CN111047447A - Method and device for determining number of issued voucher, computer equipment and storage medium - Google Patents
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Abstract
The application relates to a method and a device for determining the amount of a certificate of pass, computer equipment and a storage medium, wherein a node attribute characteristic set, a node behavior characteristic set and a certificate of pass issuing condition of a block chain node are obtained, a node performance characteristic set is determined according to the node attribute characteristic set and the node behavior characteristic set, and then the amount of the certificate of pass is determined by adopting different calculation modes of the amount of the certificate of pass according to two different certificate of pass issuing conditions of credit reward recording and target certificate of pass, so that the certificate of pass is allocated in a targeted manner, and the application of the certificate of pass in a block chain system is more flexible and efficient.
Description
Technical Field
The present application relates to a blockchain technology, and in particular, to a method, an apparatus, a computer device, and a storage medium for determining a voucher issuance amount.
Background
The blockchain is referred to as the value internet, which is essentially a trust mechanism. The certificate is a translation of token, and the certificate's original meaning is "token, signaling", which can be understood as a kind of "negotiable encrypted digital rights certificate". The proof of interest may be tickets, points, contracts, certificates, point cards, securities, and rights, among others. A token (hereinafter referred to as a pass) on the blockchain is a unique certificate for generating a relationship between an individual and a blockchain item, and is also a pass for using the underlying resource of the blockchain by the community individual. The general evidence is used as a value medium in a community ecosystem, the problem of excitation among block chain link points is solved, and the problem of endogenous power of long-term stable operation of the system is guaranteed.
In the current block chain system, most of the determination of the evidence amount of the block chain link points is in a non-differential mode, block chains are different for multi-currency/diversified evidence-passing block chain systems, the characteristics and the grades of the evidence are different, the determination mode of the evidence amount of the block chain nodes is lack of pertinence, and the effect of the evidence-passing in the block chain system is difficult to play.
Disclosure of Invention
Therefore, it is necessary to provide a targeted method, an apparatus, a computer device and a storage medium for determining the amount of issued voucher, aiming at the problems that the determination method of the amount of issued voucher of the blockchain node is lack of pertinence and the function of voucher in the blockchain system is difficult to be exerted.
A method for determining the amount of issued certificates, which comprises the following steps:
acquiring a node attribute feature set, a node behavior feature set and a pass certificate issuing condition of a block chain node;
determining a node performance characteristic set according to the node attribute characteristic set and the node behavior characteristic set;
when the certification issuing condition is that the block chain nodes have credit reward records, obtaining certification issuing basic data, and determining a target first certification issuing amount based on the certification issuing basic data, the node attribute feature set, the node behavior feature set and the node performance feature set, wherein the target certification is used for casting a rejection ticket or canceling a non-target certification in the process that the block chain nodes achieve consensus through voting;
and when the certification passing issuing condition is that the block link point uses the target certification, acquiring target certification passing use data of the block link node, and determining a second target certification passing issuing amount based on the target certification passing use data.
In one embodiment, determining the node performance feature set according to the node attribute feature set and the node behavior feature set includes:
extracting node type data in the node attribute feature set;
screening out corresponding historical operation records from the node behavior characteristic set according to the node type data;
and determining a node performance characteristic set according to the screened historical operation records.
In one embodiment, determining the first target credentialing amount based on the credentialing base data, the node attribute feature set, the node behavior feature set and the node performance feature set comprises:
acquiring a preset accreditation amount calculation function, wherein the accreditation amount calculation function is constructed on the basis of the feature vectors of the block chain nodes;
and determining the first target voucher issuing amount according to the voucher issuing basic data, the node attribute characteristic set, the node behavior characteristic set, the node performance characteristic set and the preset voucher amount calculation function.
In one embodiment, the target pass use data comprises a target pass use evaluation result and a target pass use degree grade;
determining a second target passphrase issuance amount based on the target passphrase usage data comprises:
selecting a corresponding amount issuing rule from a preset amount issuing rule set according to the target evidence-passing use evaluation result;
determining an initial issuing amount of the target pass certificate based on the selected amount issuing rule;
detecting whether the target pass evidence use degree grade is a preset strong grade or not to obtain a target pass evidence use degree grade detection result;
and adjusting the initial issuing amount of the target voucher according to the detection result of the target voucher usage degree grade to obtain a second target voucher issuing amount.
In one embodiment, the step of screening out the corresponding historical operation record from the node behavior feature set according to the node type data includes:
if the node type of the block chain node is a common node, the historical operation records screened from the node behavior feature set comprise the model of the historical access equipment, the historical feedback time, the general ledger updating frequency and the offline transaction record;
if the node type of the block chain node is a verification node, the historical operation records screened from the node behavior feature set comprise verification transaction number per second, packaging time, block output time and block output records.
In one embodiment, the credential issuance base data includes: the total number of the block chain nodes, the number of the block chain links holding the target pass certificate, the issuing quantity and the flow quantity of the target pass certificate and the historical reward records of each block chain node.
A passcard issuance amount determination apparatus comprising:
the data acquisition module is used for acquiring a node attribute feature set, a node behavior feature set and a certification issuing condition of the block chain node;
the node performance determining module is used for determining a node performance characteristic set according to the node attribute characteristic set and the node behavior characteristic set;
the first issuing amount determining module is used for acquiring the certification issuing basic data when the certification issuing condition is that the block link points have credit reward records, and determining a first target certification issuing amount based on the certification issuing basic data, the node attribute feature set, the node behavior feature set and the node performance feature set, wherein the target certification is used for casting a rejection ticket or offsetting a non-target certification in the process that the block link nodes achieve consensus through voting;
and the second issuing amount determining module is used for acquiring target pass-certificate use data of the block chain nodes when the pass-certificate issuing condition is that the block chain link points use the target pass-certificate, and determining a second target pass-certificate issuing amount based on the target pass-certificate use data.
In one embodiment, the node performance determining module is further configured to extract node type data in the node attribute feature set, screen a corresponding historical operation record from the node behavior feature set according to the node type data, and determine the node performance feature set according to the screened historical operation record.
A computer device comprising a memory and a processor, the memory storing a computer program, the processor implementing the following steps when executing the computer program:
acquiring a node attribute feature set, a node behavior feature set and a pass certificate issuing condition of a block chain node;
determining a node performance characteristic set according to the node attribute characteristic set and the node behavior characteristic set;
when the certification issuing condition is that the block chain nodes have credit reward records, obtaining certification issuing basic data, and determining a first target certification issuing amount based on the certification issuing basic data, the node attribute feature set, the node behavior feature set and the node performance feature set, wherein the target certification is used for casting a rejection ticket or canceling a non-target certification in the process that the block chain nodes achieve consensus through voting;
and when the certification passing issuing condition is that the block link point uses the target certification, acquiring target certification passing use data of the block link node, and determining a second target certification passing issuing amount based on the target certification passing use data.
A computer-readable storage medium, on which a computer program is stored which, when executed by a processor, carries out the steps of:
acquiring a node attribute feature set, a node behavior feature set and a pass certificate issuing condition of a block chain node;
determining a node performance characteristic set according to the node attribute characteristic set and the node behavior characteristic set;
when the certification issuing condition is that the block chain nodes have credit reward records, obtaining certification issuing basic data, and determining a first target certification issuing amount based on the certification issuing basic data, the node attribute feature set, the node behavior feature set and the node performance feature set, wherein the target certification is used for casting a rejection ticket or canceling a non-target certification in the process that the block chain nodes achieve consensus through voting;
and when the certification passing issuing condition is that the block link point uses the target certification, acquiring target certification passing use data of the block link node, and determining a second target certification passing issuing amount based on the target certification passing use data.
The method, the device, the computer equipment and the storage medium for determining the number of the passed certificates are used for acquiring a node attribute feature set, a node behavior feature set and a passed certificate issuing condition of a block chain node, determining a node performance feature set according to the node attribute feature set and the node behavior feature set, and then determining the number of the passed certificates according to different passed certificate issuing conditions, namely good reward records and target passed certificates, by adopting different calculation modes of the number of the passed certificates, realizing targeted distribution of the passed certificates, and enabling the application of the passed certificates in a block chain system to be more flexible and efficient.
Drawings
FIG. 1 is a diagram of an application environment of a method for determining a number of a voucher issuance in one embodiment;
FIG. 2 is a flow chart illustrating a method for determining a number of a voucher issuance according to an embodiment;
FIG. 3 is a flowchart illustrating a method for determining a number of a voucher issuance amount according to another embodiment;
FIG. 4 is a flowchart illustrating the step of determining a second target summons issuance amount based on the target summons usage data in one embodiment;
FIG. 5 is a block diagram showing the construction of a voucher issuance amount determining apparatus according to an embodiment;
FIG. 6 is a diagram illustrating an internal structure of a computer device according to an embodiment.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The method for determining the amount of the issued voucher can be applied to the application environment shown in FIG. 1. The blockchain node 102 communicates with a server 104 (hereinafter referred to as server 104) of a multi-currency/evidence-passing type blockchain system through a network. Specifically, a plurality of block link points 102 to be distributed with pass certificates may exist in the block chain system, when the server 104 receives a pass certificate amount determination request, the server responds to the request, obtains a node attribute feature set, a node behavior feature set and a pass certificate issuing condition of the block chain nodes, determines a node performance feature set according to the node attribute feature set and the node behavior feature set, obtains pass certificate issuing basic data when the pass certificate issuing condition is that the block link points have credit reward records, and determines a first target pass certificate issuing amount based on the pass certificate issuing basic data, the node attribute feature set, the node behavior feature set and the node performance feature set, the target pass certificate is a pass certificate used for casting an objection ticket or canceling a non-target pass certificate in the process that the block chain nodes achieve consensus through voting, when the pass certificate issuing condition is that the block link points use the target pass certificate, and acquiring target pass-certificate use data of the blockchain node, and determining a second target pass-certificate issuing amount based on the target pass-certificate use data. The blockchain node 102 may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and portable wearable devices, and the server 104 may be implemented by an independent server or a server cluster formed by a plurality of servers.
In one embodiment, as shown in fig. 2, a method for determining the amount of a voucher issued is provided, which is exemplified by the application of the method to the server 104 in fig. 1, and includes the following steps:
and step S200, acquiring a node attribute feature set, a node behavior feature set and a certification-passing issuing condition of the block chain node.
The node attribute feature set includes, but is not limited to, node type (e.g., primary node, verification node, organization node, and personal node), uplink mode (e.g., invited uplink (which may be obtained by link automatic analysis during registration) and autonomous uplink), uplink time, professional scope, professional grade (e.g., high grade), and historical node interaction record (e.g., transaction time, transaction frequency, transaction amount, whether there is an exception record, etc.). The area of profession can be divided by industry professions, general invited nodes have fields filled automatically to represent the professions, and nodes on the autonomous uplink can be selected or skipped. In this embodiment, the node attribute feature set may be represented by T1. The node behavior feature set includes, but is not limited to, general operation records (issuing, accounting, transaction, etc.), target operation records, and the target operation records refer to records operated by using target pass-through (inhibitory pass-through), in this embodiment, the target pass-through is a pass-through for casting a negative vote or canceling non-inhibitory pass-through in the process of sharing a consensus by voting among the block nodes. Specifically, the general operation record may be further refined into operation time/frequency, a transaction object, whether the transaction is honest, and the targeted operation may be further refined into an operation scene (voting or emergency, etc.), a target number of certificates used, an operation result, and the like. In specific implementation, a plurality of trigger conditions for obtaining the evidence of each block link point are set. Specifically, it may include whether the block link point has good credit record and whether the target pass is used.
And step S400, determining a node performance characteristic set according to the node attribute characteristic set and the node behavior characteristic set.
The node performance feature set may also be understood as a computational feature set, which includes but is not limited to a CPU (central Processing Unit)/GPU (Graphic Processing Unit) model, an accessible time, a network latency, and the like. After the node attribute feature set and the node behavior feature set are obtained, the recorded data in the node attribute feature set and the node behavior feature set can be extracted, and the performance feature set of the block chain node is evaluated. For example, different evaluations may be performed depending on the type of node.
Step S600, when the certification issuing condition is that the block link points have credit reward records, obtaining certification issuing basic data, and determining a first target certification issuing amount based on the certification issuing basic data, the node attribute feature set, the node behavior feature set and the node performance feature set.
In this embodiment, the target pass is a pass for casting a negative vote or canceling a non-target pass in a process of making a consensus by voting by the blockchain node, and the target pass may be referred to as an inhibitory pass in the present application. In a blockchain network, when a node owner volunteers to contribute its own computing resources to store and validate transactions, there is an opportunity to charge transaction fees and obtain corresponding rewards in potential cryptocurrency. Good credit records can obtain inhibitory evidence, the system carries out node behavior evaluation irregularly, good credit record keepers are awarded, and in order to avoid moral risks, the time for implementing awards and the number of awards which can be obtained are not necessary. If the current condition of issuing the voucher is that the good credit record is provided, obtaining basic data of issuing the voucher, wherein the basic data of issuing the voucher can comprise the total number of block link points, the number of the block link points holding the target voucher, good credit reward data and the like, and then calculating a first target amount of issuing the voucher based on the obtained basic data of issuing the voucher, the node attribute characteristic set, the node behavior characteristic set and the node performance characteristic set. Specifically, the calculation may be performed by calculating the amount of the voucher through a preset feature function.
Step S800, when the certification passing issuing condition is that the block chain link point uses the target certification, acquiring target certification passing using data of the block chain link point, and determining a second target certification passing issuing amount based on the target certification passing using data.
In specific implementation, if the certification issuing condition is that the block link point uses the target certification, target certification use data of the current block link node is acquired, wherein the target certification use data includes an evaluation result of target certification use, a target certification use degree grade and the like, then, based on the target certification use data, a corresponding target certification amount calculation rule is used, and then, a second target certification issuing amount is determined.
The method, the device, the computer equipment and the storage medium for determining the number of the passed certificates are used for acquiring a node attribute feature set, a node behavior feature set and a passed certificate issuing condition of a block chain node, determining a node performance feature set according to the node attribute feature set and the node behavior feature set, and then determining the number of the passed certificates according to different passed certificate issuing conditions, namely good reward records and target passed certificates, by adopting different calculation modes of the number of the passed certificates, realizing targeted distribution of the passed certificates, and enabling the application of the passed certificates in a block chain system to be more flexible and efficient.
In one embodiment, as shown in fig. 3, determining the node performance feature set according to the node attribute feature set and the node behavior feature set includes: step S420, extracting node type data in the node attribute feature set, screening out corresponding historical operation records from the node behavior feature set according to the node type data, and determining a node performance feature set according to the screened historical operation records.
A node in a blockchain refers to a computer in a blockchain network, including a mobile phone, a mining machine, a server, and the like. The operational nodes may be common wallet users, miners, and multiple people collaborating, storing, and authenticating, all of which may be nodes of a blockchain. The node type data comprises verification nodes, common nodes, organization nodes and the like, after the node attribute feature set is obtained, the node type data can be extracted, and then, according to the node type data and a preset rule, corresponding historical operation records are screened from the node behavior feature set, for example, offline transaction records, block output records, the updating frequency of an account book and the like are screened. And deducing a calculation force characteristic set, namely a performance characteristic set, of the current block link node based on the screened historical operation records. In another embodiment, if the node type of the blockchain node is a common node, historical operation records including the model of the historical access device, the historical feedback time, the general ledger update frequency, the offline transaction record and the like are screened from the node behavior feature set; and if the node type of the block chain node is a verification node, screening historical operation records including verification transaction number per second, packaging time, block output records and the like from the node behavior characteristic set. Then, the screened historical operation records are respectively given to obtain the computation force characteristic set of the current block link node, including but not limited to average access time, network delay, whether operation offline occurs or not, and the like. In the embodiment, different historical operation records are screened out according to different node types, and the performance characteristic set of the node is determined, so that the method has higher pertinence.
In one embodiment, determining the first target credentialing amount based on the credentialing base data, the node attribute feature set, the node behavior feature set and the node performance feature set comprises: the method comprises the steps of obtaining a preset voucher amount calculation function, constructing the voucher amount calculation function based on feature vectors of block chain nodes, and determining a target voucher issuing amount according to voucher issuing basic data, a node attribute feature set, a node behavior feature set, a node performance feature set and the preset voucher amount calculation function.
In practical application, a developer builds a corresponding pass characteristic function in advance based on a characteristic vector in a characteristic set of a block chain node, specifically builds a characteristic function f1 according to a node attribute characteristic set T1, builds a characteristic function f2 according to a node behavior characteristic set T2, and builds a characteristic function f3 according to a node performance characteristic set, and combines and inhibits total issued traffic (I) and current traffic or issued traffic (T). When the condition of issuing the certificate of pass is that the block link points have credit reward records, the acquired basic data of issuing the certificate of pass comprises the total number N of the block link nodes, the number S of the block link points holding the target certificate of pass, the issuing quantity I and the traffic T of the target certificate of pass and historical reward records H of each block link node, then, the constructed characteristic functions of calculating the certificate of pass amount, including f1, f2, f3 and a function A, are correspondingly acquired, and based on T1, T2 and T3, the basic data of issuing the certificate of pass and the characteristic functions are combined, and A ═ (lambda, f) is adopted1(T1),f2(T2),f3(T3) I, T, N, S, H) to calculate the amount a of the inhibitory general evidence obtainable this time. Where F is a function used to calculate the amount of the voucher, λ represents a system parameter, and λ is variable in response to changes in system size, but is generally relatively stable in the short term. In this embodiment, the amount of the voucher is calculated by constructingThe function enables to calculate quickly and accurately the amount of inhibitory evidence available for the current blockchain node.
In one embodiment, as shown in fig. 4, the target passport usage data includes a target passport usage evaluation result and a target passport usage level, and determining the second target passport issuance amount based on the target passport usage data includes:
step S820, selecting a corresponding amount issuing rule from a preset amount issuing rule set according to the target evidence-passing use evaluation result;
step S860, detecting whether the target permit use degree grade is a preset strong grade or not to obtain a target permit use degree grade detection result;
and step S880, adjusting the initial issuing amount of the target voucher according to the detection result of the usage degree level of the target voucher to obtain a second target voucher issuing amount.
In practical application, the target pass-certificate usage data includes a target pass-certificate usage evaluation result and a target pass-certificate usage degree grade. Result evaluation (correct use, unmistakable use, incorrect use), target pass usage level rating (strong, general), etc., and then, based on the result evaluation and the target pass usage level, it is determined whether the used suppressive pass is eligible for compensation and whether the suppressive pass can be rewarded additionally. The system is not real-time to evaluate the use of the target evidence, waits for the proposal fermentation for a period of time, and judges according to the implementation effect of the proposal. For example, if the proposal is executed with serious consequences, the system is lost with general evidence, or there is negative news (it can be judged whether negative news is caused by NLP (Natural Language Processing) sentiment analysis by accessing external news data), or there is complaint proposal of large-scale users, then the users who have applied inhibitory general evidence at that time can be considered as giving "correct" results. If all inhibitory passes are used correctly, such as in an emergency, additional inhibitory passes will be returned and awarded afterwards. There are cases where inhibitory evidence may be used, not necessarily the best, but without malignant consequences, and return (all or a portion) of the evidence may be considered. The judgment of the target pass evidence use degree grade is positively correlated with the specific use amount and frequency of the inhibitory pass evidence, namely, if the inhibitory pass evidence used at the time accounts for more than 80% of the inhibitory pass evidence held by the node, or the inhibitory pass evidence is continuously applied for 3 times or more to a certain proposal, the target pass evidence use degree grade of the node can be considered as 'strong', otherwise, the node is 'normal'; if the target general evidence use degree grade and the evaluation result are mutually superposed, if the target general evidence use degree grade is correctly used and the target general evidence use degree grade is strong, not only the spent inhibitory general evidence amount can be returned, but also the extra reward amount is added, and the reward amount is not more than 10% of the spent inhibitory general evidence, namely, the node obtains 110% of the spent inhibitory general evidence at most. If not used incorrectly, a maximum of 100% cost-out of inhibitory evidence is generally obtained. If the system is used by mistake, the system generally obtains 50% of the spent inhibitory certificates at most, and in the case of error and strong grade, the inhibitory certificates may not be issued temporarily. In the embodiment, according to the target currency use degree grade and the use evaluation result, how to issue the inhibitory currency of a specific amount is determined, so that moral risks can be avoided to a certain extent, professional spirit can be encouraged, and the cautious use of the inhibitory currency is encouraged.
It should be understood that although the various steps in the flow charts of fig. 2-4 are shown in order as indicated by the arrows, the steps are not necessarily performed in order as indicated by the arrows. The steps are not performed in the exact order shown and described, and may be performed in other orders, unless explicitly stated otherwise. Moreover, at least some of the steps in fig. 2-4 may include multiple sub-steps or multiple stages that are not necessarily performed at the same time, but may be performed at different times, and the order of performance of the sub-steps or stages is not necessarily sequential, but may be performed in turn or alternating with other steps or at least some of the sub-steps or stages of other steps.
In one embodiment, as shown in fig. 5, there is provided a voucher issuance amount determination apparatus including: a data acquisition module 410, a node performance determination module 420, a first release amount determination module 430, and a second release amount determination module 440, wherein:
the data obtaining module 410 is configured to obtain a node attribute feature set, a node behavior feature set, and a credential issuance condition of a blockchain node.
The node performance determining module 420 is configured to determine a node performance feature set according to the node attribute feature set and the node behavior feature set.
The first issuing amount determining module 430 is configured to, when the voucher issuing condition is that the block link points have the credit reward record, obtain voucher issuing basis data, and determine a first target voucher issuing amount based on the voucher issuing basis data, the node attribute feature set, the node behavior feature set, and the node performance feature set.
And a second issuing amount determining module 440, configured to, when the pass issuing condition is that the block link point uses the target pass, obtain target pass using data of the block link node, and determine a second target pass issuing amount based on the target pass using data.
The node performance determining module 420 is further configured to extract node type data in the node attribute feature set, screen a corresponding historical operation record from the node behavior feature set according to the node type data, and determine a node performance feature set according to the screened historical operation record.
The first issuance amount determining module 430 is further configured to obtain feature functions corresponding to the node attribute feature set, the node behavior feature set, and the node performance feature set, and determine a target issuance amount of the voucher according to the voucher issuance basic data, the node attribute feature set, the node behavior feature set, the node performance feature set, and the preset voucher amount calculating function.
In one embodiment, the first issuing amount determining module 430 is further configured to select a corresponding amount issuing rule from a preset amount issuing rule set according to the target passport use evaluation result, detect whether the target passport use level is a preset strong level, obtain a target passport use level detection result, adjust the selected amount issuing rule according to the target passport use level detection result, and determine the target passport issuing amount.
The node performance determining module 420 is further configured to, if the node type of the block chain node is a common node, filter out a historical operation record from the node behavior feature set, where the historical operation record includes a model of a historical access device, historical feedback time, a general ledger update frequency, and an offline transaction record, and if the node type of the block chain node is a verification node, filter out a historical operation record from the node behavior feature set, where the historical operation record includes a number of verification transactions per second, a packing time, a block output time, and a block output record.
For the specific definition of the passthrough issuance amount determination apparatus, reference may be made to the above definition of the passthrough issuance amount determination method, which is not described herein again. The respective modules in the above-described passcertificate issuance amount determining apparatus may be implemented in whole or in part by software, hardware, and a combination thereof. The modules can be embedded in a hardware form or independent from a processor in the computer device, and can also be stored in a memory in the computer device in a software form, so that the processor can call and execute operations corresponding to the modules.
In one embodiment, a computer device is provided, which may be a server, and its internal structure diagram may be as shown in fig. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The database of the computer equipment is used for storing and acquiring the node attribute feature set, the node behavior feature set data, the evidence obtaining conditions and the like of the block chain nodes. The network interface of the computer device is used for communicating with an external terminal through a network connection. The computer program when executed by a processor implements a method of determining a passcertificate issuance amount.
Those skilled in the art will appreciate that the architecture shown in fig. 6 is merely a block diagram of some of the structures associated with the disclosed aspects and is not intended to limit the computing devices to which the disclosed aspects apply, as particular computing devices may include more or less components than those shown, or may combine certain components, or have a different arrangement of components.
In one embodiment, a computer device is provided, comprising a memory and a processor, the memory having a computer program stored therein, the processor implementing the following steps when executing the computer program: the method comprises the steps of obtaining a node attribute feature set, a node behavior feature set and a certification issuing condition of a block chain node, determining a node performance feature set according to the node attribute feature set and the node behavior feature set, obtaining certification issuing basic data when the certification issuing condition is that a block chain node has credit reward records, determining a first target certification issuing amount based on the certification issuing basic data, the node attribute feature set, the node behavior feature set and the node performance feature set, wherein target certification is used for casting a negative ticket or cancelling non-target certification in the process that the block chain node achieves consensus through voting, obtaining target certification use data of the block chain node when the certification issuing condition is that the block chain node uses the target certification, and determining a second target certification issuing amount based on the target certification use data.
In one embodiment, the processor, when executing the computer program, further performs the steps of: extracting node type data in the node attribute feature set, screening a corresponding historical operation record from the node behavior feature set according to the node type data, and determining a node performance feature set according to the screened historical operation record.
In one embodiment, the processor, when executing the computer program, further performs the steps of: and acquiring a preset voucher amount calculation function, and determining the target voucher issuing amount according to the voucher issuing basic data, the node attribute feature set, the node behavior feature set, the node performance feature set and the preset voucher amount calculation function.
In one embodiment, the processor, when executing the computer program, further performs the steps of: according to the target pass-certificate use evaluation result, selecting a corresponding amount issuing rule from a preset amount issuing rule set, determining an initial issuing amount of the target pass-certificate based on the selected amount issuing rule, detecting whether the target pass-certificate use degree grade is a preset strong grade, obtaining a target pass-certificate use degree grade detection result, and adjusting the initial issuing amount of the target pass-certificate according to the target pass-certificate use degree grade detection result to obtain a second target pass-certificate issue amount.
In one embodiment, the processor, when executing the computer program, further performs the steps of: if the node type of the block chain node is a common node, the historical operation records screened from the node behavior characteristic set comprise the model of the historical access equipment, the historical feedback time, the general ledger updating frequency and the offline transaction record, and if the node type of the block chain node is a verification node, the historical operation records screened from the node behavior characteristic set comprise the verification transaction number per second, the packaging time, the block output time and the block output record.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which when executed by a processor performs the steps of: the method comprises the steps of obtaining a node attribute feature set, a node behavior feature set and a certification issuing condition of a block chain node, determining a node performance feature set according to the node attribute feature set and the node behavior feature set, obtaining certification issuing basic data when the certification issuing condition is that a block chain node has credit reward records, determining a first target certification issuing amount based on the certification issuing basic data, the node attribute feature set, the node behavior feature set and the node performance feature set, wherein target certification is used for casting a negative ticket or cancelling non-target certification in the process that the block chain node achieves consensus through voting, obtaining target certification use data of the block chain node when the certification issuing condition is that the block chain node uses the target certification, and determining a second target certification issuing amount based on the target certification use data.
In one embodiment, the computer program when executed by the processor further performs the steps of: extracting node type data in the node attribute feature set, screening a corresponding historical operation record from the node behavior feature set according to the node type data, and determining a node performance feature set according to the screened historical operation record.
In one embodiment, the computer program when executed by the processor further performs the steps of: and acquiring a preset voucher amount calculation function, and determining the target voucher issuing amount according to the voucher issuing basic data, the node attribute feature set, the node behavior feature set, the node performance feature set and the preset voucher amount calculation function.
In one embodiment, the computer program when executed by the processor further performs the steps of: according to the target pass-certificate use evaluation result, selecting a corresponding amount issuing rule from a preset amount issuing rule set, determining an initial issuing amount of the target pass-certificate based on the selected amount issuing rule, detecting whether the target pass-certificate use degree grade is a preset strong grade, obtaining a target pass-certificate use degree grade detection result, and adjusting the initial issuing amount of the target pass-certificate according to the target pass-certificate use degree grade detection result to obtain a second target pass-certificate issue amount.
In one embodiment, the computer program when executed by the processor further performs the steps of: : if the node type of the block chain node is a common node, the historical operation records screened from the node behavior characteristic set comprise the model of the historical access equipment, the historical feedback time, the general ledger updating frequency and the offline transaction record, and if the node type of the block chain node is a verification node, the historical operation records screened from the node behavior characteristic set comprise the verification transaction number per second, the packaging time, the block output time and the block output record.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A method of determining a passcertificate issuance amount, the method comprising:
acquiring a node attribute feature set, a node behavior feature set and a pass certificate issuing condition of a block chain node;
determining a node performance characteristic set according to the node attribute characteristic set and the node behavior characteristic set;
when the certification issuing condition is that the block chain nodes have credit reward records, obtaining certification issuing basic data, and determining a first target certification issuing amount based on the certification issuing basic data, the node attribute feature set, the node behavior feature set and the node performance feature set, wherein the target certification is used for casting a negative vote or offsetting a non-target certification in the process that the block chain nodes achieve consensus through voting;
and when the certification passing issuing condition is that the block link point uses the target certification, acquiring target certification passing use data of the block link node, and determining a second target certification passing issuing amount based on the target certification passing use data.
2. The method of claim 1, wherein determining a set of node performance characteristics based on the set of node attribute characteristics and the set of node behavior characteristics comprises:
extracting node type data in the node attribute feature set;
screening out corresponding historical operation records from the node behavior characteristic set according to the node type data;
and determining a node performance characteristic set according to the screened historical operation records.
3. The method of claim 1, wherein determining a first target passphrase issuance amount based on the passphrase issuance base data, the node attribute feature set, the node behavior feature set, and the node performance feature set comprises:
acquiring a preset evidence-passing amount calculation function, wherein the preset evidence-passing amount calculation function is constructed based on the feature vectors of the block chain nodes;
and determining a first target currency issuing amount according to the currency issuing basic data, the node attribute feature set, the node behavior feature set, the node performance feature set and the preset currency amount calculation function.
4. The method of claim 1, wherein the target LC usage data includes a target LC usage evaluation result and a target LC usage level;
the determining a second target passphrase issuance amount based on the target passphrase usage data comprises:
selecting a corresponding amount issuing rule from a preset amount issuing rule set according to the target voucher usage evaluation result;
determining an initial issuing amount of the target pass certificate based on the selected amount issuing rule;
detecting whether the target pass evidence use degree grade is a preset strong grade or not to obtain a target pass evidence use degree grade detection result;
and adjusting the initial issuing amount of the target pass according to the detection result of the target pass service degree grade to obtain a second target pass issuing amount.
5. The method of claim 2, wherein the step of screening the node behavior feature set for corresponding historical operational records according to the node type data comprises:
if the node type of the block chain node is a common node, the model of the historical access equipment, the historical feedback time, the general ledger updating frequency and the offline transaction record are screened from the node behavior feature set;
and if the node type of the block chain node is a verification node, screening verification transaction number per second, packaging time, block output time and block output records from the node behavior feature set.
6. The method of claim 1, wherein the credentialing basis data comprises a total number of blockchain nodes, a number of blockchain link points holding a target credentialing, an issuing amount and a traffic amount of the target credentialing, and a historical reward record of each blockchain node.
7. A device for determining a passcertificate issuance amount, the device comprising:
the data acquisition module is used for acquiring a node attribute feature set, a node behavior feature set and a certification issuing condition of the block chain node;
the node performance determining module is used for determining a node performance characteristic set according to the node attribute characteristic set and the node behavior characteristic set;
the first issuing amount determining module is used for acquiring the basic data of the certification issuing when the certification issuing condition is that the block chain link points have credit reward records, and determining a first target certification issuing amount based on the basic data of the certification issuing, the node attribute feature set, the node behavior feature set and the node performance feature set, wherein the target certification is used for casting a negative vote or counteracting the non-target certification in the process that the block chain link points achieve consensus through voting;
and the second issuing amount determining module is used for acquiring target pass-certificate use data of the block chain nodes when the pass-certificate issuing condition is that the block chain link points use the target pass-certificate, and determining a second target pass-certificate issuing amount based on the target pass-certificate use data.
8. The apparatus of claim 7, wherein the node performance determining module is further configured to extract node type data in the node attribute feature set, screen a corresponding historical operation record from the node behavior feature set according to the node type data, and determine a node performance feature set according to the screened historical operation record.
9. A computer device comprising a memory and a processor, the memory storing a computer program, wherein the processor implements the steps of the method of any one of claims 1 to 6 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 6.
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