A Review: Consensus Algorithms on Blockchain

Blockchain is a distributed public ledger that keeps track of all transactions that have ever taken place in the system. As a distributed ledger, a consensus mechanism is required to ensure all the transaction functions properly. In order to reach a consensus, it is critical to emphasize the importance of performance and efficiency. The use of the right consensus algorithm will significantly improve the efficiency of a blockchain application. This paper reviewed several types of consensus algorithms used in blockchain and discusses the idea of a new consensus algorithm that can improve the performance of consortium blockchain.

A consensus time synchronization protocol in wireless sensor network

Time synchronization is one of the base techniques in wireless sensor networks(WSNs).This paper proposes a novel time synchronization protocol which is a robust consensusbased algorithm in the existence of transmission delay and packet loss.It compensates for transmission delay and packet loss firstly,and then,estimates clock skew and clock offset in two steps.Simulation and experiment results show that the proposed protocol can keep synchronization error below 2μs in the grid network of 10 nodes or the random network of 90 nodes.Moreover,the synchronization accuracy in the proposed protocol can keep constant when the WSN works up to a month.

Blockchain Based Consensus Algorithm and Trustworthy Evaluation of Authenticated Subgraph Queries

Over the past era,subgraph mining from a large collection of graph database is a crucial problem.In addition,scalability is another big problem due to insufficient storage.There are several security challenges associated with subgraph mining in today’s on-demand system.To address this downside,our proposed work introduces a Blockchain-based Consensus algorithm for Authenticated query search in the Large-Scale Dynamic Graphs(BCCA-LSDG).The two-fold process is handled in the proposed BCCA-LSDG:graph indexing and authenticated query search(query processing).A blockchain-based reputation system is meant to maintain the trust blockchain and cloud server of the proposed architecture.To resolve the issues and provide safe big data transmission,the proposed technique also combines blockchain with a consensus algorithm architecture.Security of the big data is ensured by dividing the BC network into distinct networks,each with a restricted number of allowed entities,data kept in the cloud gate server,and data analysis in the blockchain.The consensus algorithm is crucial for maintaining the speed,performance and security of the blockchain.Then Dual Similarity based MapReduce helps in mapping and reducing the relevant subgraphs with the use of optimal feature sets.Finally,the graph index refinement process is undertaken to improve the query results.Concerning query error,fuzzy logic is used to refine the index of the graph dynamically.The proposed technique outperforms advanced methodologies in both blockchain and non-blockchain systems,and the combination of blockchain and subgraph provides a secure communication platform,according to the findings.

Improved PBFT Consensus Algorithm Based on Node Role Division

The PBFT (Practical Byzantine Fault Tolerance, PBFT) consensus algorithm, which addressed the issue of malicious nodes sending error messages to disrupt the system operation in distributed systems, was challenging to support massive network nodes, the common participation over all nodes in the consensus mechanism would lead to increased communication complexity, and the arbitrary selection of master nodes would also lead to inefficient consensus. This paper offered a PBFT consensus method (Role Division-based Practical Byzantine Fault Tolerance, RD-PBFT) to address the above problems based on node role division. First, the nodes in the system voted with each other to divide the high reputation group and low reputation group, and determined the starting reputation value of the nodes. Then, the mobile node in the group was divided into roles according to the high reputation value, and a total of three roles were divided into consensus node, backup node, and supervisory node to reduce the number of nodes involved in the consensus process and reduced the complexity of communication. In addition, an adaptive method was used to select the master nodes in the consensus process, and an integer value was introduced to ensure the unpredictability and equality of the master node selection. Experimentally, it was verified that the algorithm has lower communication complexity and better decentralization characteristics compared with the PBFT consensus algorithm, which improved the efficiency of consensus.

LMI Consensus Condition for Discrete-time Multi-agent Systems

This paper examines a consensus problem in multiagent discrete-time systems, where each agent can exchange information only from its neighbor agents. A decentralized protocol is designed for each agent to steer all agents to the same vector. The design condition is expressed in the form of a linear matrix inequality. Finally, a simulation example is presented and a comparison is made to demonstrate the effectiveness of the developed methodology.

Enhancing IoT Data Security with Lightweight Blockchain and Okamoto Uchiyama Homomorphic Encryption

Blockchain technology has garnered significant attention from global organizations and researchers due to its potential as a solution for centralized system challenges.Concurrently,the Internet of Things(IoT)has revolutionized the Fourth Industrial Revolution by enabling interconnected devices to offer innovative services,ultimately enhancing human lives.This paper presents a new approach utilizing lightweight blockchain technology,effectively reducing the computational burden typically associated with conventional blockchain systems.By integrating this lightweight blockchain with IoT systems,substantial reductions in implementation time and computational complexity can be achieved.Moreover,the paper proposes the utilization of the Okamoto Uchiyama encryption algorithm,renowned for its homomorphic characteristics,to reinforce the privacy and security of IoT-generated data.The integration of homomorphic encryption and blockchain technology establishes a secure and decentralized platformfor storing and analyzing sensitive data of the supply chain data.This platformfacilitates the development of some business models and empowers decentralized applications to perform computations on encrypted data while maintaining data privacy.The results validate the robust security of the proposed system,comparable to standard blockchain implementations,leveraging the distinctive homomorphic attributes of the Okamoto Uchiyama algorithm and the lightweight blockchain paradigm.

Three-dimensional(3D)parametric measurements of individual gravels in the Gobi region using point cloud technique

Gobi spans a large area of China,surpassing the combined expanse of mobile dunes and semi-fixed dunes.Its presence significantly influences the movement of sand and dust.However,the complex origins and diverse materials constituting the Gobi result in notable differences in saltation processes across various Gobi surfaces.It is challenging to describe these processes according to a uniform morphology.Therefore,it becomes imperative to articulate surface characteristics through parameters such as the three-dimensional(3D)size and shape of gravel.Collecting morphology information for Gobi gravels is essential for studying its genesis and sand saltation.To enhance the efficiency and information yield of gravel parameter measurements,this study conducted field experiments in the Gobi region across Dunhuang City,Guazhou County,and Yumen City(administrated by Jiuquan City),Gansu Province,China in March 2023.A research framework and methodology for measuring 3D parameters of gravel using point cloud were developed,alongside improved calculation formulas for 3D parameters including gravel grain size,volume,flatness,roundness,sphericity,and equivalent grain size.Leveraging multi-view geometry technology for 3D reconstruction allowed for establishing an optimal data acquisition scheme characterized by high point cloud reconstruction efficiency and clear quality.Additionally,the proposed methodology incorporated point cloud clustering,segmentation,and filtering techniques to isolate individual gravel point clouds.Advanced point cloud algorithms,including the Oriented Bounding Box(OBB),point cloud slicing method,and point cloud triangulation,were then deployed to calculate the 3D parameters of individual gravels.These systematic processes allow precise and detailed characterization of individual gravels.For gravel grain size and volume,the correlation coefficients between point cloud and manual measurements all exceeded 0.9000,confirming the feasibility of the proposed methodology for measuring 3D parameters of individual gravels.The proposed workflow yields accurate calculations of relevant parameters for Gobi gravels,providing essential data support for subsequent studies on Gobi environments.

Distributed consensus algorithm for networked Euler-Lagrange systems with self-delays and uncertainties

A distributed coordinated consensus problem for multiple networked Euler-Lagrange systems is studied. The communication between agents is subject to time delays, unknown parameters and nonlinear inputs, but only with their states available for measurement. When the communication topology of the system is connected, an adaptive control algorithm with selfdelays and uncertainties is suggested to guarantee global full-state synchro-nization that the difference between the agent＇s positions and ve-locities asymptotically converges to zero. Moreover, the distributed sliding-mode law is given for chaotic systems with nonlinear inputs to compensate for the effects of nonlinearity. Finally, simulation results show the effectiveness of the proposed control algorithm.

A Novel GLS Consensus Algorithm for Alliance Chain in Edge Computing Environment

Edge computing devices are widely deployed.An important issue that arises is in that these devices suffer from security attacks.To deal with it,we turn to the blockchain technologies.The note in the alliance chain need rules to limit write permissions.Alliance chain can provide security management functions,using these functions to meet the management between the members,certification,authorization,monitoring and auditing.This article mainly analyzes some requirements realization which applies to the alliance chain,and introduces a new consensus algorithm,generalized Legendre sequence(GLS)consensus algorithm,for alliance chain.GLS algorithms inherit the recognition and verification efficiency of binary sequence ciphers in computer communication and can solve a large number of nodes verification of key distribution issues.In the alliance chain,GLS consensus algorithm can complete node address hiding,automatic task sorting,task automatic grouping,task node scope confirmation,task address binding and stamp timestamp.Moreover,the GLS consensus algorithm increases the difficulty of network malicious attack.

Microcontroller Design Based on Dynamic Heterogeneous Redundancy Architecture

Redundancy control can effectively enhance the stability and robustness of a system.Based on the conventional redundancy control switchover and majority arbitration strategy,this paper introduces the concept of heterogeneity and dynamics,constructs a dynamic heterogeneous redundancy-based microcontroller architecture DHR-MCU,and designs a fixed-leader distributed consensus algorithm that satisfies the program running state control of this architecture.The theoretical analysis and actual measurement of the prototype system prove that this architecture has good anti-attack and self-recovery capabilities under normal functions and performances and meets the general robust features in terms of safety and security.

Vertical Federated Learning Based on Consortium Blockchain for Data Sharing in Mobile Edge Computing

The data in Mobile Edge Computing(MEC)contains tremendousmarket value,and data sharing canmaximize the usefulness of the data.However,certain data is quite sensitive,and sharing it directly may violate privacy.Vertical Federated Learning(VFL)is a secure distributed machine learning framework that completes joint model training by passing encryptedmodel parameters rather than raw data,so there is no data privacy leakage during the training process.Therefore,the VFL can build a bridge between data demander and owner to realize data sharing while protecting data privacy.Typically,the VFL requires a third party for key distribution and decryption of training results.In this article,we employ the consortium blockchain instead of the traditional third party and design a VFL architecture based on the consortium blockchain for data sharing in MEC.More specifically,we propose a V-Raft consensus algorithm based on Verifiable Random Functions(VRFs),which is a variant of the Raft.The VRaft is able to elect leader quickly and stably to assist data demander and owner to complete data sharing by VFL.Moreover,we apply secret sharing todistribute the private key to avoid the situationwhere the training result cannot be decrypted if the leader crashes.Finally,we analyzed the performance of the V-Raft and carried out simulation experiments,and the results show that compared with Raft,the V-Raft has higher efficiency and better scalability.

Distributed Cooperative Control Algorithm for Multi-UAV Mission Rendezvous

Multiple unmanned aerial vehicles(UAVs)cooperative operation is the main form for UAVs fighting in battlefield,and multi-UAV mission rendezvous is the premise of cooperative reconnaissance and attack missions.We propose a rendezvous control strategy,which divides the rendezvous process into two parts:The loose formation rendezvous and the close formation rendezvous.In the first stage,UAVs are supposed to reach the specific target locations simultaneously and form a loose formation.A distributed control strategy based on first-order consensus algorithm is presented to achieve this goal.Then the second stage is designed based on the second-order consensus algorithm to complete the transition from the loose formation to the close formation.This process needs the speeds and heading angles of UAVs to reach an agreement.Besides,control algorithms with a virtual leader are proposed,by which the formation states can reach a specific value.Finally,simulation results show that the control algorithms are capable of realizing the mission rendezvous of multi-UAV and the consistence of UAVs′final states,which verify the effectiveness and feasibility of the designed control strategy.

Model of decentralized cross-chain energy trading for power systems

With the development of the energy Internet, more distributed generators are connected to the power grid, resulting in numerous heterogeneous energy networks. However, different energy networks cannot perform efficient energy trading in the centralized management mode, this deeply affecting the complementary ability of heterogeneous energy, resulting in the islanded energy phenomenon. In this model, the same energy on the chain is traded within the chain, and the heterogeneous energy on different chains is traded across chains. To trade energy between heterogeneous energy networks more efficiently, the blockchain-based cross-chain model is proposed based on the existing infrastructure. Heterogeneous energy nodes are assigned to different energy sub-chains and cross-chain energy transactions are performed through a relay-chain, which utilizes the improved Boneh–Lynn–Shacham signature scheme consensus algorithm based on the proof-of-stake and practical Byzantine fault tolerance. The experimental simulations on energy trading efficiency, throughput, and security, show its superiority over existing systems. Further, the simulation results provide a reference for the application of cross-chain technology in energy interconnection.

Can blockchain link the future?

Recently,decentralization has been extensively explored by researchers.Blockchain,as a representation of decentralized technology,has attracted attention with its unique characteristics,such as irrevocability and security.Consequently,herein,we introduce cutting-edge blockchain technologies from four directions:blockchain system,consensus algorithms,smart contract,and scalability.Subsequently,we analyze the current lack of consensus mechanism,fault tolerance,and block capacity of the blockchain,and the integration of blockchain into 5G/6G mobile communication.Furthermore,we discuss the possible applications of blockchain in intellectual property protection,the Internet of Things,digital twins,standardization,and epidemic prevention and control.Finally,explore the impacts and solutions of blockchain on human society beyond technology.

Consensus control for heterogeneous uncertain multi-agent systems with hybrid nonlinear dynamics via iterative learning algorithm

In this study,We propose a compensated distributed adaptive learning algorithm for heterogeneous multi-agent systems with repetitive motion,where the leader's dynamics are unknown,and the controlled system's parameters are uncertain.The multiagent systems are considered a kind of hybrid order nonlinear systems,which relaxes the strict requirement that all agents are of the same order in some existing work.For theoretical analyses,we design a composite energy function with virtual gain parameters to reduce the restriction that the controller gain depends on global information.Considering the stability of the controller,we introduce a smooth continuous function to improve the piecewise controller to avoid possible chattering.Theoretical analyses prove the convergence of the presented algorithm,and simulation experiments verify the effectiveness of the algorithm.

Constrained cooperative control design for distributed morphing wing systems

An efficient design method is proposed for the cooperative control problem of morphing wing systems with distributed structures and bounded control inputs. The multi-agent model of the distributed morphing wing system is established. The cooperative controllers with saturation constraints are presented. By introducing the concepts in consensus algorithms, the cooperative information links in the controllers are described by graphs, and the corresponding Laplacian matrix is defined. The design conditions of the cooperative controllers are proposed, in the form of linear matrix inequalities. For the case of undirected information links, the controller design conditions are simplified as algebraic inequalities, which highly reduce the computation cost. The designed controllers are implemented on a distributed morphing wing platform, and experiments are carried out. Simulation and experiment results show that the controllers can make all the actuating units in the morphing wing system cooperatively achieve the desired positions, which demonstrates the effectiveness of the proposed theory.

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%.

Consensus-based dispatch optimization of a microgrid considering meta-heuristic-based demand response scheduling and network packet loss characterization

The uncertainty inherent in power load forecasts represents a major factor in the mismatches between supply and demand in renewables-rich electricity networks, which consequently increases the energy bills and curtailed generation. As the transition to a power grid founded on the so-called grid-of-grids becomes more evident, the need for distributed control algorithms capable of handling computationally challenging problems in the energy sector does so as well. In this light, the consensus-based distributed algorithm has recently been shown to provide an effective platform for solving the complex energy management problem in microgrids. More specifically, in a microgrid context, the consensus-based distributed algorithm requires reliable information exchange with customers to achieve convergence. However, packet losses remain an important issue, which can potentially result in the failure of the overall system. In this setting, this paper introduces a novel method to effectively characterize such packet losses during information exchange between the customers and the microgrid operator, whilst solving the microgrid scheduling optimization problem for a multi-agent-based microgrid. More specifically, the proposed framework leverages the virulence optimization algorithm and the earth-worm optimization algorithm to optimally shift the energy consumption during peak periods to lower-priced off-peak hours. The effectiveness of the proposed method in minimizing the overall active power mismatches in the presence of packet losses has also been demonstrated based on benchmarking the results against the business-as-usual iterative scheduling algorithm. Also, the robustness of the overall meta-heuristic- and multi-agent-based method in producing optimal results is confirmed based on comparing the results obtained by several well-established meta-heuristic optimization algorithms, including the binary particle swarm optimization, the genetic algorithm, and the cuckoo search optimization.

Consensus algorithm for medical data storage and sharing based on master–slave multi-chain of alliance chain

The safe storage and sharing of medical data have promoted the development of the public medical field.At the same time,blockchain technology guarantees the safe storage and sharing of medical data.However,the consensus algorithm in the current medical blockchain cannot meet the requirements of low delay and high throughput in the large-scale network,and the identity of the primary node is exposed and vulnerable to attack.Therefore,this paper proposes an efficient consensus algorithm for medical data storage and sharing based on a master–slave multi-chain of alliance chain(ECA_MDSS).Firstly,institutional nodes in the healthcare alliance chain are clustered according to geographical location and medical system structure to form a multi-zones network.The system adopts master–slave multi-chain architecture to ensure security,and each zone processes transactions in parallel to improve consensus efficiency.Secondly,the aggregation signature is used to improve the practical Byzantine fault-tolerant(PBFT)consensus to reduce the communication interaction of consensus in each zone.Finally,an efficient ring signature is used to ensure the anonymity and privacy of the primary node in each zone and to prevent adaptive attacks.Meanwhile,a trust model is introduced to evaluate the trust degree of the node to reduce the evil done by malicious nodes.The experimental results show that ECA_MDSS can effectively reduce communication overhead and consensus delay,improve transaction throughput,and enhance system scalability.

Consensus seeking in multiagent cooperative control systems with bounded control input

Consensus algorithms in multiagent cooperative control systems with bounded control input are studied in this paper.Consensus algorithms are considered for the single-integrator dynamics and double-integrator dynamics under different communication interaction topologies,and show that consensus is reached asymptotically using the algorithm proposed in this paper for the single-integrator dynamics if the undirected interaction graph is connected,and consensus is reached asymptotically if the directed interaction graph is strongly connected,respectively.In addition,the paper further shows that consensus is reached asymptotically using the algorithm proposed for the double-integrator dynamics if the directed interaction graph is strongly connected.The effectiveness of these algorithms is demonstrated through simulations.