基于凝聚型层次聚类的PBFT优化共识机制

面对粮食联盟链网络中的大量共识节点,由于传统实用拜占庭容错(practical Byzantine fault tolerance,PBFT)共识算法效率低下,导致通信能耗过高,从而极大地增加信息泄露和数据造假的风险。针对上述难题,本文提出了一种基于凝聚型层次聚类(agglomerative hierarchical clustering,AHC)的PBFT优化共识算法。首先,利用AHC算法对所有网络共识节点进行目标划分和聚类;其次,使所有簇并行发生PBFT共识;最后,通过簇间主节点共识达成消息一致。实验结果表明,该改进算法能够有效降低能量开销,并提高共识效率和吞吐量。     

区块链共识算法研究综述

区块链已广泛应用于货币金融、通信网络、信息安全、物联网、电力运行管理和社会职能管理等多个领域,但依然存在许多急需解决的问题。共识算法是区块链的核心技术之一,是区块链各节点达成一致性最为重要的底层技术,是解决区块链吞吐量太小、通信存在延迟等一系列问题的关键技术,是区块链安全运行的重要保证。文中基于区块链共识算法的设计原理,主要介绍了区块链的构成、分类、架构、上链、节点处理流程及存在的问题,重点阐述了现有PoW、PoS、DPoS、PBFT、Raft、Paxos、Ripple等共识算法设计思路、共识理论及流程,对共识算法中的共性问题,即算法优化、算法效果进行了综合概述和分析,并对区块链共识算法研究进行了展望,希望开发出更加高效、安全的共识算法。     

异步区块链支持的安全频谱共享

针对目前频谱稀缺的困境,一个经济有效的解决方案是将未充分利用的授权频谱以机会的方式分配给未授权用户。然而,实现大规模频谱共享面临激励缺失、隐私泄露、安全威胁和时延过大等挑战。利用区块联盟链技术的安全机制,设计了由频谱接入层、区块链网络层、区块链共识层构成的区块链动态频谱接入系统。该系统采用异步实时拜占庭容错(Practical Byzantine Fault Tolerance,PBFT)改善共识延时,设计基于最优匹配算法的匹配方案,提高频谱复用率。经仿真验证,该方案频谱复用率提升近6%。相比于实时拜占庭机制,所提方案减少了系统延时,提升吞吐量近129%。     

基于区块链高速共识方法的物联网源端数据存储技术研究

针对物联网源端数据在传输过程中易被篡改、可信度低等痛点，结合区块链技术分布式存储、数据可溯源、不可篡改等特性，在传统的物联网数据传输方式的基础上，研究了基于区块链高速共识方法的物联网源端数据存储方式。将区块链共识节点部署在采集侧的区块链物联网关，并使用区块链对采集传感器设备进行身份认证，保证数据只能由经过区块链认证的设备上链，确保数据从源头可信。同时将区块链共识节点部署于服务器机房和物联网采集侧，保证了当采集侧区块链共识节点由于故障断开连接时，区块链网络仍能稳定运行。同时，研究并优化了区块链主节点选举方法和共识方法，以达到提高联盟链稳定性和数据传输安全性的目的，实现物联网采集数据从源头到存储全程可信、可控、可溯源。     

网络共识区块链模型构建与实现

针对B/S架构以服务器作为中心存在安全隐患的问题,提出一种真实网络环境下共识区块链方案.方案基于网络中存在的多个节点,利用区块链去中心化机制存储交易数据,利用共识机制完成记账权校验.为了保护交易数据的隐私,方案对交易数据进行了哈希加密运算,同时,为了解决网络中不同节点数据同步的问题,根据最长区块链来更新网络中的节点.为...     

基于条件代理重加密的区块链医疗数据共享模型

医疗数据具有较高的私密性和敏感性，然而以往的医疗数据共享过程中往往采取中心化的集中式存储，这带来了数据隐私泄露和非法篡改的风险。针对上述问题，文中将区块链和代理重加密技术结合起来，提出基于条件代理重加密的区块链医疗数据共享模型。各级医院组成联盟区块链，采用改进的实用拜占庭共识机制选取代理节点，提高了节点达成共识的效率。借助于云服务器海量的存储能力，将患者的医疗数据存储在云服务器，联盟区块链中保存条件摘要密文，数据请求者在联盟链上进行条件搜索获取患者医疗数据，同时利用代理重加密技术实现特定数据请求者和第三方用户之间的细粒度共享。实验结果证明，基于条件代理重加密的区块链医疗数据共享模型在通信和计算开销方面更具优势。     

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...     

基于区块链的销售佣金结算方法

针对运营商销售佣金结算领域计算过程不透明、结算流程难以追溯、历史信息存证困难等问题,基于区块链技术提出一种销售佣金结算方法,设计区块数据模型,将结算全流程、全要素数据上链存证.设计基于区块链的结算流程,实现智能合约批价、历史结算轨迹追溯查询功能;在实用拜占庭容错算法(PBFT)的基础上,对其鲁棒性进行改进,提出鲁棒拜占庭共识算法(RBFT),提升系统可用性.该方法在"江苏电信区块链一线激励结算平台"上实践应用,解决了"结算流程不清晰"、"不结算原因看不懂"等业务痛点,此外在加强佣金数据存证监管方面也起到了积极作用.     

基于联盟链的运营商最佳缓存策略

基于区块链的边缘缓存技术可以实现更大范围的内容共享并提高缓存内容的使用效率。针对不同运营商各自建设边缘设备,缓存内容相互隔离,难以共享信息的问题,该文提出一种基于联盟链的边缘缓存系统框架并设计了内容共享和交易流程,实现了不同运营商之间的内容共享。此外,为了降低高维缓存节点的共识开销,设计了基于内容缓存的部分实用拜占庭容错(pPBFT)共识机制,仅选取缓存相关内容的联盟链节点作为验证智能合约的执行节点。最后,将运营商内容共享所带来的收益进行量化并构建为最大化收益的优化问题。通过所提出的内容缓存算法,得到了最优缓存决策的闭式表达式和与内容流行度相关的最优缓存策略。仿真结果表明,在该框架中所提出的共识机制和缓存策略能够有效增加运营商的缓存收益。     

一种基于ε-greedy的领导选举方法

随着区块链的广泛部署,无人协同等延迟敏感型的应用对区块链系统的低时延需求日益提高。在协同场景下,区块链节点通常跨地域部署,节点异构性较强。在基于领导节点的拜占庭容错(Byzantine Foult Tolerant, BFT)共识协议中,不稳定的或能力较差的领导节点将导致不必要的高延迟,并降低区块链的可用性,特别是在资源有限的移动或传感器网络下。针对上述问题,提出了ε-LE,一种带有网络感知的领导选举方法,基于节点到领导节点的通信延迟测量结果,采用ε-greedy策略对领导节点进行选择,使得当前性能较优或网络中关键位置的节点具有更高概率成为领导节点,从而优化共识延迟。相较于AWARE等方法,ε-LE实现O(N)的通信复杂度,更加适用于具备线性通信复杂度的共识协议。实验结果表明,ε-LE能够选择可优化集群共识延迟的节点作为领导节点,在线性拓扑网络中实现了约21%的吞吐量提升。     

Research on sybil attack in defense blockchain based on improved PBFT algorithm

Aiming at the problem that sybil attack has great harm to block chain technology,a method to improve the PBFT algorithm in the alliance chain to defend against sybil attacks was proposed.Firstly,using the idea of consensus algorithm based on proof of rights and interests,a reputation model was established,the reputation value of each node accorded to the behavior of each node in the consensus process was calculated,and different discourse rights accorded to the size of the reputation value was given.Then pre-commit phase was added to the PBFT algorithm to reduce the number of communication between nodes.The solution through formal analysis and reasoning and security testing shows that the improved PBFT algorithm can not only effectively defend against sybil attacks in the blockchain,but also make the performance of the blockchain system in terms of TPS and block generation delay.     

Extensive game analysis and improvement strategy of DPOS consensus mechanism

Delegated proof-of-stake ( DPOS) consensus mechanism is widely adopted in blockchain platforms, but problems exist in its current applications. In order to explore the security risks in the voting attack of the DPOS consensus mechanism, an extensive game model between nodes was constructed, and it was concluded that the DPOS consensus mechanism relies too much on tokens, and the possibility of node attacks is very high. In order to solve the problems of frequent changes of DPOS consensus mechanism nodes, inactive node voting, excessive reliance on tokens, and malicious nodes, a dynamic, credible, and attack-evading DPOS consensus mechanism was proposed. In addition, the Python simulation results show that the improved Bayesian voting algorithm is effective in calculating node scores.     

Imp Raft: a consensus algorithm based on Raft and storage compression consensus for IoT scenario

In order to meet various challenges in the Internet of things (IoT), such as identity authentication, privacy preservation of distributed data and network security, the integration of blockchain and IoT became a new trend in recent years. As the key supporting technology of blockchain, the consensus algorithm is a hotspot of distributed system research. At present, the research direction of the consensus algorithm is mainly focused on improving throughput and reducing delay. However, when blockchain is applied to IoT scenario, the storage capacity of lightweight IoT devices is limited, and the normal operations of blockchain system cannot be guaranteed. To solve this problem, an improved version of Raft (Imp Raft) based on Raft and the storage compression consensus (SCC) algorithm is proposed, where initialization process and compression process are added into the flow of Raft. Moreover, the data validation process aims to ensure that blockchain data cannot be tampered with. It is obtained from experiments and analysis that the new proposed algorithm can effectively reduce the size of the blockchain and the storage burden of lightweight IoT devices.     

基于节点动静态指标的电网节点重要度的评估研究

随着智能电网技术的不断发展,对高可靠性的智能电网的精确评估提出了更高的要求。智能电网中重要节点的故障将会导致大规模停电,因此对智能电网中重要节点的评估是评估智能电网可靠性程度的重要体现。文中针对节点所处的局部环境、全局属性、网络拓扑结构以及节点所承载负荷等级等多个不同的动静态综合指标进行研究,以这些综合指标模型来评估节点在智能电网中的重要度,最后使用TOPSIS方法将动静态指标糅合,共同对智能电网节点重要度进行评估,并对IEEE-30节点进行了仿真验证。结果显示节点6的重要度较高,应对其重点保护。     

Blockchain-driven distributed consensus mechanism in defensing Byzantine attack for the Internet of spectrum device

To meet the requirement of the precisely spectrum sharing triggered by large-scale and ultra-dense deployment of mobile internet and internet of things,a framework based on blockchain technology for networking the massive personal wireless devices to form the Internet of spectrum device (IoSD) was proposed.The architecture of cloud with edge computing was proposed as the architecture of IoSD,which consists of spectrum management server,mobile base station,and personal wireless devices.The mechanism of spectrum data acquisition,spectrum block appending,spectrum data transmission,and spectrum sensing incentive,consist of basic operational mechanism of IoSD.The distributed consensus mechanism,including fusion consensus among sensing-nodes,verification consensusamong checking-nodes,and confirmation consensus among head-nodes,was applied to determine whether the spectrum data was falsified by the Byzantine attack of malicious sensing-nodesunder the hypothesis test of certain confidence.The simulation results show the effectiveness and robustness of proposed distributed consensus mechanism in preventing spectrum sensing data falsification by the malicious nodes.     

Distributed cooperative spectrum sensing based on reinforcement learning in cognitive radio networks

Spectrum sensing is an initial task for the successful operation of cognitive radio networks (CRN). During cooperative spectrum sensing, malicious secondary user (SU) may report false sensing data which would degrade the final aggregated sensing outcome. In this paper, we propose a distributed cooperative spectrum sensing (CSS) method based on reinforcement learning (RL) to remove data fusion between users with different reputations in CRN. This method regards each SU as an agent, which is selected from the adjacent nodes of CRN participating in CSS. The reputation value is used as reward to ensure that the agent tends to merge with high reputation nodes. The conformance fusion is adopted to promote consensus of the whole network, while it’s also compared with the decision threshold to complete CSS. Simulation results show that the proposed method can identify malicious users effectively. As a result, the whole CRN based on RL is more intelligent and stable.     

Performance analysis and comparison of PoW,PoS and DAG based blockchains

In the blockchain, the consensus mechanism plays a key role in maintaining the security and legitimation of contents recorded in the blocks. Various blockchain consensus mechanisms have been proposed. However, there is no technical analysis and comparison as a guideline to determine which type of consensus mechanism should be adopted in a specific scenario/application. To this end, this work investigates three mainstream consensus mechanisms in the blockchain, namely, Proof of Work (PoW), Proof of Stake (PoS), and Direct Acyclic Graph (DAG), and identifies their performances in terms of the average time to generate a new block, the confirmation delay, the Transaction Per Second (TPS) and the confirmation failure probability. The results show that the consensus process is affected by both network resource (computation power/coin age, buffer size) and network load conditions. In addition, it shows that PoW and PoS are more sensitive to the change of network resource while DAG is more sensitive to network load conditions.     

多域协同的TDD大规模组网方法研究

如何在有着大量、广域、时变协同需求的海量节点间和多维资源约束下实现网络服务能力最大化是时分双工（time-division duplex,TDD）移动通信大规模组网面临的核心问题。从架构角度进行研究,创新性地提出适用于TDD大规模组网的全局协同优化架构,分为无线连接层、信号处理层和服务控制层,通过层间全局协同优化和层内资源域高效转化实现多维资源成本与网络服务能力的最优化。基于该架构,聚焦无线连接层的空口资源,对多资源域协同转化的无线组网方法进行深入研究,明确了时域、频域、空域、码域等多资源域协同转化机理,并设计了相应的无线组网机制。4G/5G现网实践验证结果表明,所提TDD大规模无线组网架构和方法可在有效控制干扰的同时高效利用各域资源,实现网络服务能力最大化。