CN110197373B - Data processing method, device, block chain node and computer readable storage medium - Google Patents
Data processing method, device, block chain node and computer readable storage medium Download PDFInfo
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Abstract
The application provides a data processing method, a data processing device, a block chain node and a computer readable storage medium, and relates to the technical field of the Internet.
Description
Technical Field
The present application relates to the field of internet technologies, and in particular, to a data processing method, an apparatus, a block chain node, and a computer-readable storage medium.
Background
The block chain network comprises two roles, namely a verifier (Validator) and a Delegator (Delegator), wherein the verifier is responsible for operating a verifier node, verifying and broadcasting newly submitted blocks in the block chain network, and the voting weight of the verifier is determined by the number of tokens Token bound by the verifier; the principal does not have the capability of operating the verifier node, and corresponding rights can be obtained only by entrusting Token possessed by the principal as the verifier.
In the prior art, the measurement criteria for the verifier access threshold is based on the total number of tokens bound to the verifier, i.e. the sum of the number of tokens owned by the verifier and the number of tokens accepted by the verifier. In the block chain network, if a new block chain link point is to be added to become a verifier, the total number of tokens bound by the new block chain link point only contains the number of tokens owned by the new block chain link point, so that a node which is a verifier in the first place is caused.
Disclosure of Invention
The present application aims to provide a data processing method, an apparatus, a block chain node, and a computer-readable storage medium, which can avoid that a node which previously becomes a verifier in a block chain network obtains a larger voting weight by relying on more accepted delegated tokens on the premise that the node has a smaller number of tokens, thereby enabling the right of the verifier in the block chain network to be publicly leveled.
In order to achieve the above purpose, the embodiments of the present application employ the following technical solutions:
in a first aspect, an embodiment of the present application provides a data processing method, where the method includes:
acquiring target self-binding proportion according to Token number information corresponding to target block link points in a block chain network, wherein the Token number information comprises target self-binding Token numbers of the target block chain nodes and target entrusted Token numbers for receiving entrusts, and the target self-binding proportion represents the comparison level of the self-binding Token numbers and the entrusted Token numbers in all the Token points held by the target block chain nodes;
acquiring an average self-binding proportion according to total Token number information corresponding to the block chain network, wherein the total Token number information comprises the sum of self-binding Token numbers of validators of all verifiers in the block chain network and the sum of entrusted Token numbers received by all verifiers in the block chain network, and the average self-binding proportion represents the contrast level of the sum of the self-binding Token numbers and the sum of the entrusted Token numbers in the block chain network;
and acquiring the voter voting weight corresponding to the target block link point according to the target self-binding proportion, the average self-binding proportion and the Token number information.
In a second aspect, an embodiment of the present application provides a data processing apparatus, where the apparatus includes:
the proportion calculation module is used for acquiring target self-binding proportion according to Token number information corresponding to a target block chain link point in a block chain network, wherein the Token number information comprises target self-binding Token number of the target block chain node self-binding and target entrusted Token number of receiving entrustment, and the target self-binding proportion represents the contrast level of the self-binding Token number and the entrusted Token number in all the Token held by the target block chain link point;
the proportion calculation module is further configured to obtain an average self-binding proportion according to total Token number information corresponding to the blockchain network, where the total Token number information includes a sum of self-binding Token numbers of validators self-binding all verifiers in the blockchain network, and a sum of delegation Token numbers of receiving delegations of all verifiers in the blockchain network, and the average self-binding proportion characterizes a comparison level of the sum of self-binding Token numbers in the blockchain network and the sum of delegation Token numbers;
and the voting weight calculation module is used for obtaining the verifier voting weight corresponding to the target block link point according to the target self-binding proportion, the average self-binding proportion and the Token quantity information.
In a third aspect, embodiments of the present application provide a block link point, including a memory for storing one or more programs; a processor. The one or more programs, when executed by the processor, implement the data processing method described above.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when executed by a processor, implements the data processing method described above.
Compared with the prior art, the data processing method, the data processing device, the block chain node and the computer readable storage medium provided by the embodiments of the present application obtain the verifier voting weight corresponding to the target block chain link point from the target self-binding specific gravity corresponding to the target block chain link point in the block chain network and the average self-binding specific gravity corresponding to the block chain network, and further from the target self-binding specific gravity, the average self-binding specific gravity and the Token number information corresponding to the target block chain link point, obtain the verifier voting weight corresponding to the target block chain link point by integrating the contrast level of the self-binding Token number and the commitment Token number in all tokens held by the target block chain link point, the contrast level of the sum of the self-binding Token number and the commitment Token number in the block chain network and the Token number information corresponding to the target block chain link point, avoid that a node which first becomes a verifier in the block chain network has a smaller Token number per se, and obtaining a larger voting weight by depending on more accepted entrusted tokens, thereby flattening the equity of the verifier in the block chain network.
In order to make the aforementioned objects, features and advantages of the present application more comprehensible, preferred embodiments accompanied with figures are described in detail below.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are required to be used in the embodiments will be briefly described below, it should be understood that the following drawings only illustrate some embodiments of the present application and therefore should not be considered as limiting the scope, and it will be apparent to those skilled in the art that other related drawings can be obtained from the drawings without inventive effort.
Fig. 1 is a schematic block diagram of a block link point provided in an embodiment of the present application;
FIG. 2 is a schematic flow chart of a data processing method provided by an embodiment of the present application;
FIG. 3 is a schematic flow chart of the substeps of S205 of FIG. 2;
FIG. 4 is another schematic flow chart of a data processing method provided by an embodiment of the present application;
FIG. 5 is a schematic flow chart of the substeps of S207 in FIG. 4;
fig. 6 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application.
In the figure: 100-block link points; 101-a memory; 102-a processor; 103-a communication interface; 300-a data processing apparatus; 301-a specific gravity calculation module; 302-voting weight calculation module; 303-revenue distribution calculation module.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. The components of the embodiments of the present application, generally described and illustrated in the figures herein, can be arranged and designed in a wide variety of different configurations.
Thus, the following detailed description of the embodiments of the present application, presented in the accompanying drawings, is not intended to limit the scope of the claimed application, but is merely representative of selected embodiments of the application. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, it need not be further defined and explained in subsequent figures. Meanwhile, in the description of the present application, the terms "first", "second", and the like are used only for distinguishing the description, and are not to be construed as indicating or implying relative importance.
It is noted that, herein, relational terms such as first and second, and the like may be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, 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 an … …" does not exclude the presence of other identical elements in a process, method, article, or apparatus that comprises the element.
Some embodiments of the present application will be described in detail below with reference to the accompanying drawings. The embodiments described below and the features of the embodiments can be combined with each other without conflict.
As described above, in the prior art, since the measurement criteria for the admission threshold of the verifier is based on the total Token number bound to the verifier (including the sum of the Token number owned by the verifier and the Token number delegated by the verifier), it may cause that a previous node may obtain a larger voting weight on the premise that the previous node owns a smaller Token number, so as to form an oligopoint and operate the transaction verification and voting results in the blockchain network.
Based on the above defects, a possible implementation manner provided by the embodiment of the present application is as follows: the method comprises the steps of integrating the contrast level of the number of self-binding tokens in all tokens held by a target block chain link point and the number of entrusts, the contrast level of the sum of the number of self-binding tokens in a block chain network and the sum of the number of entrusts, and the number information of tokens corresponding to the target block chain link point to obtain the voting weight of a verifier corresponding to the target block chain link point, and avoiding that a node which is a verifier in the block chain network depends on more accepted entrusts to obtain larger voting weight on the premise that the node has less tokens.
Referring to fig. 1, fig. 1 is a schematic block diagram of a block link point 100 according to an embodiment of the present disclosure. The block link point 100 includes a memory 101, a processor 102 and a communication interface 103, wherein the memory 101, the processor 102 and the communication interface 103 are electrically connected to each other directly or indirectly to realize data transmission or interaction. For example, the components may be electrically connected to each other via one or more communication buses or signal lines. The memory 101 may be used for storing software programs and modules, such as program instructions/modules corresponding to the data processing apparatus 300 provided in the embodiments of the present application, and the processor 102 executes the software programs and modules stored in the memory 101, thereby executing various functional applications and data processing. The communication interface 103 may be used for communicating signaling or data with other node devices.
The Memory 101 may be, but is not limited to, a Random Access Memory (RAM), a Read Only Memory (ROM), a Programmable Read-Only Memory (PROM), an Erasable Read-Only Memory (EPROM), an electrically Erasable Read-Only Memory (EEPROM), and the like.
The processor 102 may be an integrated circuit chip having signal processing capabilities. The Processor 102 may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components.
It will be appreciated that the configuration shown in fig. 1 is merely illustrative and that block link point 100 may also include more or fewer components than shown in fig. 1 or have a different configuration than shown in fig. 1. The components shown in fig. 1 may be implemented in hardware, software, or a combination thereof.
Referring to fig. 2, fig. 2 is a schematic flowchart of a data processing method according to an embodiment of the present application, including the following steps:
s201, obtaining the target self-binding proportion according to the Token quantity information corresponding to the target block link point in the block chain network.
S203, acquiring the average self-binding proportion according to the total Token number information corresponding to the block chain network.
S205, obtaining the verifier voting weight corresponding to the target block link point according to the target self-binding specific gravity, the average self-binding specific gravity and the Token number information.
In the embodiment of the application, a block chain node with a role as a verifier in a block chain network is taken as a target block chain node for example to calculate the voting weight of the verifier, wherein each block chain node in the block chain network stores Token number information of all verifiers in the block chain network, the Token number information of each verifier comprises a self-binding Token number and a consignment Token number, each self-binding Token number represents the sum of the Token numbers owned by the corresponding verifier, and each consignment Token number represents the sum of the Token numbers delegated by the consignor by the corresponding verifier.
The target block chain nodes are used as verifiers, and the Token number information of all the verifiers stored by each block chain node comprises Token number information corresponding to the target block chain link, wherein the Token number information corresponding to the target block chain link comprises target self-binding Token numbers of the target block chain nodes and target consignment Token numbers for accepting consignment.
When calculating the voter voting weight of the target block chain node, acquiring a target self-binding proportion according to the number information of the Token corresponding to the target block chain link point in the block chain network, wherein the target self-binding proportion represents the comparison level between the number of the self-binding tokens in all the tokens held by the target block chain link point and the number of the entrustments, namely the comparison level between the number of the tokens held by the target block chain link point and the number of the tokens accepted entrustments.
In addition, each block chain node in the block chain network also stores total Token number information corresponding to the block chain network, and the total Token number information includes the sum of self-binding Token numbers of all verifiers in the block chain network and the sum of entrusted Token numbers of all verifiers in the block chain network for receiving entrusts. As a possible implementation manner, the sum of the self-binding Token numbers may be obtained by summing the self-binding Token numbers of all verifiers by the block link point, and the sum of the entrusted Token numbers may be obtained by summing the entrusted Token numbers of all verifiers by the block link point.
Therefore, when the voter voting weight of the target block chain node is calculated, the average self-binding proportion is obtained according to the total Token number information corresponding to the block chain network, and the average self-binding proportion represents the contrast level of the sum of the self-binding Token numbers in the block chain network and the sum of the entrusted Token numbers, namely the contrast level of the sum of the Token numbers owned by all the verifiers and the sum of the Token numbers accepted by all the verifiers in the block chain network.
Therefore, in the application, the voter voting weight corresponding to the target block link point is calculated and obtained according to the target self-binding specific gravity, the average self-binding specific gravity and the Token number information corresponding to the target block link point.
Based on the above design, the data processing method provided in the embodiments of the present application obtains the target binding specific gravity corresponding to the target block link point in the block chain network and the average self-binding specific gravity corresponding to the block chain network, and further obtains the verifier voting weight corresponding to the target block link point from the target self-binding specific gravity, the average self-binding specific gravity and the Token number information corresponding to the target block link point, and compared with the prior art, obtains the verifier voting weight corresponding to the target block link point by integrating the contrast level of the self-binding Token number and the entrusted Token number in all tokens held by the target block link point, the contrast level of the sum of the self-binding Token number and the entrusted Token number in the block chain network and the Token number information corresponding to the target block link point, and avoids the node which first becomes the verifier in the block chain network having a smaller Token number on the premise that the node itself has a smaller Token number, and obtaining a larger voting weight by depending on more accepted entrusted tokens, thereby flattening the equity of the verifier in the block chain network.
Optionally, to implement S201, as a possible implementation manner, the formula for obtaining the target self-binding specific gravity corresponding to the link point of the target block may be:
wherein, wiIs a target self-binding proportion, T, corresponding to a target block chain node iisIs the target self-binding Token number T corresponding to the target block chain node iiwAnd entrusting the number of tokens for the target corresponding to the target block chain node i.
That is, as a possible implementation manner, the target self-binding specific gravity corresponding to the target block link point may be a ratio of the target self-binding Token number corresponding to the target block link point to the target delegation Token number, where if the value of the target self-binding specific gravity is greater than 1, the Token representing that the self-binding Token is more than the Token accepting the delegation in all tokens held by the target block link point; if the value of the target self-binding proportion is less than 1, more Token accepting the delegation than self-binding Token in all Token held by the link points of the representation target block.
It should be noted that the target self-binding specific gravity may also be obtained by calculating in some other possible manners, for example, calculating a ratio of the target self-binding Token number corresponding to the target block link point to all Token numbers held by the target block link point, as long as the target self-binding specific gravity corresponding to the target block link point can be obtained by calculation.
Optionally, to implement S203, as a possible implementation manner, the formula for obtaining the average self-binding proportion corresponding to the blockchain network may be:
wherein the content of the first and second substances,
is the average self-binding weight, T, corresponding to the blockchain networkS0Is the sum of the number of self-binding tokens, T, in a blockchain networkW0Is the sum of the delegated Token numbers in the blockchain network.
That is to say, as a possible implementation manner, the average self-binding proportion corresponding to the blockchain network may be a ratio of a sum of self-binding tokens self-bound by all verifiers in the blockchain network to a sum of delegation tokens accepted by all verifiers, where if the value of the average self-binding proportion is greater than 1, a total number of self-binding tokens characterizing all verifiers in the blockchain network is more than a total number of tokens accepted by all verifiers; if the value of the target self-binding proportion is less than 1, the total number of tokens for accepting the delegation by all verifiers in the representation block chain network is more than the total number of the self-binding tokens.
It should be noted that the average self-binding proportion may also be calculated and obtained by some other possible manners, for example, calculating a ratio of the sum of the self-binding Token numbers of all verifiers in the block chain network to the sum of all Token numbers in the block chain network, as long as the average self-binding proportion corresponding to the block chain network can be calculated and obtained.
Optionally, to implement the above S205, please refer to fig. 3, fig. 3 is a schematic flowchart of sub-steps of S205 in fig. 2, and as a possible implementation, S205 includes the following sub-steps:
s205-1, judging whether the number of target entrustment tokens for the target block chain node to accept the entrustment is 0; if not, executing S205-2; if so, S205-5 is performed.
S205-2, judging whether the target self-binding specific gravity is smaller than the average self-binding specific gravity; if so, executing S205-3; if not, S205-4 is executed.
S205-3, obtaining the voter voting weight corresponding to the target block chain link point according to the target self-binding Token number, the target entrustment Token number and the target entrustment lever coefficient corresponding to the target block chain link point.
S205-4, obtaining the verifier voting weight corresponding to the target block link point according to the target self-binding Token number and the target entrustment Token number.
S205-5, obtaining the verifier voting weight corresponding to the target block chain link point according to the target self-binding Token number.
In the embodiment of the application, when the voter voting weight corresponding to the target block link point is calculated, different calculations are performed on the voter voting weight corresponding to the target block link point based on the target entrusted Token number received by the target block link point and the sizes of the target self-binding specific gravity and the average self-binding specific gravity.
If the number of target entrusted tokens which are entrusted by the target block chain node is 0, the target block chain node is characterized not to accept to obtain the tokens of the entrustor, at the moment, the voter voting weight corresponding to the target block chain link point is directly calculated according to the number of the target self-binding tokens which are self-bound by the target block chain node, for example, the number of the target self-binding tokens corresponding to the target block chain link point is used as the voter voting weight.
If the number of target entrusted tokens accepted by the target block link point is not 0, the sizes of the target self-binding specific gravity and the average self-binding specific gravity are continuously judged, if the target self-binding specific gravity is smaller than the average self-binding specific gravity, the comparison level between the number of self-binding tokens and the number of entrusted tokens in all tokens held by the target block link point is lower than the average level of the whole block chain network, the target block link point may be a block link point which uses less self-binding tokens to accept more entrusted tokens, at this time, the verifier voting weight corresponding to the target block link point is calculated according to the number of target self-binding tokens, the number of target entrusted tokens and the target entrusting lever coefficient corresponding to the target block link point, for example, the target entrusting lever coefficient is used as the scaling multiple of the target entrusted tokens and then summed with the number of target self-binding tokens, or the summed number of target self-binding tokens and the number of target entrusted tokens, and multiplying by a target entrusting lever coefficient, and taking the finally obtained product as the verifier voting weight corresponding to the target block link point, wherein the target entrusting lever coefficient is the scaling coefficient of Token held by the target block link point.
If the target self-binding proportion is greater than or equal to the average self-binding proportion, it is indicated that the contrast level between the number of self-binding tokens and the number of entrusted tokens in all tokens held by the target block link point reaches the average level of the whole block chain network, the target block chain node may be a block link point which uses the self-binding tokens to accept less entrusted tokens, and at this time, according to the number of target self-binding tokens and the number of target entrusted tokens, a verifier voting weight corresponding to the target block link point is obtained by calculation, for example, the sum of the number of target self-binding tokens and the number of target entrusted tokens is used as the verifier voting weight, or the sum of the number of target entrusted tokens and the number of binding tokens is added after the number of target entrusted tokens is multiplied by a preset scaling multiple, and the obtained sum is used as the verifier voting weight.
Optionally, as a possible implementation manner, the calculation formula of the verifier voting weight corresponding to the target block link point may be:
wherein, PiVoting weights for verifiers, TisTarget self-binding Token number, TiwEntrusted Token number, G, for the targetiEntrust leverage factor, w, for targetiIn order to target the self-binding weight,
is the average self-binding weight.
Analyzing the above formula, as a possible implementation manner, when calculating the voter voting weight corresponding to the target block link point, if the target entrusted Token number of the target block link point acceptance entrustment is 0, taking the target self-binding Token number corresponding to the target block link point as the voter voting weight; if the number of target entrusted tokens for accepting the delegation of the target block link point is not 0 and the target self-binding proportion is greater than or equal to the average self-binding proportion, taking the sum of the number of the target self-binding tokens and the number of the target entrusted tokens as the voting weight of the verifier; and if the number of target entrustment tokens for accepting the entrustment of the target block link point is not 0 and the target self-binding proportion is smaller than the average self-binding proportion, taking the sum of the product of the target entrustment lever coefficient and the target entrustment tokens and the target self-binding tokens as the voting weight of the verifier.
As a possible implementation manner, the calculation formula of the target entrusting lever coefficient in the above formula may be:
that is, in the embodiment of the present application, the target entrusting lever coefficient corresponding to the target block link point may be obtained by using the above equation and combining the target self-binding specific gravity and the average self-binding specific gravity.
It should be noted that, in some other possible implementation manners of the embodiment of the present application, the target entrusting leverage coefficient may be calculated in other manners, for example, a ratio of the target self-binding specific gravity to the average self-binding specific gravity is used as the target entrusting leverage coefficient, as long as the target entrusting leverage coefficient can be obtained according to the target self-binding specific gravity and the average self-binding specific gravity, for example, a result obtained by multiplying the ratio of the target self-binding specific gravity to the average self-binding specific gravity by a pre-examination coefficient may also be used as the target entrusting leverage coefficient.
Therefore, based on the design, a calculation mode of the voting weight of the verifier of the target block chain node is determined according to the target self-binding proportion and the average self-binding proportion, when the target self-binding proportion is smaller than the average self-binding proportion, a target entrusting lever coefficient is calculated according to the target self-binding proportion and the average self-binding proportion, and then the target entrusting lever coefficient is used for scaling the target entrusting lever number corresponding to the target block chain link point, so that a large number of clients in the block chain network can not entrust the held Token to the same verifier (if entrusting is the same verifier, the target self-binding proportion of the verifier is far lower than the average self-binding proportion, the entrusting lever coefficient of the verifier is small), but the delegation is balanced according to the distribution condition of the self-binding Token numbers respectively held by different verifiers, the equitable rights and interests of verifiers in the block chain network are ensured, and the situation that a verifier with less Token numbers obtains more delegated tokens to form oligopeptides is avoided.
In order to avoid the block chain nodes which become the verifiers in the block chain network, the block chain nodes which become the verifiers in the prior art are few in number and more in revenue distribution, so that the block chain nodes which become the verifiers in the prior art become short.
Therefore, optionally, on the basis of fig. 2, please refer to fig. 4, where fig. 4 is another schematic flowchart of the data processing method provided in the embodiment of the present application, and after S205, the data processing method further includes the following steps:
and S207, acquiring the distribution quantity of each block of income according to the current number of verifiers in the block chain network.
In the embodiment of the application, at least part of each profit is allocated based on the number of current verifiers in the block chain network, rather than directly allocating all profits.
For example, if 50 tokens are obtained from a mine excavation, based on the number of current verifiers in the blockchain network, it is possible to allocate revenue among the verifiers only by 30 tokens out of the 50 tokens.
Optionally, referring to fig. 5, fig. 5 is a schematic flow chart of the sub-step of S207 in fig. 4, and as a possible implementation, S207 includes the following sub-steps:
s207-1, judging whether the number of current verifiers in the block chain network reaches a target number threshold; if yes, executing S207-2; if not, S207-3 is executed.
And S207-2, taking the preset profit allocation amount as the allocation amount of the profits per block.
And S207-3, obtaining the distribution quantity of each income according to the current number of verifiers, the target number of people threshold and the preset income distribution quantity.
In the embodiment of the application, each block chain node as a verifier stores a target number threshold, the target number threshold represents the upper limit of the distribution number of each profit in the block chain network along with the change of the number of verifiers, and if the number of the current verifiers in the block chain network reaches the target number threshold, the preset profit distribution number is used as the distribution number of each profit; otherwise, if the number of the current verifiers in the block chain network does not reach the target number threshold, calculating according to the number of the current verifiers, the target number threshold and the preset profit distribution number to obtain the distribution number of each profit.
Alternatively, as a possible implementation manner, the calculation formula of the allocation amount of each block of earnings may be:
wherein Q is the allocated amount of revenue per block, Q0For a predetermined amount of revenue distribution, RiFor the current number of verifiers, R0Is the target population threshold.
Namely, if the number of current verifiers in the block chain network reaches the target number threshold, taking the preset profit distribution number as the distribution number of each profit; and if the number of the current verifiers in the block chain network does not reach the target number of people threshold, taking the arithmetic square root of the ratio of the number of the current verifiers to the target number of people threshold as an adjustment coefficient, multiplying the adjustment coefficient by the preset profit distribution number, and taking the obtained product as the distribution number of each profit.
For instance, assume illustratively a preset revenue distribution amount Q0A target number of people threshold R of 1000Is 20, if the number of the current verifiers RiIf the number of revenue is 30, the distribution quantity Q of each block is 100; if the number R of the current verifiersiAnd 5, the allocated amount of revenue per block is 50.
It is worth to be noted that, in some other possible implementation manners of the embodiment of the present application, other formulas may also be used to calculate the allocation amount of each profit, for example, when the number of current verifiers reaches the target number threshold, a preset coefficient smaller than 1 is multiplied by the preset allocation amount of profits, or a scaling coefficient calculated according to other formulas is multiplied by the preset allocation amount of profits, and an obtained result is used as the allocation amount of each profit; or, for example, when the number of current verifiers does not reach the target number of people threshold, taking the ratio of the number of current verifiers to the target number of people threshold as the calculated scaling factor to multiply the preset profit distribution number, taking the obtained result as the distribution number of each profit, and mainly calculating the distribution number of each profit according to the number of current verifiers.
From this, through by the current verifier quantity in the block chain network, obtain the distribution quantity of every income, and then make the distribution quantity of every income in the visual block chain network of current as the verifier's block chain link point quantity and decide, avoid all earnings of every income to distribute for the block chain node that becomes the verifier earlier, when the verifier is less in the block chain network, the income distribution is more, and then forms the oligopolism.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a data processing apparatus 300 according to an embodiment of the present disclosure, where the data processing apparatus 300 includes a specific gravity calculation module 301 and a voting weight calculation module 302.
The proportion calculation module 301 is configured to obtain a target self-binding proportion according to Token number information corresponding to a target block link point in the block chain network, where the Token number information includes a target self-binding Token number of the target block chain node self-binding and a target entrusted Token number for accepting an entrustment, and the target self-binding proportion represents a comparison level between the self-binding Token number and the entrusted Token number in all Token nodes held by the target block chain link point.
The proportion calculation module 301 is further configured to obtain an average self-binding proportion according to total Token number information corresponding to the blockchain network, where the total Token number information includes a sum of self-binding Token numbers of validators of all verifiers in the blockchain network, and a sum of entrusted Token numbers received by all verifiers in the blockchain network, and the average self-binding proportion characterizes a comparison level between the sum of self-binding Token numbers in the blockchain network and the sum of entrusted Token numbers.
The voting weight calculation module 302 is configured to obtain a verifier voting weight corresponding to a target block link point according to the target self-binding specific gravity, the average self-binding specific gravity, and the Token number information.
Optionally, as a possible implementation manner, the formula for the proportion calculation module 301 to obtain the target self-binding proportion corresponding to the link point of the target block is as follows:
wherein, wiIs a target self-binding proportion, T, corresponding to a target block chain node iisIs the target self-binding Token number T corresponding to the target block chain node iiwAnd entrusting the number of tokens for the target corresponding to the target block chain node i.
Optionally, as a possible implementation manner, the formula for obtaining the average self-binding weight corresponding to the blockchain network by the weight calculation module 301 is as follows:
wherein the content of the first and second substances,
is the average self-binding weight, T, corresponding to the blockchain networkS0Is the sum of the number of self-binding tokens, T, in a blockchain networkW0Is the sum of the delegated Token numbers in the blockchain network.
Optionally, as a possible implementation manner, the voting weight calculating module 302 is specifically configured to:
if the number of target entrusted tokens for accepting entrustment of the target block link point is 0, obtaining the voting weight of the verifier corresponding to the target block link point according to the number of target self-binding tokens;
if the number of target entrusts Token for accepting the entrusts of the link points of the target block is larger than 0, judging whether the target self-binding proportion is smaller than the average self-binding proportion;
if the target self-binding proportion is smaller than the average self-binding proportion, obtaining the voter voting weight corresponding to the target block chain link point according to the target self-binding Token number, the target entrustment Token number and the target entrustment lever coefficient corresponding to the target block chain link point, wherein the target entrustment lever coefficient is the scaling coefficient of Token held by the target block chain link point;
and if the target self-binding proportion is greater than or equal to the average self-binding proportion, acquiring the verifier voting weight corresponding to the target block link point according to the target self-binding Token number and the target entrustment Token number.
Optionally, as a possible implementation manner, the formula for the voting weight calculation module 302 to calculate the verifier voting weight corresponding to the target block link point is as follows:
wherein, PiVoting weights for verifiers, TisTarget self-binding Token number, TiwEntrusted Token number, G, for the targetiEntrust leverage factor, w, for targetiIn order to target the self-binding weight,
is the average self-binding weight.
Optionally, as a possible implementation manner, the formula for the voting weight calculation module 302 to calculate the target entrusting leverage coefficient is as follows:
optionally, as a possible implementation manner, the data processing apparatus 300 further includes a revenue distribution calculating module 303, where the revenue distribution calculating module 303 is configured to obtain the distribution amount of each revenue according to the current number of verifiers in the blockchain network.
Optionally, as a possible implementation manner, the profit sharing calculation module 303 is specifically configured to:
if the number of current verifiers in the block chain network reaches a target number threshold, taking the preset profit distribution number as the distribution number of each profit;
and if the number of the current verifiers in the block chain network does not reach the target number of persons threshold, obtaining the distribution number of each block of income according to the number of the current verifiers, the target number of persons threshold and the preset income distribution number.
Optionally, as a possible implementation manner, the formula for the profit sharing calculation module 303 to calculate the sharing amount of the profits per block is as follows:
wherein Q is the allocated amount of revenue per block, Q0For a predetermined amount of revenue distribution, RiFor the current number of verifiers, R0Is the target population threshold.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other ways. The apparatus embodiments described above are merely illustrative and, for example, the flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods and computer program products according to embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In addition, the functional modules in the embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.
The functions, if implemented in the form of software functional modules and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application or portions thereof that substantially contribute to the prior art may be embodied in the form of a software product stored in a storage medium and including instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In summary, according to the data processing method, apparatus, block chain node, and computer-readable storage medium provided in the embodiments of the present application, by obtaining the target binding specific gravity corresponding to the target block chain link point in the block chain network and the average self-binding specific gravity corresponding to the block chain network, and further obtaining the verifier voting weight corresponding to the target block chain link point from the target self-binding specific gravity, the average self-binding specific gravity, and the Token number information corresponding to the target block chain link point, compared to the prior art, by synthesizing the contrast level of the self-binding Token number and the commitment Token number in all tokens held by the target block chain link point, the contrast level of the sum of the self-binding Token number and the commitment Token number in the block chain network, and the Token number information corresponding to the target block chain link point, the verifier voting weight corresponding to the target block chain link point is obtained, so as to avoid that a node which first becomes a verifier in the block chain network has a smaller Token number per se, and obtaining a larger voting weight by depending on more accepted entrusted tokens, thereby flattening the equity of the verifier in the block chain network.
In addition, the distribution quantity of each income is obtained through the quantity of the current verifiers in the block chain network, so that the distribution quantity of each income is determined according to the quantity of the block chain link points which are currently used as the verifiers in the block chain network, and the whole income of each income is prevented from being distributed, so that the block chain nodes which are the verifiers firstly become, and when the verifiers are fewer in the block chain network, the income is distributed more, so that the shortages are formed.
The above description is only a preferred embodiment of the present application and is not intended to limit the present application, and various modifications and changes may be made by those skilled in the art. Any modification, equivalent replacement, improvement and the like made within the spirit and principle of the present application shall be included in the protection scope of the present application.
It will be evident to those skilled in the art that the present application is not limited to the details of the foregoing illustrative embodiments, and that the present application may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the application being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Claims (11)
1. A method of data processing, the method comprising:
acquiring target self-binding proportion according to Token number information corresponding to a target block link point in a block chain network, wherein the Token number information comprises target self-binding Token numbers of the target block chain node self-binding and target consignment Token numbers for accepting consignment, and the target self-binding proportion represents the comparison level of the target self-binding Token numbers and the target consignment Token numbers in all Token points held by the target block link point;
acquiring an average self-binding proportion according to total Token number information corresponding to the block chain network, wherein the total Token number information comprises the sum of self-binding Token numbers of validators of all verifiers in the block chain network and the sum of entrusted Token numbers received by all verifiers in the block chain network, and the average self-binding proportion represents the contrast level of the sum of the self-binding Token numbers and the sum of the entrusted Token numbers in the block chain network;
obtaining the verifier voting weight corresponding to the target block chain link point according to the target self-binding proportion, the average self-binding proportion and the Token number information;
if the number of target entrusted tokens for the target block chain node to accept entrustment is 0, obtaining the voter voting weight corresponding to the target block chain link point according to the number of target self-binding tokens;
if the number of the target entrusted tokens accepted by the target block chain node is greater than 0, judging whether the target self-binding proportion is less than the average self-binding proportion;
if the target self-binding proportion is smaller than the average self-binding proportion, obtaining the voter voting weight corresponding to the target block chain link point according to the target self-binding Token number, the target entrustment Token number and a target entrusting lever coefficient corresponding to the target block chain link point, wherein the target entrusting lever coefficient is a scaling coefficient of Token held by the target block chain link point;
and if the target self-binding proportion is greater than or equal to the average self-binding proportion, acquiring the voter voting weight corresponding to the target block link point according to the target self-binding Token number and the target entrusted Token number.
2. The method of claim 1, wherein the formula for obtaining the target self-binding specific gravity corresponding to the target block link point is as follows:
wherein, wiThe target self-binding proportion, T, corresponding to the target block chain node iisCorresponding to the target block chain node iThe target self-binding Token number, TiwAnd entrusting the number of tokens for the target corresponding to the target block chain node i.
3. The method of claim 1, wherein the formula for obtaining the average self-binding weight corresponding to the blockchain network is:
wherein the content of the first and second substances,
for the average self-binding specific gravity, T, corresponding to the blockchain networkS0Is the sum of the self-binding Token numbers, T, in the blockchain networkW0Is the sum of the delegated Token numbers in the blockchain network.
4. The method of claim 3, wherein the verifier voting weight for the target block link point correspondence is calculated by:
wherein, PiVoting a weight, T, for the verifierisIs the target self-binding Token number, T, corresponding to the target block chain node iiwEntrusted Token number G corresponding to the target block chain node iiEntrusted leverage factor, w, for the targetiThe target self-binding proportion corresponding to the target block chain node i,
the average self-binding weight corresponding to the blockchain network.
5. The method of claim 3 or 4, wherein the target entrusting leverage coefficient is calculated by the formula:
wherein G isiEntrusted leverage factor, w, for the targetiThe target self-binding proportion corresponding to the target block chain node i,
the average self-binding weight corresponding to the blockchain network.
6. The method of claim 1, wherein after the step of obtaining the verifier voting weight corresponding to the target block link point according to the target self-binding specific gravity, the average self-binding specific gravity, and the Token number information, the method further comprises:
and acquiring the distribution quantity of each block of income according to the current number of verifiers in the block chain network.
7. The method of claim 6, wherein said step of obtaining an allocated amount of revenue per block based on a current number of verifiers in said blockchain network comprises:
if the number of current verifiers in the block chain network reaches a target number threshold, taking a preset income distribution number as the distribution number of each income;
and if the number of the current verifiers in the block chain network does not reach the target number threshold, obtaining the distribution number of each block of income according to the number of the current verifiers, the target number threshold and the preset income distribution number.
8. The method of claim 7, wherein the allocation amount per block of revenue is calculated by the formula:
wherein Q is the allocated amount of each revenue, Q0For the predetermined profit allocation amount, RiTo the number of current verifiers, R0The target number of people is the threshold value.
9. A data processing apparatus, characterized in that the apparatus comprises:
the proportion calculation module is used for acquiring target self-binding proportion according to Token number information corresponding to a target block chain link point in a block chain network, wherein the Token number information comprises target self-binding Token number of the target block chain link point and target entrusted Token number for accepting entrustment, and the target self-binding proportion represents the contrast level of the target self-binding Token number and the target entrusted Token number in all the Token held by the target block chain link point;
the proportion calculation module is further configured to obtain an average self-binding proportion according to total Token number information corresponding to the blockchain network, where the total Token number information includes a sum of self-binding Token numbers of validators self-binding all verifiers in the blockchain network, and a sum of delegation Token numbers of receiving delegations of all verifiers in the blockchain network, and the average self-binding proportion characterizes a comparison level of the sum of self-binding Token numbers in the blockchain network and the sum of delegation Token numbers;
and the voting weight calculation module is used for obtaining the verifier voting weight corresponding to the target block link point according to the target self-binding proportion, the average self-binding proportion and the Token quantity information.
10. A block link point, comprising:
a memory for storing one or more programs;
a processor;
the one or more programs, when executed by the processor, implement the method of any of claims 1-8.
11. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-8.
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