CN117692463B - Block generation method, device, equipment and medium based on block chain network - Google Patents
Block generation method, device, equipment and medium based on block chain network Download PDFInfo
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Abstract
The embodiment of the disclosure discloses a block generation method, a device, equipment and a medium based on a block chain network, wherein the method comprises the following steps: obtaining block generation information of a current block, wherein the block generation information comprises a weight threshold value and a block outlet duration, and the current block is a block with the block outlet moment closest to the current moment on a block chain corresponding to a block chain network; when the weight threshold corresponding to the current block meets the preset threshold adjustment condition according to the block outlet time length corresponding to the current block and the preset standard block outlet time length, acquiring a weight adjustment coefficient; determining a target weight threshold based on the weight threshold and the weight adjustment coefficient corresponding to the current block; acquiring weight information of transaction data; generating a new block based on the weight information of the transaction data and the target weight threshold, wherein the sum of the weight information of the transaction data in the new block is smaller than or equal to the target weight threshold; the newly added block is synchronized into the blockchain network such that the newly added block is added to the blockchain.
Description
Technical Field
The disclosure relates to the technical field of blockchain and the technical field of block generation, in particular to a block generation method, a device, equipment and a medium based on a blockchain network.
Background
With the continuous use of blockchain technology, the application field of blockchain technology is becoming wider and wider. In blockwork techniques, blockwork generation is typically the packaging of a preset amount of transaction data into new blocks, after which the new blocks are added to the blockchain to enable the storage of transactions into the blockchain. However, in practical applications, the blockchain usually has a fixed block duration, however, due to the different sizes of the transaction data, when generating a block including larger transaction data, the duration of generating the block exceeds the fixed block duration, which results in failure of generating the block.
Disclosure of Invention
In order to solve the above problems, embodiments of the present disclosure provide a block generation method, apparatus, device, and medium based on a blockchain network.
In one aspect of the disclosed embodiments, a block generation method based on a block chain network is provided, including: obtaining block generation information of a current block, wherein the block generation information comprises a weight threshold value and a block outlet time length corresponding to the current block, and the current block is a block with the block outlet time closest to the current time on a block chain corresponding to a block chain network; determining whether a weight threshold corresponding to the current block meets a preset threshold adjustment condition according to the block outlet time length corresponding to the current block and a preset standard block outlet time length, and acquiring a weight adjustment coefficient in response to the weight threshold corresponding to the current block meeting the preset threshold adjustment condition; determining a target weight threshold based on the weight threshold corresponding to the current block and the weight adjustment coefficient; acquiring weight information of transaction data; generating a new block based on the weight information of the transaction data and the target weight threshold, wherein the sum of the weight information of the transaction data in the new block is smaller than or equal to the target weight threshold; the new added block is synchronized into the blockchain network such that the new added block is added to the blockchain.
In another aspect of the embodiments of the present disclosure, there is provided a block generating apparatus based on a block chain network, including: the first acquisition module is used for acquiring block generation information of a current block, wherein the block generation information comprises a weight threshold value and a block outlet duration corresponding to the current block, and the current block is a block with the block outlet moment closest to the current moment on a block chain corresponding to a block chain network; the second obtaining module is used for determining whether the weight threshold value corresponding to the current block meets a preset threshold value adjusting condition according to the block outlet duration corresponding to the current block and a preset standard block outlet duration, and obtaining a weight adjusting coefficient according to the weight threshold value corresponding to the current block meeting the preset threshold value adjusting condition; the first determining module is used for determining a target weight threshold value based on the weight threshold value corresponding to the current block and the weight adjustment coefficient; the third acquisition module is used for acquiring weight information of the transaction data; the generation module is used for generating a new added block based on the weight information of the transaction data and the target weight threshold value, and the sum of the weight information of the transaction data in the new added block is smaller than or equal to the target weight threshold value; and the synchronization module is used for synchronizing the new added block into the blockchain network so as to enable the new added block to be added to the blockchain.
In yet another aspect of the disclosed embodiments, there is provided an electronic device including: a memory for storing a computer program; and the processor is used for executing the computer program stored in the memory and realizing a block generation method based on a block chain network when the computer program is executed.
In yet another aspect of the disclosed embodiments, a computer-readable storage medium is provided having a computer program stored thereon that, when executed by a processor, implements a blockchain network-based blockgeneration method.
In the embodiment of the disclosure, according to the block-out duration corresponding to the current block and the preset standard block-out duration, determining whether a weight threshold corresponding to the current block meets a preset threshold adjustment condition, acquiring a weight adjustment coefficient based on the weight adjustment coefficient when the preset threshold adjustment condition is met, and then determining a target weight threshold based on the weight threshold corresponding to the current block and the weight adjustment coefficient; generating a new added block based on the weight information of the transaction data and the target weight threshold, wherein the sum of the weight information of the transaction data in the new added block is smaller than or equal to the target weight threshold; the newly added block is then synchronized into the blockchain network such that the newly added block is added to the blockchain. Therefore, in the embodiment of the disclosure, when a new block is generated, the weight threshold is adjusted according to the corresponding relation between the block outlet time length corresponding to the current block and the preset standard block outlet time length, so that the target weight threshold for generating the new block is obtained, the block outlet time length of the new block can be accurately controlled to be near the preset standard block outlet time length according to the weight information of the transaction data, the stability of the block outlet time lengths among the new blocks is further ensured, the block outlet efficiency and the block outlet success rate of the block chain network are improved, and the problem of block outlet failure caused by overlong block outlet time due to overlarge transaction data is solved.
The technical scheme of the present disclosure is described in further detail below through the accompanying drawings and examples.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and together with the description, serve to explain the principles of the disclosure.
The disclosure may be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings in which:
FIG. 1 is a flowchart of a block generation method based on a blockchain network provided by an exemplary embodiment of the present disclosure;
FIG. 2 is a flow chart of a blockchain network-based blockgenerating method provided by another exemplary embodiment of the present disclosure;
FIG. 3 is a flow chart of step S130 provided by an exemplary embodiment of the present disclosure;
FIG. 4 is a flow chart of step S140 provided by an exemplary embodiment of the present disclosure;
FIG. 5 is a schematic diagram of an application example provided by an exemplary embodiment of the present disclosure;
FIG. 6 is a block diagram of a block generation apparatus based on a blockchain network provided by an exemplary embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an application embodiment of the electronic device of the present disclosure.
Detailed Description
Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present disclosure unless it is specifically stated otherwise.
It will be appreciated by those of skill in the art that the terms "first," "second," etc. in embodiments of the present disclosure are used merely to distinguish between different steps, devices or modules, etc., and do not represent any particular technical meaning nor necessarily logical order between them.
It should also be understood that in embodiments of the present disclosure, "plurality" may refer to two or more, and "at least one" may refer to one, two or more.
It should also be appreciated that any component, data, or structure referred to in the presently disclosed embodiments may be generally understood as one or more without explicit limitation or the contrary in the context.
In addition, the term "and/or" in this disclosure is merely an association relationship describing an association object, and indicates that three relationships may exist, for example, a and/or B may indicate: a exists alone, A and B exist together, and B exists alone. In addition, the character "/" in the present disclosure generally indicates that the front and rear association objects are an or relationship.
It should also be understood that the description of the various embodiments of the present disclosure emphasizes the differences between the various embodiments, and that the same or similar features may be referred to each other, and for brevity, will not be described in detail.
Meanwhile, it should be understood that the sizes of the respective parts shown in the drawings are not drawn in actual scale for convenience of description.
The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the disclosure, its application, or uses.
Techniques, methods, and apparatus known to one of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.
It should be noted that: like reference numerals and letters denote like items in the following figures, and thus once an item is defined in one figure, no further discussion thereof is necessary in subsequent figures.
Embodiments of the present disclosure may be applicable to electronic devices such as terminal devices, computer systems, servers, etc., which may operate with numerous other general purpose or special purpose computing system environments or configurations. Examples of well known terminal devices, computing systems, environments, and/or configurations that may be suitable for use with the terminal device, computer system, server, or other electronic device include, but are not limited to: personal computer systems, server computer systems, thin clients, thick clients, hand-held or laptop devices, microprocessor-based systems, set-top boxes, programmable consumer electronics, network personal computers, small computer systems, mainframe computer systems, and distributed cloud computing technology environments that include any of the foregoing, and the like.
Electronic devices such as terminal devices, computer systems, servers, etc. may be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules may include routines, programs, objects, components, logic, data structures, etc., that perform particular tasks or implement particular abstract data types. The computer system/server may be implemented in a distributed cloud computing environment in which tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules may be located in both local and remote computing system storage media including memory storage devices.
In the disclosed embodiments:
The Block Chain (Block Chain) is a distributed account book technology based on a point-to-point network, each Node (Node) in the Block Chain network has the same complete data, and the nodes realize the data consistency on the Chain of each Node through a consensus mechanism. Nodes in a blockchain network, commonly referred to as computing devices in the blockchain network, that is, any computing device connected to the blockchain network (including cell phones, servers, etc.) are referred to as nodes, wherein the nodes may be used to store, run, validate, etc. blockdata in the blockchain network.
The block-out refers to that any node in the blockchain network carries out consensus on a certain amount of transaction data in any node and other nodes, and then each node packs the consensus transaction data to generate block data and stores the block data, so that the block-out of the block data is completed.
Fig. 1 is a flowchart of a block generation method based on a blockchain network according to an exemplary embodiment of the present disclosure. The embodiment can be applied to an electronic device, as shown in fig. 1, and includes the following steps:
Step S110, obtaining block generation information of the current block.
The current block is the block with the block out moment closest to the current moment on the block chain corresponding to the block chain network, namely the current block is the latest block on the block chain. The block generation information comprises a weight threshold value corresponding to the current block and a block-out duration, wherein the block-out duration corresponding to the current block is the duration consumed for generating the current block.
The current block comprises a plurality of transaction data, each transaction data corresponds to the weight of the transaction data, and the weight of each transaction data is in direct proportion to the time spent for packing the transaction data, namely, the longer the time spent for packing the transaction data is in the process of generating the block, the larger the weight corresponding to the transaction data is. The sum of the weights corresponding to the transaction data in the current block is smaller than or equal to the weight threshold corresponding to the current block.
In one particular implementation, when a blockchain network needs to generate a new block, any node in the blockchain network may obtain the block generation information for the current block from the transaction log of the blockchain network.
Step S120, determining whether the weight threshold corresponding to the current block meets the preset threshold adjustment condition according to the block outlet time length corresponding to the current block and the preset standard block outlet time length, and acquiring the weight adjustment coefficient in response to the weight threshold corresponding to the current block meeting the preset threshold adjustment condition.
The weight adjustment coefficient is used for adjusting the weight threshold.
In an alternative embodiment, a preset standard block out duration, a preset difference threshold, and a correspondence between preset comparison data and weight adjustment coefficients are preset.
And determining the absolute value of the difference between the preset standard block-out time length and the block-out time length of the current block as comparison data, when the comparison data is larger than or equal to a preset difference threshold value, determining that the weight threshold value corresponding to the current block meets a preset threshold value adjustment condition, and when the comparison data is smaller than the preset difference threshold value, determining that the weight threshold value corresponding to the current block does not meet the preset threshold value adjustment condition.
When the weight threshold corresponding to the current block is determined to meet the preset threshold adjustment condition, the weight adjustment coefficient corresponding to the comparison data can be determined in the corresponding relation between the preset comparison data and the weight adjustment coefficient, so that the weight adjustment coefficient is obtained.
Step S130, determining a target weight threshold based on the weight threshold and the weight adjustment coefficient corresponding to the current block.
The weight adjustment coefficient may be multiplied by a weight threshold corresponding to the current block to obtain a target weight threshold.
Step S140, obtaining weight information of the transaction data.
The weight information of the transaction data comprises weights corresponding to the transaction data. The weight in the weight information of the transaction data is proportional to the packing time length of the transaction data.
In a specific implementation manner, a plurality of processed and unbroken transaction data are stored in a transaction pool of any node, and weight information corresponding to the transaction data can be determined. For example, a correspondence between the preset transaction data size and the predicted packing time period and a correspondence between the preset packing time period and the weight may be preset. In the corresponding relation between the preset packing time length and the weight, the packing time length is in direct proportion to the weight.
For each transaction data in the transaction pool, firstly, according to the size of the transaction data, determining the predicted packing time length corresponding to the transaction data from the corresponding relation between the preset transaction data size and the predicted packing time length, then, based on the predicted packing time length corresponding to the transaction data, determining the weight corresponding to the transaction data from the corresponding relation between the preset packing time length and the weight, and then, forming the weight information of the transaction data by the weight corresponding to the transaction data.
Step S150, generating a new block based on the weight information of the transaction data and the target weight threshold.
Wherein the sum of the weight information of the transaction data in the new added block is smaller than or equal to the target weight threshold.
In an alternative embodiment, a plurality of transaction data may be selected as the transaction data for generating the new block, the sum of the weight information of the plurality of transaction data for generating the new block is less than or equal to the target weight threshold, and then the plurality of transaction data for generating the new block is packaged to obtain the new block.
Step S160, the newly added block is synchronized to the blockchain network, so that the newly added block is added to the blockchain corresponding to the blockchain network.
In one specific implementation, any node synchronizes the newly added block to each node in the block network, then each node performs consensus processing on the newly added block, and each node adds the newly added block to the block chain after the newly added block passes the consensus so as to complete the uplink of the newly added block.
In the embodiment of the disclosure, according to the block-out duration corresponding to the current block and the preset standard block-out duration, determining whether a weight threshold corresponding to the current block meets a preset threshold adjustment condition, acquiring a weight adjustment coefficient based on the weight adjustment coefficient when the preset threshold adjustment condition is met, and then determining a target weight threshold based on the weight threshold corresponding to the current block and the weight adjustment coefficient; generating a new added block based on the weight information of the transaction data and the target weight threshold, wherein the sum of the weight information of the transaction data in the new added block is smaller than or equal to the target weight threshold; the newly added block is then synchronized into the blockchain network such that the newly added block is added to the blockchain. Therefore, in the embodiment of the disclosure, when a new block is generated, the weight threshold is adjusted according to the corresponding relation between the block outlet time length corresponding to the current block and the preset standard block outlet time length, so that the target weight threshold for generating the new block is obtained, the block outlet time length of the new block can be accurately controlled to be near the preset standard block outlet time length according to the weight information of the transaction data, the stability of the block outlet time lengths among the new blocks is further ensured, the block outlet efficiency and the block outlet success rate of the block chain network are improved, and the problem of block outlet failure caused by overlong block outlet time due to overlarge transaction data is solved.
In some optional implementations, the tile generation information for the current tile in the disclosed embodiments further includes the amount of transaction data in the current tile. Fig. 2 is a flowchart illustrating a block generation method based on a blockchain network according to another exemplary embodiment of the present disclosure. As shown in fig. 2, step S110 in the embodiment of the present disclosure further includes the following steps:
Step S210, determining a corrected block-out duration based on the block-out duration corresponding to the current block, the weight threshold and the number of transaction data.
In a specific implementation manner, based on the block-out duration corresponding to the current block, the weight threshold and the amount of transaction data in the current block, calculating to obtain a corrected block-out duration by using the formula (1);
tr=t×（L/N） （1）
Wherein tr is the corrected block-out duration, t is the block-out duration corresponding to the current block, L is the weight threshold corresponding to the current block, and N is the amount of transaction data in the current block.
Step S220, determining a block duration range based on the preset first parameter, the preset second parameter and the preset standard block duration.
In a specific implementation manner, a preset first parameter and a preset second parameter may be preset, where the preset first parameter is greater than the preset second parameter. The first boundary value may be determined based on m1=a1×t, the second boundary value may be determined based on m2=a2×t, and since the preset first parameter is greater than the preset second parameter, the first boundary value is correspondingly greater than the second boundary value, and the block duration range is constructed by the first boundary value and the second boundary value, that is, the block duration range is M1-M2, where M1 is the first boundary value, M2 is the second boundary value, T is the preset standard block duration, a1 is the preset first parameter, and a2 is the preset second parameter.
For example, assuming that the preset first parameter is 1.2, the preset second parameter is 0.8, and the corresponding first boundary value is 1.2T and the second boundary value is 0.8T, the block-out duration range is 1.2T to 0.8T.
Step S230, in response to the corrected block-out duration not being within the block-out duration range, it is determined that the weight threshold corresponding to the current block satisfies the preset threshold adjustment condition.
In an alternative embodiment, when tr > M1 or tr < M2, it is determined that the weight threshold corresponding to the current block satisfies the preset threshold adjustment condition.
For example, taking the example in step S220 as an example, when tr > 1.2T or tr < 0.8T, it is determined that the weight threshold corresponding to the current block satisfies the preset threshold adjustment condition.
In some optional implementations, the out-of-block duration range in the embodiments of the present disclosure includes a first duration threshold and a second duration threshold, and the first duration threshold is greater than the second duration threshold.
In a specific implementation, a first boundary value in the block duration range may be selected as the first duration threshold P1, and a second boundary value in the block duration range may be selected as the second duration threshold P2, i.e., p1=m1, p2=m2.
Step S120 in the embodiment of the present disclosure may include:
in response to the corrected block out duration being greater than the first time duration threshold, a weight adjustment coefficient is determined based on the first time duration threshold and the corrected block out duration.
Where tr > P1, a weight adjustment coefficient may be determined based on coe =p1/tr, where coe is the weight adjustment coefficient.
Illustratively, the example in step S220 is also taken as an example, where M1 is taken as P1, and coe =1.2T/tr when tr > 1.2T.
And determining a weight adjustment coefficient based on the second time length threshold and the corrected block time length in response to the corrected block time length being less than the second time length threshold.
Wherein, when tr is smaller than P2, the weight adjustment coefficient may be determined based on coe =p2/tr.
Illustratively, the example in step S220 is also taken as an example, where M2 is taken as P2, and coe =0.8T/tr when tr < 0.8T.
Fig. 3 is a flowchart illustrating step S130 according to an exemplary embodiment of the present disclosure. In some alternative embodiments, as shown in fig. 3, step S130 includes the steps of:
step S131, the weight threshold corresponding to the current block is adjusted by the weight adjustment coefficient to obtain the initial adjustment weight threshold.
Wherein, the initial adjustment weight threshold can be determined by using the formula (2) based on the weight adjustment coefficient and the weight threshold corresponding to the current block;
L1=L×coe （2）
Wherein L1 is an initial adjustment weight threshold.
Step S132, determining a weight threshold adjustment range based on a preset first adjustment threshold, a preset second adjustment threshold and a weight threshold corresponding to the current block.
In an alternative embodiment, the setting of the preset first adjustment threshold and the preset second adjustment threshold needs to be satisfied: A1×L > L/A2. Wherein A1 is a preset first adjustment threshold, and A2 is a preset second adjustment threshold. A1 xL can be used as a third boundary value, L/A2 is used as a fourth boundary value, and a weight threshold adjustment range is constructed by the third boundary value and the fourth boundary value, namely the weight threshold adjustment range is (A1 xL) to (L/A2).
Illustratively, assume that a first adjustment threshold is preset to 1.5 and a second adjustment threshold is preset to 100. Correspondingly, the weight threshold adjustment range can be 1.5L-L/100.
And step S133, determining the initial adjustment weight threshold as a target weight threshold in response to the initial adjustment weight threshold being within the weight threshold adjustment range.
Wherein, when L/A2 is less than or equal to L1 and less than or equal to (A1×L), determining L1 as a target weight threshold.
Illustratively, further to the example in step S132, when L/100 is equal to or less than L1 is equal to or less than 1.5L, L1 is determined as the target weight threshold.
In some alternative embodiments, as shown in fig. 3, step S130 may further include the steps of:
step S134, in response to the initial adjustment weight threshold not being in the weight threshold adjustment range, correcting the initial adjustment weight threshold based on the preset first adjustment threshold or the preset second adjustment threshold to obtain the target weight threshold.
In one specific implementation, when L1 > (a1×l), L1 may be corrected based on A1 and L, for example, L1 may be corrected to a1×l, even if l1=a1×l, and the corrected L1 is determined as the target weight threshold. When L1 < L/A2, L1 may be corrected to L/A2, even if l1=l/A2, and the corrected L1 is determined as the target weight threshold.
Illustratively, further describing the example in step S132 as an example, when L1 > 1.5L, L1 is corrected to 1.5L, even if l1=1.5l, the corrected L1 is determined as the target weight threshold; when L1 < L/100, L1 is corrected to L/100, even if l1=l/100, and the corrected L1 is determined as the target weight threshold.
It should be noted that, in the embodiment of the disclosure, the step S133 and the step S134 are not performed in sequence.
In some optional implementations, step S110 in the embodiments of the disclosure may further include: and determining the weight threshold corresponding to the current block as a target weight threshold in response to determining that the weight threshold corresponding to the current block does not meet the preset threshold adjustment condition according to the block-out duration corresponding to the current block and the preset standard block-out duration.
In a specific implementation manner, in response to the corrected block out duration being within the block out duration range, it is determined that the weight threshold corresponding to the current block does not satisfy the preset threshold adjustment condition. When M1 is smaller than or equal to tr and smaller than or equal to M2, determining that the weight threshold corresponding to the current block does not meet the preset threshold adjustment condition.
For example, taking the example in step S220 as an example, when 1.2T is equal to or less than tr is equal to or less than 0.8T, it is determined that the weight threshold corresponding to the current block does not satisfy the preset threshold adjustment condition.
Fig. 4 is a flowchart illustrating step S140 according to an exemplary embodiment of the present disclosure. In some alternative embodiments, as shown in fig. 4, step S140 includes the steps of:
in step S141, feature information of the transaction data is acquired.
Wherein the characteristic information of the transaction data is at least one of: transaction type, fee information, transaction data size information, contract information, transaction duration, number of operations, and type of operation. The transaction types may include, for example, but are not limited to: vehicle transactions, parking fee transactions, ticket transactions, etc.; the fee information may be Gas fee; the transaction data size information includes a size of the transaction data; the contract information includes whether the transaction data includes a contract; the transaction duration is the duration spent in completing the transaction data; the operation number represents the number of operation steps to complete the transaction data; the operation type can be set in a self-defined manner, for example, the operation type can be a simplified flow type, a multiparty subscription type and the like, and when the operation type is multiparty subscription, the corresponding transaction data is processed by common signatures of a plurality of subscription parties needing the transaction data.
In step S142, the feature information of the transaction data is input into the transaction weight model trained in advance, and the weight information of the transaction data is output through the transaction weight model.
The transaction weight model may be a tree model, for example, the transaction weight model may be XGboost model.
In an alternative embodiment, the transaction weight model may be obtained by:
And acquiring a plurality of historical transaction data of the same transaction type in a plurality of blocks from a transaction log of a blockchain network, acquiring characteristic information of the historical transaction data for each historical transaction data, and then determining the packing time length of the historical transaction data based on the block outlet time length of the block where the historical transaction data is located, for example, the block outlet time length of the block where the historical transaction data is located is 2s, the number of the historical transaction data included in the block is 10, and the packing time length of the historical transaction data is 2s/10. And normalizing the packaging time length of the historical transaction data, and taking the normalization result as the tag weight information of the historical transaction data.
Training XGboost the model based on the characteristic information and the label weight information of each piece of historical transaction data to obtain a transaction weight model.
Fig. 5 is a schematic diagram of an application example provided by an exemplary embodiment of the present disclosure. As shown in fig. 5, it is assumed that a new block is generated by any node in the blockchain network, and specifically includes:
The arbitrary node includes: the system comprises a transaction pool, a threshold dynamic adjustment module and a transaction characteristic database. The transaction pool includes a plurality of transaction data.
Multiple historical transaction data of the same transaction type in multiple blocks are obtained from a transaction log of the blockchain network and stored in a transaction characteristic database, and a transaction weight model can be obtained by training XGboost a model based on the multiple historical transaction data in the transaction characteristic database in an offline state.
Acquiring a plurality of transaction data from a transaction pool of any node, acquiring characteristic information of the transaction data for each transaction data, inputting the characteristic information of the transaction data into a transaction weight model, and outputting weight information of the transaction data through the transaction weight model;
Acquiring block generation information of a current block, acquiring a weight adjustment coefficient from a threshold dynamic adjustment module when determining that a weight threshold corresponding to the current block meets a preset threshold adjustment condition, and determining a target weight threshold based on the weight threshold corresponding to the current block and the weight adjustment coefficient; based on the weight information of the plurality of transaction data and the target weight threshold, determining a plurality of packaged transaction data, wherein the sum of the weight information corresponding to the plurality of packaged transaction data is smaller than or equal to the target weight threshold, packaging the plurality of packaged transaction data, generating a new added block, and sending the block-out duration of the new added block to the threshold dynamic adjustment module.
Fig. 6 is a block diagram of a block generating apparatus based on a blockchain network according to an exemplary embodiment of the present disclosure. As shown in fig. 6, the blockchain-based blockchain network-based blockgenerating device includes:
the first obtaining module 300 is configured to obtain block generation information of a current block, where the block generation information includes a weight threshold value and a block-out duration corresponding to the current block, and the current block is a block on a blockchain corresponding to a blockchain network, where a block-out time is closest to a current time;
A second obtaining module 310, configured to determine, according to a block-out duration corresponding to the current block and a preset standard block-out duration, whether a weight threshold corresponding to the current block meets a preset threshold adjustment condition, and obtain a weight adjustment coefficient in response to the weight threshold corresponding to the current block meeting the preset threshold adjustment condition;
A first determining module 320, configured to determine a target weight threshold based on the weight threshold corresponding to the current block and the weight adjustment coefficient;
A third obtaining module 330, configured to obtain weight information of the transaction data;
A generating module 340, configured to generate a new added block based on the weight information of the transaction data and the target weight threshold, where a sum of the weight information of the transaction data in the new added block is less than or equal to the target weight threshold;
A synchronization module 350, configured to synchronize the new added block into the blockchain network, so that the new added block is added to the blockchain.
In one embodiment of the present disclosure, the tile generation information in the embodiment of the present disclosure further includes the amount of transaction data in the current tile;
in one embodiment of the present disclosure, the block generating apparatus based on a block chain network in the embodiment of the present disclosure further includes:
The second determining module is used for determining a corrected block outlet duration based on the block outlet duration corresponding to the current block, the weight threshold and the number of transaction data;
the third determining module is used for determining a block duration range based on a preset first parameter, a preset second parameter and the preset standard block duration;
And a fourth determining module, configured to determine that a weight threshold corresponding to the current block meets the preset threshold adjustment condition in response to the corrected block-out duration not being within the block-out duration range.
In one embodiment of the present disclosure, the block out duration range in the embodiment of the present disclosure includes a first duration threshold and a second duration threshold, and the first duration threshold is greater than the second duration threshold;
In one embodiment of the present disclosure, the second obtaining module 310 in the embodiment of the present disclosure is specifically configured to:
determining the weight adjustment coefficient based on the first time length threshold and the corrected block out duration in response to the corrected block out duration being greater than the first time length threshold;
and determining the weight adjustment coefficient based on the second time length threshold and the corrected block time length in response to the corrected block time length being smaller than the second time length threshold.
In one embodiment of the present disclosure, the first determining module 320 in an embodiment of the present disclosure includes:
The adjustment sub-module is used for adjusting the weight threshold corresponding to the current block by utilizing the weight adjustment coefficient to obtain an initial adjustment weight threshold;
the first determining submodule is used for determining a weight threshold adjusting range based on a preset first adjusting threshold value, a preset second adjusting threshold value and a weight threshold value corresponding to the current block;
and the second determining submodule is used for determining that the initial adjustment weight threshold is the target weight threshold in response to the initial adjustment weight threshold being in the weight threshold adjustment range.
In one embodiment of the present disclosure, the block generating apparatus based on a block chain network in the embodiment of the present disclosure further includes:
And the third determining submodule is used for responding to the fact that the initial adjustment weight threshold value is not in the weight threshold value adjusting range, correcting the initial adjustment weight threshold value based on the preset first adjusting threshold value or the preset second adjusting threshold value, and obtaining the target weight threshold value.
In one embodiment of the present disclosure, the block generating apparatus based on a block chain network in the embodiment of the present disclosure further includes:
And a fifth determining module, configured to determine, as the target weight threshold, the weight threshold corresponding to the current block in response to determining that the weight threshold corresponding to the current block does not meet a preset threshold adjustment condition according to the block-out duration corresponding to the current block and a preset standard block-out duration.
In one embodiment of the present disclosure, the third obtaining module 330 in an embodiment of the present disclosure includes:
The acquisition sub-module is used for acquiring the characteristic information of the transaction data, wherein the characteristic information of the transaction data comprises at least one of the following components: transaction type, cost information, transaction data size information, contract information, transaction duration, operation number and operation type;
And the fourth determination submodule is used for inputting the characteristic information of the transaction data into a pre-trained transaction weight model and outputting the weight information of the transaction data through the transaction weight model.
The block generating device based on the blockchain network in the embodiment of the present disclosure corresponds to the embodiment of the block generating method based on the blockchain network in the present disclosure, and the related contents may be referred to each other and are not described herein again.
Advantageous technical effects corresponding to the exemplary embodiments of the blockchain network-based blockgenerating device of the embodiments of the present disclosure may refer to the corresponding advantageous technical effects of the corresponding exemplary method section described above, and are not described herein again.
In addition, the embodiment of the disclosure also provides an electronic device, which comprises:
A memory for storing a computer program;
And a processor, configured to execute the computer program stored in the memory, and when the computer program is executed, implement the block generation method based on the block chain network according to any one of the embodiments of the disclosure.
Fig. 7 is a schematic structural diagram of an application embodiment of the electronic device of the present disclosure. Next, an electronic device according to an embodiment of the present disclosure is described with reference to fig. 7. The electronic device may be either or both of the first device and the second device, or a stand-alone device independent thereof, which may communicate with the first device and the second device to receive the acquired input signals therefrom.
As shown in fig. 7, the electronic device includes one or more processors and memory.
The processor may be a Central Processing Unit (CPU) or other form of processing unit having data processing and/or instruction execution capabilities, and may control other components in the electronic device to perform the desired functions.
The memory may include one or more computer program products that may include various forms of computer-readable storage media, such as volatile memory and/or non-volatile memory. The volatile memory may include, for example, random Access Memory (RAM) and/or cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like. One or more computer program instructions may be stored on the computer readable storage medium that can be executed by a processor to implement the blockchain network-based blockgenerating method and/or other desired functions of the various embodiments of the present disclosure as described above.
In one example, the electronic device may further include: input devices and output devices, which are interconnected by a bus system and/or other forms of connection mechanisms (not shown).
In addition, the input device may include, for example, a keyboard, a mouse, and the like.
The output device may output various information including the determined distance information, direction information, etc., to the outside. The output devices may include, for example, a display, speakers, a printer, and a communication network and remote output devices connected thereto, etc.
Of course, only some of the components of the electronic device relevant to the present disclosure are shown in fig. 7 for simplicity, components such as buses, input/output interfaces, and the like being omitted. In addition, the electronic device may include any other suitable components depending on the particular application.
In addition to the methods and apparatus described above, embodiments of the present disclosure may also be a computer program product comprising computer program instructions which, when executed by a processor, cause the processor to perform the steps in a blockchain network-based blockgeneration method described in the above section of the specification, according to various embodiments of the present disclosure.
The computer program product may write program code for performing the operations of embodiments of the present disclosure in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, embodiments of the present disclosure may also be a computer-readable storage medium having stored thereon computer program instructions which, when executed by a processor, cause the processor to perform the steps in the blockchain network-based blockgenerating method described in the above section of the present disclosure.
The computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples (a non-exhaustive list) of the readable storage medium would include the following: an electrical connection having one or more wires, a portable disk, a hard disk, random Access Memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
Those of ordinary skill in the art will appreciate that: all or part of the steps for implementing the above method embodiments may be implemented by hardware associated with program instructions, where the foregoing program may be stored in a computer readable storage medium, and when executed, the program performs steps including the above method embodiments; and the aforementioned storage medium includes: various media that can store program code, such as ROM, RAM, magnetic or optical disks.
The basic principles of the present disclosure have been described above in connection with specific embodiments, but it should be noted that the advantages, benefits, effects, etc. mentioned in the present disclosure are merely examples and not limiting, and these advantages, benefits, effects, etc. are not to be considered as necessarily possessed by the various embodiments of the present disclosure. Furthermore, the specific details disclosed herein are for purposes of illustration and understanding only, and are not intended to be limiting, since the disclosure is not necessarily limited to practice with the specific details described.
In this specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that the same or similar parts between the embodiments are mutually referred to. For system embodiments, the description is relatively simple as it essentially corresponds to method embodiments, and reference should be made to the description of method embodiments for relevant points.
The block diagrams of the devices, apparatuses, devices, systems referred to in this disclosure are merely illustrative examples and are not intended to require or imply that the connections, arrangements, configurations must be made in the manner shown in the block diagrams. As will be appreciated by one of skill in the art, the devices, apparatuses, devices, systems may be connected, arranged, configured in any manner. Words such as "including," "comprising," "having," and the like are words of openness and mean "including but not limited to," and are used interchangeably therewith. The terms "or" and "as used herein refer to and are used interchangeably with the term" and/or "unless the context clearly indicates otherwise. The term "such as" as used herein refers to, and is used interchangeably with, the phrase "such as, but not limited to.
The methods and apparatus of the present disclosure may be implemented in a number of ways. For example, the methods and apparatus of the present disclosure may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present disclosure are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present disclosure may also be implemented as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present disclosure. Thus, the present disclosure also covers a recording medium storing a program for executing the method according to the present disclosure.
It is also noted that in the apparatus, devices and methods of the present disclosure, components or steps may be disassembled and/or assembled. Such decomposition and/or recombination should be considered equivalent to the present disclosure.
The previous description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present disclosure. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects without departing from the scope of the disclosure. Thus, the present disclosure is not intended to be limited to the aspects shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
The foregoing description has been presented for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of the disclosure to the form disclosed herein. Although a number of example aspects and embodiments have been discussed above, a person of ordinary skill in the art will recognize certain variations, modifications, alterations, additions, and subcombinations thereof.
Claims (10)
1. A block generation method based on a block chain network, comprising:
obtaining block generation information of a current block, wherein the block generation information comprises a weight threshold value and a block outlet time length corresponding to the current block, and the current block is a block with the block outlet time closest to the current time on a block chain corresponding to a block chain network;
Determining whether a weight threshold corresponding to the current block meets a preset threshold adjustment condition according to the block outlet duration corresponding to the current block and a preset standard block outlet duration, and acquiring a weight adjustment coefficient in response to the weight threshold corresponding to the current block meeting the preset threshold adjustment condition, wherein the current block comprises a plurality of transaction data, any transaction data corresponds to the weight of any transaction data, and the sum of the weights corresponding to all the transaction data in the current block is smaller than or equal to the weight threshold corresponding to the current block;
Determining a target weight threshold based on the weight threshold corresponding to the current block and the weight adjustment coefficient;
Acquiring weight information of transaction data;
generating a new block based on the weight information of the transaction data and the target weight threshold, wherein the sum of the weight information of the transaction data in the new block is smaller than or equal to the target weight threshold;
The new added block is synchronized into the blockchain network such that the new added block is added to the blockchain.
2. The method of claim 1, wherein the tile generation information further comprises an amount of transaction data in the current tile;
After the block generation information of the current block is obtained, the method further comprises:
determining a corrected block-out duration based on the block-out duration corresponding to the current block, a weight threshold and the number of transaction data;
Determining a block duration range based on a preset first parameter, a preset second parameter and the preset standard block duration;
And determining that the weight threshold corresponding to the current block meets the preset threshold adjustment condition according to the fact that the corrected block-out duration is not in the block-out duration range.
3. The method of claim 2, wherein the out-of-block duration range includes a first duration threshold and a second duration threshold, and wherein the first duration threshold is greater than the second duration threshold;
Acquiring weight adjustment coefficients, including:
determining the weight adjustment coefficient based on the first time length threshold and the corrected block out duration in response to the corrected block out duration being greater than the first time length threshold;
and determining the weight adjustment coefficient based on the second time length threshold and the corrected block time length in response to the corrected block time length being smaller than the second time length threshold.
4. The method of claim 2, wherein the determining a target weight threshold based on the weight threshold corresponding to the current block and the weight adjustment coefficient comprises:
adjusting the weight threshold corresponding to the current block by using the weight adjustment coefficient to obtain an initial adjustment weight threshold;
Determining a weight threshold adjustment range based on a preset first adjustment threshold, a preset second adjustment threshold and a weight threshold corresponding to the current block;
And determining the initial adjustment weight threshold as the target weight threshold in response to the initial adjustment weight threshold being within the weight threshold adjustment range.
5. The method of claim 4, wherein after determining the weight threshold adjustment range based on the preset first adjustment threshold, the preset second adjustment threshold, and the weight threshold corresponding to the current block, further comprises:
and responding to the initial adjustment weight threshold not being in the weight threshold adjustment range, correcting the initial adjustment weight threshold based on the preset first adjustment threshold or the preset second adjustment threshold, and obtaining the target weight threshold.
6. The method of claim 1, wherein after the obtaining the block generation information of the current block, further comprising:
And determining the weight threshold corresponding to the current block as the target weight threshold in response to determining that the weight threshold corresponding to the current block does not meet a preset threshold adjustment condition according to the block-out duration corresponding to the current block and a preset standard block-out duration.
7. The method according to any one of claims 1-6, wherein the obtaining weight information of the transaction data comprises:
Acquiring characteristic information of the transaction data, wherein the characteristic information of the transaction data comprises at least one of the following components: transaction type, cost information, transaction data size information, contract information, transaction duration, operation number and operation type;
And inputting the characteristic information of the transaction data into a pre-trained transaction weight model, and outputting the weight information of the transaction data through the transaction weight model.
8. A blockchain network-based blockgenerating device, comprising:
The first acquisition module is used for acquiring block generation information of a current block, wherein the block generation information comprises a weight threshold value and a block outlet duration corresponding to the current block, and the current block is a block with the block outlet moment closest to the current moment on a block chain corresponding to a block chain network;
The second obtaining module is used for determining whether a weight threshold corresponding to the current block meets a preset threshold adjustment condition according to the block outlet duration corresponding to the current block and a preset standard block outlet duration, and obtaining a weight adjustment coefficient in response to the weight threshold corresponding to the current block meeting the preset threshold adjustment condition, wherein the current block comprises a plurality of transaction data, any transaction data corresponds to the weight of any transaction data, and the sum of the weights corresponding to all the transaction data in the current block is smaller than or equal to the weight threshold corresponding to the current block;
The first determining module is used for determining a target weight threshold value based on the weight threshold value corresponding to the current block and the weight adjustment coefficient;
The third acquisition module is used for acquiring weight information of the transaction data;
the generation module is used for generating a new added block based on the weight information of the transaction data and the target weight threshold value, and the sum of the weight information of the transaction data in the new added block is smaller than or equal to the target weight threshold value;
And the synchronization module is used for synchronizing the new added block into the blockchain network so as to enable the new added block to be added to the blockchain.
9. An electronic device, comprising:
A memory for storing a computer program;
A processor for executing a computer program stored in the memory, and when executed, implementing the blockchain network-based blockgeneration method of any of the preceding claims 1-7.
10. A computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the blockchain network-based blockgenerating method of any of the preceding claims 1-7.
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Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107067242A (en) * | 2017-03-24 | 2017-08-18 | 钱德君 | Difficulty value creation method in a kind of block chain generating process |
| CN108830712A (en) * | 2018-05-17 | 2018-11-16 | 易链科技（深圳）有限公司 | Method, apparatus, equipment and the medium that block generates |
| CN112348681A (en) * | 2021-01-11 | 2021-02-09 | 北京知帆科技有限公司 | Block chain transaction commission determining method and device and electronic equipment |
| CN112911011A (en) * | 2021-02-05 | 2021-06-04 | 深圳前海益链网络科技有限公司 | Block generation control method applied to block chain and related device |
| CN113393061A (en) * | 2021-08-17 | 2021-09-14 | 腾讯科技（深圳）有限公司 | Transaction packing method based on block chain and related device |
| KR20220129388A (en) * | 2021-03-16 | 2022-09-23 | 라인 가부시키가이샤 | Method and system for remitting virtual currency |
| CN115168370A (en) * | 2022-02-22 | 2022-10-11 | 湖北文理学院 | Method, device, equipment and storage medium for determining block chaining-out time |
| CN116886712A (en) * | 2023-06-05 | 2023-10-13 | 绍兴数亿科技有限公司 | Block chain consensus mechanism based on time limitation |
-
2024
- 2024-02-01 CN CN202410147261.XA patent/CN117692463B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107067242A (en) * | 2017-03-24 | 2017-08-18 | 钱德君 | Difficulty value creation method in a kind of block chain generating process |
| CN108830712A (en) * | 2018-05-17 | 2018-11-16 | 易链科技（深圳）有限公司 | Method, apparatus, equipment and the medium that block generates |
| CN112348681A (en) * | 2021-01-11 | 2021-02-09 | 北京知帆科技有限公司 | Block chain transaction commission determining method and device and electronic equipment |
| CN112911011A (en) * | 2021-02-05 | 2021-06-04 | 深圳前海益链网络科技有限公司 | Block generation control method applied to block chain and related device |
| KR20220129388A (en) * | 2021-03-16 | 2022-09-23 | 라인 가부시키가이샤 | Method and system for remitting virtual currency |
| CN113393061A (en) * | 2021-08-17 | 2021-09-14 | 腾讯科技（深圳）有限公司 | Transaction packing method based on block chain and related device |
| CN115168370A (en) * | 2022-02-22 | 2022-10-11 | 湖北文理学院 | Method, device, equipment and storage medium for determining block chaining-out time |
| CN116886712A (en) * | 2023-06-05 | 2023-10-13 | 绍兴数亿科技有限公司 | Block chain consensus mechanism based on time limitation |
Non-Patent Citations (1)
| Title |
|---|
| 区块链性能的量化分析研究;王旭等;《计算机工程与应用》;20200215(第3期);全文 * |
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