CN111930847B - Data processing method and device based on block chain and storage medium - Google Patents
Data processing method and device based on block chain and storage medium Download PDFInfo
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Abstract
The application relates to the technical field of blockchain technology and digital medical technology, in particular to a data processing method, a device and a storage medium based on blockchain, which are applied to a first node device in a blockchain system, wherein the system also comprises A second node devices, and the method comprises the following steps: when a distributed transaction is executed, sending a first request to each second node device in the A second node devices, and indicating that each second node device can process the first request, returning a confirmation response message and returning a rejection response message when the first request cannot be processed; receiving response messages returned by the A second node devices within a preset time length to obtain a response message set, wherein the response message set comprises P confirmation response messages and Q refusal response messages, and the sum of P and Q is less than or equal to A; and when the P is equal to the A, executing the preset operation of the distributed transaction. By adopting the method and the device, the medical data processing efficiency based on the block chain can be improved.
Description
Technical Field
The present application relates to the field of blockchain technologies, and in particular, to a method and an apparatus for processing data based on a blockchain, and a storage medium.
Background
The block chain is a continuously-growing distributed database which is substantially jointly maintained by multiple parties, and is also called a distributed shared account book, the core of the block chain is that a trust relationship is established among the distributed network, a cryptology account book with unalterable time sequence and a distributed consensus mechanism, data is programmed and operated through an intelligent contract formed by automatic scripts, and finally the evolution from information interconnection to value interconnection is realized, for example, the block chain technology is also applied to the field of digital medical treatment. At present, the problem of ensuring data consistency of cross-chain operation by such implementation needs to be solved urgently.
Disclosure of Invention
The embodiment of the application provides a data processing method and device based on a block chain and a storage medium, which can ensure the data consistency of cross-chain operation.
In a first aspect, an embodiment of the present application provides a data processing method based on a blockchain, where the data processing method is applied to a first node device in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, and the method includes:
when a distributed transaction is executed, sending a first request to each second node device in the A second node devices, and indicating that each second node device can process the first request, returning a confirmation response message and returning a rejection response message when the first request cannot be processed;
receiving response messages returned by the A second node devices within a preset time length to obtain a response message set, wherein the response message set comprises P confirmation response messages and Q refusal response messages, and the sum of P and Q is less than or equal to A;
and when the P is equal to the A, executing preset operation of the distributed transaction.
In a second aspect, an embodiment of the present application provides a data processing apparatus based on a blockchain, where the data processing apparatus is applied to a first node device in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, and the apparatus includes:
a communication unit, configured to send a first request to each of the a second node devices when a distributed transaction is executed, and return a confirmation response message when each of the a second node devices is capable of processing the first request, and return a rejection response message when the first request cannot be processed;
the communication unit is further configured to receive response messages returned by the a second node devices within a preset time length to obtain a response message set, where the response message set includes P acknowledgement response messages and Q rejection response messages, and a sum of P and Q is less than or equal to a;
and the execution unit is used for executing the preset operation of the distributed transaction when the P is equal to the A.
In a third aspect, an embodiment of the present application provides a node device, including a processor, a memory, a communication interface, and one or more programs, where the one or more programs are stored in the memory and configured to be executed by the processor, and the program includes instructions for executing the steps in the first aspect of the embodiment of the present application.
In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, where the computer-readable storage medium stores a computer program for electronic data exchange, where the computer program enables a computer to perform some or all of the steps described in the first aspect of the embodiment of the present application.
In a fifth aspect, embodiments of the present application provide a computer program product, where the computer program product includes a non-transitory computer-readable storage medium storing a computer program, where the computer program is operable to cause a computer to perform some or all of the steps as described in the first aspect of the embodiments of the present application. The computer program product may be a software installation package.
The embodiment of the application has the following beneficial effects:
it can be seen that the data processing method, apparatus, and storage medium based on blockchain described in the embodiments of the present application are applied to a first node device in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, and when a distributed transaction is performed, send a first request to each of the a second node devices, and indicate that each of the second node devices can process the first request, return an acknowledgement response message and, when the first request cannot be processed, return a rejection response message, receive response messages returned by the a second node devices within a preset time duration, obtain a response message set, where the response message set includes P acknowledgement response messages and Q rejection response messages, and a sum of P and Q is less than or equal to a, and when P is equal to a, perform a preset operation of the distributed transaction, thus, the bottom layer supports a distributed transaction mechanism, and data consistency of cross-chain operation is solved. The application layer is not required to be modified, so that the application development is simpler, and the development of the service is more concentrated.
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In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flowchart of a data processing method based on a block chain according to an embodiment of the present application;
fig. 2 is a schematic flowchart of another data processing method based on a blockchain according to an embodiment of the present disclosure;
fig. 3 is a schematic structural diagram of a first node device according to an embodiment of the present application;
fig. 4 is a block diagram illustrating functional units of a data processing apparatus based on a block chain according to an embodiment of the present application;
fig. 5 is a block diagram of functional units of another data processing apparatus based on a block chain according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions of the present application better understood, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first," "second," and the like in the description and claims of the present application and in the above-described drawings are used for distinguishing between different objects and not for describing a particular order. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
In this application embodiment, no matter the first node device and the second node device are electronic devices, the electronic devices related to this application embodiment may include various handheld devices, desktop computers, vehicle-mounted devices, wearable devices (smart watches, smart bracelets, wireless headsets, augmented reality/virtual reality devices, smart glasses), computing devices or other processing devices connected to wireless modems, and various forms of User Equipment (UE), Mobile Stations (MS), terminal devices (terminal device), and the like. For convenience of description, the above-mentioned devices are collectively referred to as electronic devices, and each node in the block chain may be referred to as a node device.
The following describes embodiments of the present application in detail.
Referring to fig. 1, fig. 1 is a schematic flowchart of a data processing method based on a blockchain according to an embodiment of the present disclosure, where as shown, the data processing method is applied to a first node device in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, and the data processing method based on a blockchain includes:
101. when the distributed transaction is executed, a first request is sent to each second node device in the A second node devices, and when each second node device is indicated to be capable of processing the first request, a confirmation response message is returned, and when the first request cannot be processed, a rejection response message is returned.
In a specific implementation, the distributed transaction refers to that a participant of the transaction, a server supporting the transaction, a resource server, and a transaction manager are respectively located on different nodes of different distributed systems. The blockchain system may be a digital medical system. Based on the digital medical system, the following functions can be realized: medical informatization, intelligent medical treatment, remote medical treatment, electronic information files, disease risk assessment, precision medical treatment, health management, AI + medical treatment, and the like, without limitation. The block chain technology can ensure the safety among different digital medical systems and ensure the consistency of cross-chain data. Of course, the blockchain system may also be other systems, such as a ticketing system, a banking system, a stock system, an insurance system, a school system, an enterprise system, a government system, etc., and is not limited herein.
In a specific implementation, the first node device may be a coordinator, the second node device may be a participant, and both the first node device and the second node device are users in a blockchain. The first node device and the second node device can be in the same chain or different chains, and when the first node device and the second node device are in different chains, the consistency of cross-chain data can be ensured.
In a specific implementation, the first node device may send, when executing the distributed transaction, a first request to each of the a second node devices, and return a confirmation response message when indicating that each of the second node devices can process the first request, and return a rejection response message when not being able to process the first request.
102. And receiving response messages returned by the A second node devices within a preset time length to obtain a response message set, wherein the response message set comprises P confirmation response messages and Q rejection response messages, and the sum of P and Q is less than or equal to A.
The preset time period may be set by the user or default by the system, and the preset time period may be 5s, 10s, 15s, and so on, which is not limited herein, and the preset time period may be a period of time counted from the receiving of the first response message. In a specific implementation, the first node device may receive response messages returned by a second node devices within a preset time length to obtain a response message set, where the response message set may include P acknowledgement response messages and Q rejection response messages, a sum of P and Q is less than or equal to a, P + Q = a when response messages returned by the a second node devices are received within the preset time length, and on the contrary, P + Q < a when response messages returned by at least one second node device of the a second node devices are not received within the preset time length.
103. And when the P is equal to the A, executing preset operation of the distributed transaction.
The preset operation may be set by the user or default to the system, for example, the preset operation may be at least one of the following: a cancommit operation, a prescommit operation, a commit/rollback operation, and the like. When P is equal to a, which is equivalent to the first node device receiving the acknowledgement response message sent by each of the a second node devices, the preset operation of the distributed transaction may be performed.
For example, taking a digital medical system as an example, the digital medical system may be a blockchain system, where the blockchain system includes a first node device and a second node devices, where a is an integer greater than 1, the first node device may be one node device of the blockchain system, the first node device, when performing a distributed transaction, sends a first request to each of the a second node devices, and indicates that each of the second node devices can process the first request, returns an acknowledgement response message and, when the first request cannot be processed, returns a rejection response message, receives response messages returned by the a second node devices within a preset time period, and obtains a response message set, where the response message set includes P acknowledgement response messages and Q rejection response messages, and the sum of P and Q is less than or equal to a, and when P is equal to a, and executing preset operation of the distributed transaction, so that the bottom layer supports a distributed transaction mechanism, and the problem of data consistency of cross-chain operation is solved for the digital medical system. The method does not need any modification on an application layer, so that the application development is simpler, the development of the business is more concentrated, and the data processing efficiency and the safety of the medical system are improved.
Optionally, in step 103, executing the preset operation of the distributed transaction may be implemented as follows:
and sending a pre-commit request to each second node device in the A second node devices, and instructing each second node device in the A second node devices to execute the transaction operation corresponding to the pre-commit request after receiving the pre-commit request, and recording the execution condition in a transaction log.
The first node device may send a pre-commit (presommit) request to each of the a second node devices, and instruct each of the a second node devices to execute a transaction operation corresponding to the pre-commit request after receiving the pre-commit request, and record an execution condition in a transaction log, where the transaction log records whether the second node device can successfully execute the operation corresponding to the pre-commit request.
Optionally, the step of sending the first request to each of the a second node devices may include the following steps:
a1, determining a channel evaluation value between the first node device and each of the a second node devices to obtain a channel evaluation values;
a2, obtaining a predicted transmission time length between the first node device and each of the A second node devices to obtain A predicted transmission time lengths;
a3, optimizing the A predicted transmission durations according to the A channel evaluation values to obtain A effective transmission durations;
a4, determining a sending time corresponding to each second node device in the A second node devices according to the A effective transmission durations to obtain A sending times;
a5, respectively sending a first request to each of the a second node devices according to the a sending time instants.
In a specific implementation, the first node device may determine a channel evaluation value between the first node device and each of the a second node devices, to obtain a channel evaluation values, obtain a predicted transmission time length between the first node device and each of the a second node devices, to obtain a predicted transmission time length, specifically, may send a test signal, and determine the predicted transmission time length by using the test signal, further, the first node device may pre-store a mapping relationship between the channel evaluation values and adjustment coefficients, determine an adjustment coefficient corresponding to each channel evaluation value in the a channel evaluation values, to obtain a adjustment coefficients, adjust the corresponding a predicted transmission time lengths by using the a adjustment coefficients, to obtain a valid transmission time lengths, where a value of the adjustment coefficient may be in a range of-1 to 1, for example, -0.15 to 0.15, then: effective transmission duration = (1 + adjustment coefficient) × predicted transmission duration
Further, the first node device may determine, according to the a effective transmission durations, a sending time corresponding to each of the a second node devices, to obtain the a sending times, for example, the effective transmission durations may be sent later, that is, the sending times are late; the effective transmission time length can be sent first, namely the sending time is early, so that the first request can be guaranteed to reach A second node devices at the same time, and then the first node device can respectively send the first request to each second node device in the A second node devices according to the A sending times, and therefore the first request can be guaranteed to reach at the same time.
Optionally, in the step a1, determining a channel evaluation value between the first node device and each of the a second node devices, to obtain a channel evaluation values, the method may include:
a11, acquiring a signal intensity curve i between the first node device and an ith second node device within a preset time period, wherein the ith second node device is any one of the A second node devices;
a12, sampling the signal intensity curve i to obtain a plurality of signal intensity values;
a13, carrying out mean value operation according to the signal intensity values to obtain a first mean signal intensity value;
a14, determining a target signal strength level corresponding to the first average signal strength value;
a15, determining a target first evaluation value corresponding to the target signal intensity level according to a mapping relation between a preset signal intensity level and the first evaluation value;
a16, performing mean square error operation according to the signal intensity values to obtain a first mean square error;
a17, determining a target second evaluation value corresponding to the first mean square error according to a mapping relation between a preset mean square error and the second evaluation value;
a18, determining a target weight pair corresponding to the target signal strength level according to a mapping relation between preset signal strength levels and the weight pair, wherein the target weight pair comprises a target first weight and a target second weight, the target first weight is a first weight corresponding to the first evaluation value, and the second target weight is a second weight corresponding to the second evaluation value;
and a19, performing weighted operation according to the target first evaluation value, the target second evaluation value, the target first weight and the target second weight, and obtaining a channel evaluation value between the first node device and the ith second node device.
In the embodiment of the present application, the preset time period may be set by a user or default by a system. The first node device may store in advance a mapping relationship between a preset signal strength level and the first evaluation value, a mapping relationship between a preset mean square error and the second evaluation value, and a mapping relationship between a preset signal strength level and a pair of weights. The weight pair may include a first weight of the first evaluation value and a second weight of the second evaluation value, and a sum of the first weight and the first weight may be 1, and of course, the higher the signal strength level is, the larger the first weight is, and the lower the signal strength level is, the smaller the first weight is.
In specific implementation, the first node device may obtain a signal strength curve of the first node device within a preset time period, and sample the signal strength curve to obtain a plurality of signal strength values, where a specific sampling manner may be to sample at preset time intervals or to sample at random, and the specific sampling manner is not limited herein, and the preset time intervals may be set by a user or may be default to a system.
Further, the first node device may perform a mean operation according to a plurality of signal strength values to obtain a first mean signal strength value, and may further store a mapping relationship between the signal strength value and the signal strength level in advance in the first node device, and further may determine a target signal strength level corresponding to the first mean signal strength value according to the mapping relationship, and may determine a target first evaluation value corresponding to the target signal strength level according to the mapping relationship between the preset signal strength level and the first evaluation value, and further perform a mean square error operation according to the plurality of signal strength values to obtain a first mean square error, where the mean square error reflects a fluctuation condition of the signal strength to a certain extent, and of course, the smaller the mean square error is, the better the signal strength stability is, and the larger the mean square error is, the worse the signal stability is. The first node device may determine the target second evaluation value corresponding to the first mean square error according to the preset mapping relationship between the mean square error and the second evaluation value.
Further, the first node device may determine, according to the preset mapping relationship between the signal strength and the weight pair, a target weight pair corresponding to the target signal strength, where the target weight pair includes a target first weight and a target second weight, the target first weight is a first weight corresponding to the first evaluation value, and the second target weight is a second weight corresponding to the second evaluation value, and finally, a channel evaluation value between the first node device and the ith second node device may be obtained by performing weighted operation according to the target first evaluation value, the target second evaluation value, the target first weight, and the target second weight, that is, a specific formula is as follows:
channel evaluation value = target first evaluation value + target second weight
Therefore, in the embodiment of the application, not only is a signal strength curve in a period of time selected, but also an average signal strength value and a mean square error are determined based on the signal strength curve to determine an evaluation value, one of which can reflect the stability of a channel in a period of time, the second of which reflects the stability of the channel, the larger the signal strength value, the more stable the channel, the mean square error reflects the stability of the channel, the smaller the mean square error, the more stable the channel, and the third of which is that the weight corresponding to the signal strength value and the weight corresponding to the mean square error can be dynamically adjusted in the signal strength evaluation process, so that accurate channel quality can be realized.
Further, the method can also comprise the following steps:
and receiving a success response message returned by any one of the A second node devices when the transaction operation is successfully executed, and indicating the any one of the A second node devices to wait for executing a preset instruction.
In a specific implementation, the preset instruction may be set by a user or default to a system, for example, the preset instruction may be a final instruction, and the first node device may receive a success response message returned by any one of the a second node devices when the transaction operation is successfully executed, and instruct the any one of the second node devices to wait for execution of the preset instruction.
Optionally, after the step 102, the following steps may be further included:
interrupting the distributed transaction when the P is not equal to the A.
In a specific implementation, if P is not equal to a, the first node device may abort the distributed transaction.
In a specific implementation, the three stages are CanCommit, prescommit, commit/rollback and CanCommit stages, the coordinator can send a CanCommit request to the underlying chain, and if the coordinator can submit, the participant returns a Yes response, otherwise, the participant returns a No response. The coordinator decides whether the PreCommit operation of the transaction can be continued according to the reaction condition of each bottom chain, and specifically, according to the response condition, there are two possible conditions:
in case one, if the feedback the coordinator gets from all underlying chains is a Yes response, then pre-execution of the transaction will proceed: a pre-commit request is sent. The coordinator sends a PreCommit request to the bottom layer chain and enters a Preprepared stage; the transaction is pre-committed. After receiving the PreCommit request, the bottom link executes the transaction operation and records the undo and redo information into the transaction log; responding to the feedback. If the transaction operation is successfully executed by the bottom layer chain, an ACK response is returned, and meanwhile, the final instruction is waited.
Case two, if either underlying chain sends a No response to the coordinator, or if after waiting for a timeout, the coordinator does not have a response to the underlying chain, then the transaction is interrupted: an interrupt request is sent. The coordinator sends an abort request to all underlying chains.
Further, for an interrupt transaction, the underlying chain may perform the interrupt operation for the distributed transaction after receiving an abort request from the coordinator (or after a timeout, a request not yet received to the underlying chain).
The actual transaction commit for this phase may include the following four steps:
A. a commit request is sent. The coordinator receives the ACK response sent to the bottom chain, and then it will go from the pre-commit state to the commit state. And sends a doCommit request to all underlying chains.
B. The transaction commits. After the bottom link receives the doCommit request, a formal transaction commit is performed. And releases all transaction resources after completion of the transaction commit.
C. Responding to the feedback. After the transaction is committed, an ACK response is sent to the coordinator.
D. The transaction is completed. The coordinator completes the transaction after receiving the ACK responses for all underlying chains.
In addition, if the coordinator does not receive an ACK response sent to the underlying chain (which may be either an ACK response or a timeout response sent by the coordinator), then an interrupt transaction is performed.
Optionally, before the step 101, the following steps may be included:
b1, acquiring a target fingerprint image;
b2, determining a target image quality evaluation value of the target fingerprint image;
b3, matching the target fingerprint image with a preset fingerprint template when the target image quality evaluation value is larger than a preset threshold value;
b4, when the target fingerprint image is successfully matched with the preset fingerprint template, executing the step 101.
Wherein, the preset threshold value can be set by the user or the default of the system. The first node device may store a preset fingerprint template in advance. In a specific implementation, the first node device may acquire a target fingerprint image, and may perform image quality evaluation on the target fingerprint image by using at least one image quality evaluation index to obtain a target image quality evaluation value, where the image quality evaluation index may include at least one of: information entropy, sharpness, edge preservation, mean square error, mean gradient, etc., and is not limited herein. Further, when the target image quality evaluation value is greater than the preset threshold value, the first node device matches the target fingerprint image with the preset fingerprint template, and when the target fingerprint image is successfully matched with the preset fingerprint template, step 101 is executed, otherwise, the user is prompted to continue inputting the fingerprint image.
Further, the step B2, determining the target image quality evaluation value of the target fingerprint image, may include the following steps:
b21, performing multi-scale feature decomposition on the target fingerprint image to obtain a low-frequency feature component and a high-frequency feature component;
b22, dividing the low-frequency characteristic components into a plurality of areas;
b23, determining the information entropy corresponding to each of the plurality of areas to obtain a plurality of information entropies;
b24, determining average information entropy and target mean square error according to the plurality of information entropies;
b25, determining a target adjusting coefficient corresponding to the target mean square error;
b26, adjusting the average information entropy according to the target adjustment coefficient to obtain a target information entropy;
b27, determining a first evaluation value corresponding to the target information entropy according to a mapping relation between preset information entropy and evaluation values;
b28, acquiring target shooting parameters corresponding to the target fingerprint image;
b29, determining a target low-frequency weight corresponding to the target shooting parameter according to a mapping relation between preset shooting parameters and the low-frequency weight, and determining a target high-frequency weight according to the target low-frequency weight;
b30, determining the distribution density of the target characteristic points according to the high-frequency characteristic components;
b31, determining a second evaluation value corresponding to the target feature point distribution density according to a preset mapping relation between the feature point distribution density and the evaluation value;
and B32, performing weighting operation according to the first evaluation value, the second evaluation value, the target low-frequency weight and the target high-frequency weight to obtain a target image quality evaluation value of the target fingerprint image.
In specific implementation, the first node device may perform multi-scale feature decomposition on the target fingerprint image by using a multi-scale decomposition algorithm to obtain a low-frequency feature component and a high-frequency feature component, where the multi-scale decomposition algorithm may be at least one of the following: pyramid transform algorithms, wavelet transforms, contourlet transforms, shear wave transforms, etc., and are not limited herein. Further, the low-frequency characteristic component may be divided into a plurality of regions, and the area size of each region may be the same or different. The low-frequency feature component reflects the main features of the image, and the high-frequency feature component reflects the detail information of the image.
Further, the first node device may determine an information entropy corresponding to each of the plurality of regions to obtain a plurality of information entropies, and determine an average information entropy and a target mean square error according to the plurality of information entropies, where the information entropy reflects the amount of image information to a certain extent, and the mean square error may reflect the stability of the image information. The first node device may pre-store a mapping relationship between a preset mean square error and an adjustment coefficient, and further determine a target adjustment coefficient corresponding to the target mean square error according to the mapping relationship, in this embodiment, a value range of the adjustment coefficient may be-0.15 to 0.15.
Further, the first node device may adjust the average information entropy according to a target adjustment coefficient to obtain a target information entropy, where the target information entropy = (1 + target adjustment coefficient) × the average information entropy. The first node device may store a mapping relationship between a preset information entropy and an evaluation value in advance, and further may determine a first evaluation value corresponding to the target information entropy according to the mapping relationship between the preset information entropy and the evaluation value.
In addition, the first node device may acquire target shooting parameters corresponding to the target fingerprint image, where the target shooting parameters may be at least one of: ISO, exposure duration, white balance parameter, focus parameter, etc., without limitation. The first node device may further pre-store a mapping relationship between a preset shooting parameter and a low frequency weight, and further determine a target low frequency weight corresponding to the target shooting parameter according to the mapping relationship between the preset shooting parameter and the low frequency weight, and determine a target high frequency weight according to the target low frequency weight, where the target low frequency weight + the target high frequency weight = 1.
Further, the first node device may determine a target feature point distribution density from the high-frequency feature components, the target feature point distribution density = total number of feature points/area of the high-frequency feature components. The first node device may further store a mapping relationship between a preset feature point distribution density and an evaluation value in advance, further determine a second evaluation value corresponding to the target feature point distribution density according to the mapping relationship between the preset feature point distribution density and the evaluation value, and finally perform a weighting operation according to the first evaluation value, the second evaluation value, the target low-frequency weight, and the target high-frequency weight to obtain a target image quality evaluation value of the target fingerprint image, which is specifically as follows:
target image quality evaluation value = first evaluation value + target low-frequency weight + second evaluation value + target high-frequency weight
Therefore, image quality evaluation can be performed based on two dimensions of the low-frequency component and the high-frequency component of the fingerprint image, and evaluation parameters suitable for a shooting environment, namely a target image quality evaluation value, can be accurately obtained.
It can be seen that the data processing method based on a blockchain described in the embodiment of the present application is applied to a first node device in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, when a distributed transaction is performed, a first request is sent to each of the a second node devices, and indicates that each of the second node devices can process the first request, an acknowledgement response message is returned, and when the first request cannot be processed, a rejection response message is returned, a response message returned by the a second node devices is received within a preset time duration, a response message set is obtained, the response message set includes P acknowledgement response messages and Q rejection response messages, a sum of P and Q is less than or equal to a, when P is equal to a, a preset operation of the distributed transaction is performed, thus, the bottom layer supports a distributed transaction mechanism, and data consistency of cross-chain operation is solved. The application layer is not required to be modified, so that the application development is simpler, and the development of the service is more concentrated.
Referring to fig. 2, fig. 2 is a schematic flowchart of a data processing method based on a blockchain according to an embodiment of the present application, and the data processing method is applied to a first node device in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, and as shown in the drawing, the data processing method based on a blockchain includes:
201. when the distributed transaction is executed, a first request is sent to each second node device in the A second node devices, and when each second node device is indicated to be capable of processing the first request, a confirmation response message is returned, and when the first request cannot be processed, a rejection response message is returned.
202. And receiving response messages returned by the A second node devices within a preset time length to obtain a response message set, wherein the response message set comprises P confirmation response messages and Q rejection response messages, and the sum of P and Q is less than or equal to A.
203. And when the P is equal to the A, executing preset operation of the distributed transaction.
204. Interrupting the distributed transaction when the P is not equal to the A.
The detailed description of the steps 201 to 204 may refer to the corresponding steps described in the above fig. 1, and is not repeated herein.
It can be seen that, in the data processing method based on the blockchain described in the embodiment of the present application, the bottom layer supports a distributed transaction mechanism, and the data consistency of the cross-chain operation is solved. The application layer is not required to be modified, so that the application development is simpler, and the development of the service is more concentrated.
In accordance with the foregoing embodiments, please refer to fig. 3, where fig. 3 is a schematic structural diagram of a first node device provided in an embodiment of the present application, and as shown in the drawing, the first node device includes a processor, a memory, a communication interface, and one or more programs, the one or more programs are stored in the memory and configured to be executed by the processor, and are applied in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, and in an embodiment of the present application, the programs include instructions for performing the following steps:
when a distributed transaction is executed, sending a first request to each second node device in the A second node devices, and indicating that each second node device can process the first request, returning a confirmation response message and returning a rejection response message when the first request cannot be processed;
receiving response messages returned by the A second node devices within a preset time length to obtain a response message set, wherein the response message set comprises P confirmation response messages and Q refusal response messages, and the sum of P and Q is less than or equal to A;
and when the P is equal to the A, executing preset operation of the distributed transaction.
It can be seen that, the first node device based on a blockchain described in this embodiment of the present application is applied to a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, and when a distributed transaction is performed, sends a first request to each of the a second node devices, and indicates that each of the second node devices can process the first request, returns an acknowledgement response message, and when the first request cannot be processed, returns a rejection response message, receives response messages returned by the a second node devices within a preset time duration, and obtains a response message set, where the response message set includes P acknowledgement response messages and Q rejection response messages, and a sum of P and Q is less than or equal to a, and when P is equal to a, performs a preset operation of the distributed transaction, and thus, a distributed transaction mechanism is supported on an underlying layer, data consistency of cross-chain operation is solved. The application layer is not required to be modified, so that the application development is simpler, and the development of the service is more concentrated.
Optionally, the program further comprises instructions for performing the steps of:
interrupting the distributed transaction when the P is not equal to the A.
Optionally, in terms of the preset operation of executing the distributed transaction, the program includes instructions for performing the following steps:
and sending a pre-commit request to each second node device in the A second node devices, and instructing each second node device in the A second node devices to execute the transaction operation corresponding to the pre-commit request after receiving the pre-commit request, and recording the execution condition in a transaction log.
Optionally, the program further comprises instructions for performing the steps of:
and receiving a success response message returned by any one of the A second node devices when the transaction operation is successfully executed, and indicating the any one of the A second node devices to wait for executing a preset instruction.
Optionally, in the aspect of sending the first request to each of the a second node devices, the program includes instructions for performing the following steps:
determining a channel evaluation value between the first node device and each of the a second node devices to obtain a plurality of channel evaluation values;
obtaining a predicted transmission time length between the first node device and each of the A second node devices to obtain A predicted transmission time lengths;
optimizing the A predicted transmission durations according to the A channel evaluation values to obtain A effective transmission durations;
determining a sending time corresponding to each second node device in the A second node devices according to the A effective transmission durations to obtain A sending times;
and respectively sending a first request to each second node device in the A second node devices according to the A sending moments.
Optionally, the program further comprises instructions for performing the steps of:
acquiring a target fingerprint image;
determining a target image quality evaluation value of the target fingerprint image;
when the quality evaluation value of the target image is larger than a preset threshold value, matching the target fingerprint image with a preset fingerprint template;
and when the target fingerprint image is successfully matched with the preset fingerprint template, executing the step of sending a first request to each second node device in the A second node devices.
Optionally, in the aspect of determining the target image quality evaluation value of the target fingerprint image, the program includes instructions for:
performing multi-scale feature decomposition on the target fingerprint image to obtain a low-frequency feature component and a high-frequency feature component;
dividing the low-frequency feature components into a plurality of regions;
determining an information entropy corresponding to each of the plurality of regions to obtain a plurality of information entropies;
determining an average information entropy and a target mean square error according to the plurality of information entropies;
determining a target adjusting coefficient corresponding to the target mean square error;
adjusting the average information entropy according to the target adjustment coefficient to obtain a target information entropy;
determining a first evaluation value corresponding to the target information entropy according to a mapping relation between a preset information entropy and the evaluation value;
acquiring target shooting parameters corresponding to the target fingerprint image;
determining a target low-frequency weight corresponding to the target shooting parameter according to a mapping relation between a preset shooting parameter and the low-frequency weight, and determining a target high-frequency weight according to the target low-frequency weight;
determining the distribution density of the target characteristic points according to the high-frequency characteristic components;
determining a second evaluation value corresponding to the target feature point distribution density according to a preset mapping relation between the feature point distribution density and the evaluation value;
and performing weighting operation according to the first evaluation value, the second evaluation value, the target low-frequency weight and the target high-frequency weight to obtain a target image quality evaluation value of the target fingerprint image.
The above description has introduced the solution of the embodiment of the present application mainly from the perspective of the method-side implementation process. It is understood that the first node device comprises corresponding hardware structures and/or software modules for performing the respective functions in order to implement the above-mentioned functions. Those of skill in the art will readily appreciate that the present application is capable of hardware or a combination of hardware and computer software implementing the various illustrative elements and algorithm steps described in connection with the embodiments provided herein. Whether a function is performed as hardware or computer software drives hardware depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiment of the present application, the first node device may be divided into the functional units according to the above method example, for example, each functional unit may be divided corresponding to each function, or two or more functions may be integrated into one processing unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit. It should be noted that the division of the unit in the embodiment of the present application is schematic, and is only a logic function division, and there may be another division manner in actual implementation.
Fig. 4 is a block diagram of functional units of a block chain-based data processing apparatus 400 according to an embodiment of the present application. The data processing apparatus 400 based on a blockchain is applied to a first node device in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, and the apparatus includes:
a communication unit 401, configured to send a first request to each of the a second node devices when a distributed transaction is executed, and return a confirmation response message when each of the a second node devices is capable of processing the first request, and return a rejection response message when the first request cannot be processed;
the communication unit 401 is further configured to receive response messages returned by the a second node devices within a preset time duration to obtain a response message set, where the response message set includes P acknowledgement response messages and Q rejection response messages, and a sum of P and Q is less than or equal to a;
an executing unit 402, configured to execute a preset operation of the distributed transaction when P is equal to a.
It can be seen that the data processing apparatus based on a blockchain described in the embodiment of the present application is applied to a first node device in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, when a distributed transaction is performed, a first request is sent to each of the a second node devices, and indicates that each of the second node devices can process the first request, an acknowledgement response message is returned, and when the first request cannot be processed, a rejection response message is returned, a response message returned by the a second node devices is received within a preset time duration, a response message set is obtained, the response message set includes P acknowledgement response messages and Q rejection response messages, a sum of P and Q is less than or equal to a, when P is equal to a, a preset operation of the distributed transaction is performed, thus, the bottom layer supports a distributed transaction mechanism, and data consistency of cross-chain operation is solved. The application layer is not required to be modified, so that the application development is simpler, and the development of the service is more concentrated.
Optionally, the execution unit 402 is further specifically configured to:
interrupting the distributed transaction when the P is not equal to the A.
Optionally, in terms of the preset operation of executing the distributed transaction, the execution unit 402 is specifically configured to:
and sending a pre-commit request to each second node device in the A second node devices, and instructing each second node device in the A second node devices to execute the transaction operation corresponding to the pre-commit request after receiving the pre-commit request, and recording the execution condition in a transaction log.
Optionally, the communication unit 401 is further specifically configured to:
and receiving a success response message returned by any one of the A second node devices when the transaction operation is successfully executed, and indicating the any one of the A second node devices to wait for executing a preset instruction.
Optionally, in terms of the sending the first request to each of the a second node devices, the communication unit 401 is further specifically configured to:
determining a channel evaluation value between the first node device and each of the a second node devices to obtain a plurality of channel evaluation values;
obtaining a predicted transmission time length between the first node device and each of the A second node devices to obtain A predicted transmission time lengths;
optimizing the A predicted transmission durations according to the A channel evaluation values to obtain A effective transmission durations;
determining a sending time corresponding to each second node device in the A second node devices according to the A effective transmission durations to obtain A sending times;
and respectively sending a first request to each second node device in the A second node devices according to the A sending moments.
Optionally, as shown in fig. 5, fig. 5 is a further modified structure of the data processing apparatus based on the block chain shown in fig. 4, which may further include an obtaining unit 403, a determining unit 404, and a matching unit 405, as follows:
the acquiring unit 403 is configured to acquire a target fingerprint image;
the determining unit 404 is configured to determine a target image quality evaluation value of the target fingerprint image;
the matching unit 405 is configured to match the target fingerprint image with a preset fingerprint template when the target image quality evaluation value is greater than a preset threshold;
the step of sending a first request to each of the a second node devices is performed by the communication unit 401 when the target fingerprint image is successfully matched with the preset fingerprint template.
Optionally, in terms of determining the target image quality evaluation value of the target fingerprint image, the determining unit 404 is specifically configured to:
performing multi-scale feature decomposition on the target fingerprint image to obtain a low-frequency feature component and a high-frequency feature component;
dividing the low-frequency feature components into a plurality of regions;
determining an information entropy corresponding to each of the plurality of regions to obtain a plurality of information entropies;
determining an average information entropy and a target mean square error according to the plurality of information entropies;
determining a target adjusting coefficient corresponding to the target mean square error;
adjusting the average information entropy according to the target adjustment coefficient to obtain a target information entropy;
determining a first evaluation value corresponding to the target information entropy according to a mapping relation between a preset information entropy and the evaluation value;
acquiring target shooting parameters corresponding to the target fingerprint image;
determining a target low-frequency weight corresponding to the target shooting parameter according to a mapping relation between a preset shooting parameter and the low-frequency weight, and determining a target high-frequency weight according to the target low-frequency weight;
determining the distribution density of the target characteristic points according to the high-frequency characteristic components;
determining a second evaluation value corresponding to the target feature point distribution density according to a preset mapping relation between the feature point distribution density and the evaluation value;
and performing weighting operation according to the first evaluation value, the second evaluation value, the target low-frequency weight and the target high-frequency weight to obtain a target image quality evaluation value of the target fingerprint image.
It can be understood that the functions of each program module of the data processing apparatus based on the block chain according to this embodiment may be specifically implemented according to the method in the foregoing method embodiment, and the specific implementation process may refer to the related description of the foregoing method embodiment, which is not described herein again.
Embodiments of the present application also provide a computer storage medium, where the computer storage medium stores a computer program for electronic data exchange, the computer program enabling a computer to execute part or all of the steps of any one of the methods described in the above method embodiments, and the computer includes a first node device.
Embodiments of the present application also provide a computer program product comprising a non-transitory computer readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the methods as described in the above method embodiments. The computer program product may be a software installation package, the computer comprising a first node device.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present application is not limited by the order of acts described, as some steps may occur in other orders or concurrently depending on the application. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required in this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed apparatus may be implemented in other manners. For example, the above-described embodiments of the apparatus are merely illustrative, and for example, the above-described division of the units is only one type of division of logical functions, and other divisions may be realized in practice, for example, a plurality of 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 of some interfaces, devices or units, and may be an electric 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 application 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, and can also be realized in a form of a software functional unit.
The integrated unit may be stored in a computer readable memory if it is implemented in the form of a software functional unit and sold or used as a stand-alone product. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a memory, and including several instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the above-mentioned method of the embodiments of the present application. And the aforementioned memory comprises: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable memory, which may include: flash Memory disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The foregoing detailed description of the embodiments of the present application has been presented to illustrate the principles and implementations of the present application, and the above description of the embodiments is only provided to help understand the method and the core concept of the present application; meanwhile, for a person skilled in the art, according to the idea of the present application, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present application.
Claims (9)
1. A data processing method based on a block chain is applied to a first node device in a block chain system, the block chain system comprises the first node device and A second node devices, A is an integer greater than 1, and the method comprises the following steps:
when a distributed transaction is executed, sending a first request to each second node device in the A second node devices, and indicating that each second node device can process the first request, returning a confirmation response message and returning a rejection response message when the first request cannot be processed;
receiving response messages returned by the A second node devices within a preset time length to obtain a response message set, wherein the response message set comprises P confirmation response messages and Q refusal response messages, and the sum of P and Q is less than or equal to A;
when the P is equal to the A, executing preset operation of the distributed transaction;
wherein the executing the preset operation of the distributed transaction comprises:
and sending a pre-commit request to each second node device in the A second node devices, and instructing each second node device in the A second node devices to execute the transaction operation corresponding to the pre-commit request after receiving the pre-commit request, and recording the execution condition in a transaction log.
2. The method of claim 1, further comprising:
interrupting the distributed transaction when the P is not equal to the A.
3. The method of claim 1, further comprising:
and receiving a success response message returned by any one of the A second node devices when the transaction operation is successfully executed, and indicating the any one of the A second node devices to wait for executing a preset instruction.
4. The method of claim 1 or 2, wherein said sending a first request to each of the a second node devices comprises:
determining a channel evaluation value between the first node device and each of the a second node devices to obtain a channel evaluation values, where the channel evaluation values are used to evaluate channel quality;
obtaining a predicted transmission time length between the first node device and each of the A second node devices to obtain A predicted transmission time lengths;
optimizing the A predicted transmission durations according to the A channel evaluation values to obtain A effective transmission durations;
determining a sending time corresponding to each second node device in the A second node devices according to the A effective transmission durations to obtain A sending times;
and respectively sending a first request to each second node device in the A second node devices according to the A sending moments.
5. The method according to claim 1 or 2, characterized in that the method further comprises:
acquiring a target fingerprint image;
determining a target image quality evaluation value of the target fingerprint image;
when the target image quality evaluation value is larger than a preset threshold value, matching the target fingerprint image with a preset fingerprint template;
and when the target fingerprint image is successfully matched with the preset fingerprint template, executing the step of sending a first request to each second node device in the A second node devices.
6. The method of claim 5, wherein determining a target image quality assessment value for the target fingerprint image comprises:
performing multi-scale feature decomposition on the target fingerprint image to obtain a low-frequency feature component and a high-frequency feature component;
dividing the low-frequency feature components into a plurality of regions;
determining an information entropy corresponding to each of the plurality of regions to obtain a plurality of information entropies;
determining an average information entropy and a target mean square error according to the plurality of information entropies;
determining a target adjusting coefficient corresponding to the target mean square error;
adjusting the average information entropy according to the target adjustment coefficient to obtain a target information entropy;
determining a first evaluation value corresponding to the target information entropy according to a mapping relation between a preset information entropy and the evaluation value;
acquiring target shooting parameters corresponding to the target fingerprint image;
determining a target low-frequency weight corresponding to the target shooting parameter according to a mapping relation between preset shooting parameters and the low-frequency weight, and determining a target high-frequency weight according to the target low-frequency weight, wherein the low-frequency weight is a preset weight, the target low-frequency weight is a weight corresponding to the low-frequency characteristic component, and the target high-frequency weight is a weight corresponding to the high-frequency characteristic component;
determining the distribution density of the target characteristic points according to the high-frequency characteristic components;
determining a second evaluation value corresponding to the target feature point distribution density according to a preset mapping relation between the feature point distribution density and the evaluation value;
and performing weighting operation according to the first evaluation value, the second evaluation value, the target low-frequency weight and the target high-frequency weight to obtain a target image quality evaluation value of the target fingerprint image.
7. A data processing apparatus based on a blockchain, applied to a first node device in a blockchain system, where the blockchain system includes the first node device and a second node devices, where a is an integer greater than 1, the apparatus comprising:
a communication unit, configured to send a first request to each of the a second node devices when a distributed transaction is executed, and return a confirmation response message when each of the a second node devices is capable of processing the first request, and return a rejection response message when the first request cannot be processed;
the communication unit is further configured to receive response messages returned by the a second node devices within a preset time length to obtain a response message set, where the response message set includes P acknowledgement response messages and Q rejection response messages, and a sum of P and Q is less than or equal to a;
the execution unit is used for executing the preset operation of the distributed transaction when the P is equal to the A;
in the aspect of the preset operation of executing the distributed transaction, the execution unit is specifically configured to:
and sending a pre-commit request to each second node device in the A second node devices, and instructing each second node device in the A second node devices to execute the transaction operation corresponding to the pre-commit request after receiving the pre-commit request, and recording the execution condition in a transaction log.
8. A node device comprising a processor, a memory for storing one or more programs and configured for execution by the processor, the programs comprising instructions for performing the steps in the method of any of claims 1-6.
9. A computer-readable storage medium, characterized in that the computer-readable storage medium stores a computer program comprising program instructions that, when executed by a processor, cause the processor to carry out the method according to any one of claims 1-6.
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Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4866707A (en) * | 1987-03-03 | 1989-09-12 | Hewlett-Packard Company | Secure messaging systems |
| CN106504091A (en) * | 2016-10-27 | 2017-03-15 | 上海亿账通区块链科技有限公司 | The method and device that concludes the business on block chain |
| CN106789095A (en) * | 2017-03-30 | 2017-05-31 | 腾讯科技（深圳）有限公司 | Distributed system and message treatment method |
| CN107240001A (en) * | 2017-06-06 | 2017-10-10 | 北京汇通金财信息科技有限公司 | Transaction method and system for digital assets |
| CN108848056A (en) * | 2018-05-03 | 2018-11-20 | 南京理工大学 | Block chain common recognition method based on verifying |
| CN109495540A (en) * | 2018-10-15 | 2019-03-19 | 深圳市金证科技股份有限公司 | A kind of method, apparatus of data processing, terminal device and storage medium |
| CN109871279A (en) * | 2019-03-11 | 2019-06-11 | 京东方科技集团股份有限公司 | Task coordination method of knowing together and device, block catenary system, storage medium |
| EP3509006A1 (en) * | 2016-08-30 | 2019-07-10 | Soramitsu Co., Ltd. | Information sharing system |
| CN110490588A (en) * | 2019-08-23 | 2019-11-22 | 深圳前海环融联易信息科技服务有限公司 | Letter of identity management method, device, computer equipment and storage medium |
| CN110601995A (en) * | 2019-09-12 | 2019-12-20 | 腾讯科技（深圳）有限公司 | Method, apparatus, storage medium, and device for controlling traffic in a blockchain network |
| US10693958B2 (en) * | 2019-09-05 | 2020-06-23 | Alibaba Group Holding Limited | System and method for adding node in blockchain network |
| CN111417946A (en) * | 2020-02-24 | 2020-07-14 | 支付宝(杭州)信息技术有限公司 | Block chain based consensus processing |
Family Cites Families (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP3403213A2 (en) * | 2016-01-15 | 2018-11-21 | Enrico Maim | Methods and systems implemented in a network architecture with nodes capable of performing message-based transactions |
| CN106650572A (en) * | 2016-09-12 | 2017-05-10 | 深圳芯启航科技有限公司 | Method for assessing quality of fingerprint image |
| LT3539026T (en) * | 2016-11-10 | 2022-03-25 | Swirlds, Inc. | Methods and apparatus for a distributed database including anonymous entries |
| GB201714987D0 (en) * | 2017-09-18 | 2017-11-01 | Nchain Holdings Ltd | Computer-implemented system and method |
| CN107992356B (en) * | 2017-12-13 | 2021-09-14 | 深圳壹账通智能科技有限公司 | Block chain transaction block processing method, electronic device and readable storage medium |
| US20190319938A1 (en) * | 2018-04-12 | 2019-10-17 | Bank Of America Corporation | Network authentication for real-time interaction using pre-authorized data record |
| CN108958787B (en) * | 2018-06-25 | 2021-11-12 | 百度在线网络技术（北京）有限公司 | Block chain system upgrading method, device, equipment and storage medium |
| CN108768665B (en) * | 2018-07-02 | 2021-06-08 | 上海达家迎信息科技有限公司 | Block chain generation method and device, computer equipment and storage medium |
| US20200013025A1 (en) * | 2018-07-06 | 2020-01-09 | International Business Machines Corporation | Conditional deferred transactions for blockchain |
| CN111191271B (en) * | 2018-11-15 | 2023-06-23 | 国际商业机器公司 | Computer-implemented method, system and storage medium |
| CN110457157B (en) * | 2019-08-05 | 2021-05-11 | 腾讯科技（深圳）有限公司 | Distributed transaction exception handling method and device, computer equipment and storage medium |
| CN110599174B (en) * | 2019-09-20 | 2023-11-24 | 腾讯科技（深圳）有限公司 | Block chain information processing method and related equipment |
| CN111312352B (en) * | 2020-02-19 | 2023-07-21 | 百度在线网络技术（北京）有限公司 | Data processing method, device, equipment and medium based on block chain |
| CN111488202B (en) * | 2020-04-07 | 2023-08-15 | 百度国际科技（深圳）有限公司 | Transaction processing method, device, equipment, system and medium of multi-chain system |
| CN111930847B (en) * | 2020-09-16 | 2021-01-08 | 深圳壹账通智能科技有限公司 | Data processing method and device based on block chain and storage medium |
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2020
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Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US4866707A (en) * | 1987-03-03 | 1989-09-12 | Hewlett-Packard Company | Secure messaging systems |
| EP3509006A1 (en) * | 2016-08-30 | 2019-07-10 | Soramitsu Co., Ltd. | Information sharing system |
| CN106504091A (en) * | 2016-10-27 | 2017-03-15 | 上海亿账通区块链科技有限公司 | The method and device that concludes the business on block chain |
| CN106789095A (en) * | 2017-03-30 | 2017-05-31 | 腾讯科技（深圳）有限公司 | Distributed system and message treatment method |
| CN107240001A (en) * | 2017-06-06 | 2017-10-10 | 北京汇通金财信息科技有限公司 | Transaction method and system for digital assets |
| CN108848056A (en) * | 2018-05-03 | 2018-11-20 | 南京理工大学 | Block chain common recognition method based on verifying |
| CN109495540A (en) * | 2018-10-15 | 2019-03-19 | 深圳市金证科技股份有限公司 | A kind of method, apparatus of data processing, terminal device and storage medium |
| CN109871279A (en) * | 2019-03-11 | 2019-06-11 | 京东方科技集团股份有限公司 | Task coordination method of knowing together and device, block catenary system, storage medium |
| CN110490588A (en) * | 2019-08-23 | 2019-11-22 | 深圳前海环融联易信息科技服务有限公司 | Letter of identity management method, device, computer equipment and storage medium |
| US10693958B2 (en) * | 2019-09-05 | 2020-06-23 | Alibaba Group Holding Limited | System and method for adding node in blockchain network |
| CN110601995A (en) * | 2019-09-12 | 2019-12-20 | 腾讯科技（深圳）有限公司 | Method, apparatus, storage medium, and device for controlling traffic in a blockchain network |
| CN111417946A (en) * | 2020-02-24 | 2020-07-14 | 支付宝(杭州)信息技术有限公司 | Block chain based consensus processing |
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