to measure the blockchain size, propagation time, consensus delay time, and transactions per second (TPS) were conducted using IoT. The blockchain did not exceed a certain size, and the delay time was reduced by 96% to 99% on average compared to the existing consensus algorithm. In the throughput tests, the maximum was 1701 TPS and the minimum was 1024 TPS.

Consensus of Switched Nonlinear Multiagent Systems Subject to Cyber Attacks

In this article, the output consensus problem is investigated for a class of switched nonlinear multiagent systems, where denial-of-service attacks and faults are considered in communication channels and agents’ actuators, respectively. The cyber attacks can damage the communication channels, which will cause the consensus performance degradation or even failure to achieve consensus. Compared with the existing results on consensus of multiagent systems under cyber attacks, the agents’ dynamics in this article are described by higher order heterogeneous switched nonlinear systems. The cyber attacks, actuator faults, asynchronous switchings, and the high complexity of the system make the existing consensus algorithms ineffective. A novel control scheme for the output consensus of the multiagent system subject to cyber attacks is proposed. By the graph theory, switched system theory and Lyapunov function method, sufficient conditions are presented to check whether the consensus objective can be achieved. Finally, the effectiveness of the proposed scheme is illustrated by two numerical simulations.

Optimization of PBFT Algorithm Based on QoS-Aware Trust Service Evaluation

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.