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.

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 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.

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.

Comparing Eight Computing Algorithms and Four Consensus Methods to Analyze Relationship between Land Use Pattern and Driving Forces

Although many computing algorithms have been developed to analyze the relationship between land use pattern and driving forces (RLPDF), little has been done to assess and reduce the uncertainty of predictions. In this study, we investigated RLPDF based on 1990, 2005 and 2012 datasets at two spatial scales using eight state-of-the-art single computing algorithms and four consensus methods in Jinjing rive catchment in Hunan Province, China. At the entire catchment scale, the mean AUC values were between 0.715 (ANN) and 0.948 (RF) for the single-algorithms, and from 0.764 to 0.962 for the consensus methods. At the subcatchment scale, the mean AUC values between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. At the subcatchment scale, the mean AUC values were between 0.624 (CTA) and 0.972 (RF) for the single-algorithms, and from 0.758 to 0.979 for the consensus methods. The result suggested that among the eight single computing algorithms, RF performed the best overall for woodland and paddy field;consensus method showed higher predictive performance for woodland and paddy field models than the single computing algorithms. We compared the simulation results of the best - and worst-performing algorithms for the entire catchment in 2012, and found that approximately 72.5% of woodland and 72.4% of paddy field had probabilities of occurrence of less than 0.1, and 3.6% of woodland and 14.5% of paddy field had probabilities of occurrence of more than 0.5. In other words, the simulation errors associated with using different computing algorithms can be up to 14.5% if a probability level of 0.5 is set as the threshold. The results of this study showed that the choice of modeling approaches can greatly affect the accuracy of RLPDF prediction. The computing algorithms for specific RLPDF tasks in specific regions have to be localized and optimized.

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.

Hipro-HoneyBadgerBFT:一种基于并行运行机制的高性能异步共识算法

在大数据时代,信息流通数量极速增长。区块链技术非常适用于数据共享系统。目前数据共享系统搭建在区块链网络中会出现一些性能方面的瓶颈。为此,在HoneyBadgerBFT共识算法的基础上,提出一种更加高效的异步拜占庭共识算法——Hipro-HoneyBadgerBFT。该算法在不牺牲安全性的前提下,可以降低系统的计算资源,提升算法的共识效率。实验结果表明:Hipro-HoneyBadgerBFT共识算法的时延约为HoneyBadgerBFT共识算法时延的1%,吞吐量提升了7倍,CPU利用率则减少了54.09%。

二值分解压缩和Consensus算法

奇异值分解(SVD)是一种流行的用于高维数据压缩的方法,二值分解是奇异值分解的一种简化形式。实现二值分解的主要算法有两种:迭代启发式算法和贪婪算法。但这两种算法都不是很理想的算法:迭代启发式算法在很多情况下不能保证收敛性,贪婪算法不满足大型数值矩阵分解的需要。采用了一种新的算法来实现二值分解:Consensus的算法。Consensus算法可在渐进多项式时间内找到一般图中的极大二分团。对于某些二分图,该算法的复杂度是多项式时间的。实验结果表明,当迭代启发式算法不起作用时,Consensus算法是一种很好的求解二值分解的方法。该算法远比贪婪算法的效率高,且具有稳定收敛性。

Research on Distributed Coordination Control Method for Microgrid System Based on Finite-time Event-triggered Consensus Algorithm

Microgrids are networked control systems with multiple distributed generators(DGs).Microgrids are associated with many problems,such as communication delays,high sampling rates,and frequent controller updates,which make it challenging to realize coordination control among the DGs.Therefore,finite-time consensus algorithms and event-triggered control methods are combined to propose a distributed coordination control method for microgrid systems.The DG in the microgrid system serves as an agent node in the control network,and a distributed secondary controller is designed using finite-time consensus algorithm,such that the frequency and voltage restoration control has a faster convergence time and better anti-interference performance.The event-triggered function was designed based on the state information of the agents.The controller exchanges the state information at the trigger instants.System stability is analyzed using the Lyapunov stability theory,and it is verified that the controller cannot exhibit the Zeno phenomenon in the event-triggered process.A simulation platform was developed in Matlab/Simulink to verify that the proposed control method can effectively reduce the frequency of controller updates during communication delays and the burden on the communication network.

Detecting community structure using label propagation with consensus weight in complex network

Community detection is a fundamental work to analyse the structural and functional properties of complex networks. The label propagation algorithm （LPA） is a near linear time algorithm to find a good community structure. Despite various subsequent advances, an important issue of this algorithm has not yet been properly addressed. Random update orders within the algorithm severely hamper the stability of the identified community structure. In this paper, we executed the basic label propagation algorithm on networks multiple times, to obtain a set of consensus partitions. Based on these consensus partitions, we created a consensus weighted graph. In this consensus weighted graph, the weight value of the edge was the proportion value that the number of node pairs allocated in the same cluster was divided by the total number of partitions. Then, we introduced consensus weight to indicate the direction of label propagation. In label update steps, by computing the mixing value of consensus weight and label frequency, a node adopted the label which has the maximum mixing value instead of the most frequent one. For extending to different networks, we introduced a proportion parameter to adjust the proportion of consensus weight and label frequency in computing mixing value. Finally, we proposed an approach named the label propagation algorithm with consensus weight （LPAcw）, and the experimental results showed that the LPAcw could enhance considerably both the stability and the accuracy of community partitions.

Necessary and Sufficient Conditions for Consensus in Third Order Multi-Agent Systems

We deal with a consensus control problem for a group of third order agents which are networked by digraphs.Assuming that the control input of each agent is constructed based on weighted difference between its states and those of its neighbor agents, we aim to propose an algorithm on computing the weighting coefficients in the control input. The problem is reduced to designing Hurwitz polynomials with real or complex coefficients. We show that by using Hurwitz polynomials with complex coefficients, a necessary and sufficient condition can be obtained for designing the consensus algorithm. Since the condition is both necessary and sufficient, we provide a kind of parametrization for all the weighting coefficients achieving consensus. Moreover, the condition is a natural extension to second order consensus, and is reasonable and practical due to its comparatively decreased computation burden. The result is also extended to the case where communication delay exists in the control input.

Consensus-Based Distributed Control with Communication Time Delays for Virtual Synchronous Generators in Isolate Microgrid

A consensus-based distributed control method of coordinated VSGs with communication time delays in isolate microgrid is proposed. When time delays are considered in communication, there are some effects on frequency restoration and active power output allocation. In the control structure, only local information exchange is needed, while the final frequency can be controlled to the nominal value and the VSGs can automatically share loads according to their rated values. An AC microgrid with three VSGs and some loads is implemented. The proposed control strategy is verified by MATLAB/ Simulink simulation results.

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.

论政策共识构建中的算法支配:模式与维度

人类社会进入算法时代,政策共识构建无论是在科学化发展还是在民主化进程中都受到算法影响,当这种影响发展到一定程度时则会出现算法支配的现象。根据算法的自动化程度与相对于人类的独立性,政策共识构建中的算法支配可分为四种模式:工具性支配、平台式支配、博弈性支配、自动化支配。四种模式对政策共识构建的影响体现在不同层面,但都是从四个方面展开:通过代码设计对政策诉求进行标准化解读;对个体感知做出隐蔽控制以此编辑诉求内容;形成严密的审查体系对行为进行监控并做出引导;设定计算规则塑造共识构建的程序和方式。总体而言,政策共识构建的算法支配体现为技术支配与权力支配的混合,需要基于对算法的全面认知做出应对。

基于区块链共识激励机制的新型联邦学习系统

随着云存储、人工智能等技术的发展,数据的价值已获得显著增长。但由于昂贵的通信代价和难以承受的数据泄露风险迫使各机构间产生了“数据孤岛”问题,大量数据无法发挥它的经济价值。虽然将区块链作为承载联邦学习的平台能够在一定程度上解决该问题,但也带来了三个重要的缺陷:1)工作量证明(Proof of Work,POW)、权益证明(Proof of Stake,POS)等共识过程与联邦学习训练过程并无关联,共识将浪费大量算力和带宽;2)节点会因为利益的考量而拒绝或消极参与训练过程,甚至因竞争关系干扰训练过程;3)在公开的环境下,模型训练过程的数据难以溯源,也降低了攻击者的投毒成本。研究发现,不依靠工作量证明、权益证明等传统共识机制而将联邦学习与模型水印技术予以结合来构造全新的共识激励机制,能够很好地避免联邦学习在区块链平台上运用时所产生的算力浪费及奖励不均衡等情况。基于这种共识所设计的区块链系统不仅仍然满足不可篡改、去中心化、49%拜占庭容错等属性,还天然地拥有49%投毒攻击防御、数据非独立同分布(Not Identically and Independently Distributed,Non-IID)适应以及模型产权保护的能力。实验与论证结果都表明,本文所提出的方案非常适用于非信任的机构间利用大量本地数据进行商业联邦学习的场景,具有较高的实际价值。

基于侧链和信任管理模型的数据共享方案

为解决在不信任的区块链环境中由于数据转售而造成的用户不愿共享数据等问题,提出一种基于侧链和信任管理模型的数据共享方案。使用信任管理模型量化节点信任值,将节点信任值集成到数据共享智能合约中,为用户提供可信的共享环境和动态的访问控制接口。对联盟链进行侧链扩容,使用信任管理模型优化共识算法。规定主链使用具有拜占庭容错能力的T-PBFT算法,侧链使用仅适用于高信任场景的T-Raft算法。用户根据预先设置的阈值动态决定在主链或侧链共享数据。实验就方案的安全性和性能进行分析,表明了该方案的可行性和有效性。

基于信誉分类的拜占庭容错共识算法

针对许可区块链场景下实用拜占庭容错(Practical Byzantine Fault Tolerance,PBFT)共识算法通信开销大、主节点选取随意以及吞吐量低等问题,通过引入并优化信誉评分模型(Reputation Scoring Model,RSM)。提出了一种基于信誉分类的拜占庭容错(Byzantine Fault Tolerance Based on Reputation Classification,RCBFT)共识算法。定义RSM,依据节点的历史共识行为所获得的信誉评分排序对参与节点进行动态分类以及分级管理,提出基于信誉分类的多层次节点架构;在可信节点层中随机选取节点来担任主节点,优化主节点选取机制;设计了缓冲节点层类型转换策略(Type Conversion Strategy for Nodes,TCSN),兼顾了环境等非主观因素导致低信誉评分的诚实节点不能参与共识的问题,使得诚实节点尽可能多地参与共识,而拜占庭节点快速下降到最差类型中限制共识权限;RCBFT共识算法还对传统三阶段共识协议进行优化,减少通信开销,在确保容错性的同时能够提高算法性能。实验分析表明,相较于PBFT共识算法,RCBFT共识算法能够提升交易吞吐量,降低通信开销与共识时延。

基于模型预测的直流微网多电力弹簧协同控制策略研究

针对新能源接入、负荷投切所导致的直流微电网电压质量下降与系统呈现低惯性的问题,传统惯性控制随着电网规模的扩大适应性降低,因此提出一种多直流电力弹簧(DC electric springs,DCESs)单元下的直流微网电压协同控制策略,首先采用分布式一致性算法通过稀疏通信网络交换本地信息与相邻信息,求解全局母线电压平均值,并引入积分环节提高传统通信方式的收敛性。接着考虑系统负荷投切以及源侧功率波动导致的电压突变,基于DCES中的双向全桥DC/DC变换器构建预测模型,令各DCES根据系统功率波动状态自适应求解最佳虚拟电容值,平滑直流母线电压,提升了动态响应速度,同时分析了系统电压的收敛性与稳定性。最后通过MATLAB/Simulink在随机波动负荷、实际光伏场景下从电压质量、即插即用性能、系统惯性3个方面验证了模型的有效性,所提出的控制策略在保证系统电压平稳的同时,具有更优的动态响应能力。

事件触发改进一致性算法的孤岛混合微电网并联互联变流器分布式协调控制策略

在交直流混合微电网中,并联互联变流器(parallel bidirectional power converters,BPCs)可以实现大容量的功率传输,以满足新型电力系统在空间上的供需匹配。如何在占用更少资源的同时协调控制BPCs实现功率的比例共享,是交直流混合微电网中BPCs控制的研究难点。因此,该文设计了一种针对BPCs的事件触发改进一致性协调控制策略。以归一化下垂控制为基础,提出了改进的比例功率一致性算法,实现BPCs间高精度比例功率共享。在此之上,基于BPCs比例功率误差建立事件触发改进一致性算法,并预设触发函数的预判阈值,从而降低系统在稳定状态下的通信次数。最后进行仿真对比分析,结果表明该文提出的方法相比基本一致性算法通信量减少98.35%;同时,与现有控制策略相比,该文提出的方法有着更好的控制性能。