CN111064776B - Block generation method in block chain, accounting node and storage medium - Google Patents
Block generation method in block chain, accounting node and storage medium Download PDFInfo
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- CN111064776B CN111064776B CN201911237438.0A CN201911237438A CN111064776B CN 111064776 B CN111064776 B CN 111064776B CN 201911237438 A CN201911237438 A CN 201911237438A CN 111064776 B CN111064776 B CN 111064776B
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
- H04L67/104—Peer-to-peer [P2P] networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L9/00—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols
- H04L9/50—Cryptographic mechanisms or cryptographic arrangements for secret or secure communications; Network security protocols using hash chains, e.g. blockchains or hash trees
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Abstract
The embodiment of the invention provides a block generation method in a block chain, an accounting node and a storage medium. According to the embodiment of the invention, the corresponding relation between the block generation time and the block generation difficulty value is determined according to the generation time of each history block in a plurality of history blocks and the generation difficulty value of each history block, and further, the generation difficulty value of the next block can be determined according to the target generation time of the next block and the corresponding relation, namely, the block generation difficulty value can be adjusted through the generation time of the history blocks, when the block is generated slowly, the block generation difficulty value can be reduced, and when the block is generated quickly, the block generation difficulty value can be improved, so that the block can be generated stably.
Description
Technical Field
The embodiment of the invention relates to the technical field of communication, in particular to a block generation method in a block chain, an accounting node and a storage medium.
Background
In the prior art, a block chain network may have a plurality of accounting nodes, and the plurality of accounting nodes may rob accounting rights of new blocks in the block chain. Typically, which accounting node finds the smallest Deadline time from the pre-stored content, the accounting node obtains the accounting right for the new block. However, the Deadline is a random value, and thus there is no guarantee that a new block is generated at a fixed time.
Disclosure of Invention
The embodiment of the invention provides a block generation method in a block chain, an accounting node and a storage medium, so as to ensure that a block can be stably generated.
In a first aspect, an embodiment of the present invention provides a method for generating a block in a block chain, including:
determining the target generation time of the next block according to the target generation time of the block and the generation times of the plurality of historical blocks;
determining the corresponding relation between the block generation time and the block generation difficulty value according to the generation time of each historical block in the historical blocks and the generation difficulty value of each historical block;
determining the generation difficulty value of the next block according to the target generation time of the next block and the corresponding relation;
and generating the next block according to the target generation time of the next block and the generation difficulty value of the next block.
In a second aspect, an embodiment of the present invention provides an accounting node, including:
a memory;
a processor;
a communication interface; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to:
determining the target generation time of the next block according to the target generation time of the block and the generation times of a plurality of historical blocks;
determining the corresponding relation between the block generation time and the block generation difficulty value according to the generation time of each historical block in the plurality of historical blocks and the generation difficulty value of each historical block;
determining the generation difficulty value of the next block according to the target generation time of the next block and the corresponding relation;
and generating the next block according to the target generation time of the next block and the generation difficulty value of the next block.
In a third aspect, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the method in the first aspect.
According to the block generation method, the accounting node and the storage medium in the block chain provided by the embodiment of the invention, the corresponding relation between the block generation time and the block generation difficulty value is determined according to the generation time of each historical block and the generation difficulty value of each historical block in a plurality of historical blocks, and further, the block generation difficulty value of the next block can be determined according to the target generation time of the next block and the corresponding relation, namely, the block generation difficulty value can be adjusted through the historical block generation time, when the block is generated slowly, the block generation difficulty value can be reduced, and when the block is generated quickly, the block generation difficulty value can be improved, so that the block can be generated stably. A
Drawings
Fig. 1 is a schematic diagram of a communication system according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for generating a block in a block chain according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a fitted curve provided by an embodiment of the present invention;
fig. 4 is a schematic structural diagram of an accounting node according to an embodiment of the present invention.
With the foregoing drawings in mind, certain embodiments of the disclosure have been shown and described in more detail below. These drawings and written description are not intended to limit the scope of the disclosed concepts in any way, but rather to illustrate the concepts of the disclosure to those skilled in the art by reference to specific embodiments.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
The method for generating a block in a block chain according to the embodiment of the present invention is applicable to the communication system shown in fig. 1. As shown in fig. 1, the communication system includes: a plurality of accounting nodes, wherein the plurality of accounting nodes are participating nodes in a blockchain network. It is understood that the description is only illustrative and does not limit the number and types of nodes in the blockchain network. The accounting node can be one or a plurality of cloud servers, the cloud servers are a server cluster, a plurality of servers are arranged, the server cluster is similar to a universal computer framework, and the cloud servers comprise processors, hard disks, memories, system buses and the like. The electronic voting initiator node or the voting node may specifically be a user terminal, e.g. a smartphone, a tablet, a personal computer, etc. In addition, in the embodiment of the present application, the blockchain network is a decentralized peer-to-peer (P2P) communication network.
The method for generating a block in a block chain according to an embodiment of the present invention is directed to solve the above technical problems in the prior art.
The following describes the technical solutions of the present invention and how to solve the above technical problems with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present invention will be described below with reference to the accompanying drawings.
Fig. 2 is a flowchart of a method for generating a block in a blockchain according to an embodiment of the present invention. The embodiment of the present invention provides a method for generating a block in a block chain, which includes the following steps:
Optionally, the plurality of history blocks are a plurality of history blocks before the current time. In the embodiment of the present application, it is assumed that the target generation time of a block is T. Specifically, T may be a desired generation time of a new tile. The accounting node in the block chain network may query the generation times of the last N history blocks from the current time, for example, the generation times of the N history blocks are T1, T2, …, tn in sequence.
The target generation time of the next block can be calculated according to the following formula (1), and the target generation time of the next block is assumed to be denoted as Tn1.
T＝(T1+T2+…+Tn+Tn1)/(n+1) (1)
After Tn1 is calculated according to the formula (1), the generation difficulty value Nn1 of the next block can be inversely calculated.
For example, the generation difficulty values of the N history blocks are N1, N2, …, and Nn in this order. The correspondence between the block generation time and the block generation difficulty value can be determined from the generation times of the N history blocks and the generation difficulty values of the N history blocks, i.e., (N1, T1), (N2, T2), (N3, T3), (N4, T4), (N5, T5), …, and (Nn, tn). The block here may be a general name of the N history blocks and the next block. The generation time of the block can be recorded as T, and the generation difficulty value of the block can be recorded as N.
Optionally, the determining a correspondence between the block generation time and the block generation difficulty value includes: and determining the corresponding relation between the generation time of the block and the generation difficulty value of the block by adopting a linear regression model.
For example, a linear regression model is used to determine the correspondence between T and N according to (N1, T1), (N2, T2), (N3, T3), (N4, T4), (N5, T5), …, (Nn, tn), where T is a dependent variable and N is an independent variable. Specifically, a linear regression model may be used to model the correspondence between T and N, and regression analysis may be performed.
Optionally, the linear regression model is fitted by at least one of least square method, minimum absolute error regression, and minimum least square loss function.
For example, the linear regression model may be fit using least squares, or may be fit using other methods, for example, fitting may also be performed using minimization of "fit defects" in some other criteria (e.g., least absolute error regression). Alternatively, the fitting may also be performed by a multiplication that minimizes a least squares loss function in the regression.
And 203, determining the generation difficulty value of the next block according to the target generation time of the next block and the corresponding relation.
In particular, a curve between T and N may be fitted according to a linear regression model as described above, for example, the curve may be represented as N = f (T), that is, N is a function of T.
Further, according to the fitted curve and the target generation time Tn1 of the next block, the generation difficulty value Nn1 of the next block can be determined in the fitted curve.
Optionally, the determining the generation difficulty value of the next block according to the target generation time of the next block and the corresponding relationship includes: and substituting the target generation time of the next block into the functional expression of the corresponding relation to obtain the generation difficulty value of the next block.
For example, as shown in fig. 3, 31 denotes a point corresponding to the generation time and the generation difficulty value of any one history block, 32 denotes a fitting curve generated by fitting the generation time and the generation difficulty value of a plurality of history blocks, and a function corresponding to the fitting curve may be expressed as N = f (T). The target generation time Tn1 of the next block is substituted into N = f (T), and the generation difficulty value Nn1 of the next block is obtained.
And 204, generating the next block according to the target generation time of the next block and the generation difficulty value of the next block.
For example, the accounting node may generate the next chunk from the target generation time Tn1 of the next chunk and the generation difficulty value Nn1 of the next chunk.
In this embodiment of the present application, a Target hash value generated based on the content stored in the hard disk may be denoted as Target, and a value of the first 8 bytes obtained by dividing Target by base Target is Deadline. The base target may be regarded as a difficulty value, and the larger the difficulty value is, the smaller the quotient is, the smaller the Deadline is, and the shorter the block generation time is.
Alternatively, the remainder of dividing Target by base Target may be set as Deadline, and as base Target is larger, the larger the possibility that the remainder of dividing Target by base Target is larger, the longer the block generation time is.
According to the embodiment of the invention, the corresponding relation between the block generation time and the block generation difficulty value is determined according to the generation time of each history block in a plurality of history blocks and the generation difficulty value of each history block, and further, the generation difficulty value of the next block can be determined according to the target generation time of the next block and the corresponding relation, namely, the block generation difficulty value can be adjusted through the generation time of the history blocks, when the block is generated slowly, the block generation difficulty value can be reduced, and when the block is generated quickly, the block generation difficulty value can be improved, so that the block can be generated stably.
Fig. 4 is a schematic structural diagram of an accounting node according to an embodiment of the present invention. The accounting node provided in the embodiment of the present invention may execute the processing flow provided in the embodiment of the block generation method in the block chain, as shown in fig. 4, the accounting node 40 includes: memory 41, processor 42, computer programs and communication interface 43; wherein the computer program is stored in the memory 41 and is configured to be executed by the processor 42 for: determining the target generation time of the next block according to the target generation time of the block and the generation times of the plurality of historical blocks; determining the corresponding relation between the block generation time and the block generation difficulty value according to the generation time of each historical block in the plurality of historical blocks and the generation difficulty value of each historical block; determining the generation difficulty value of the next block according to the target generation time of the next block and the corresponding relation; and generating the next block according to the target generation time of the next block and the generation difficulty value of the next block.
Optionally, the history blocks are history blocks before the current time.
Optionally, when the processor determines the correspondence between the block generation time and the block generation difficulty value, the processor is specifically configured to: and determining the corresponding relation between the generation time of the block and the generation difficulty value of the block by adopting a linear regression model.
Optionally, the linear regression model is fitted by at least one of least square method, minimum absolute error regression, and minimum least square loss function.
Optionally, when determining the generation difficulty value of the next block according to the target generation time of the next block and the corresponding relationship, the processor is specifically configured to: and substituting the target generation time of the next block into the functional expression of the corresponding relation to obtain the generation difficulty value of the next block.
The accounting node of the embodiment shown in fig. 4 may be configured to implement the technical solution of the above method embodiment, and the implementation principle and the technical effect are similar, and are not described herein again.
In addition, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor to implement the method for generating a block in a blockchain described in the foregoing embodiment.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
It is obvious to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions. For the specific working process of the device described above, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (11)
1. A method for generating a block in a block chain, comprising:
determining the target generation time of the next block according to the target generation time of the block and the generation times of the plurality of historical blocks;
determining the corresponding relation between the block generation time and the block generation difficulty value according to the generation time of each historical block in the plurality of historical blocks and the generation difficulty value of each historical block;
determining the generation difficulty value of the next block according to the target generation time of the next block and the corresponding relation;
generating the next block according to the target generation time of the next block and the generation difficulty value of the next block;
determining the target generation time of the next block according to the target generation time of the block and the generation times of the plurality of historical blocks, wherein the step of determining the target generation time of the next block comprises the following steps:
calculating the target generation time of the next block according to the following formula (1), and assuming that the target generation time of the next block is denoted as Tn1;
T＝(T1+T2+…+Tn+Tn1)/(n+1) (1)
t is the desired generation time of the new block, and the generation times of the N history blocks are T1, T2, …, tn in this order.
2. The method of claim 1, wherein the plurality of history blocks are a plurality of history blocks prior to a current time.
3. The method according to claim 1 or 2, wherein the determining a correspondence between the generation time of the block and the generation difficulty value of the block comprises:
and determining the corresponding relation between the block generation time and the block generation difficulty value by adopting a linear regression model.
4. The method of claim 3, wherein the linear regression model is fitted using at least one of least squares, least absolute error regression, and least squares loss function.
5. The method according to claim 4, wherein determining the generation difficulty value of the next block according to the target generation time of the next block and the corresponding relationship comprises:
and substituting the target generation time of the next block into the functional formula of the corresponding relation to obtain the generation difficulty value of the next block.
6. An accounting node, comprising:
a memory;
a processor;
a communication interface; and
a computer program;
wherein the computer program is stored in the memory and configured to be executed by the processor to:
determining the target generation time of the next block according to the target generation time of the block and the generation times of the plurality of historical blocks;
determining the corresponding relation between the block generation time and the block generation difficulty value according to the generation time of each historical block in the plurality of historical blocks and the generation difficulty value of each historical block;
determining the generation difficulty value of the next block according to the target generation time of the next block and the corresponding relation;
generating the next block according to the target generation time of the next block and the generation difficulty value of the next block;
the method for determining the target generation time of the next block according to the target generation time of the block and the generation times of a plurality of historical blocks comprises the following steps:
calculating the target generation time of the next block according to the following formula (1), and assuming that the target generation time of the next block is denoted as Tn1;
T＝(T1+T2+…+Tn+Tn1)/(n+1) (1)
t is the desired generation time of the new block, and the generation times of the N history blocks are T1, T2, …, tn in this order.
7. An accounting node according to claim 6, wherein the plurality of history blocks are a plurality of history blocks prior to the current time.
8. An accounting node according to claim 6 or 7, wherein the processor, when determining the correspondence between the generation time of the block and the generation difficulty value of the block, is specifically configured to:
and determining the corresponding relation between the generation time of the block and the generation difficulty value of the block by adopting a linear regression model.
9. A billing node according to claim 8, characterized in that the linear regression model is fitted using at least one of least squares, minimum absolute error regression, minimum least squares loss function.
10. The accounting node of claim 9, wherein the processor, when determining the generation difficulty value of the next block according to the target generation time of the next block and the correspondence, is specifically configured to:
and substituting the target generation time of the next block into the functional expression of the corresponding relation to obtain the generation difficulty value of the next block.
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 1-5.
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| CN114916065A (en) * | 2021-02-08 | 2022-08-16 | 索尼公司 | Electronic device, wireless communication method, and computer-readable storage medium |
| CN114285860B (en) * | 2021-10-30 | 2023-07-07 | 中国银联股份有限公司 | Method, device, equipment and storage medium for adjusting block generation difficulty |
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| CN107733651B (en) * | 2017-09-11 | 2020-06-19 | 联动优势科技有限公司 | Block chain generation method, node and system |
| US10764325B2 (en) * | 2018-03-30 | 2020-09-01 | Konica Minolta Laboratory U.S.A., Inc. | Method for adjusting mining difficulty of a cryptocurrency blockchain system by monitoring malicious forks and implementing a miners blockchain |
| CN110489485B (en) * | 2018-04-28 | 2023-05-30 | 腾讯科技（深圳）有限公司 | Federated blockchain network, method and storage medium for storing product data therein |
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| CN109408595B (en) * | 2018-10-26 | 2020-08-11 | 全链通有限公司 | Block chain accounting method, device and computer readable storage medium |
| CN110489231B (en) * | 2019-08-09 | 2023-08-22 | 全链通有限公司 | Transaction information recording method, apparatus and computer readable storage medium |
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