WO2020168477A1 - Procédé de construction de topologie satisfaisant une tolérance de partition sous un consensus de chaîne d'alliance et système - Google Patents

Procédé de construction de topologie satisfaisant une tolérance de partition sous un consensus de chaîne d'alliance et système Download PDF

Info

Publication number
WO2020168477A1
WO2020168477A1 PCT/CN2019/075547 CN2019075547W WO2020168477A1 WO 2020168477 A1 WO2020168477 A1 WO 2020168477A1 CN 2019075547 W CN2019075547 W CN 2019075547W WO 2020168477 A1 WO2020168477 A1 WO 2020168477A1
Authority
WO
WIPO (PCT)
Prior art keywords
probability
partition
partition tolerance
alliance chain
state
Prior art date
Application number
PCT/CN2019/075547
Other languages
English (en)
Chinese (zh)
Inventor
李挥
王菡
邬江兴
伊鹏
陆平
安辉耀
黄健森
Original Assignee
北京大学深圳研究生院
佛山赛思禅科技有限公司
深圳赛思鹏科技发展有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 北京大学深圳研究生院, 佛山赛思禅科技有限公司, 深圳赛思鹏科技发展有限公司 filed Critical 北京大学深圳研究生院
Priority to CN201980005054.8A priority Critical patent/CN111512332B/zh
Priority to PCT/CN2019/075547 priority patent/WO2020168477A1/fr
Publication of WO2020168477A1 publication Critical patent/WO2020168477A1/fr

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G06Q20/389—Keeping log of transactions for guaranteeing non-repudiation of a transaction
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10—Complex mathematical operations
    • G06F17/18—Complex mathematical operations for evaluating statistical data, e.g. average values, frequency distributions, probability functions, regression analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/08—Computing arrangements based on specific mathematical models using chaos models or non-linear system models
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q20/00—Payment architectures, schemes or protocols
    • G06Q20/38—Payment protocols; Details thereof
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Definitions

  • the invention belongs to the technical improvement field of network construction, and in particular relates to a topology construction method that satisfies the partition tolerance under the alliance chain consensus.
  • Blockchain refers to the construction of unforgeable, non-tamperable and traceable block-chain data in a peer-to-peer network (Peer-to-Peer Networking, also known as peer-to-peer network) environment through transparent and trusted rules Structure to implement and manage the transaction processing mode.
  • Peer-to-Peer Networking also known as peer-to-peer network
  • a blockchain is a chained data structure that combines data blocks in a chronological order and is not tamperable with cryptographic methods.
  • blockchain uses block-chain data structures to verify and store data, uses distributed node consensus algorithms to generate and update data, and uses cryptography to ensure data transmission and access A new distributed infrastructure and calculation method that safely uses smart contracts composed of automated script codes to program and manipulate data.
  • the blockchain is essentially a decentralized distributed ledger, and long before the emergence of the blockchain, the idea of distributed has been proposed and matured day by day.
  • Consistency Consistency
  • availability A: Availability
  • partition tolerance Partition tolerance
  • Lynch et al. proved this conjecture and raised it to the CAP theorem.
  • the CAP theorem refines the three factors of consistency, availability, and partition tolerance as important features of distributed system design.
  • Consistency means that any operation in the system should appear to be "atomic" or serial, and all operations appear to be globally ordered;
  • Availability means that any normal node will be Responses should be given within a limited time;
  • Partition tolerance means that when the network is partitioned at a certain moment, the system can still meet consistency and availability.
  • Bitcoin uses an Internet-based peer-to-peer distributed network architecture, and each node has a network routing function. When a new node needs to be connected to the Bitcoin network, perform the following steps:
  • the node After the startup is completed, the node will remember the recently successfully connected node, and can quickly re-establish a connection with the previous node after restarting. If none of the previous nodes can be connected, start from step (1) again.
  • PoA Proof of Authority
  • the same signer can only sign one of (SIGNER_COUNT/2)+1 blocks.
  • one signer at each height is in the IN-TURN state, and other signers are in the OUT-OF-TURN state.
  • the signer in the IN-TURN state can immediately broadcast their own block, OUT-OF -When a signer in TURN state generates a block, it will be broadcast after a random delay.
  • the PoA consensus relies on an effective and trustworthy identity authentication mechanism. Considering that the identity of the signer is open to the entire network, once an attacker attacks more than half of the signers, the system cannot guarantee the correctness of the block. On the other hand, compared with the traditional PBFT consensus algorithm, the PoA consensus algorithm achieves high availability and partition tolerance by weakening the consistency requirement to non-consistency (Aura client) or eventual consistency (Clique client).
  • the purpose of the present invention is to provide a topology construction method that satisfies the partition tolerance under the alliance chain consensus, and aims to solve the above technical problems.
  • the present invention is realized in this way, a topology construction method that satisfies the partition tolerance under the alliance chain consensus, and the topology construction method includes the following steps:
  • step S2 the Markov process converges to a steady-state distribution of an independent initial distribution, and obtaining the steady-state probability of the system under a single network topology includes the following steps:
  • a further technical solution of the present invention is: the MTBF and MTTR of each analysis element in step S3 are independent processes without memory and have a constant mean value; obtaining the partition tolerance probability of the system under a single network topology includes the following steps:
  • the total probability formula is: l indicates the total number of channels, and i indicates that there are and only i channels in the steady state system are in a fault state.
  • a further technical solution of the present invention is: obtaining the average minimum repair time of the system under a single network topology structure includes the following steps:
  • the further technical solution of the present invention is: in the hierarchical network topology, according to the consensus process, the partition tolerance of the lower-level domain is not only affected by its own network topology, but also related to the partition tolerance of the higher-level domain; the partition tolerance of the system Probability is
  • the average minimum repair time of the system is the average minimum repair time of the system.
  • Another object of the present invention is to provide a topology construction system that satisfies the partition tolerance under the alliance chain consensus, and the topology construction system includes
  • the combination module is used to combine the alliance chain consensus mechanism with the network topology to make the alliance chain consensus meet the partition tolerance in probability;
  • Convergence module used to abstract the partition tolerance of the system into a kind of convergent Markov process and obtain the steady-state probability of the system
  • Sampling estimation module used to estimate the probability and minimum repair time of partition failure and not meet the consistency or availability when the number of faulty channels is certain, and obtain the partition tolerance probability and average minimum repair time of the system;
  • a further technical solution of the present invention is that the Markov process in the convergence module converges to a steady-state distribution of an independent initial distribution, and obtaining the steady-state probability of the system under a single network topology includes
  • the cyclic multiplication unit is used to cyclically multiply the state transition matrix P with itself;
  • the judgment unit is used to judge whether the matrix 2-norm of the difference between two consecutive products is less than the set convergence accuracy. If it is less, then the power of P at this time is considered to be the steady-state probability matrix P * , if not less than, Then return to the loop multiplication unit.
  • a further technical solution of the present invention is: the MTBF and MTTR of each analysis element in the sampling estimation module are independent processes without memory and have a constant mean; obtaining the partition tolerance probability of the system under a single network topology includes
  • Sampling unit used to sample N times for each possible state of the steady-state system
  • the estimation unit is used to estimate the probability of partition failure in each state and not meeting consistency or availability
  • the calculation unit is used to calculate the partition tolerance probability of the system according to the total probability formula.
  • the total probability formula is:
  • l indicates the total number of channels
  • i indicates that there are and only i channels in the steady state system are in a fault state.
  • the further technical solution of the present invention is: obtaining the average minimum repair time of the system under a single network topology structure includes
  • the further technical solution of the present invention is: in the hierarchical network topology, according to the consensus process, the partition tolerance of the lower-level domain is not only affected by its own network topology, but also related to the partition tolerance of the higher-level domain; the partition tolerance of the system Probability is
  • the average minimum repair time of the system is the average minimum repair time of the system.
  • the beneficial effects of the present invention are: the network topology is combined with the alliance chain consensus mechanism, so that the alliance chain consensus meets the partition tolerance in probability, and can realize the coexistence of the three CAP factors, which has high practical significance;
  • the mean time between failures and mean time to repair that remain constant over a period of time are used as parameters to improve the Markov model's prediction accuracy for the probability distribution trend of the system state; when the number of failed channels is estimated, the partition failure occurs and does not meet the consistency or availability. Probability and minimum repair time are adapted to the partition tolerance of the consensus mechanism and the characteristics of the network topology to the greatest extent.
  • Figure 1 is a schematic diagram of the Markov state transition diagram of the general network topology.
  • Figure 2 is a schematic diagram of the domain numbering of the hierarchical network topology provided by an embodiment of the present invention.
  • FIG. 3 is a schematic diagram of the partition tolerance probability of a multi-dimensional hypersquare network topology provided by an embodiment of the present invention.
  • Fig. 4 is a schematic diagram of the average minimum repair time of the multi-dimensional hypersquare network topology provided by an embodiment of the present invention.
  • FIG. 5 is a schematic diagram of the partition tolerance probability of a multipoint fully connected network topology provided by an embodiment of the present invention.
  • FIG. 6 is a schematic diagram of the average minimum repair time of the multipoint fully connected network topology provided by an embodiment of the present invention.
  • Fig. 7 is a schematic diagram of the lower boundary of the hierarchical network topology provided by an embodiment of the present invention.
  • Figure 8 is a schematic diagram of a fully symmetric hierarchical network topology provided by an embodiment of the present invention.
  • Fig. 9 is a schematic diagram of a semi-symmetric hierarchical network topology according to an embodiment of the present invention.
  • Fig. 10 is a schematic diagram of an asymmetric hierarchical network topology provided by an embodiment of the present invention.
  • FIG. 11 is a flowchart of a topology construction method that satisfies partition tolerance under the alliance chain consensus provided by an embodiment of the present invention.
  • the present invention provides a topology construction method that satisfies partition tolerance under the alliance chain consensus, which is detailed as follows:
  • the existing blockchain system only strengthens the two factors of consistency, availability, and partition tolerance at the consensus level, and is accompanied by a significant weakening of the third factor, which is still far from the CAP limit.
  • the current mainstream blockchain systems do not consider how to maintain the network topology, which brings potential network communication risks and waste of resources.
  • the present invention a topology construction method and system that meets the tolerance of partitions under the consensus of the alliance chain, combines the network topology with the consensus mechanism of the alliance chain, so that the consensus of the alliance chain meets the tolerance of the partition in probability, and then Able to achieve the coexistence of the three factors of CAP.
  • the present invention also proposes a partition tolerance calculation method, which abstracts the partition tolerance of the system into a kind of convergent Markov process, and uses MATLAB and other simulation software to sample and calculate the network that does not meet the consistency or availability when a partition failure occurs. Probability and average minimum repair time.
  • the present invention specifically analyzes the resource overhead and partition tolerance under different network topologies, and constructs a network topology structure with suitable scale and high partition tolerance for alliance chain consensus with different requirements.
  • the technical scheme of the present invention combines the network topology and the alliance chain consensus mechanism on the basis of not affecting the consistency and availability of the consensus algorithm itself, so that the alliance chain consensus satisfies the partition tolerance in probability, thereby achieving the three factors of CAP Coexistence has high practical significance.
  • a calculation method of partition tolerance is proposed.
  • the partition tolerance problem of the system is abstracted into a kind of convergent Markov process.
  • the mean time between failures and mean time to repair are used as parameters to improve the Markov model’s
  • the prediction accuracy of the trend of the system state probability distribution is proposed.
  • the calculation method under a single network topology structure further derives the partition tolerance under the hierarchical network topology structure, which is not only suitable for general single-chain architecture, but also for multi-chain and cross-chain architecture, and has broad application prospects.
  • Domains at different levels may adopt the same or different network topologies and parameters, and the network topologies of different domains at the same level may not be exactly the same.
  • MTBF Mel Time Between Failures, Mean Time Between Failures
  • MTTR Mel Time To Repair, Mean Time To Repair
  • MTBF is much greater than MTTR.
  • v Total number of network nodes.
  • ⁇ the probability of failure interruption per unit time of the channel
  • ⁇ the probability that a channel in a faulty state in the system is repaired per unit time, namely
  • v nodes and l channels make a Markov state transition diagram, as shown in Figure 1.
  • the i-th system state indicates that there are and only i channels in the network are in a fault state (0 ⁇ i ⁇ l).
  • the state transition matrix of the Markov model is a matrix P with a scale of (l+1) ⁇ (l+1), where the element p ji represents the probability of transitioning from the i-th system state to the j-th system state.
  • m denote the number of the same failed channels in state i and state j, and the value range of m is [max ⁇ i+jl, 0 ⁇ , min ⁇ i, j ⁇ ].
  • each system state can come from any other state, that is, the Markov state transition diagram above is fully connected, so P satisfies the irreducibility.
  • Algorithm 1 describes the iterative calculation process of the system steady-state probability. Multiply the state transition matrix P by itself. If the matrix 2-norm of the difference between two consecutive products is less than the given convergence accuracy, then the power of P at this time is considered to be the steady-state probability matrix P * .
  • Algorithm 2 describes the calculation process of the partition tolerance probability of the system under a single network topology. For the various states that the system may be in at steady state, sample N times respectively, estimate the probability of partition failure and not meet consistency or availability, and then calculate the partition tolerance probability of the system according to the full probability formula.
  • the minimum repair time is defined as the minimum time required for the system to repair some channels when a certain failure occurs, so that the system meets consistency and availability.
  • Algorithm 3 describes the calculation process of the average minimum repair time of the system under a single network topology. On the basis of Algorithm 2, for each instance that has a partition failure and does not meet consistency or availability, calculate its minimum repair time, and then multiply it by the weight of the instance in the total system partition tolerance problem to get the average of the system Minimum repair time.
  • each domain is numbered according to a tree structure of (i 1 i 2 i 3 ...), as shown in Figure 2.
  • the partition tolerance of the lower-level domain is not only affected by its own network topology, but also related to the partition tolerance of the higher-level domain. make Represents the partition tolerance probability of each domain. Then the partition tolerance probability of the system is
  • the following is to calculate the partition tolerance probability and the average minimum repair time when the Proof of Vote consensus mechanism (Proof of Vote, PoV) in the alliance chain adopts the hypersquare network topology and the fully connected network topology.
  • a digital optical cable communication system with automatic switching of main and standby systems should meet the annual indicators shown in Table 1. Therefore, taking parameters ( ⁇ , ⁇ ) ⁇ ⁇ ( 4.5662 ⁇ 10 -4, 4.1667 ⁇ 10 -2), (2.7397 ⁇ 10 -4, 6.9444 ⁇ 10 -2), (3.8358 ⁇ 10 -5, 4.9603 ⁇ 10 - 1 ), (2.5571 ⁇ 10 -5 , 7.4405 ⁇ 10 -1 ) ⁇ .
  • Table 2 shows the resource overhead of the two network topologies of multi-dimensional hyper-square and multi-point full connection.
  • Figure 7 shows the lower boundary of this method, that is, the top-level, second-level, and third-level domains are all 2-dimensional hypersquare topological structures;
  • Figure 8 shows a completely symmetrical 3-level topology construction method, the top level The topological structures of the second, second, and third-level domains are all 3-dimensional hypersquares;
  • Figure 9 shows a semisymmetric 2-level topology construction method.
  • the topological structure of the same-level domains is the same, but the top-level domain topology is 4
  • the topological structure of the second-level domain is a 3-dimensional hyper-square;
  • Figure 10 shows an asymmetric 2-level topology construction method.
  • the topological structure of the upper and lower domains and the same-level domains are different. Specifically , The top-level domain adopts a 4-dimensional hyper-square structure, while there are 4, 8, and 4 secondary domains using 4-dimensional hyper-square, 3-dimensional hyper-square and 7-point fully connected structures.
  • the partition tolerance probability and the average minimum repair time of the four hierarchical network topologies in Figure 7 to Figure 10 are further calculated as:
  • t [t 1 *(1-p 1 )+t 11 *p 1 *(1-p 11 )*4+t 111 *p 1 *p 11 *(1-p 111 )*4*4]/( 1-p) ⁇ 21h, that is, the average minimum repair time after a partition failure occurs is about 21 hours.
  • t [t 1 *(1-p 1 )+t 11 *p 1 *(1-p 11 )*8+t 111 *p 1 *p 11 *(1-p 111 )*8*8]/( 1-p) ⁇ 23h, that is, the average minimum repair time after a partition failure occurs is about 23 hours.
  • p 1-[(1-p 1 )+p 1 *(1-p 11 )*16] ⁇ 1-1 ⁇ 10 -8 , that is, a partition failure failure occurs approximately every 11,416 years.
  • t [t 1 *(1-p 1 )+t 11 *p 1 *(1-p 11 )*16]/(1-p) ⁇ 14h, that is, the average minimum repair time after a partition failure occurs is approximately 14 hours.
  • p 1-[(1-p 1 )+p 1 *(1-p 11 )*4+p 1 *(1-p 12 )*8+p 1 *(1-p 13 )*4] ⁇ 1 -6 ⁇ 10 -9 , that is, a partition failure occurs approximately every 19,026 years.
  • t [t 1 *(1-p 1 )+t 11 *p 1 *(1-p 11 )*4+t 12 *p 1 *(1-p 12 )*8+t 13 *p 1 *( 1-p 13 )*4]/(1-p) ⁇ 14h, that is, the average minimum repair time after a partition failure occurs is approximately 14 hours.
  • Another object of the present invention is to provide a topology construction system that satisfies the partition tolerance under the alliance chain consensus, and the topology construction system includes
  • the combination module is used to combine the alliance chain consensus mechanism with the network topology to make the alliance chain consensus meet the partition tolerance in probability;
  • the convergence module is used to abstract the partition tolerance of the system into a kind of convergent Markov process and obtain the steady-state probability of the system;
  • Sampling estimation module used to estimate the probability and minimum repair time of partition failure and not meet the consistency or availability when the number of faulty channels is certain, and obtain the partition tolerance probability and average minimum repair time of the system;
  • the Markov process in the convergence module converges to a steady-state distribution of an independent initial distribution, and obtaining the steady-state probability of the system under a single network topology includes
  • the cyclic multiplication unit is used to cyclically multiply the state transition matrix P with itself;
  • the judgment unit is used to judge whether the matrix 2-norm of the difference between two consecutive products is less than the set convergence accuracy. If it is less, then the power of P at this time is considered to be the steady-state probability matrix P * , if not less than, Then return to the loop multiplication unit.
  • the MTBF and MTTR of each analysis element in the sampling estimation module are independent processes without memory and the mean value is constant; obtaining the partition tolerance probability of the system under a single network topology includes
  • the estimation unit is used to estimate the probability of partition failure in each state and not meeting consistency or availability
  • the calculation unit is used to calculate the partition tolerance probability of the system according to the total probability formula.
  • the total probability formula is:
  • l indicates the total number of channels
  • i indicates that there are and only i channels in the steady state system are in a fault state.
  • the partition tolerance of the lower-level domain is not only affected by its own network topology, but also related to the partition tolerance of the higher-level domain;
  • the partition tolerance probability of the system is The average minimum repair time of the system is among them, Indicates the partition tolerance probability of each domain, Indicates the average minimum repair time of each domain.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Business, Economics & Management (AREA)
  • Data Mining & Analysis (AREA)
  • Accounting & Taxation (AREA)
  • Databases & Information Systems (AREA)
  • Finance (AREA)
  • Mathematical Physics (AREA)
  • General Engineering & Computer Science (AREA)
  • Pure & Applied Mathematics (AREA)
  • Mathematical Optimization (AREA)
  • Mathematical Analysis (AREA)
  • Computational Mathematics (AREA)
  • Strategic Management (AREA)
  • General Business, Economics & Management (AREA)
  • Algebra (AREA)
  • Software Systems (AREA)
  • Computing Systems (AREA)
  • Economics (AREA)
  • Bioinformatics & Cheminformatics (AREA)
  • Probability & Statistics with Applications (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Technology Law (AREA)
  • Marketing (AREA)
  • Evolutionary Biology (AREA)
  • Operations Research (AREA)
  • Development Economics (AREA)
  • Bioinformatics & Computational Biology (AREA)
  • Nonlinear Science (AREA)
  • Artificial Intelligence (AREA)
  • Evolutionary Computation (AREA)
  • Data Exchanges In Wide-Area Networks (AREA)

Abstract

L'invention porte sur un procédé de construction d'une topologie satisfaisant une tolérance de partition dans le cadre d'un consensus de chaîne d'alliance, applicable au domaine de l'amélioration de la technologie de construction des réseaux. Le procédé comprend les étapes suivantes consistant à : combiner le mécanisme de consensus de la chaîne d'alliance avec la structure de topologie du réseau pour que le consensus de la chaîne d'alliance satisfasse de manière probabiliste à la tolérance de partition (P) (S1) ; abstraire la tolérance de partition d'un système dans un processus de Markov convergent et obtenir la probabilité de stabilité du système (S2) ; estimer la probabilité d'une défaillance de partition et de ne pas satisfaire la cohérence (C) ou la disponibilité (A) lorsque le nombre de canaux défectueux est fixé et la durée de réparation la plus courte pour obtenir la probabilité de tolérance de partition et la durée de réparation moyenne la plus courte du système (S3) ; et en fonction de la probabilité de tolérance de partition obtenue et de la durée moyenne de réparation la plus courte, analyser le surdébit de ressources et la tolérance de partition sous différentes structures de topologie de réseau, et construire pour un consensus de chaîne d'alliance ayant différentes exigences, une topologie de réseau ayant une dimension appropriée et une tolérance de partition élevée (S4). Cette méthode permet de réaliser la coexistence des trois facteurs (CAP) et présente une grande importance pratique.
PCT/CN2019/075547 2019-02-20 2019-02-20 Procédé de construction de topologie satisfaisant une tolérance de partition sous un consensus de chaîne d'alliance et système WO2020168477A1 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN201980005054.8A CN111512332B (zh) 2019-02-20 2019-02-20 一种联盟链共识下满足分区容忍性的拓扑构造方法及系统
PCT/CN2019/075547 WO2020168477A1 (fr) 2019-02-20 2019-02-20 Procédé de construction de topologie satisfaisant une tolérance de partition sous un consensus de chaîne d'alliance et système

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2019/075547 WO2020168477A1 (fr) 2019-02-20 2019-02-20 Procédé de construction de topologie satisfaisant une tolérance de partition sous un consensus de chaîne d'alliance et système

Publications (1)

Publication Number Publication Date
WO2020168477A1 true WO2020168477A1 (fr) 2020-08-27

Family

ID=71864549

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2019/075547 WO2020168477A1 (fr) 2019-02-20 2019-02-20 Procédé de construction de topologie satisfaisant une tolérance de partition sous un consensus de chaîne d'alliance et système

Country Status (2)

Country Link
CN (1) CN111512332B (fr)
WO (1) WO2020168477A1 (fr)

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114401099A (zh) * 2021-08-17 2022-04-26 同济大学 一种基于网络拓扑的区块链PoW自私挖矿攻击防御方法
CN116506444A (zh) * 2023-06-28 2023-07-28 北京科技大学 一种基于深度强化学习与信誉机制的区块链稳定分片方法

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN113708963B (zh) * 2021-08-20 2022-08-16 北京大学深圳研究生院 一种满足联盟链分区容忍性的优化拓扑递归方法及系统

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140317222A1 (en) * 2012-01-13 2014-10-23 Hui Li Data Storage Method, Device and Distributed Network Storage System
CN106211196A (zh) * 2016-06-22 2016-12-07 西北工业大学 基于马尔科夫随机场的多无人航行体协同一致性方法
CN108124502A (zh) * 2017-03-31 2018-06-05 北京大学深圳研究生院 一种基于联盟链的顶级域名管理方法及系统
CN109194444A (zh) * 2018-09-01 2019-01-11 哈尔滨工程大学 一种基于网络拓扑的平衡二叉树修复方法

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9672115B2 (en) * 2013-08-26 2017-06-06 Vmware, Inc. Partition tolerance in cluster membership management
CN105592098B (zh) * 2016-01-16 2018-09-14 杭州复杂美科技有限公司 区块链上的投票及ca证书的管理方法
CN107038638A (zh) * 2017-02-24 2017-08-11 杭州象链网络技术有限公司 一种基于联盟链的股权登记交易系统构建方法
CN108492103B (zh) * 2018-02-07 2021-04-27 北京大学深圳研究生院 一种联盟区块链共识方法

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20140317222A1 (en) * 2012-01-13 2014-10-23 Hui Li Data Storage Method, Device and Distributed Network Storage System
CN106211196A (zh) * 2016-06-22 2016-12-07 西北工业大学 基于马尔科夫随机场的多无人航行体协同一致性方法
CN108124502A (zh) * 2017-03-31 2018-06-05 北京大学深圳研究生院 一种基于联盟链的顶级域名管理方法及系统
CN109194444A (zh) * 2018-09-01 2019-01-11 哈尔滨工程大学 一种基于网络拓扑的平衡二叉树修复方法

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN114401099A (zh) * 2021-08-17 2022-04-26 同济大学 一种基于网络拓扑的区块链PoW自私挖矿攻击防御方法
CN114401099B (zh) * 2021-08-17 2023-05-09 同济大学 一种基于网络拓扑的区块链PoW自私共识抵抗方法
CN116506444A (zh) * 2023-06-28 2023-07-28 北京科技大学 一种基于深度强化学习与信誉机制的区块链稳定分片方法
CN116506444B (zh) * 2023-06-28 2023-10-17 北京科技大学 一种基于深度强化学习与信誉机制的区块链稳定分片方法

Also Published As

Publication number Publication date
CN111512332B (zh) 2022-12-09
CN111512332A (zh) 2020-08-07

Similar Documents

Publication Publication Date Title
US20190220768A1 (en) Constructing topology for satisfying partition tolerance in consortium blockchain consensus
Kobo et al. Fragmentation-based distributed control system for software-defined wireless sensor networks
CN108769150B (zh) 区块链网络的数据处理方法、装置、集群节点和存储介质
Yu et al. Distributed adaptive control for synchronization in directed complex networks
WO2020168477A1 (fr) Procédé de construction de topologie satisfaisant une tolérance de partition sous un consensus de chaîne d'alliance et système
CN109919771B (zh) 一种应用分层区块链技术的工业互联网交易装置
Zoican et al. Blockchain and consensus algorithms in internet of things
CN114626547A (zh) 一种基于区块链的群组协同学习方法
Zeng et al. Intelligent blockchain-based secure routing for multidomain SDN-enabled IoT networks
CN113469371A (zh) 联邦学习方法和装置
Jiang et al. A trust-based hierarchical consensus mechanism for consortium blockchain in smart grid
Yi et al. Consensus in Markovian jump second‐order multi‐agent systems with random communication delay
Huang et al. Blockchain based log system
CN112395113A (zh) 实用拜占庭容错共识方法及装置、可读存储介质
Xiong et al. A distributed security SDN cluster architecture for smart grid based on blockchain technology
Lin et al. Security function virtualization based moving target defense of SDN-enabled smart grid
Wu et al. Reinforced practical Byzantine fault tolerance consensus protocol for cyber physical systems
Li et al. EBFT: A hierarchical and group-based byzantine fault tolerant consensus algorithm
Bhonsle et al. ETIS--Efficient Trust and Identity Management System for Federated Service Providers
Shao et al. Accelerating bgp configuration verification through reducing cycles in smt constraints
Xian et al. A distributed efficient blockchain oracle scheme for internet of things
Monshizadeh et al. Uniform synchronization in multi‐agent systems with switching topologies
CN103118105A (zh) 一种基于无线传感器网络的数据查询系统及其查询方法
Wang et al. A physical topology for optimizing partition tolerance in consortium blockchains to reach CAP guarantee bound
Hao et al. Doppel: A BFT consensus algorithm for cyber-physical systems with low latency

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 19916237

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 19916237

Country of ref document: EP

Kind code of ref document: A1