CN111914299B - Method, device and equipment for optimizing predictive machine interface and storage medium - Google Patents
Method, device and equipment for optimizing predictive machine interface and storage medium Download PDFInfo
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Abstract
The invention relates to the field of block structure improvement and discloses a method, a device, equipment and a storage medium for optimizing a propheter interface. The method comprises the following steps: receiving a contract execution request and connecting a block chain system built based on a super ledger protocol; analyzing the contract execution request to obtain the data response time of the block chain system, substituting the data response time into a preset node algorithm, and calculating to obtain an execution node set; and connecting the execution nodes in the execution node set according to a preset connection algorithm, generating an execution topological structure corresponding to the contract execution request, and completing the contract execution request through the execution topological structure.
Description
Technical Field
The present invention relates to the field of block structure improvement, and in particular, to a method, an apparatus, a device, and a storage medium for optimizing a predictive speech machine interface.
Background
Since the advent of blockchain technology, it has received widespread attention from all ages. Blockchains are a novel application of computer technologies such as distributed data storage, point-to-point transmission, consensus mechanisms, encryption algorithms, and the like. The block chain determines the content of the stored data through a longer chain, is a decentralized technology, and has the characteristics of openness, independence, safety, anonymity and the like. The advantages of the block chain technology enable the block chain to be widely applied to the fields of finance, internet of things, copyright, public service, public welfare and the like.
At present, a preplanning machine in the block chain technology runs a corresponding task on a public chain of a block chain, but the performance of the public chain is low and the overall running speed is slow due to the synchronization requirement of a consensus mechanism on all nodes in the public chain of the block chain. When the public link is congested, in order to accelerate the running speed, more public link digital currencies are used for contract processing, so that the performance of the prediction machine is sharply reduced, and the prediction machine which is higher in efficiency and higher in data processing capacity than the existing prediction machine is needed.
Disclosure of Invention
The main objective of the present invention is to solve the technical problem of block structure improvement.
The invention provides a method for optimizing a predictive player interface in a first aspect, which comprises the following steps:
receiving a contract execution request and connecting a block chain system built based on a super ledger protocol;
analyzing the contract execution request to obtain the data response time of the block chain system, substituting the data response time into a preset node algorithm, and calculating to obtain an execution node set;
according to a preset connection algorithm, connecting execution nodes in the execution node set, generating an execution topological structure corresponding to the contract execution request, and executing the contract execution request through the execution topological structure.
Optionally, in a first implementation manner of the first aspect of the present invention, after the connecting the blockchain system built based on the super ledger protocol, before the data response time of reading the blockchain system, the method further includes:
and setting a parameter according to preset data, setting the number N of nodes which can be operated by the block chain system, and setting an upper limit value M of the number of connecting nodes, wherein M is an integer which is more than or equal to 3, and N is an integer which is more than or equal to 3.
Optionally, in a second implementation manner of the first aspect of the present invention, the analyzing the contract execution request to obtain the data response time of the blockchain system includes:
acquiring a preset request analysis frame, and reading the analysis label characteristics of each frame in the request analysis frame;
reading the contract label feature of each data in the contract execution request, and writing the data in the contract execution request into the request analysis frame according to the matching of the analysis label feature and the contract label feature to obtain request analysis data;
and reading the tag characteristic data corresponding to the data response time in the request analysis data to obtain the data response time of the block chain system.
Optionally, in a third implementation manner of the first aspect of the present invention, the request parsing framework includes: the method comprises a data type frame, a numerical value frame, a data level frame, a data response time frame, a data source frame and a data source quantity frame, wherein the reading of the resolution tag characteristics of each frame in the request resolution frame comprises the following steps:
initializing the data of the data type frame, the numerical frame, the data level frame, the data response time frame, the data source frame and the data source quantity frame, and extracting the analysis label characteristics of the data type frame, the numerical frame, the data level frame, the data response time frame, the data source frame and the data source quantity frame.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the substituting the data response time into a preset node algorithm to calculate an execution node set includes:
substituting the data response time into a preset optimization function, and calculating to obtain the number of constraint nodes;
grabbing nodes which can run in the block chain system according to the number of the constraint nodes, and generating a constraint node set;
traversing and reading label values corresponding to the constraint nodes in the constraint node set, and judging whether the label values are larger than a preset label threshold value;
if the label value is larger than the label threshold value, writing a constraint node corresponding to the label value into a preset execution node set frame, and traversing the constraint node set to generate an execution node set.
Optionally, in a fifth implementation manner of the first aspect of the present invention, the connection algorithm includes: optimizing a function, requesting a node weight value and a response time weight value, wherein the step of connecting the execution nodes in the execution node set according to a preset connection algorithm to generate an execution topological structure corresponding to the contract execution request comprises the following steps:
a number of requesting nodes in the contract execution request;
substituting the request node number, the request node weight value, the data response time and the response time weight value into the optimization function to calculate the number of optimized connection nodes;
and randomly connecting the execution nodes in the execution node set according to the number of the optimized connection nodes, and generating an execution topological structure corresponding to the contract execution request.
Optionally, in a sixth implementation manner of the first aspect of the present invention, the executing, by the execution topology, the contract execution request includes:
sending the data acquired by the execution topological structure to a preset server according to the contract execution request;
and receiving the processing data of the server and sending the processing data to the sending IP address of the contract execution request.
The second aspect of the present invention provides an optimizing apparatus for a prediction machine interface, including:
the receiving module is used for receiving the contract execution request and connecting a block chain system built based on the super ledger protocol;
the analysis calculation module is used for analyzing the contract execution request to obtain the data response time of the block chain system, substituting the data response time into a preset node algorithm, and calculating to obtain an execution node set;
and the execution module is used for connecting the execution nodes in the execution node set according to a preset connection algorithm, generating an execution topological structure corresponding to the contract execution request, and executing the contract execution request through the execution topological structure.
A third aspect of the present invention provides an optimizing apparatus for a prediction machine interface, including: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line; the at least one processor calls the instructions in the memory to cause the optimization device of the predictive machine interface to perform the optimization method of the predictive machine interface described above.
A fourth aspect of the present invention provides a computer-readable storage medium having stored therein instructions, which, when run on a computer, cause the computer to perform the method for optimizing a predictive machine interface described above.
Drawings
FIG. 1 is a schematic diagram of a first embodiment of an optimization method of a prediction machine interface according to an embodiment of the present invention;
FIG. 2 is a diagram of a second embodiment of the method for optimizing the predictive interface according to the embodiment of the invention;
FIG. 3 is a diagram of a third embodiment of the method for optimizing the prediction machine interface according to the embodiment of the present invention;
FIG. 4 is a schematic diagram of an embodiment of an optimizing apparatus for a prediction machine interface according to an embodiment of the present invention;
FIG. 5 is a schematic diagram of another embodiment of the optimizing apparatus for the prediction machine interface in the embodiment of the present invention;
fig. 6 is a schematic diagram of an embodiment of an optimization device of a prediction machine interface in the embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a method, a device, equipment and a storage medium for optimizing a predictive player interface.
The terms "first," "second," "third," "fourth," and the like in the description and in the claims, as well as in the drawings, if any, are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that the embodiments described herein may be practiced otherwise than as specifically illustrated or described herein. Furthermore, the terms "comprises," "comprising," or "having," and any variations thereof, are intended to cover non-exclusive inclusions, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
For convenience of understanding, a specific flow of the embodiment of the present invention is described below, and referring to fig. 1, a first embodiment of the method for optimizing a prediction machine interface in the embodiment of the present invention includes:
101. receiving a contract execution request and connecting a block chain system built based on a super ledger protocol;
in this embodiment, the contract execution request is a task request sent by a client, such as a smart phone, and the contract execution request includes a data type, a numerical value, a data level, data response time, a data source, and a data source number. Unlike public links, the super ledger protocol can modify parameters internally by setting nodes within a personalized blockchain, which is fast and consumes few resources. In specific implementation, the prediction machine has an uplink node and a downlink node, the uplink node is an alliance chain system based on a super account book, and the downlink node is a data acquisition node connected with a data source.
102. Analyzing the contract execution request to obtain the data response time of the block chain system, substituting the data response time into a preset node algorithm, and calculating to obtain an execution node set;
in this embodiment, tags of the data type, the numerical value, the data level, the data response time, the data source, and the data source number in the contract execution request are read, and data of the tag corresponding to the data response time is extracted. The data response time value is t, and the number of operable summary points in the super book is n. The optimization function is:
wherein f ═ x]Taking the integer part of x, T, as a Gaussian functionmaxIs the maximum value of the response time, and t is the data response time value. Obtaining a data value of n in the optimization functionrThen grab n in the blockchain systemrThe node then captures n according to a preset tag value qrNode each node performs a tag value of r1…rmIf the value is larger than the label value q, extracting the point number of the node entering the execution node frame to be common:
if the last obtained data of the F is larger than 0, topological connection is carried out according to the obtained nodes, if the F is equal to 0, the data are not met, and the task is stopped.
103. According to a preset connection algorithm, executing nodes in the executing node set are connected, an executing topological structure corresponding to the contract executing request is generated, and the contract executing request is completed through the executing topological structure.
In this embodiment, the connection algorithm may relate to both the data response time t and the number k of the collection nodes executing the data collection task, and the optimization function of the number of the execution nodes may be:
wherein, the number of the collecting nodes is k, the weight of the influence factor determined by the response time in the number of the nodes is wtThe weight of the influence silver determined by the number of the collection nodes in the number of the nodes is wkThe data response time is t. Selecting a topological structure for collecting data according to the number of the collection nodes, connecting the collection nodes to form an execution topological structure, for example, using A-B-E-G as the execution topological structure, and completing the data content of the contract execution request through a data storage and collection channel formed by A-B-E-G
In the embodiment of the invention, the block chain technology based on the super book is used for changing the interface of the prediction machine, so that the node recognition number required to be transferred when data is stored and modified is reduced, the calculation efficiency during calculation is improved, the resources required to be consumed by calculation are reduced, and the intelligent contract can be more flexibly executed.
Referring to fig. 2, a second embodiment of the method for optimizing a prediction machine interface according to the embodiment of the present invention includes:
201. receiving a contract execution request and connecting a block chain system built based on a super ledger protocol;
the method embodiment described in this embodiment is similar to the first embodiment, and reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
202. Setting parameters according to preset data, setting the number N of nodes which can be operated by a block chain system, and setting an upper limit value M of the number of connecting nodes, wherein M is an integer which is more than or equal to 3, and N is an integer which is more than or equal to 3;
in this embodiment, when the system is connected to the blockchain system, the number of nodes that can be operated by the blockchain system is set to 5000, and the upper limit value of the number of connected nodes is set to 600.
203. Acquiring a preset request analysis frame, and reading the analysis label characteristics of each frame in the request analysis frame;
in this embodiment, a request parsing frame is obtained, then data of a data type frame, a numerical value frame, a data level frame, a data response time frame, a data source frame, and a data source number frame is initialized to change the data therein to 0 or Null, and a parsing tag feature of each frame is read.
204. Reading the contract label characteristics of each datum in the contract execution request, and writing the datum in the contract execution request into a request analysis frame according to the matching of the analysis label characteristics and the contract label characteristics to obtain request analysis data;
in the embodiment, label characteristics of a data type, a numerical value, a data level, a data response time, a data source and a data source number exist in the contract execution request, and data of the data type (characters), the numerical value (222), the data level (6), the data response time (52s), the data source (IP: XXX. sSX. xs) and the data source number (55) are written into a data type frame, a numerical value frame, a data level frame, a data response time frame, the data source frame and the data source number frame according to label characteristic matching to generate request analysis data.
205. Reading the tag characteristic data corresponding to the data response time in the request analysis data to obtain the data response time of the block chain system;
in this embodiment, the data corresponding to the character "data response time" in the read request analysis data is obtained, and the data response time of the block chain system is 52 s.
206. Substituting the data response time into a preset optimization function, and calculating to obtain the number of constraint nodes;
in this embodiment, the optimization function is:
wherein f ═ x]Taking the integer part of x, T, as a Gaussian functionmaxIs the maximum value of the response time, and t is the data response time value. And obtaining the number of beam nodes as k after substitution, wherein k is more than or equal to 2 due to function setting.
207. Capturing nodes which can run in a block chain system according to the number of the constraint nodes to generate a constraint node set;
in this embodiment, k nodes are randomly selected from 5000 executable nodes in the blockchain system, and a constrained node set is generated.
208. Traversing and reading label values corresponding to the constraint nodes in the constraint node set, and judging whether the label values are larger than a preset label threshold value;
in this embodiment, there are k constraint nodes in total, and the label value of each node is r1…rkIf the set label threshold is q, the size of the label value of each bundle node and the label threshold is respectively judged, and the formula of comparison calculation is as follows:
wherein r is1…rkIs the tag value and q is the tag threshold.
209. If the label value is larger than the label threshold value, writing the constraint node corresponding to the label value into a preset execution node set frame, and traversing the constraint node set to generate an execution node set;
in the present embodiment, r1…rkMiddle r5、r9、r12、r19If the label value of the node is larger than the label threshold value q, generating an execution node set { P }5、P9、P12、P19In which P is5、P9、P12、P19Is r5、r9、r12、r19A corresponding executing node.
210. According to a preset connection algorithm, executing nodes in the executing node set are connected, an executing topological structure corresponding to the contract executing request is generated, and the contract executing request is completed through the executing topological structure.
The method embodiment described in this embodiment is similar to the first embodiment, and reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the embodiment of the invention, the block chain technology based on the super book is used for changing the interface of the prediction machine, so that the node recognition number required to be transferred when data is stored and modified is reduced, the calculation efficiency during calculation is improved, the resources required to be consumed by calculation are reduced, and the intelligent contract can be more flexibly executed.
Referring to fig. 3, a third embodiment of the method for optimizing a prediction machine interface according to the embodiment of the present invention includes:
301. receiving a contract execution request and connecting a block chain system built based on a super ledger protocol;
the method embodiment described in this embodiment is similar to the first embodiment, and reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
302. Analyzing the contract execution request to obtain the data response time of the block chain system, substituting the data response time into a preset node algorithm, and calculating to obtain an execution node set;
the method embodiment described in this embodiment is similar to the first embodiment, and reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
303. Reading the number of request nodes in the contract execution request;
in this embodiment, the number of read request nodes is k.
304. Substituting the request node number, the request node weight value, the data response time and the response time weight value into an optimization function to calculate the number of optimized connection nodes;
in this embodiment, the optimization function expression is:
wherein, the number of the request nodes is k, the weight value of the request nodes is wkWith a response time weight of wtAnd the data response time is t, and the number of the optimized connection nodes is H according to the optimization function.
305. Randomly connecting execution nodes in the execution node set according to the number of the optimized connection nodes, and generating an execution topological structure corresponding to the contract execution request;
in the embodiment, the number of the connecting nodes is H, H executing nodes are connected in the executing node set, and the executing topological structure is generated according to the connection condition A-T-E-I-W.
306. Sending data acquired by the execution topological structure to a preset server according to a contract execution request;
in the embodiment, the data X collected by the block chain nodes such as A-T-E-I-W is sent to the server.
307. And receiving the processing data of the server and transmitting the processing data to the transmission IP address of the contract execution request.
In this embodiment, after processing the data X according to the contract execution request, the server sends the result O to the sending IP address (IP: xxx. sx. xs) recorded in the data source in the contract execution request.
In the embodiment of the invention, the block chain technology based on the super book is used for changing the interface of the prediction machine, so that the node recognition number required to be transferred when data is stored and modified is reduced, the calculation efficiency during calculation is improved, the resources required to be consumed by calculation are reduced, and the intelligent contract can be more flexibly executed.
With reference to fig. 4, the method for optimizing a predictive interface according to an embodiment of the present invention is described above, and an embodiment of the apparatus for optimizing a predictive interface according to an embodiment of the present invention includes:
the receiving module 401 is configured to receive a contract execution request and connect a block chain system established based on a super ledger protocol;
an analysis calculation module 402, configured to analyze the contract execution request to obtain a data response time of the block chain system, and substitute the data response time into a preset node algorithm to calculate an execution node set;
the executing module 403 is configured to connect executing nodes in the executing node set according to a preset connection algorithm, generate an executing topology structure corresponding to the contract executing request, and complete the contract executing request through the executing topology structure.
In the embodiment of the invention, the block chain technology based on the super book is used for changing the interface of the prediction machine, so that the node recognition number required to be transferred when data is stored and modified is reduced, the calculation efficiency during calculation is improved, the resources required to be consumed by calculation are reduced, and the intelligent contract can be more flexibly executed.
Referring to fig. 5, another embodiment of the optimizing apparatus for a prediction machine interface according to the embodiment of the present invention includes:
the receiving module 401 is configured to receive a contract execution request and connect a block chain system established based on a super ledger protocol;
an analysis calculation module 402, configured to analyze the contract execution request to obtain a data response time of the block chain system, and substitute the data response time into a preset node algorithm to calculate an execution node set;
the executing module 403 is configured to connect executing nodes in the executing node set according to a preset connection algorithm, generate an executing topology structure corresponding to the contract executing request, and complete the contract executing request through the executing topology structure.
The optimizing apparatus for a prediction machine interface includes a parameter setting module 404, where the parameter setting module 404 is specifically configured to:
and setting a parameter according to preset data, setting the number N of nodes which can be operated by the block chain system, and setting an upper limit value M of the number of connecting nodes, wherein M is an integer which is more than or equal to 3, and N is an integer which is more than or equal to 3.
Wherein the parsing calculation module 402 comprises:
an obtaining unit 4021, configured to obtain a preset request parsing frame, and read a parsing tag feature of each frame in the request parsing frame;
the matching unit 4022 is configured to read a contract tag feature of each piece of data in the contract execution request, and write the data in the contract execution request into the request parsing framework according to matching between the parsing tag feature and the contract tag feature, so as to obtain request parsing data;
the reading unit 4023 is configured to read tag feature data corresponding to the data response time in the request parsing data, so as to obtain the data response time of the blockchain system.
The obtaining unit 4021 is specifically configured to:
initializing the data of the data type frame, the numerical frame, the data level frame, the data response time frame, the data source frame and the data source quantity frame, and extracting the analysis label characteristics of the data type frame, the numerical frame, the data level frame, the data response time frame, the data source frame and the data source quantity frame.
The parsing calculation module 402 may be further specifically configured to:
substituting the data response time into a preset optimization function, and calculating to obtain the number of constraint nodes;
grabbing nodes which can run in the block chain system according to the number of the constraint nodes, and generating a constraint node set;
traversing and reading label values corresponding to the constraint nodes in the constraint node set, and judging whether the label values are larger than a preset label threshold value;
if the label value is larger than the label threshold value, writing a constraint node corresponding to the label value into a preset execution node set frame, and traversing the constraint node set to generate an execution node set.
The execution module 403 is specifically configured to:
reading the number of request nodes in the contract execution request;
substituting the request node number, the request node weight value, the data response time and the response time weight value into the optimization function to calculate the number of optimized connection nodes;
and randomly connecting the execution nodes in the execution node set according to the number of the optimized connection nodes, and generating an execution topological structure corresponding to the contract execution request.
The executing module 403 may be further specifically configured to:
sending the data acquired by the execution topological structure to a preset server according to the contract execution request;
and receiving the processing data of the server and sending the processing data to the sending IP address of the contract execution request.
In the embodiment of the invention, the block chain technology based on the super book is used for changing the interface of the prediction machine, so that the node recognition number required to be transferred when data is stored and modified is reduced, the calculation efficiency during calculation is improved, the resources required to be consumed by calculation are reduced, and the intelligent contract can be more flexibly executed.
Fig. 4 and 5 describe the optimization apparatus of the predictive phone interface in the embodiment of the present invention in detail from the perspective of the modular functional entity, and the optimization device of the predictive phone interface in the embodiment of the present invention is described in detail from the perspective of hardware processing.
Fig. 6 is a schematic structural diagram of an optimization device of a predictive machine interface according to an embodiment of the present invention, where the optimization device 600 of the predictive machine interface may generate a relatively large difference due to different configurations or performances, and may include one or more processors (CPUs) 610 (e.g., one or more processors) and a memory 620, and one or more storage media 630 (e.g., one or more mass storage devices) storing applications 633 or data 632. Memory 620 and storage medium 630 may be, among other things, transient or persistent storage. The program stored in the storage medium 630 may include one or more modules (not shown), each of which may include a series of instruction operations in the optimization apparatus 600 for the predictive player interface. Still further, the processor 610 may be configured to communicate with the storage medium 630 to execute a series of instruction operations in the storage medium 630 on the predictive player interface optimizing device 600.
The predictive-machine-interface-based optimizer 600 may also include one or more power supplies 640, one or more wired or wireless network interfaces 650, one or more input-output interfaces 660, and/or one or more operating systems 631, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, and the like. Those skilled in the art will appreciate that the configuration of the predictive-machine-interface-based optimization device shown in fig. 6 does not constitute a limitation of the predictive-machine-interface-based optimization device, and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium, and which may also be a volatile computer-readable storage medium, having stored therein instructions, which, when run on a computer, cause the computer to perform the steps of the method for optimizing a predictive computer interface.
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses, and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a read-only memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (9)
1. A method for optimizing a prediction machine interface is characterized by comprising the following steps:
receiving a contract execution request and connecting a block chain system built based on a super ledger protocol;
analyzing the contract execution request to obtain the data response time of the block chain system, substituting the data response time into a preset node algorithm, and calculating to obtain an execution node set;
according to a preset connection algorithm, connecting execution nodes in the execution node set, generating an execution topological structure corresponding to the contract execution request, and completing the contract execution request through the execution topological structure; wherein the analyzing the contract execution request to obtain the data response time of the blockchain system comprises:
acquiring a preset request analysis frame, and reading the analysis label characteristics of each frame in the request analysis frame;
reading the contract label feature of each data in the contract execution request, and writing the data in the contract execution request into the request analysis frame according to the matching of the analysis label feature and the contract label feature to obtain request analysis data;
and reading the tag characteristic data corresponding to the data response time in the request analysis data to obtain the data response time of the block chain system.
2. The optimizing method for a preplan interface according to claim 1, wherein after the connecting a blockchain system built based on a hyper book protocol, before the data response time of reading the blockchain system, the method further comprises:
and setting a parameter according to preset data, setting the number N of nodes which can be operated by the block chain system, and setting an upper limit value M of the number of connecting nodes, wherein M is an integer which is more than or equal to 3, and N is an integer which is more than or equal to 3.
3. The method of optimizing a predictive machine interface of claim 1 wherein said request resolution framework comprises: the method comprises a data type frame, a numerical value frame, a data level frame, a data response time frame, a data source frame and a data source quantity frame, wherein the reading of the resolution tag characteristics of each frame in the request resolution frame comprises the following steps:
initializing the data of the data type frame, the numerical frame, the data level frame, the data response time frame, the data source frame and the data source quantity frame, and extracting the analysis label characteristics of the data type frame, the numerical frame, the data level frame, the data response time frame, the data source frame and the data source quantity frame.
4. The method according to claim 1, wherein the step of substituting the data response time into a preset node algorithm to calculate an execution node set comprises:
substituting the data response time into a preset optimization function, and calculating to obtain the number of constraint nodes;
grabbing nodes which can run in the block chain system according to the number of the constraint nodes, and generating a constraint node set;
traversing and reading label values corresponding to the constraint nodes in the constraint node set, and judging whether the label values are larger than a preset label threshold value;
if the label value is larger than the label threshold value, writing a constraint node corresponding to the label value into a preset execution node set frame, and traversing the constraint node set to generate an execution node set.
5. The method of optimizing a predictive interface of claim 1 wherein said connection algorithm comprises: optimizing a function, requesting a node weight value and a response time weight value, wherein the step of connecting the execution nodes in the execution node set according to a preset connection algorithm to generate an execution topological structure corresponding to the contract execution request comprises the following steps:
reading the number of request nodes in the contract execution request;
substituting the request node number, the request node weight value, the data response time and the response time weight value into the optimization function to calculate the number of optimized connection nodes;
and randomly connecting the execution nodes in the execution node set according to the number of the optimized connection nodes, and generating an execution topological structure corresponding to the contract execution request.
6. The method for optimizing a predictive machine interface of any one of claims 1-5 wherein said fulfilling the contract execution request via the execution topology comprises:
sending the data acquired by the execution topological structure to a preset server according to the contract execution request;
and receiving the processing data of the server and sending the processing data to the sending IP address of the contract execution request.
7. An optimization device of a predictive speech machine interface, characterized in that the optimization device of the predictive speech machine interface comprises:
the receiving module is used for receiving the contract execution request and connecting a block chain system built based on the super ledger protocol;
the analysis calculation module is used for analyzing the contract execution request to obtain the data response time of the block chain system, substituting the data response time into a preset node algorithm, and calculating to obtain an execution node set;
the execution module is used for connecting execution nodes in the execution node set according to a preset connection algorithm, generating an execution topological structure corresponding to the contract execution request and completing the contract execution request through the execution topological structure; wherein the execution module is specifically configured to: acquiring a preset request analysis frame, and reading the analysis label characteristics of each frame in the request analysis frame;
reading the contract label feature of each data in the contract execution request, and writing the data in the contract execution request into the request analysis frame according to the matching of the analysis label feature and the contract label feature to obtain request analysis data;
and reading the tag characteristic data corresponding to the data response time in the request analysis data to obtain the data response time of the block chain system.
8. An optimization device for a predictive-machine interface, the optimization device comprising: a memory having instructions stored therein and at least one processor, the memory and the at least one processor interconnected by a line;
the at least one processor invokes the instructions in the memory to cause the optimization device of the predictive machine interface to perform the optimization method of the predictive machine interface of any of claims 1-6.
9. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out a method of optimizing a predictive interface according to any one of claims 1 to 6.
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