CN116668452A - Block chain core network construction method and device - Google Patents
Block chain core network construction method and device Download PDFInfo
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Abstract
The embodiment of the invention provides a block chain core network construction method and a device, which can be used in the technical field of artificial intelligence, wherein the method comprises the following steps: acquiring a block chain initial network, wherein the block chain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened; generating a block chain test network according to a plurality of nodes to be screened and connecting edges among the nodes to be screened through a preset initial weighting coefficient, wherein the block chain test network comprises a plurality of core nodes; iteratively updating the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient; updating the blockchain testing network according to a target weighting coefficient to obtain a blockchain core network according to a preset time period, wherein the blockchain core network comprises a plurality of updated core nodes, the blockchain core network is constructed based on a centrality algorithm, the core nodes are determined, the labor cost is reduced, the node utilization rate is improved, and therefore the transaction processing efficiency is improved.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to the field of artificial intelligence technologies, and in particular, to a method and an apparatus for constructing a blockchain core network.
Background
In the decentralized internet (web 3.0) running in blockchain technology, there are numerous communication nodes and the different node configurations are quite different. Blockchain coalition chains are commonly used in small networks in the industry. In the related art, before deployment, the blockchain node is manually assigned with a role-related configuration, and the roles of the blockchain node are basically equivalent, and the capability of distinguishing the core node is not needed, but if the related technology is applied to a large or ultra-large web3.0 network, namely: the blockchain continuously applies all nodes to bear the peer-to-peer task, and executes all blockchain transaction processing in the network, so that the cost is greatly consumed, the node utilization rate is reduced, and the transaction processing efficiency is low.
Disclosure of Invention
The invention aims to provide a block chain core network construction method, which is used for constructing a block chain core network based on a centrality algorithm to determine core nodes, thereby reducing labor cost and improving node utilization rate and transaction processing efficiency. Another object of the present invention is to provide a blockchain core network construction device. It is yet another object of the present invention to provide a computer readable medium. It is a further object of the invention to provide a computer device.
In order to achieve the above objective, an aspect of the present invention discloses a method for constructing a blockchain core network, including:
acquiring a block chain initial network, wherein the block chain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened;
generating a block chain test network according to a plurality of nodes to be screened and connecting edges among the nodes to be screened through a preset initial weighting coefficient, wherein the block chain test network comprises a plurality of core nodes;
iteratively updating the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient;
updating the blockchain testing network according to a preset time period and a target weighting coefficient to obtain a blockchain core network, wherein the blockchain core network comprises a plurality of updated core nodes.
Preferably, generating the blockchain test network according to the plurality of nodes to be screened and the connection edges between the nodes to be screened by using a preset initial weighting coefficient includes:
generating a comprehensive centrality score of each node to be screened according to a plurality of nodes to be screened and connecting edges among the nodes to be screened through a preset initial weighting coefficient;
and generating a blockchain test network according to the comprehensive centrality score of each node to be screened, wherein the blockchain test network comprises a plurality of core nodes.
Preferably, generating, by a preset initial weighting coefficient, a comprehensive centrality score of each node to be screened according to a plurality of nodes to be screened and connection edges between the nodes to be screened, including:
generating a degree centrality score, a proximity centrality score, an intermediate centrality score, a feature vector centrality score, a K-kernel centrality score and a consensus centrality score of each node to be screened according to a plurality of nodes to be screened and connecting edges among the nodes to be screened according to a preset time period by a centrality algorithm;
and according to the initial weighting coefficient, weighting and calculating the centrality score, the approaching centrality score, the intermediation centrality score, the feature vector centrality score, the K-nuclear centrality score and the consensus centrality score to obtain the comprehensive centrality score of the node to be screened.
Preferably, a blockchain test network is generated according to the comprehensive centrality score of each node to be screened, wherein the blockchain test network comprises a plurality of core nodes, and the method comprises the following steps:
comparing a preset centrality score threshold with the comprehensive centrality score of each node to be screened, and screening out the comprehensive centrality score larger than the centrality score threshold;
Determining the node to be screened corresponding to the screened comprehensive centrality score as a core node;
and constructing a blockchain test network according to the plurality of core nodes and the connecting edges among the core nodes.
Preferably, the iterative updating of the initial weighting coefficient is performed by a machine learning algorithm to obtain a target weighting coefficient, including:
and inputting the initial weighting coefficient into a machine learning algorithm for iterative training until the transaction processing average delay of the blockchain system is smaller than a preset transaction processing delay threshold value, and outputting a target weighting coefficient.
Preferably, updating the blockchain test network according to a target weighting coefficient according to a preset time period to obtain a blockchain core network, including:
generating a centrality score, a near centrality score, an intermediate centrality score, a feature vector centrality score, a K-core centrality score and a consensus centrality score of each core node according to a connecting edge between a plurality of core nodes and each core node in a blockchain test network by a centrality algorithm and a preset time period;
according to the target weighting coefficient, weighting calculation is carried out on the centrality score, the near centrality score, the intermediate centrality score, the feature vector centrality score, the K-nuclear centrality score and the consensus centrality score to obtain the comprehensive centrality score of the core node;
And updating the blockchain testing network according to the comprehensive centrality score of the core node to obtain a blockchain core network.
Preferably, updating the blockchain test network according to the comprehensive centrality score of the core node to obtain a blockchain core network, including:
screening out comprehensive centrality scores from a plurality of core nodes in a blockchain test network, wherein the comprehensive centrality scores are smaller than a preset centrality score threshold value in a preset time period of a continuous appointed number;
determining the core node corresponding to the screened comprehensive centrality score as a node to be exited;
filtering the node to be exited from the blockchain test network to obtain a blockchain core network, wherein the blockchain core network comprises a plurality of updated core nodes.
Preferably, after updating the blockchain test network according to the target weighting coefficient and the preset time period to obtain the blockchain core network, the method further comprises:
responding to a new node joining request, and screening out a comprehensive centrality score larger than the access threshold according to the comprehensive centrality score of the core node through a preset access threshold;
determining the core node corresponding to the screened comprehensive centrality score as a node to be accessed;
And sending the node to be accessed to the new node so that the new node can select one node to be accessed for accessing.
The invention also discloses a block chain core network construction device, which comprises:
the system comprises a block chain initial network acquisition unit, a block chain initial network generation unit and a block chain selection unit, wherein the block chain initial network acquisition unit is used for acquiring a block chain initial network, and the block chain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened;
the block chain test network generation unit is used for generating a block chain test network according to a plurality of nodes to be screened and connecting edges among the nodes to be screened through a preset initial weighting coefficient, wherein the block chain test network comprises a plurality of core nodes;
the weighting coefficient updating unit is used for carrying out iterative updating on the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient;
and the block chain core network generating unit is used for updating the block chain test network according to a preset time period and a target weighting coefficient to obtain a block chain core network, wherein the block chain core network comprises a plurality of updated core nodes.
The invention also discloses a computer readable medium having stored thereon a computer program which when executed by a processor implements a method as described above.
The invention also discloses a computer device comprising a memory for storing information comprising program instructions and a processor for controlling the execution of the program instructions, the processor implementing the method as described above when executing the program.
The invention also discloses a computer program product comprising a computer program/instruction which, when executed by a processor, implements a method as described above.
The method comprises the steps of obtaining a block chain initial network, wherein the block chain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened; generating a block chain test network according to a plurality of nodes to be screened and connecting edges among the nodes to be screened through a preset initial weighting coefficient, wherein the block chain test network comprises a plurality of core nodes; iteratively updating the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient; updating the blockchain testing network according to a target weighting coefficient to obtain a blockchain core network according to a preset time period, wherein the blockchain core network comprises a plurality of updated core nodes, the blockchain core network is constructed based on a centrality algorithm, the core nodes are determined, the labor cost is reduced, the node utilization rate is improved, and therefore the transaction processing efficiency is improved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the drawings that are required in the embodiments or the description of the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a blockchain core network construction method according to an embodiment of the present invention;
fig. 2 is a flowchart of another block chain core network construction method according to an embodiment of the present invention;
fig. 3 is a schematic structural diagram of a blockchain core network construction device according to an embodiment of the present invention;
fig. 4 is a schematic structural diagram of a computer device according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that the method and the device for constructing the blockchain core network disclosed by the application can be used in the technical field of artificial intelligence and can also be used in any field except the technical field of artificial intelligence, and the application field of the method and the device for constructing the blockchain core network disclosed by the application is not limited.
In order to facilitate understanding of the technical scheme provided by the application, the following description will explain relevant contents of the technical scheme of the application. The centrality algorithm can be used for identifying the roles of specific nodes in the graph and the influence of the specific nodes on the graph network, can identify the most important nodes, and calculates the reliability, accessibility and speed of transaction propagation of the nodes and the connection between groups. In order to ensure that the blockchain alliance chain can be applied to a large or ultra-large web3 network, the application provides a blockchain core network construction method based on a centrality algorithm, the bottom layer communication of the blockchain network is combined with various centrality algorithms to identify the roles of specific nodes in the network and the influence of the specific nodes on the network, various centrality algorithm results are comprehensively considered, a comprehensive centrality calculation method is provided, the parameter adjustment of a comprehensive centrality calculation model is carried out by using Artificial Intelligence (AI) modeling, and the core nodes are positioned and analyzed, so that the transaction average delay of the blockchain network is minimized, and the cost of network maintenance or upgrading is reduced.
The method comprises a training stage and an application stage, wherein block chain nodes in the training stage calculate the score of each centrality criterion; according to the centrality criterion scores, a comprehensive centrality score is calculated, and a blockchain node with a higher comprehensive centrality score is a core node, so that a blockchain test network is established, and 6 weighting coefficients in the comprehensive centrality are iterated and adjusted periodically by means of an AI modeling technology, so that the blockchain transaction delay reaches a preset target.
In the application stage, each block link point calculates each centrality criterion score, calculates comprehensive centrality, and the block chain node with high score is used as a core node to establish a block chain core network, has the priority access right of new node access to the network, and the block chain node with low long-term score executes the processing of exiting the block chain network.
The implementation process of the blockchain core network construction method provided by the embodiment of the invention is described below by taking the blockchain core network construction device as an execution body as an example. It can be appreciated that the implementation subject of the blockchain core network construction method provided by the embodiments of the present invention includes, but is not limited to, a blockchain core network construction device.
Fig. 1 is a flowchart of a blockchain core network construction method according to an embodiment of the present invention, as shown in fig. 1, where the method includes:
Step 101, obtaining a blockchain initial network, wherein the blockchain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened.
Step 102, generating a blockchain test network according to a plurality of nodes to be screened and connecting edges among the nodes to be screened by a preset initial weighting coefficient, wherein the blockchain test network comprises a plurality of core nodes.
And 103, carrying out iterative updating on the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient.
Step 104, updating the blockchain test network according to a target weighting coefficient according to a preset time period to obtain a blockchain core network, wherein the blockchain core network comprises a plurality of updated core nodes.
In the technical scheme provided by the embodiment of the invention, a blockchain initial network is obtained, wherein the blockchain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened; generating a block chain test network according to a plurality of nodes to be screened and connecting edges among the nodes to be screened through a preset initial weighting coefficient, wherein the block chain test network comprises a plurality of core nodes; iteratively updating the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient; updating the blockchain testing network according to a target weighting coefficient to obtain a blockchain core network according to a preset time period, wherein the blockchain core network comprises a plurality of updated core nodes, the blockchain core network is constructed based on a centrality algorithm, the core nodes are determined, the labor cost is reduced, the node utilization rate is improved, and therefore the transaction processing efficiency is improved.
Fig. 2 is a flowchart of another block chain core network construction method according to an embodiment of the present invention, as shown in fig. 2, where the method includes:
step 201, obtaining a blockchain initial network, wherein the blockchain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened.
In the embodiment of the invention, each step is executed by each node of the blockchain.
In the embodiment of the invention, the role configuration of the node to be screened is unknown so as to screen out the core node; and the connection edges between the nodes to be screened identify the connection relationship between the nodes to be screened, and if the connection edges exist between the two nodes to be screened, the connection relationship between the two nodes to be screened is indicated.
Step 202, generating a comprehensive centrality score of each node to be screened according to a plurality of nodes to be screened and connecting edges between the nodes to be screened through a preset initial weighting coefficient.
In the embodiment of the present invention, step 202 specifically includes:
step 2021, generating a centrality score, a near centrality score, an intermediate centrality score, a feature vector centrality score, a K-kernel centrality score and a consensus centrality score of each node to be screened according to a connection edge between a plurality of nodes to be screened and each node to be screened according to a preset time period by a centrality algorithm.
In the embodiment of the present invention, the preset time period may be set according to actual requirements, which is not limited in the embodiment of the present invention.
In the embodiment of the invention, the centrality algorithm is used for calculating centrality indexes of each node, wherein the centrality indexes include but are not limited to: center of degree, near center, intermediate center, feature vector center, K-kernel center, and consensus center.
In the embodiment of the invention, the node to be screened counts the connection number of the connecting edge according to the preset time period, and the counted connection number is used as the centrality score S1. The node to be screened with the connection number higher than the preset connection number threshold is a degree center, wherein the connection number threshold can be set according to actual requirements, and the embodiment of the invention is not limited to the degree center.
To avoid nodes from hooking each other to raise the centrality, a weighted centrality algorithm may be used to calculate the centrality score. Specifically, weight may be set for each connecting edge to perform weighted calculation, so as to obtain a centrality score, which is not limited in the embodiment of the present invention.
In the embodiment of the invention, the node to be screened counts the reciprocal of the sum of the shortest path lengths between the node to be screened and other nodes to be screened in the initial network of the block chain according to a preset time period; the counted reciprocal result is taken as the proximity centrality score S2. The greater the proximity centrality score S2, the higher the efficiency with which the node to be screened transmits messages; the smaller the proximity centrality score S2, the less efficient the node to be screened is in delivering messages. After node consensus in the blockchain, calculating the expectation of the average number of network hops of the blocks transmitted to each node of the whole network in a period of time, wherein the larger the expectation is, the more complex the blockchain network structure is, and the lower the network output efficiency is; the smaller the expectations, the simpler the blockchain network structure, and the higher the network yield efficiency. If the blockchain employs a consensus algorithm for multi-node voting, statistics of slave (pollers) nodes are typically collected by a consensus master (leader) node and calculated. The network hop count refers to the number of routes that the communication between two nodes passes through.
In the embodiment of the invention, the nodes to be screened count the number of the shortest paths passing through the nodes according to a preset time period; the counted number is taken as the intermediate centrality score S3. The larger the intermediate centrality score S3 is, the larger the influence of the node to be screened on the block chain information flow transmission is, and the node interrupt service can possibly cause the common increase of the shortest path in the block chain network; the smaller the mediating centrality score S3, the smaller the impact of the node to be screened on blockchain information flow delivery.
In the embodiment of the invention, according to a preset time period, a node to be screened generates a feature vector centrality score S4 of the node to be screened according to a proximity centrality score S2 of a neighboring node directly adjacent to the node. The more the number of the nodes to be screened are directly connected with the adjacent nodes with the S2 high score, the higher the characteristic vector centrality score S4 of the nodes to be screened is, and the influence on the score of the nodes to be screened is smaller when the nodes to be screened are connected with the adjacent nodes with the S2 low score. The feature vector centrality mainly considers that the core nodes are more concentrated, and has convenience when human intervention management is needed, so that the core nodes calculated by the block chain network tend to be concentrated as much as possible.
As an alternative, the proximity centrality scores S2 of the neighboring nodes of the own node may be accumulated to generate a feature vector centrality score S4 of the node to be screened; the proximity centrality score S2 of the adjacent node of the node can be weighted according to a preset adjacent node weight coefficient to obtain a feature vector centrality score S4 of the node to be screened. The embodiment of the present invention is not limited thereto.
In the embodiment of the invention, the node to be screened determines the average number of the proximity centrality scores S2 of all the neighbor nodes within K from the node to be screened as the K-core centrality score S5 of the node to be screened according to a preset time period. All neighbor nodes comprise neighbor nodes directly adjacent to each other and neighbor nodes indirectly adjacent to each other. The influence of the directly adjacent neighbor nodes and the indirectly adjacent neighbor nodes is considered by the K-kernel centrality, the influence of the number of the directly adjacent neighbor nodes and the proximity centrality score S2 on the current node to be screened is larger, and the influence of the indirectly adjacent neighbor nodes is smaller due to the attenuation factor.
It should be noted that the value of K may be set according to actual requirements, which is not limited in the embodiment of the present invention.
In the embodiment of the invention, if the block chain adopts a multi-node voting consensus algorithm, the node to be screened counts the total number of outgoing blocks in the period of bearing the consensus leader node; taking the counted total number as a consensus centrality score S6; if the blockchain does not employ the consensus algorithm for multi-node voting, then the consensus centrality score S6 is 0. The higher the consensus centrality score S6, the greater the impact of the node to be screened in the blockchain network.
Step 2022, performing weighted calculation on the centrality score, the near centrality score, the intermediate centrality score, the feature vector centrality score, the K-kernel centrality score and the consensus centrality score according to the initial weighting coefficient to obtain a comprehensive centrality score of the node to be screened.
In the embodiment of the invention, in order to avoid that the change amplitude of a certain centrality criterion value is too large or too small, so that the consideration of the comprehensive centrality calculation result is not comprehensive enough, a1 to a6 are introduced as the weighting coefficients of each centrality index score, and 6 weighting coefficients are initialized to obtain initial weighting coefficients. The initial weighting coefficients are set according to actual requirements, and the weighting coefficients are corresponding to different centrality indexes, which is not limited in the embodiment of the present invention.
Specifically, the initial weighting coefficient, the degree centrality score, the near centrality score, the intermediate centrality score, the feature vector centrality score, the K-kernel centrality score, and the consensus centrality score are weighted by s=a1×s1+a2×s2+a3×s3+a4×s4+a5×s5+a6×s6, to obtain a comprehensive centrality score. Wherein S is a comprehensive centrality score, S1 is a centrality score, a1 is an initial weighting coefficient corresponding to a centrality index, S2 is a near centrality score, a2 is an initial weighting coefficient corresponding to a near centrality index, S3 is an intermediate centrality score, a3 is an initial weighting coefficient corresponding to an intermediate centrality index, S4 is a feature vector centrality score, a4 is an initial weighting coefficient corresponding to a feature vector centrality index, S5 is a K-nuclear centrality score, a5 is an initial weighting coefficient corresponding to a K-nuclear centrality index, S6 is a consensus centrality score, and a6 is an initial weighting coefficient corresponding to a consensus centrality index.
Step 203, generating a blockchain test network according to the comprehensive centrality score of each node to be screened, wherein the blockchain test network comprises a plurality of core nodes.
In the embodiment of the present invention, step 203 specifically includes:
Step 2031, comparing the preset centrality score threshold with the comprehensive centrality score of each node to be screened, and screening out the comprehensive centrality score greater than the centrality score threshold.
In the embodiment of the invention, the centrality score threshold is set according to actual requirements, and the embodiment of the invention is not limited to the above.
In the embodiment of the invention, if the comprehensive centrality of the node to be screened is larger than the centrality score threshold value, the comprehensive centrality score of the node to be screened is higher, the node to be screened has stronger comprehensive capability, and the influence in the blockchain network is larger; if the comprehensive centrality of the node to be screened is smaller than or equal to the centrality score threshold, the comprehensive centrality score of the node to be screened is lower, the comprehensive capability is poorer, the influence in the blockchain network is smaller, and the node to be screened is not suitable for being used as a core node.
Step 2032, determining the node to be screened corresponding to the screened comprehensive centrality score as a core node.
In the embodiment of the invention, if the node to be screened has stronger comprehensive capability, the influence in the blockchain network is larger, and the node to be screened is determined to be a core node.
Step 2033, constructing a blockchain test network according to the plurality of core nodes and the connection edges between the core nodes.
In the embodiment of the invention, the connecting edges between each core node and each core node are screened out from the initial network of the block chain, and the block chain test network is constructed.
Further, the blockchain testing network is applied to actual production, transaction processing is carried out through the blockchain testing network, and the average delay of blockchain transaction processing in a period of time is counted.
And 204, carrying out iterative updating on the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient.
Specifically, the initial weighting coefficient is input into a machine learning algorithm for iterative training until the average transaction processing delay of the blockchain system is smaller than a preset transaction processing delay threshold value, and a target weighting coefficient is output.
It is worth to be noted that, the specific algorithm selection of the machine learning algorithm is not limited, and the selection can be performed according to actual conditions; the invention does not limit the setting of the transaction processing delay threshold, can be selected according to actual conditions, and is used as an alternative scheme, wherein the transaction processing delay threshold is 3 seconds.
According to the invention, through the association relation and characteristics among the centrality indexes of each core node in the AI modeling self-learning blockchain test network, 6 initial weighting coefficients are continuously adjusted in training, so that the average transaction processing delay is smaller and smaller until the average transaction processing delay of a blockchain system is smaller than a preset transaction processing delay threshold, namely: the loss function of the AI model is the average delay of transaction processing in the blockchain system.
Step 205, according to a preset time period and according to a connection edge between a plurality of core nodes in a blockchain test network and each core node, generating a degree centrality score, a near centrality score, an intermediate centrality score, a feature vector centrality score, a K-core centrality score and a consensus centrality score of each core node.
In the embodiment of the present invention, the preset time period may be set according to actual requirements, which is not limited in the embodiment of the present invention.
Note that, the calculation manners of the center score, the proximity center score, the intermediate center score, the feature vector center score, the K-core center score, and the consensus center score of the core node are the same as those of step 2021, and are not described herein.
And 206, carrying out weighted calculation on the centrality score, the approaching centrality score, the intermediating centrality score, the feature vector centrality score, the K-kernel centrality score and the consensus centrality score according to the target weighting coefficient to obtain the comprehensive centrality score of the core node.
Specifically, the target weighting coefficient, the degree centrality score, the near centrality score, the intermediate centrality score, the feature vector centrality score, the K-kernel centrality score, and the consensus centrality score are weighted by S ' =a1 ' ×s1+a2' ×s2+a3' ×s3+a4' ×s4+a5' ×s5+a6' ×s6, to obtain the comprehensive centrality score. Wherein, S ' is the comprehensive centrality score of the core node, S1 is the centrality score, a1' is the target weighting coefficient corresponding to the centrality index, S2 is the near centrality score, a2' is the target weighting coefficient corresponding to the near centrality index, S3 is the intermediate centrality score, a3' is the target weighting coefficient corresponding to the intermediate centrality index, S4 is the feature vector centrality score, a4' is the target weighting coefficient corresponding to the feature vector centrality index, S5 is the K-core centrality score, a5' is the target weighting coefficient corresponding to the K-core centrality index, S6 is the consensus centrality score, and a6' is the target weighting coefficient corresponding to the consensus centrality index.
Step 207, updating the blockchain testing network according to the comprehensive centrality score of the core node to obtain a blockchain core network.
In the embodiment of the present invention, step 207 specifically includes:
step 2071, screening out comprehensive centrality scores from a plurality of core nodes in the blockchain test network, wherein the comprehensive centrality scores are smaller than a preset centrality score threshold value in a preset time period of a continuous designated number.
In the embodiment of the invention, the continuous designated number, the preset time period and the centrality score threshold value can be set according to actual requirements, and the embodiment of the invention is not limited to the above.
In the embodiment of the invention, if the comprehensive centrality scores of the core nodes are smaller than the centrality score threshold value in a preset time period with a continuous appointed number, the comprehensive centrality scores of the core nodes are lower for a long term, the comprehensive capacity of the core nodes is weaker, the influence in the blockchain network is smaller, the core nodes are not suitable to be used as the core nodes any more, and the core nodes with the lower comprehensive centrality scores are screened out from the blockchain test network.
Step 2072, determining the core node corresponding to the screened comprehensive centrality score as the node to be exited.
In the embodiment of the invention, the screened core nodes are nodes with lower comprehensive centrality score for a long term, weaker comprehensive capacity and smaller influence in a block chain network; these nodes are no longer suitable as core nodes; these core nodes are determined as nodes to be exited.
Step 2073, filtering the node to be exited from the blockchain test network to obtain a blockchain core network, where the blockchain core network includes a plurality of updated core nodes.
Specifically, the node to be exited and the connection relation thereof are filtered from the blockchain test network, and the filtered network is a blockchain core network. The blockchain core network comprises a plurality of updated core nodes and connection relations thereof.
And step 208, responding to a new node joining request, and screening out the comprehensive centrality score larger than the access threshold according to the comprehensive centrality score of the core node through a preset access threshold.
In the embodiment of the invention, the access threshold is set according to actual requirements, and the embodiment of the invention is not limited to the above.
In the embodiment of the invention, when a new node requests to join a blockchain core network, core nodes with comprehensive centrality scores larger than an access threshold are screened out.
And 209, determining the core node corresponding to the screened comprehensive centrality score as the node to be accessed.
In the embodiment of the invention, the core nodes with the comprehensive centrality score larger than the access threshold value are the nodes with strong comprehensive capacity and larger influence in the blockchain network, and are suitable for receiving the access of the new nodes.
Step 210, the node to be accessed is sent to the new node, so that the new node can select one node to be accessed for accessing.
In the embodiment of the invention, if the number of the nodes to be accessed is 1, the node identification and the node information to be accessed are sent to the new node so as to be accessed by the new node; if the number of the nodes to be accessed is multiple, the multiple access node identifiers and the node information are sent to the new node, so that the new node can select one node to be accessed for access according to the node information.
It should be noted that, the new node may select one node to be accessed according to its own requirement, or may randomly select one node to be accessed for access, which is not limited in the embodiment of the present invention.
According to the invention, the blockchain core nodes under the web3.0 network can be automatically and intelligently positioned and analyzed through the blockchain intelligent contracts, the core nodes can be purposefully and regularly maintained or upgraded, the blockchain nodes which deviate from the result of the centrality algorithm are automatically exited through the intelligent contracts, the probability of intervention of operation and maintenance personnel is reduced, and the equipment of the blockchain nodes in the region requiring operation and maintenance is reduced.
The method comprises the steps of using a plurality of centrality algorithms for positioning and analyzing block chain core nodes under a web3.0 network, comprehensively considering various centrality algorithm results, providing a comprehensive centrality calculation method, using AI modeling for parameter adjustment of a comprehensive centrality calculation model, thereby minimizing transaction average delay of the block chain network, determining the block chain core nodes under the web3 network, and building the block chain core network by the plurality of core nodes. The central node has more comprehensive consideration factors and more intelligent parameter adjustment in the discrimination logic design.
It is worth to be noted that, in the technical scheme of the application, the acquisition, storage, use, processing and the like of the data all conform to the relevant regulations of laws and regulations. The user information in the embodiment of the application is obtained through legal compliance approaches, and the user information is obtained, stored, used, processed and the like through the approval of the client.
In the technical scheme of the block chain core network construction method provided by the embodiment of the application, a block chain initial network is obtained, wherein the block chain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened; generating a block chain test network according to a plurality of nodes to be screened and connecting edges among the nodes to be screened through a preset initial weighting coefficient, wherein the block chain test network comprises a plurality of core nodes; iteratively updating the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient; updating the blockchain testing network according to a target weighting coefficient to obtain a blockchain core network according to a preset time period, wherein the blockchain core network comprises a plurality of updated core nodes, the blockchain core network is constructed based on a centrality algorithm, the core nodes are determined, the labor cost is reduced, the node utilization rate is improved, and therefore the transaction processing efficiency is improved.
Fig. 3 is a schematic structural diagram of a blockchain core network construction device according to an embodiment of the present invention, where the device is configured to execute the blockchain core network construction method, as shown in fig. 3, and the device includes: a blockchain initial network acquisition unit 11, a blockchain test network generation unit 12, a weighting coefficient update unit 13, and a blockchain core network generation unit 14.
The blockchain initial network acquiring unit 11 is configured to acquire a blockchain initial network, where the blockchain initial network includes a plurality of nodes to be screened and connection edges between the nodes to be screened.
The blockchain test network generating unit 12 is configured to generate a blockchain test network according to a plurality of nodes to be screened and connection edges between the nodes to be screened by using a preset initial weighting coefficient, where the blockchain test network includes a plurality of core nodes.
The weighting coefficient updating unit 13 is configured to iteratively update the initial weighting coefficient to obtain the target weighting coefficient through a machine learning algorithm.
The blockchain core network generating unit 14 is configured to update the blockchain test network according to a target weighting coefficient according to a preset time period to obtain a blockchain core network, where the blockchain core network includes a plurality of updated core nodes.
In the embodiment of the present invention, the blockchain test network generating unit 12 is specifically configured to generate, according to a preset initial weighting coefficient, a comprehensive centrality score of each node to be screened according to a plurality of nodes to be screened and a connection edge between the nodes to be screened; and generating a blockchain test network according to the comprehensive centrality score of each node to be screened, wherein the blockchain test network comprises a plurality of core nodes.
In the embodiment of the present invention, the blockchain test network generating unit 12 is specifically configured to generate, according to a preset time period and according to a preset time period, a degree centrality score, a proximity centrality score, an intermediary centrality score, a feature vector centrality score, a K-kernel centrality score and a consensus centrality score of each node to be screened according to a connection edge between a plurality of nodes to be screened; and according to the initial weighting coefficient, weighting and calculating the centrality score, the approaching centrality score, the intermediation centrality score, the feature vector centrality score, the K-nuclear centrality score and the consensus centrality score to obtain the comprehensive centrality score of the node to be screened.
In the embodiment of the present invention, the blockchain test network generating unit 12 is specifically configured to compare a preset centrality score threshold value with a comprehensive centrality score of each node to be screened, and screen out a comprehensive centrality score greater than the centrality score threshold value; determining the node to be screened corresponding to the screened comprehensive centrality score as a core node; and constructing a blockchain test network according to the plurality of core nodes and the connecting edges among the core nodes.
In the embodiment of the present invention, the weighting coefficient updating unit 13 is specifically configured to input the initial weighting coefficient into the machine learning algorithm for iterative training until the average transaction processing delay of the blockchain system is less than the preset transaction processing delay threshold, and output the target weighting coefficient.
In the embodiment of the present invention, the blockchain core network generating unit 14 is specifically configured to generate, according to a preset time period and according to a preset time period, a degree centrality score, a proximity centrality score, an intermediate centrality score, a feature vector centrality score, a K-core centrality score and a consensus centrality score of each core node according to a connecting edge between a plurality of core nodes in the blockchain test network; according to the target weighting coefficient, weighting calculation is carried out on the centrality score, the near centrality score, the intermediate centrality score, the feature vector centrality score, the K-nuclear centrality score and the consensus centrality score to obtain the comprehensive centrality score of the core node; and updating the blockchain testing network according to the comprehensive centrality score of the core node to obtain a blockchain core network.
In the embodiment of the present invention, the blockchain core network generating unit 14 is specifically configured to screen out, from a plurality of core nodes in the blockchain test network, a comprehensive centrality score that is smaller than a preset centrality score threshold value in a preset time period of a continuously specified number; determining the core node corresponding to the screened comprehensive centrality score as a node to be exited; filtering the node to be exited from the blockchain test network to obtain a blockchain core network, wherein the blockchain core network comprises a plurality of updated core nodes.
In the embodiment of the invention, the device further comprises: a screening unit 15, a determining unit 16 and an access unit 17.
The screening unit 15 is configured to, in response to a new node joining request, screen out a comprehensive centrality score greater than the access threshold according to the comprehensive centrality score of the core node through a preset access threshold.
The determining unit 16 is configured to determine a core node corresponding to the screened integrated centrality score as a node to be accessed.
The access unit 17 is configured to send the node to be accessed to the new node, so that the new node selects one node to be accessed for access.
In the scheme of the embodiment of the invention, a block chain initial network is obtained, wherein the block chain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened; generating a block chain test network according to a plurality of nodes to be screened and connecting edges among the nodes to be screened through a preset initial weighting coefficient, wherein the block chain test network comprises a plurality of core nodes; iteratively updating the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient; updating the blockchain testing network according to a target weighting coefficient to obtain a blockchain core network according to a preset time period, wherein the blockchain core network comprises a plurality of updated core nodes, the blockchain core network is constructed based on a centrality algorithm, the core nodes are determined, the labor cost is reduced, the node utilization rate is improved, and therefore the transaction processing efficiency is improved.
The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. A typical implementation device is a computer device, which may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
The embodiment of the application provides a computer device, which comprises a memory and a processor, wherein the memory is used for storing information comprising program instructions, the processor is used for controlling the execution of the program instructions, and the program instructions realize the steps of the embodiment of the block chain core network construction method when being loaded and executed by the processor.
Referring now to FIG. 4, there is illustrated a schematic diagram of a computer device 600 suitable for use in implementing embodiments of the present application.
As shown in fig. 4, the computer apparatus 600 includes a Central Processing Unit (CPU) 601, which can perform various appropriate works and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage section 608 into a Random Access Memory (RAM) 603. In the RAM603, various programs and data required for the operation of the computer device 600 are also stored. The CPU601, ROM602, and RAM603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, mouse, etc.; an output portion 607 including a Cathode Ray Tube (CRT), a liquid crystal feedback device (LCD), and the like, and a speaker, and the like; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The drive 610 is also connected to the I/O interface 605 as needed. Removable media 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on drive 610 as needed, so that a computer program read therefrom is mounted as needed as storage section 608.
In particular, according to embodiments of the present invention, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, embodiments of the present invention include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the method shown in the flowchart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication portion 609, and/or installed from the removable medium 611.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in the same piece or pieces of software and/or hardware when implementing the present application.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
The technical scheme of the application obtains, stores, uses, processes and the like the data, which all meet the relevant regulations of national laws and regulations.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The application may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The application may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and variations of the present application will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. which come within the spirit and principles of the application are to be included in the scope of the claims of the present application.
Claims (12)
1. A method for constructing a blockchain core network, the method comprising:
acquiring a block chain initial network, wherein the block chain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened;
generating a blockchain test network according to the nodes to be screened and the connecting edges among the nodes to be screened by a preset initial weighting coefficient, wherein the blockchain test network comprises a plurality of core nodes;
iteratively updating the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient;
and updating the block chain test network according to the target weighting coefficient according to a preset time period to obtain a block chain core network, wherein the block chain core network comprises a plurality of updated core nodes.
2. The blockchain core network construction method of claim 1, wherein the generating the blockchain test network according to the plurality of nodes to be screened and the connection edges between the nodes to be screened by the preset initial weighting coefficient includes:
Generating a comprehensive centrality score of each node to be screened according to the plurality of nodes to be screened and the connecting edges among the nodes to be screened through a preset initial weighting coefficient;
and generating a blockchain test network according to the comprehensive centrality score of each node to be screened, wherein the blockchain test network comprises a plurality of core nodes.
3. The blockchain core network construction method of claim 2, wherein the generating, by a preset initial weighting coefficient, a comprehensive centrality score of each node to be screened according to the plurality of nodes to be screened and a connection edge between the nodes to be screened includes:
generating a degree centrality score, a proximity centrality score, an intermediate centrality score, a feature vector centrality score, a K-kernel centrality score and a consensus centrality score of each node to be screened according to a connecting edge between the nodes to be screened and each node to be screened according to a preset time period by a centrality algorithm;
and according to the initial weighting coefficient, carrying out weighted calculation on the centrality score, the approaching centrality score, the intermediate centrality score, the feature vector centrality score, the K-kernel centrality score and the consensus centrality score to obtain the comprehensive centrality score of the node to be screened.
4. The blockchain core network construction method of claim 2, wherein the generating a blockchain test network according to the comprehensive centrality score of each node to be screened, the blockchain test network including a plurality of core nodes includes:
comparing a preset centrality score threshold with the comprehensive centrality score of each node to be screened, and screening out a comprehensive centrality score larger than the centrality score threshold;
determining the node to be screened corresponding to the screened comprehensive centrality score as a core node;
and constructing the blockchain test network according to the plurality of core nodes and the connecting edges among the core nodes.
5. The blockchain core network construction method of claim 1, wherein iteratively updating the initial weighting coefficients by a machine learning algorithm to obtain target weighting coefficients comprises:
and inputting the initial weighting coefficient into a machine learning algorithm for iterative training until the transaction processing average delay of the blockchain system is smaller than a preset transaction processing delay threshold value, and outputting the target weighting coefficient.
6. The method for constructing a blockchain core network according to claim 1, wherein updating the blockchain test network according to the target weighting coefficient to obtain the blockchain core network according to the preset time period includes:
Generating a degree centrality score, a near centrality score, an intermediate centrality score, a feature vector centrality score, a K-core centrality score and a consensus centrality score of each core node according to the preset time period and according to the connecting edges between a plurality of core nodes in the blockchain test network and each core node;
according to the target weighting coefficient, weighting calculation is carried out on the centrality score, the approaching centrality score, the intermediating centrality score, the characteristic vector centrality score, the K-kernel centrality score and the consensus centrality score to obtain a comprehensive centrality score of the kernel node;
and updating the blockchain testing network according to the comprehensive centrality score of the core node to obtain a blockchain core network.
7. The blockchain core network construction method of claim 6, wherein updating the blockchain test network according to the comprehensive centrality score of the core node to obtain a blockchain core network comprises:
screening out the comprehensive centrality scores from a plurality of core nodes in the blockchain test network, wherein the comprehensive centrality scores are smaller than a preset centrality score threshold value in a continuous specified number of preset time periods;
Determining the core node corresponding to the screened comprehensive centrality score as a node to be exited;
and filtering the node to be exited from the blockchain testing network to obtain the blockchain core network, wherein the blockchain core network comprises a plurality of updated core nodes.
8. The method for constructing a blockchain core network according to claim 7, further comprising, after the updating the blockchain test network according to the target weighting coefficient for the predetermined period of time to obtain the blockchain core network:
responding to a new node joining request, and screening out a comprehensive centrality score larger than a preset access threshold according to the comprehensive centrality score of the core node through the preset access threshold;
determining the core node corresponding to the screened comprehensive centrality score as a node to be accessed;
and sending the node to be accessed to the new node so that the new node can select one node to be accessed for accessing.
9. A blockchain core network construction device, the device comprising:
the system comprises a block chain initial network acquisition unit, a block chain processing unit and a processing unit, wherein the block chain initial network acquisition unit is used for acquiring a block chain initial network, and the block chain initial network comprises a plurality of nodes to be screened and connecting edges among the nodes to be screened;
The block chain test network generation unit is used for generating a block chain test network according to the plurality of nodes to be screened and the connecting edges among the nodes to be screened through a preset initial weighting coefficient, wherein the block chain test network comprises a plurality of core nodes;
the weighting coefficient updating unit is used for carrying out iterative updating on the initial weighting coefficient through a machine learning algorithm to obtain a target weighting coefficient;
and the block chain core network generating unit is used for updating the block chain test network according to the target weighting coefficient according to a preset time period to obtain a block chain core network, wherein the block chain core network comprises a plurality of updated core nodes.
10. A computer readable medium having stored thereon a computer program, which when executed by a processor implements the blockchain core network construction method of any of claims 1 to 8.
11. A computer device comprising a memory for storing information including program instructions and a processor for controlling execution of the program instructions, wherein the program instructions when loaded and executed by the processor implement the blockchain core network construction method of any of claims 1 to 8.
12. A computer program product comprising computer programs/instructions which when executed by a processor implement the blockchain core network construction method of any of claims 1 to 8.
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