CN111614499B

CN111614499B - Information processing method based on 5G and block chain and cloud computing server

Info

Publication number: CN111614499B
Application number: CN202010448176.9A
Authority: CN
Inventors: 李大庆; 郁健兰
Original assignee: Jiangsu Yongding Communications Co ltd
Current assignee: JIANGSU YONGDING COMMUNICATIONS Co.,Ltd.
Priority date: 2020-05-25
Filing date: 2020-05-25
Publication date: 2021-03-16
Anticipated expiration: 2040-05-25
Also published as: CN111614499A

Abstract

The application provides an information processing method based on 5G and a block chain and a cloud computing server. When the method is applied, the real-time information processing state of each node device can be tracked and visualized, so that the interactivity and the influence among different node devices are taken into consideration, the thread parameters of the information processing thread of each node device can be deeply mined and analyzed, the information processing thread can be adaptively adjusted for the corresponding node device according to the difference of the thread parameters among different node devices, and the information processing flexibility of the whole block chain is improved.

Description

Information processing method based on 5G and block chain and cloud computing server

Technical Field

The application relates to the technical field of 5G communication, in particular to an information processing method based on 5G and a block chain and a cloud computing server.

Background

The 5G technology is a latest generation cellular mobile communication technology, and has the advantages of improving data rate, reducing delay, saving energy, reducing cost, improving system capacity, supporting large-scale equipment connection and the like. Depending on these advantages, the 5G technology can be applied to the fields of large data volume transmission such as high-definition video and virtual reality, and can also be applied to the fields of low delay requirements such as automatic driving and telemedicine. The block chain is used as a new generation of internet, and the characteristics of decentralization, transaction information privacy protection, historical record tamper resistance, traceability and the like can promote the efficient development of 5G application. The communication technology based on the 5G and the block chain can not only improve the data transmission rate and reduce the transmission delay, but also provide technical supports of decentralization, privacy protection, tamper resistance, traceability and the like for communication interaction through a cryptographic means. However, when information processing is performed based on the above-described technique, it is difficult to adaptively adjust according to the information processing state of each node apparatus, which may reduce the flexibility of information processing.

Disclosure of Invention

The application provides an information processing method based on 5G and a block chain and a cloud computing server, so as to solve the technical problems in the prior art.

According to a first aspect of the embodiments of the present application, there is provided an information processing method based on 5G and a blockchain, which is applied to a cloud computing server, the method including:

tracking each node device in a block chain, generating a first state log of each node device based on a first state parameter of each node device in the current time period and a second state parameter of each node device in the last time period, and determining a state track of each node device according to the first state log; the state track is used for representing the change conditions of delay and error rate of information processing of the node equipment;

in the process of monitoring each state track, acquiring track variation of each state track, and determining a second state log of each node device based on the track variation;

when determining that a first state track of first node equipment and a second state track of second node equipment have an intersection point according to a second state log of the first node equipment, extracting a first thread parameter of a first information processing thread of the first node equipment at the intersection point and a second thread parameter of a second information processing thread of the second node equipment at the intersection point;

determining a first parameter grid of the first thread parameter and a second parameter grid of the second thread parameter; a first thread script of the first node device is encapsulated in the first parameter grid, a second thread script of the second node device is encapsulated in the second parameter grid, the first parameter grid and the second parameter grid respectively comprise a plurality of grid areas, and each grid area corresponds to at least one thread parameter set;

acquiring a path difference coefficient of a first grid path of the first parameter grid and a second grid path of the second parameter grid by utilizing real-time position information of a first track node corresponding to the first parameter grid in a first state track; and when the path difference coefficient is judged to be different from a preset difference coefficient, determining a coefficient difference value between the path difference coefficient and the preset difference coefficient, generating an adjusting instruction for adjusting a first thread parameter of the first information processing thread based on the coefficient difference value, and sending the adjusting instruction to the first node equipment so that the first node equipment modifies the first thread parameter according to the adjusting instruction.

According to a second aspect of embodiments of the present application, there is provided a cloud computing server, configured to:

According to a third aspect of embodiments of the present application, there is provided a cloud computing server, including: a processor and a memory in communication with each other; the processor retrieves the computer program from the memory when running and executes the computer program to perform the above-mentioned method.

According to a fourth aspect of the embodiments of the present application, a readable storage medium applied to a computer is provided, and a computer program is burned on the readable storage medium, and when the computer program runs in a cloud computing server, the method described above is implemented.

When the information processing method based on the 5G and the block chain and the cloud computing server are applied, firstly, each node device in the block chain is tracked to determine the state track of each node device, and therefore the state track is monitored. Further, a second status log for each node device is determined during the detection of the status trace. Aiming at two different node devices, when the condition tracks of the two node devices have an intersection point according to the second condition log of the first node device, the first thread parameters and the second thread parameters of the two node devices are respectively extracted to further determine a first parameter grid and a second parameter grid. And finally, generating an adjusting instruction of the first thread parameter based on the first parameter grid and the second parameter grid so as to send the adjusting instruction to the first node equipment, thereby enabling the first node equipment to realize the self-adaptive adjustment of the information processing thread.

By the scheme provided by the application implementation, the real-time information processing state of each node device can be tracked and visualized, so that the interactivity and the influence among different node devices are taken into consideration, the thread parameters of the information processing thread of each node device can be deeply mined and analyzed, the self-adaptive adjustment of the information processing thread is carried out on the corresponding node device according to the difference of the thread parameters among different node devices, and the information processing flexibility of the whole block chain is improved.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and together with the description, serve to explain the principles of the application.

Fig. 1 is a communication architecture diagram of a 5G and blockchain based information processing system according to an exemplary embodiment of the present application.

Fig. 2 is a flowchart illustrating an information processing method based on 5G and a block chain according to an exemplary embodiment.

Fig. 3 shows a schematic diagram of the substeps of step S210 shown in fig. 2.

Fig. 4 shows a schematic diagram of the substeps of step S220 shown in fig. 2.

Fig. 5 shows a schematic diagram of the substeps of step S250 shown in fig. 2.

Fig. 6 is a functional block diagram of an information processing apparatus based on 5G and a block chain according to an exemplary embodiment of the present application.

Detailed Description

Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.

In order to solve the above problem, the present disclosure discloses an information processing method based on 5G and a block chain and a cloud computing server, which can adaptively adjust an information processing thread of each node device according to a real-time information processing state of each node device, so that information processing flexibility of the node device can be improved. To better understand the information processing method, the present disclosure first discloses a communication architecture connection diagram of the information processing system 100 based on 5G and block chain.

Referring to fig. 1, the information processing system 100 may include a cloud computing server 200 and a plurality of node devices 400 communicating with each other. The node device 400 may be understood as a block-link node device, and may be applied to a plurality of fields, such as automatic driving, remote medical treatment, smart city, unmanned aerial vehicle rescue, and bulk digital transaction, which are not limited herein. The cloud computing server 200 may be configured to monitor and analyze a real-time information processing state of each node device 400, so as to issue a corresponding adaptive adjustment instruction to each node device 400, so that each node device 400 adjusts an information processing thread according to the adaptive adjustment instruction, thereby improving flexibility of information processing.

On the basis of the above, please refer to fig. 2, which discloses a flowchart of an information processing method based on 5G and a block chain, where the information processing method may be applied to the cloud computing server 200 in fig. 1, and may specifically include the contents described in the following steps.

Step S210, tracking each node device in the block chain, generating a first state log of each node device based on a first state parameter of each node device in a current time period and a second state parameter of the node device in a previous time period, and determining a state track of each node device according to the first state log.

In this disclosure, the state trajectory is used to represent the variation of the delay and the error rate of the node device for information processing.

Step S220, in the process of monitoring each state track, collecting the track variation of each state track, and determining a second state log of each node device based on the track variation.

In the present disclosure, the track variation includes a position variation value of a track node and description information for representing a direction variation of the track node.

Step S230, when it is determined that there is an intersection between the first state trajectory of the first node device and the second state trajectory of the second node device according to the second state log of the first node device, extracting a first thread parameter of a first information processing thread of the first node device at the intersection and a second thread parameter of a second information processing thread of the second node device at the intersection.

In the present disclosure, the first node device and the second node device are two different node devices in which there is communication in the blockchain. The first state trajectory of the first node device and the state trajectory of the second node device are located in the same preset trajectory plane.

Further, the thread parameters may include configuration parameters of the information processing thread corresponding to the (first and/or second) node device when performing processing such as information receiving, information storing, information forwarding, and information screening, and different configuration parameters are used for executing different processing policies. For example, if the configuration parameter for information reception is D1, the frequency characterizing information reception may be F1, and if the configuration parameter for information reception is D2, the frequency characterizing information reception may be F2. It is understood that the thread parameter may cover multiple types of information processing manners of the (first and/or second) node device, and is not limited herein.

Step S240, determining a first parameter grid of the first thread parameter and a second parameter grid of the second thread parameter.

In this disclosure, a first thread script of the first node device is encapsulated in the first parameter mesh, a second thread script of the second node device is encapsulated in the second parameter mesh, the first parameter mesh and the second parameter mesh respectively include a plurality of mesh regions, and each mesh region corresponds to at least one thread parameter set.

Step S250, acquiring a path difference coefficient of a first grid path of the first parameter grid and a second grid path of the second parameter grid by using real-time position information of a first track node corresponding to the first parameter grid in a first state track; and when the path difference coefficient is judged to be different from a preset difference coefficient, determining a coefficient difference value between the path difference coefficient and the preset difference coefficient, generating an adjusting instruction for adjusting a first thread parameter of the first information processing thread based on the coefficient difference value, and sending the adjusting instruction to the first node equipment so that the first node equipment modifies the first thread parameter according to the adjusting instruction.

In this disclosure, the first node device can modify the manner of processing the information after modifying the first thread parameter. For example, after modifying the first thread parameter, the first node device may delay receiving information sent by the other node devices according to the size order of the device priorities of the other node devices, so that the order of information processing of the first node device may be improved. For another example, the first node device may also send the information according to the set sending frequency after modifying the first thread parameter. It should be understood that the first node device may perform information processing in various ways, and is not limited herein.

It can be understood that the cloud computing server is used for issuing the adjustment instruction to each node device, and the actual information processing process is implemented by each node device.

When the method described in the above steps S210 to S250 provided by the present disclosure is applied, each node device in the block chain is first tracked to determine a state trajectory of each node device, so as to implement monitoring of the state trajectory. Further, a second status log for each node device is determined during the detection of the status trace. Aiming at two different node devices, when the condition tracks of the two node devices have an intersection point according to the second condition log of the first node device, the first thread parameters and the second thread parameters of the two node devices are respectively extracted to further determine a first parameter grid and a second parameter grid. And finally, generating an adjusting instruction of the first thread parameter based on the first parameter grid and the second parameter grid so as to send the adjusting instruction to the first node equipment, thereby enabling the first node equipment to realize the self-adaptive adjustment of the information processing thread.

Through the content described in the steps, the real-time information processing state of each node device can be tracked and visualized, so that the interactivity and the influence among different node devices are taken into consideration, the thread parameters of the information processing thread of each node device can be deeply mined and analyzed, the self-adaptive adjustment of the information processing thread is carried out on the corresponding node device according to the difference of the thread parameters among different node devices, and the information processing flexibility of the whole block chain is improved.

In a specific implementation, in order to accurately determine the state trace of each node device, so as to ensure an accurate analysis of the information processing thread of each node device, please refer to fig. 3, where step S210 generates a first state log of each node device based on a first state parameter of each node device in a current time period and a second state parameter of the node device in a last time period, and determines the state trace of each node device according to the first state log, which may specifically include the contents described in steps S211 to S215 below.

Step S211, listing the common parameter identifiers in the first status parameter and the second status parameter.

Step S212, for each common parameter identifier, sequentially adding a first parameter group corresponding to the common parameter identifier in the first state parameter and a second parameter group corresponding to the common parameter identifier in the second state parameter to a first preset list corresponding to the common parameter identifier.

Step S213, add a first remaining parameter group of the first state parameter except the first parameter group corresponding to the common parameter identifier to a second preset list corresponding to a first setting identifier, and add a second remaining parameter group of the second state parameter except the second parameter group corresponding to the common parameter identifier to a third preset list corresponding to a second setting identifier.

Step S214, integrating the first preset list, the second preset list, and the third preset list according to the order of the list weight values of the first preset list, the second preset list, and the third preset list to obtain the first status log.

Step S215, summarizing the list units carrying the directional signatures in the first state log to obtain a list unit set, and connecting the unit nodes corresponding to each list unit according to signature registration information of the directional signatures in the list unit set to obtain a state trajectory corresponding to each node device.

It can be understood that through the descriptions in the foregoing steps S211 to S215, the common parameter identifiers of the first state parameter and the second state parameter can be analyzed, so that a first state log is generated based on a plurality of preset lists obtained through analysis, and then a state track corresponding to each node device is determined according to a list unit carrying a directional signature in the first state log. Therefore, the directional signature is analyzed, the first state parameter and the second state parameter can be tracked and visualized, so that the state track corresponding to each node device is completely and accurately determined, and a basis is provided for subsequent thread parameter analysis.

The inventor finds that, when the second state log is determined, because the second state log is determined based on the state track, a mapping result of a track variation may be missing due to a difference between a visual display of the state track and a digital display of the second state log, which may affect the integrity of the second state log and further affect the generation accuracy of a subsequent adjustment instruction. To improve the above problem, please refer to fig. 4 in combination, in step S220, a trace variation of each state trace is collected, and a second state log of each node device is determined based on the trace variation, which may specifically include the contents described in the following steps S221 to S224.

Step S221, obtaining description information of each state track and a file source code corresponding to a visual script file of each state track; fusing the description information and the file source code according to a preset corresponding relation to obtain at least two target data packets; wherein, the target data packet contains the description value and the source code character which have the incidence relation.

Step S222, obtaining distribution structure information of each target data packet and global variable information and local variable information corresponding to the target data packet, where the global variable information and the local variable information are part of the description information.

Step S223, calculating a defect weight when each target data packet is fitted to the first state log corresponding to the state trajectory according to the distribution structure information, the global variable information, and the local variable information of each target data packet, and fitting the target data packet to the corresponding variable set in the description information when the defect weight is converged relative to the state trajectory, so as to obtain mapping data of the target data packet in the variable set.

Step S224, according to the variable grade of the mapping data in the variable set, exporting the mapping data according to the format of the target variable in the variable set to obtain multiple groups of track variable quantities, and arranging the multiple groups of track variable quantities according to the sequence of export time to obtain the second state log.

When the content described in the above steps S221 to S224 is executed, the description information of the status track and the file source code can be fused, so that the difference between the visual display of the status track and the digital display of the second status log is eliminated. Further, when determining the defect weight, the mapping data can be determined on the premise that the defect weight converges, so that the integrity of the mapping data can be ensured. Therefore, the mapping result of the track variation is ensured not to be missing. And finally, arranging the track variables everywhere, and completely generating a second state log.

In an actual implementation process, in order to accurately extract the first thread parameter and the second thread parameter, in step S230, the extracting the first thread parameter of the first information processing thread at the intersection of the first node device and the second thread parameter of the second information processing thread at the intersection of the second node device may specifically include: respectively determining a first device delay of the first node device and a second device delay of the second node device; determining a first set time period of the first node device at a target time corresponding to the intersection point according to the first device delay and determining a second set time period of the second node device at the target time corresponding to the intersection point according to the second device delay; and respectively extracting a first thread parameter of the first information processing thread in the first set time interval and a second thread parameter of the second information processing thread in the second set time interval.

Therefore, the device delay of the first node device and the device delay of the second node device can be taken into consideration, and the set time periods corresponding to the first node device and the second node device can be accurately determined when the first state track and the second state track are intersected, so that the thread parameters of different information processing threads are extracted according to different set time periods, the thread parameter extraction mode of 'one-time cutting' is avoided, and the accuracy of the thread parameters is further ensured.

The inventor finds in the above-mentioned implementation that, when calculating the path difference coefficient, it is necessary to take into account the confidence of the real-time position information, otherwise, misalignment between the first trellis path and the second trellis path may occur in the comparison. To solve the above problem, please refer to fig. 5, in step S250, the real-time location information of the first trajectory node corresponding to the first parameter grid in the first state trajectory is utilized to obtain the path difference coefficient between the first grid path of the first parameter grid and the second grid path of the second parameter grid, which may specifically include the contents described in steps S251 to S255.

Step S251, obtaining grid distribution information of the first parameter grid and a grid type to which the first parameter grid belongs, and determining a plurality of target track nodes from the first state track according to the grid type; and the node category of the target track node and the grid category belong to the same classification category.

Step S252, a grid position sequence is generated according to the grid distribution information of the first parameter grid, where the grid position sequence includes a sequence weight for representing the grid density of the first parameter grid, an evaluation weight for evaluating the grid stability of the first parameter grid, and a distribution weight for recording the grid saturation of the first parameter grid.

Step S253 of generating a node description vector according to the sequence weight, the evaluation weight, and the distribution weight of the grid position sequence; when the cosine distance between the node description vector and the node vector of one target track node reaches a set value, determining the target track node as the first track node; calculating the calling frequency of the first track node in the first state track, determining a confidence coefficient corresponding to the calling frequency according to a preset mapping list, and determining the confidence coefficient as the confidence coefficient of the real-time position information of the first track node.

Step S254, determining a comparison order of the first grid path and the second grid path according to the confidence, performing traversal comparison on the first grid path and the second grid path according to the comparison order, and recording a matching degree corresponding to a comparison result of each comparison in a traversal process; wherein the matching degree is used for characterizing the distance between each path node in the first grid path and the second grid path.

And S255, distributing a weighting coefficient to each matching degree according to the confidence degree, and weighting the matching degrees based on the weighting coefficients to obtain the path difference coefficient.

Based on the above steps S251 to S255, the confidence of the real-time position information can be taken into account, so as to avoid the dislocation of the path node during the comparison between the first mesh path and the second mesh path, thereby accurately determining the path difference coefficient between the first mesh path and the second mesh path, and providing an accurate data basis for the subsequent generation of the adjustment instruction.

In order to instruct the first node device to flexibly and accurately adjust the first information processing thread to ensure stable and reliable operation of the entire block chain, in step S250, an adjustment instruction for adjusting the first thread parameter of the first information processing thread is generated based on the coefficient difference, which may specifically include the contents described in the following steps (1) - (5).

(1) When the coefficient difference value is judged to be in the set numerical range, calling an instruction resource packet; wherein the set value range is used for indicating that the first node equipment is in an adjustable state.

(2) When the first node equipment has the information list to be processed, analyzing the processing label of the information list to be processed.

(3) When the processing label of the to-be-processed information list is analyzed to be an emergency label or a label in a preset list, directly loading the to-be-processed information list corresponding to the label into a first resource pool of an instruction resource packet, or after the to-be-processed information list corresponding to the label is transmitted into the instruction resource packet, loading the to-be-processed information list corresponding to the label into the first resource pool of the instruction resource packet through the instruction resource packet.

(4) When the label of the to-be-processed information list is analyzed not to be the emergency label and not to be the label in the preset list, loading the to-be-processed information list corresponding to the label into a second resource pool of the instruction resource packet, so that the to-be-processed information list corresponding to the label cannot be transferred into the first resource pool.

(5) Extracting a resource code corresponding to the to-be-processed information list from the first resource pool or the second resource pool, generating interface request information corresponding to the first information processing thread based on the resource code, mapping an information field in the to-be-processed information list to an instruction set of the instruction resource packet to obtain an adjustment instruction corresponding to the information field in the instruction set, and encapsulating the adjustment instruction in the interface request information; wherein the interface request information is used to request instruction intervention from the first node device.

It can be understood that, through the content described in the above steps (1) - (5), the tag analysis of the to-be-processed information list can be performed according to the called instruction resource packet, so that the interface request information for instruction intervention with the first node device can be generated based on the analysis result, and the first node device is prevented from rejecting reception when issuing the adjustment instruction. Therefore, the first node equipment can be instructed to flexibly and accurately adjust the first information processing thread so as to ensure the stable and reliable operation of the whole block chain.

In an alternative embodiment, on the basis of the above steps S210 to S250, the following steps S260 to S290 may be further included.

Step S260, receiving response information fed back by the first node device based on the adjustment instruction, and analyzing the response information to obtain a plurality of instruction response results included in the response information.

Step S270, when the first process parameter adjustment progress of the first node equipment is judged not to reach the set progress based on the response information, determining a first result group and a second result group corresponding to the response information; the first result packet is used for receiving an instruction response result of the first node device that the adjustment is completed, and the second result packet is used for receiving an instruction response result of the first node device that the adjustment is not completed.

Step S280, determining a result association degree between each instruction response result of the response information in the second result group and each instruction response result of the response information in the first result group according to the instruction response result of the response information in the first result group and a result weight thereof, and adjusting the instruction response result of the response information in the second result group, which is similar to the instruction response result in the first result group, in the first result group.

Step S290, when the number of the instruction response results in the first result group does not reach the set number, modifying the adjustment instruction to obtain a target instruction, and then continuously sending the target instruction to the first node device.

Through the steps S260 to S290, the response information fed back by the first node device can be analyzed, so that the adjustment instruction is corrected when the first node device does not completely execute the adjustment instruction. In this way, adaptive adjustment of the information processing thread by the first node apparatus can be ensured.

On the basis of the above, please refer to fig. 6 in combination, a functional block diagram of an information processing apparatus 300 based on 5G and a block chain is also provided, where the information processing apparatus 300 includes:

a track determining module 310, configured to track each node device in a block chain, generate a first state log of each node device based on a first state parameter of each node device in a current time period and a second state parameter of the node device in a previous time period, and determine a state track of each node device according to the first state log; the state track is used for representing the change conditions of delay and error rate of information processing of the node equipment;

the track monitoring module 320 is configured to, in the process of monitoring each state track, acquire a track variation of each state track, and determine a second state log of each node device based on the track variation;

a parameter determining module 330, configured to, when it is determined that a first state trajectory of a first node device and a second state trajectory of a second node device have an intersection according to a second state log of the first node device, extract a first thread parameter of a first information processing thread of the first node device at the intersection and a second thread parameter of a second information processing thread of the second node device at the intersection;

a trellis determination module 340 for determining a first parameter trellis of the first thread parameter and a second parameter trellis of the second thread parameter; a first thread script of the first node device is encapsulated in the first parameter grid, a second thread script of the second node device is encapsulated in the second parameter grid, the first parameter grid and the second parameter grid respectively comprise a plurality of grid areas, and each grid area corresponds to at least one thread parameter set;

an instruction issuing module 350, configured to obtain a path difference coefficient between a first grid path of the first parameter grid and a second grid path of the second parameter grid by using real-time location information of a first track node corresponding to the first parameter grid in a first state track; and when the path difference coefficient is judged to be different from a preset difference coefficient, determining a coefficient difference value between the path difference coefficient and the preset difference coefficient, generating an adjusting instruction for adjusting a first thread parameter of the first information processing thread based on the coefficient difference value, and sending the adjusting instruction to the first node equipment so that the first node equipment modifies the first thread parameter according to the adjusting instruction.

Optionally, the instruction issuing module 350 is further configured to:

receiving response information fed back by the first node device based on the adjustment instruction, and analyzing the response information to obtain a plurality of instruction response results included in the response information;

determining a first result group and a second result group corresponding to the response information when the first process parameter adjustment progress of the first node device is judged not to reach the set progress based on the response information; the first result packet is used for recording the instruction response result of the first node device which completes the adjustment, and the second result packet is used for recording the instruction response result of the first node device which does not complete the adjustment;

determining a result association degree between each instruction response result of the response information in the second result group and each instruction response result of the response information in the first result group according to the instruction response result of the response information in the first result group and a result weight thereof, and adjusting the instruction response result of the response information in the second result group, which is similar to the instruction response result in the first result group, in the first result group;

and when the number of the instruction response results in the first result group does not reach the set number, correcting the adjustment instruction to obtain a target instruction, and then continuously sending the target instruction to the first node equipment.

Optionally, the trajectory determination module 310 is specifically configured to:

listing common parameter identifications in the first state parameter and the second state parameter;

for each common parameter identifier, sequentially adding a first parameter group corresponding to the common parameter identifier in the first state parameter and a second parameter group corresponding to the common parameter identifier in the second state parameter to a first preset list corresponding to the common parameter identifier;

adding a first residual parameter group in the first state parameters except for the first parameter group corresponding to the common parameter identifier into a second preset list corresponding to a first setting identifier, and adding a second residual parameter group in the second state parameters except for the second parameter group corresponding to the common parameter identifier into a third preset list corresponding to a second setting identifier;

integrating the first preset list, the second preset list and the third preset list according to the list weight values of the first preset list, the second preset list and the third preset list to obtain the first state log;

and summarizing the list units carrying the directional signatures in the first state log to obtain a list unit set, and connecting unit nodes corresponding to each list unit according to signature registration information of the directional signatures in the list unit set to obtain a state track corresponding to each node device.

Optionally, the trajectory monitoring module 320 is specifically configured to:

obtaining description information of each state track and a file source code corresponding to a visual script file of each state track; fusing the description information and the file source code according to a preset corresponding relation to obtain at least two target data packets; wherein, the target data packet contains a description value and a source code character which have an association relation;

acquiring distribution structure information of each target data packet and global variable information and local variable information corresponding to the target data packet, wherein the global variable information and the local variable information are part of the description information;

calculating a defect weight when each target data packet is fitted to a first state log corresponding to the state track according to the distribution structure information, the global variable information and the local variable information of each target data packet, and fitting the target data packet to a corresponding variable set in the description information to obtain mapping data of the target data packet in the variable set when the defect weight is converged relative to the state track;

and exporting the mapping data according to the variable grade of the mapping data in the variable set and the format of the target variable in the variable set to obtain multiple groups of track variable quantities, and arranging the multiple groups of track variable quantities according to the sequence of export moments to obtain the second state log.

Optionally, the parameter determining module 330 is specifically configured to:

respectively determining a first device delay of the first node device and a second device delay of the second node device;

determining a first set time period of the first node device at a target time corresponding to the intersection point according to the first device delay and determining a second set time period of the second node device at the target time corresponding to the intersection point according to the second device delay;

and respectively extracting a first thread parameter of the first information processing thread in the first set time interval and a second thread parameter of the second information processing thread in the second set time interval.

Optionally, the instruction issuing module 350 is specifically configured to:

acquiring grid distribution information of the first parameter grid and a grid type to which the first parameter grid belongs, and determining a plurality of target track nodes from the first state track according to the grid type; the node category of the target track node and the grid category belong to the same classification category;

generating a grid position sequence according to grid distribution information of the first parameter grid, wherein the grid position sequence comprises a sequence weight for representing grid density of the first parameter grid, an evaluation weight for evaluating grid stability of the first parameter grid and a distribution weight for recording grid saturation of the first parameter grid;

generating a node description vector according to the sequence weight, the evaluation weight and the distribution weight of the grid position sequence; when the cosine distance between the node description vector and the node vector of one target track node reaches a set value, determining the target track node as the first track node; calculating the calling frequency of the first track node in the first state track, determining a confidence coefficient corresponding to the calling frequency according to a preset mapping list, and determining the confidence coefficient as the confidence coefficient of the real-time position information of the first track node;

determining a comparison sequence of the first grid path and the second grid path according to the confidence, traversing and comparing the first grid path and the second grid path according to the comparison sequence, and recording the matching degree corresponding to the comparison result of each comparison in the traversing process; wherein the matching degree is used for characterizing the distance between each path node in the first grid path and the second grid path;

and distributing a weighting coefficient to each matching degree according to the confidence degree, and weighting the matching degrees based on the weighting coefficients to obtain the path difference coefficient.

Optionally, the instruction issuing module 350 is specifically configured to:

when the coefficient difference value is judged to be in the set numerical range, calling an instruction resource packet; wherein the set value range is used for indicating that the first node equipment is in an adjustable state;

when the first node equipment has a to-be-processed information list, analyzing a processing label of the to-be-processed information list;

when the processing label of the to-be-processed information list is analyzed to be an emergency label or a label in a preset list, directly loading the to-be-processed information list corresponding to the label into a first resource pool of an instruction resource packet, or after the to-be-processed information list corresponding to the label is transmitted into the instruction resource packet, loading the to-be-processed information list corresponding to the label into the first resource pool of the instruction resource packet through the instruction resource packet;

when the label of the to-be-processed information list is analyzed not to be the emergency label and not to be the label in the preset list, loading the to-be-processed information list corresponding to the label into a second resource pool of the instruction resource packet, so that the to-be-processed information list corresponding to the label cannot be transferred into the first resource pool;

extracting a resource code corresponding to the to-be-processed information list from the first resource pool or the second resource pool, generating interface request information corresponding to the first information processing thread based on the resource code, mapping an information field in the to-be-processed information list to an instruction set of the instruction resource packet to obtain an adjustment instruction corresponding to the information field in the instruction set, and encapsulating the adjustment instruction in the interface request information; wherein the interface request information is used to request instruction intervention from the first node device.

For the description of the above functional modules, reference is made to the description of the method shown in fig. 2, which is not described in detail here.

On the basis of the above, an information processing system based on 5G and a block chain is also provided, and the functionality of the system is described as follows.

An information processing system based on 5G and a block chain comprises a cloud computing server and a plurality of node devices which are in communication connection with each other, wherein the node devices form the block chain;

the cloud computing server is configured to:

acquiring a path difference coefficient of a first grid path of the first parameter grid and a second grid path of the second parameter grid by utilizing real-time position information of a first track node corresponding to the first parameter grid in a first state track; when the path difference coefficient is judged to be different from a preset difference coefficient, determining a coefficient difference value of the path difference coefficient and the preset difference coefficient, generating an adjusting instruction for adjusting a first thread parameter of the first information processing thread based on the coefficient difference value, and sending the adjusting instruction to the first node device;

the first node device is configured to:

and modifying the first thread parameter according to the adjusting instruction.

Optionally, the cloud computing server is specifically configured to:

Optionally, the cloud computing server is further configured to:

On the basis, the cloud computing server is further provided, and the cloud computing server comprises: a processor and a memory in communication with each other; the processor retrieves the computer program from the memory when running and executes the computer program to perform the above-mentioned method.

Further, a readable storage medium applied to a computer is provided, the readable storage medium is burned with a computer program, and the computer program realizes the method when running in a cloud computing server.

It will be understood that the present application is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the application is limited only by the appended claims.

Claims

1. The information processing method based on the 5G and the block chain is applied to a cloud computing server and comprises the following steps:

2. The information processing method based on 5G and the block chain as claimed in claim 1, wherein generating a first status log of each node device based on a first status parameter of the node device at a current time period and a second status parameter of the node device at a previous time period, and determining a status track of each node device according to the first status log comprises:

3. The information processing method based on 5G and the block chain as claimed in claim 1, wherein acquiring a track variation of each state track and determining the second state log of each node device based on the track variation comprises:

4. The 5G and blockchain based information processing method according to any one of claims 1 to 3, wherein extracting a first thread parameter of a first information processing thread of the first node device at the intersection and a second thread parameter of a second information processing thread of the second node device at the intersection includes:

5. The information processing method based on 5G and the block chain according to any one of claims 1 to 3, wherein obtaining the path difference coefficient of the first grid path of the first parameter grid and the second grid path of the second parameter grid by using the real-time position information of the first track node corresponding to the first parameter grid in the first state track comprises:

6. The information processing method based on 5G and block chain according to any one of claims 1 to 3, wherein generating an adjustment instruction for adjusting a first thread parameter of the first information processing thread based on the coefficient difference value comprises:

7. A cloud computing server, comprising: a processor and a memory in communication with each other; the processor retrieves the computer program from the memory when running and executes the computer program to perform the method of any of the preceding claims 1-6.

8. A readable storage medium applied to a computer, wherein the readable storage medium is burned with a computer program, and the computer program is used for implementing the method of any one of the above claims 1-6 when the computer program runs in a cloud computing server.