CN114969178A - Distributed data processing method and device - Google Patents
Distributed data processing method and device Download PDFInfo
- Publication number
- CN114969178A CN114969178A CN202210428827.7A CN202210428827A CN114969178A CN 114969178 A CN114969178 A CN 114969178A CN 202210428827 A CN202210428827 A CN 202210428827A CN 114969178 A CN114969178 A CN 114969178A
- Authority
- CN
- China
- Prior art keywords
- data
- request
- processing
- data processing
- distributed
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/25—Integrating or interfacing systems involving database management systems
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5061—Partitioning or combining of resources
- G06F9/5066—Algorithms for mapping a plurality of inter-dependent sub-tasks onto a plurality of physical CPUs
-
- H—ELECTRICITY
- H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
- H05K—PRINTED CIRCUITS; CASINGS OR CONSTRUCTIONAL DETAILS OF ELECTRIC APPARATUS; MANUFACTURE OF ASSEMBLAGES OF ELECTRICAL COMPONENTS
- H05K5/00—Casings, cabinets or drawers for electric apparatus
- H05K5/02—Details
- H05K5/0213—Venting apertures; Constructional details thereof
-
- H—ELECTRICITY
- H05—ELECTRIC TECHNIQUES NOT OTHERWISE PROVIDED FOR
- H05K—PRINTED CIRCUITS; CASINGS OR CONSTRUCTIONAL DETAILS OF ELECTRIC APPARATUS; MANUFACTURE OF ASSEMBLAGES OF ELECTRICAL COMPONENTS
- H05K5/00—Casings, cabinets or drawers for electric apparatus
- H05K5/02—Details
- H05K5/0217—Mechanical details of casings
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Microelectronics & Electronic Packaging (AREA)
- Data Mining & Analysis (AREA)
- Software Systems (AREA)
- Computing Systems (AREA)
- Computer And Data Communications (AREA)
Abstract
The invention discloses a distributed data processing method and a distributed data processing device, which comprises the following steps: a user side sends a request, and the request is converted into a data format through a data conversion module to generate request data; step two: identifying the request data in the distributed database through a region identification module to generate a data processing request; step three: sending a data processing request through a request sending module; step four: performing risk assessment on the data processing request through a risk assessment module; step five: the execution processing system passes the request data through the execution processor to work based on the evaluation result; step six: the client server receives the execution information. The request data sent by the user side is divided according to the region form, and the data processing is carried out in the divided region plate, so that the corresponding process can be executed on the management node of the corresponding region, the load of the management node is reduced, and the data processing efficiency is improved.
Description
Technical Field
The invention belongs to the technical field of information data processing, and particularly relates to a distributed data processing method and device.
Background
Distributed data processing means processing data by using a distributed computing technology. With the rapid expansion of data volume, the data volume faced by internet companies has reached PB level, and the traditional centralized data processing has gradually failed to adapt to the market demand, and meanwhile, the performance of personal computers has been greatly improved, and the popularity rate has also increased at a rapid pace, which makes it possible to assume that the processing power is distributed to all personal computers on the network, and then the concept of distributed computing has been proposed. Distributed computing is a concept opposite to centralized computing, and a distributed network is composed of a plurality of computers which can communicate with each other, each computer has a processor and a storage device, and huge computing tasks originally centralized on a single node are distributed to the computers in the distributed network in a load-balanced manner to be processed in parallel. For users, the distributed system is not different from other application systems and is an independent system, but from the view of the bottom physical equipment and the structural system, the distributed system is a huge and complex system and is formed by combining a plurality of independent computers. From a hardware perspective, the machines of a distributed system are independent, and different computers may be distributed around the world. Accessibility, transparency, openness, and extensibility are four major characteristics of a distributed system.
The following problems are presented for the distributed data processing scheme and apparatus of the prior art:
1. in the data processing scheme in the prior art, data information cannot be identified when data is processed, and when data which is not identified is subsequently processed, a management node cannot be divided into a plurality of processes to be executed in parallel, so that the service pressure of the management node is high, and the processing efficiency of distributed data is influenced;
2. in the data transmission process, some unexpected situations easily cause the situation of transmission blocking, and when the situation is processed, the same instruction can be re-sent only through the user side, and the repeated processing is needed, which is troublesome.
3. The target identification network is constructed to accurately identify the request data, so that the characteristic parameters are determined, and the request generation instruction is accurately generated according to the characteristic parameters, so that the data processing request is accurately determined, and the efficiency and the accuracy of distributed data processing are improved.
4. Through identifying and verifying the data processing request, the target data processing request is obtained, the processing task for processing the request data can be acquired more accurately, the processing task can be classified based on the service attribute, distributed data processing can be realized accurately, the data processing accuracy is improved, the processing report is encrypted, the safety of client data after distributed data processing is facilitated, and the privacy degree of the client data is increased.
Disclosure of Invention
The technical problem to be solved by the present invention is to overcome the existing defects, and provide a distributed data processing method and apparatus to solve the problems proposed in the background art.
In order to achieve the purpose, the invention provides the following technical scheme: the device comprises a data processing device body and a heat dissipation ventilating plate, wherein a data processing computer is arranged inside the data processing device body, a screen display is arranged on the outer surface of the data processing device body, a state display lamp and an adjusting switch are arranged at the lower end of the screen display, a device protective door is arranged on the outer side of the data processing device body, and the heat dissipation ventilating plate is arranged on the outer surface of the data processing device body.
Preferably, the surface of the heat dissipation ventilating plate is provided with a plurality of heat dissipation ventilating holes, and the lower end of the heat dissipation ventilating plate is provided with a plurality of data connection sockets.
A distributed data processing method, comprising the steps of:
the method comprises the following steps: a user side sends a request, and the request is converted into a data format through a data conversion module to generate request data;
step two: identifying the request data in a distributed database through a region identification module to generate a data processing request;
step three: sending the data processing request through a request sending module;
step four: performing risk assessment on the data processing request through a risk assessment module;
step five: the execution processing system passes the request data through the execution processor to work based on the evaluation result;
step six: the client server receives the execution information.
Preferably, in the first step, when the sending request is converted into a data format, the client sending request is temporarily stored in the data storage transfer station in a temporary data form.
Preferably, in the first step, the temporarily stored data is analyzed by the data analysis module during transmission, and if the data is abnormal, the data is processed by the gear-backing processing module to be transferred again.
Preferably, in the fourth step, the risk assessment system measures the input variable r (k) and the output variable y (k) at the time k of data transmission, and calculates the difference between the input variable r (k) and the output variable y (k) at the time k based on the input variable r (k) and the output variable y (k);
wherein e (k) is a difference between an input variable r (k) and an output variable y (k) at time k, and e (k) r (k) -y (k); x is the number of 1 (k)、x 2 (k)、x 3 (k) Expressing the values as stage influence values in the data transmission k moment, wherein e (k-1) is the difference value of an input variable r (k) and an output variable y (k) at the k-1 moment, and e (k-2) is the difference value of the input variable r (k) and the output variable y (k) at the k-2 moment;
calculating a risk coefficient of the data processing request based on a difference value of the input variable r (k) and the output variable y (k) at the moment k;
wherein u (k) is a risk coefficient of the data processing request at time k; phi is a p 、φ q 、φ d Is a proportional control coefficient; k is the current time; j is an initial time; u (k-1) denotes said at the time k-1A risk factor for the data processing request;
calculating a risk coefficient threshold;
wherein, K in the formula B Is the maximum value of the risk factor u (k); k A Is the minimum value of the risk factor u (k); b is the maximum error value of e (k); a is the minimum error value of e (k);
and completing the risk evaluation of the data processing request based on the risk coefficient and the risk coefficient threshold value.
Preferably, based on the risk factor threshold, calculating a control variable for u (k);
wherein ξ u(k) A control variable representing the risk coefficient u (k) at time k; xi u(k-1) A control variable representing the risk factor u (k-1) at time k-1; i represents the current variable influence factor; omega i (k) Representing the weight value corresponding to the current variable influence factor at the moment k; x is the number of i (k) The variable added value corresponding to the current variable influence factor at the moment k is represented;
and changing the risk coefficient based on the control variable of the u (k), and realizing the control of the risk coefficient based on the change result.
Preferably, in the fifth step, based on the evaluation result, the execution processing system controls the execution processor to work according to the request data under the execution condition, and finally, the execution processing result is fed back to the client server.
Preferably, in the second step, identifying the request data in a distributed database through a region identification module to generate a data processing request includes:
reading the request data based on the area identification module, and determining a data characteristic factor of the request data;
inputting the request data into the distributed database, and determining an identification node in the distributed database based on the data characteristic factor;
segmenting the request data according to the identification nodes to obtain a plurality of sub-identification data segments;
respectively reading segment head mark characters and segment tail mark characters of the plurality of sub-identification data segments, and meanwhile, determining network sub-nodes based on the segment head mark characters and the segment tail mark characters;
acquiring an incidence relation between the network sub-nodes, connecting the network sub-nodes based on the incidence relation, and generating a target data identification network in the distributed database according to a connection result;
mapping the sub-request data segments into the target identification network, and classifying the sub-request data segments by adopting a preset algorithm;
extracting a characteristic type sub-request data segment from the classification result, generating a sample sub-request data segment, and inputting the sample sub-request data segment into the target identification network again for identification;
outputting the identification result according to the distributed database, determining the characteristic parameters of the sample sub-request data segment according to the identification result, and determining a request generation instruction based on the characteristic parameters of the sample sub-request data segment;
generating the data processing request based on the request generation instruction.
Preferably, in the fifth step, the processing the request data by the execution processor includes:
based on the execution processing system reading the data processing request, determining the request type of the data processing request;
matching a verification mode for verifying the data processing request in a preset database in the execution processing system according to the request type of the data processing request;
extracting to-be-verified data of the data processing request based on the verification mode, verifying the to-be-verified data based on the verification mode, and generating feedback information data based on a verification result;
matching the feedback information data in a target parameter file, and judging whether invalid data exists in the feedback information data based on a matching result;
when the feedback information data is matched with the corresponding parameters in the target parameters, judging that invalid data does not exist in the feedback information data;
when the feedback information data does not match with the corresponding parameters in the target parameters, judging that invalid data exists in the feedback information, and optimizing the data processing request based on the invalid data to obtain a target data processing request;
determining a processing task for processing the request data based on the target data processing request;
acquiring the service attribute of the processing task, performing first division on the processing task according to the service attribute, generating a sub-processing task based on a first division result, and simultaneously determining a data processing identifier of the sub-processing task;
performing second division on the request data according to the data processing identifier, and generating target data to be processed corresponding to the sub-processing tasks based on a second division result, wherein the target data to be processed belongs to the request data;
distributing distributed processing nodes and comprehensive nodes in the execution processing system according to the sub-processing tasks and the target to be processed corresponding to the sub-processing tasks;
meanwhile, the target data to be processed are processed respectively based on the sub-processing tasks based on the distributed processing nodes, and sub-processing results are obtained;
respectively summarizing and updating the sub-processing results based on the comprehensive node, and generating a processing report for processing the request data based on the comprehensive node;
and encrypting the processing report according to the data processing identifier to generate an encrypted processing report, and transmitting the encrypted processing report to the client server.
Compared with the prior art, the invention provides a distributed data processing method and a distributed data processing device, which have the following beneficial effects:
1. the method identifies and distinguishes the request data sent by the user terminal through the area identification module in the data processing computer, compares the identified data with the data stored in the distributed database, so that the request data sent by the user terminal can be divided according to the area form, and data processing is performed in the divided area plates, so that corresponding processes can be executed on the management nodes of the corresponding areas, the load of the management nodes is reduced, and the data processing efficiency is improved;
2. according to the invention, the risk evaluation system is adopted to carry out risk evaluation calculation on the data processing request, and the specific risk coefficient range of the data processing request is calculated, so that the request sent by the user side can be monitored after the user side sends the request, the data request within the specific risk coefficient range can be subsequently processed, and the data request outside the specific risk coefficient range can be directly screened out, so that the interference of malicious data on distributed data processing can be prevented;
3. according to the invention, through the set gear-returning processing module, after the data analysis module analyzes the data, if the data transmission is abnormal, the abnormal information is fed back to the data storage transfer station through the gear-returning processing module again, and the temporarily stored data information is transmitted again through the data storage transfer station, so that the abnormal data information is transmitted again in the gear-returning mode each time, and the problem that the user side needs to send the same instruction again for cyclic processing is effectively solved.
4. The target identification network is constructed to accurately identify the request data, so that the characteristic parameters are determined, and the request generation instruction is accurately generated according to the characteristic parameters, so that the data processing request is accurately determined, and the efficiency and the accuracy of distributed data processing are improved.
5. Through identifying and verifying the data processing request, the target data processing request is obtained, the processing task for processing the request data can be acquired more accurately, the processing task can be classified based on the service attribute, distributed data processing can be realized accurately, the data processing accuracy is improved, the processing report is encrypted, the safety of client data after distributed data processing is facilitated, and the privacy degree of the client data is increased.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention without limiting the invention in which:
fig. 1 is a schematic front structural diagram of a distributed data processing method and apparatus according to the present invention;
FIG. 2 is a front view of a distributed data processing method and apparatus according to the present invention;
fig. 3 is a schematic back structure diagram of a distributed data processing method and apparatus according to the present invention;
FIG. 4 is a system flowchart of a region identification module in a distributed data processing method and apparatus according to the present invention;
FIG. 5 is a system flowchart of a request feedback module in the distributed data processing method and apparatus according to the present invention;
FIG. 6 is a system flow diagram of a risk assessment system in a distributed data processing method and apparatus according to the present invention;
FIG. 7 is a system flowchart of a logout processing module in the distributed data processing method and apparatus according to the present invention;
FIG. 8 is a system flow diagram of an execution processing system in a distributed data processing method and apparatus according to the present invention;
fig. 9 is a flowchart of a distributed data processing method according to the present invention.
In the figure: 1. a data processing apparatus body; 2. a split screen display; 3. a status display light; 4. a device protection door; 5. a heat dissipating and ventilating plate; 6. a heat dissipation vent; 7. a data connection socket; 8. and adjusting the switch.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1-8, the present invention provides the following technical solutions: a device of a distributed data processing method comprises a data processing device body 1 and a heat dissipation ventilating plate 5, a data processing computer is arranged inside the data processing device body 1, a sub-screen display 2 is arranged on the outer surface of the data processing device body 1, a state display lamp 3 and an adjusting switch 8 are arranged at the lower end of the sub-screen display 2, a device protective door 4 is arranged on the outer side of the data processing device body 1, and the heat dissipation ventilating plate 5 is arranged on the outer surface of the data processing device body 1.
In the present invention, preferably, the outer surface of the heat dissipation and ventilation plate 5 is provided with a plurality of heat dissipation and ventilation holes 6, and the lower end of the heat dissipation and ventilation plate 5 is provided with a plurality of data connection sockets 7.
A distributed data processing method, as shown in fig. 9, includes the steps of:
the method comprises the following steps: a user side sends a request, and the request is converted into a data format through a data conversion module to generate request data;
step two: identifying the request data in a distributed database through a region identification module to generate a data processing request;
step three: sending the data processing request through a request sending module;
step four: performing risk assessment on the data processing request through a risk assessment module;
step five: the execution processing system passes the request data through the execution processor to work based on the evaluation result;
step six: the client server receives the execution information.
In the present invention, preferably, in the first step, when the sending request is converted into a data format, the sending request sent by the user side is temporarily stored in the data storage transfer station in a temporary data form.
In the present invention, preferably, in the first step, the temporarily stored data is analyzed by the data analysis module during transmission, and if there is an abnormality in the data, the data is processed by the log-out processing module to log out for retransmission.
In the present invention, preferably, in step four, the risk assessment system measures the input variable r (k) and the output variable y (k) at the time of data transmission k, and calculates the difference between the input variable r (k) and the output variable y (k) at the time of k based on the input variable r (k) and the output variable y (k);
wherein e (k) is a difference between an input variable r (k) and an output variable y (k) at time k, and e (k) r (k) -y (k); x is the number of 1 (k)、x 2 (k)、x 3 (k) Expressing the influence value in a stage in the data transmission k moment, wherein e (k-1) is the difference value of an input variable r (k) and an output variable y (k) at the k-1 moment, and e (k-2) is the difference value of the input variable r (k) and the output variable y (k) at the k-2 moment;
calculating a risk coefficient of the data processing request based on a difference between the input variable r (k) and the output variable y (k) at the time k;
wherein u (k) is a risk coefficient of the data processing request at time k; phi is a p 、φ q 、φ d Is a proportional control coefficient; k is the current time; j is an initial time; u (k-1) represents a risk factor of the data processing request at time k-1;
calculating a risk coefficient threshold;
wherein, K in the formula B Is the maximum value of the risk factor u (k); k A Is the minimum value of the risk factor u (k); b is the maximum error value of e (k); a is the minimum error value of e (k);
and completing the risk evaluation of the data processing request based on the risk coefficient and the risk coefficient threshold value.
In the present invention, it is preferable that the control variable of u (k) is calculated based on the risk coefficient threshold;
wherein ξ u(k) A control variable representing the risk coefficient u (k) at time k; xi shape u(k-1) A control variable representing the risk factor u (k-1) at time k-1; i represents the current variable influence factor; omega i (k) Representing the weight value corresponding to the current variable influence factor at the moment k; x is the number of i (k) The variable added value corresponding to the current variable influence factor at the moment k is represented;
and changing the risk coefficient based on the control variable of the u (k), and realizing the control of the risk coefficient based on the change result.
The value of the output control variable u (K) is more accurate through the risk coefficient K of the change of the real-time error e (K).
In the present invention, preferably, in step five, based on the evaluation result, the execution processing system controls the execution processor to operate according to the request data under the execution condition, and finally, the execution processing result is fed back to the client server.
The first embodiment is as follows:
a distributed data processing method and device, including data processing device body 1 and heat dissipation ventilating board 5, there are data processing computers in the body of the data processing device 1, the external surface of the body of the data processing device 1 has a sub-screen display 2, the inferior extremity of the sub-screen display 2 has status display lamps 3 and regulating switches 8, there are device protective doors 4 outside the body of the data processing device 1, the external surface of the body of the data processing device 1 has heat dissipation ventilating boards 5, the external surface of the heat dissipation ventilating board 5 has a plurality of heat dissipation vents 6, the inferior extremity of the heat dissipation ventilating board 5 has a plurality of data connection sockets 7, the invention sends the request data to the user end to discern through the regional identification module in the data processing computer, compare the data after discerning with data stored inside the distributed database, thus can send the request data to the user end and divide according to the regional form, and performing data processing in the divided regional boards, and executing corresponding processes on the management nodes of the corresponding regions in such a way, so that the load of the management nodes is reduced, and the data processing efficiency is increased.
Example two:
a distributed data processing method and device, including data processing device body 1 and heat dissipation ventilating board 5, there are data processing computers in the body of the data processing device 1, the external surface of the body of the data processing device 1 has a sub-screen display 2, the inferior extremity of the sub-screen display 2 has status display lamps 3 and regulating switches 8, there are device protective doors 4 outside the body of the data processing device 1, the external surface of the body of the data processing device 1 has heat dissipation ventilating boards 5, the external surface of the heat dissipation ventilating board 5 has a plurality of heat dissipation vents 6, the inferior extremity of the heat dissipation ventilating board 5 has a plurality of data connection sockets 7, the invention sends the request data to the user end to discern through the regional identification module in the data processing computer, compare the data after discerning with data stored inside the distributed database, thus can send the request data to the user end and divide according to the regional form, the data processing is carried out in the divided area plates, and in this way, corresponding processes can be executed on the management nodes of the corresponding areas, so that the load of the management nodes is reduced, and the data processing efficiency is increased.
In the invention, preferably, a user side sends a request, and the request is converted into a data format through a data conversion module; distinguishing and identifying the request data in a distributed database through a region identification module; sending a data processing request through a request sending module; performing risk assessment on the data processing request through a risk assessment system; the execution processing system works the request data through the execution processor; the client server receives the execution information, during data conversion, the client sends a request to be temporarily stored in a data storage transfer station in a temporary data form, the temporarily stored data is analyzed by the data analysis module during transmission, the data is processed by the gear-reversing processing module for gear-reversing retransmission if the data is abnormal, after the data analysis module analyzes the data, if the data is transmitted in an abnormal condition, the abnormal information is fed back to the data storage transfer station again by the gear-reversing processing module, and the temporarily stored data information is transmitted again by the data storage transfer, so that the abnormal data information is transmitted again in the gear-reversing form, and the problem that the client needs to send the same command again for cyclic processing is effectively solved.
Example three:
a distributed data processing method and device, including data processing device body 1 and heat dissipation ventilating board 5, there are data processing computers in the body of the data processing device 1, the external surface of the body of the data processing device 1 has a sub-screen display 2, the inferior extremity of the sub-screen display 2 has status display lamps 3 and regulating switches 8, there are device protective doors 4 outside the body of the data processing device 1, the external surface of the body of the data processing device 1 has heat dissipation ventilating boards 5, the external surface of the heat dissipation ventilating board 5 has a plurality of heat dissipation vents 6, the inferior extremity of the heat dissipation ventilating board 5 has a plurality of data connection sockets 7, the invention sends the request data to the user end to discern through the regional identification module in the data processing computer, compare the data after discerning with data stored inside the distributed database, thus can send the request data to the user end and divide according to the regional form, and performing data processing in the divided regional boards, and executing corresponding processes on the management nodes of the corresponding regions in such a way, so that the load of the management nodes is reduced, and the data processing efficiency is increased.
In the invention, preferably, a user side sends a request, and the request is converted into a data format through a data conversion module; distinguishing and identifying the request data in a distributed database through a region identification module; sending a data processing request through a request sending module; performing risk assessment on the data processing request through a risk assessment system; the execution processing system works the request data through the execution processor; the client server receives the execution information, during data conversion, the client sends a request to be temporarily stored in a data storage transfer station in a temporary data form, the temporarily stored data is analyzed by the data analysis module during transmission, the data is processed by the gear-reversing processing module for gear-reversing retransmission if the data is abnormal, after the data analysis module analyzes the data, if the data is transmitted in an abnormal condition, the abnormal information is fed back to the data storage transfer station again by the gear-reversing processing module, and the temporarily stored data information is transmitted again by the data storage transfer, so that the abnormal data information is transmitted again in the gear-reversing form, and the problem that the client needs to send the same command again for cyclic processing is effectively solved.
Example four:
a distributed data processing method and device, including data processing device body 1 and heat dissipation ventilating board 5, there are data processing computers in the body of the data processing device 1, the external surface of the body of the data processing device 1 has a sub-screen display 2, the inferior extremity of the sub-screen display 2 has status display lamps 3 and regulating switches 8, there are device protective doors 4 outside the body of the data processing device 1, the external surface of the body of the data processing device 1 has heat dissipation ventilating boards 5, the external surface of the heat dissipation ventilating board 5 has a plurality of heat dissipation vents 6, the inferior extremity of the heat dissipation ventilating board 5 has a plurality of data connection sockets 7, the invention sends the request data to the user end to discern through the regional identification module in the data processing computer, compare the data after discerning with data stored inside the distributed database, thus can send the request data to the user end and divide according to the regional form, the data processing is carried out in the divided area plates, and in this way, corresponding processes can be executed on the management nodes of the corresponding areas, so that the load of the management nodes is reduced, and the data processing efficiency is increased.
In the invention, preferably, a user side sends a request, and the request is converted into a data format through a data conversion module; distinguishing and identifying the request data in a distributed database through a region identification module; sending a data processing request through a request sending module; performing risk assessment on the data processing request through a risk assessment system; the execution processing system works the request data through the execution processor; the client server receives the execution information, during data conversion, the client sends a request to be temporarily stored in a data storage transfer station in a temporary data form, the temporarily stored data is analyzed by the data analysis module during transmission, the data is processed by the gear-reversing processing module for gear-reversing retransmission if the data is abnormal, after the data analysis module analyzes the data, if the data is transmitted in an abnormal condition, the abnormal information is fed back to the data storage transfer station again by the gear-reversing processing module, and the temporarily stored data information is transmitted again by the data storage transfer, so that the abnormal data information is transmitted again in the gear-reversing form, and the problem that the client needs to send the same command again for cyclic processing is effectively solved.
In the present invention, preferably, in step four, after obtaining the result of the e (k) difference, calculating the actually obtained risk coefficient according to the formula
In the formula, kI is an integral control coefficient; kP is a proportional control coefficient; kD is the differential control coefficient, k p 、k d The risk evaluation system is adopted to carry out risk evaluation calculation on the data processing request, and the specific risk coefficient range of the data processing request is calculated, so that the client can monitor the request sent by the client after the client sends the request, and the client is in the specific windData requests within the risk coefficient range can be subsequently processed, and data requests outside the specific risk coefficient range are directly screened out, so that interference of malicious data on distributed data processing can be prevented.
In the present invention, preferably, in step four, the risk assessment system measures the input variables r (k) and the output variables at the time of data transmission k, and calculates the input variables and the output variables according to the formula
Where e (k) is the difference between the input variable r (k) and the output variable y (k) at time k, x 1 、x 2 、x 3 The method is characterized in that before a plurality of stage influence values in the data transmission k moment and calculating influence data, the numerical result of the input variable e (k) is calculated according to the following calculation formula:
the invention adopts a risk assessment system to carry out risk assessment calculation on data processing requests, calculates a specific risk coefficient range of the data processing requests, monitors the requests sent by a user side after the user side sends the requests, can carry out subsequent processing on the data requests in the specific risk coefficient range, and directly screens out the data requests outside the specific risk coefficient range, thereby preventing malicious data from interfering distributed data processing.
Example five:
in the second step, identifying the request data in the distributed database through the region identification module to generate the data processing request includes:
reading the request data based on the area identification module, and determining a data characteristic factor of the request data;
inputting the request data into the distributed database, and determining an identification node in the distributed database based on the data characteristic factor;
segmenting the request data according to the identification nodes to obtain a plurality of sub-identification data segments;
respectively reading segment head mark characters and segment tail mark characters of the plurality of sub-identification data segments, and meanwhile, determining network sub-nodes based on the segment head mark characters and the segment tail mark characters;
acquiring an incidence relation between the network sub-nodes, connecting the network sub-nodes based on the incidence relation, and generating a target data identification network in the distributed database according to a connection result;
mapping the sub-request data segments into the target identification network, and classifying the sub-request data segments by adopting a preset algorithm;
extracting a characteristic type sub-request data segment from the classification result, generating a sample sub-request data segment, and inputting the sample sub-request data segment into the target identification network again for identification;
outputting the identification result according to the distributed database, determining the characteristic parameters of the sample sub-request data segment according to the identification result, and determining a request generation instruction based on the characteristic parameters of the sample sub-request data segment;
generating the data processing request based on the request generation instruction.
In this embodiment, the data characteristic factor may be a factor for characterizing data types, data attributes, and the like of the requested data, so that the identified nodes in the distributed database may be accurately determined.
In this embodiment, the identification node is based on the presence in the distributed database for identifying the requested data in segments.
In this embodiment, the network child node is determined according to the segment header tag and the segment bit tag of the sub-request data segment, and is used to characterize the constituent node of the sub-request data segment in the target data identification network.
In this embodiment, the association relationship may be, for example, communication addresses of different network sub-nodes.
In this embodiment, the preset algorithm may be a clustering algorithm.
In this embodiment, the characteristic type sub-request data segment may be a sample sub-request data segment extracted from each type of sub-request data segment based on the classification result.
In this embodiment, the characteristic parameter may be an identification parameter in the sub-request data segment, which may be used to characterize the need to process the request data.
In this embodiment, the request generation instruction is determined based on the characteristic parameter to generate the data processing request.
In this embodiment, the data processing request may be a request for distributed processing of the requested data.
The beneficial effects of the above technical scheme are: the target identification network is constructed to accurately identify the request data, so that the characteristic parameters are determined, and the request generation instruction is accurately generated according to the characteristic parameters, so that the data processing request is accurately determined, and the efficiency and the accuracy of distributed data processing are improved.
Example six:
in step five, the processing of the request data by the execution processor includes:
based on the execution processing system reading the data processing request, determining the request type of the data processing request;
matching a verification mode for verifying the data processing request in a preset database in the execution processing system according to the request type of the data processing request;
extracting to-be-verified data of the data processing request based on the verification mode, verifying the to-be-verified data based on the verification mode, and generating feedback information data based on a verification result;
matching the feedback information data in a target parameter file, and judging whether invalid data exists in the feedback information data based on a matching result;
when the feedback information data is matched with the corresponding parameters in the target parameters, judging that invalid data does not exist in the feedback information data;
when the feedback information data does not match with the corresponding parameters in the target parameters, judging that invalid data exists in the feedback information, and optimizing the data processing request based on the invalid data to obtain a target data processing request;
determining a processing task for processing the request data based on the target data processing request;
acquiring the service attribute of the processing task, performing first division on the processing task according to the service attribute, generating a sub-processing task based on a first division result, and simultaneously determining a data processing identifier of the sub-processing task;
performing second division on the request data according to the data processing identifier, and generating target data to be processed corresponding to the sub-processing tasks based on a second division result, wherein the target data to be processed belongs to the request data;
distributing distributed processing nodes and comprehensive nodes in the execution processing system according to the sub-processing tasks and the target to be processed corresponding to the sub-processing tasks;
meanwhile, the target data to be processed are processed respectively based on the sub-processing tasks based on the distributed processing nodes, and sub-processing results are obtained;
respectively summarizing and updating the sub-processing results based on the comprehensive node, and generating a processing report for processing the request data based on the comprehensive node;
and encrypting the processing report according to the data processing identifier to generate an encrypted processing report, and transmitting the encrypted processing report to the client server.
In this embodiment, the request type may be a data processing job form that needs to be performed based on the data processing request, such as performing distributed data processing.
In this embodiment, the verification method may be a method of identifying and verifying the data processing request, and is used to determine whether invalid data exists in the data processing request, so as to affect efficiency and accuracy of performing distributed processing on the requested data.
In this embodiment, the data to be verified is data that needs to be verified after the data processing request is extracted based on the verification mode.
In this embodiment, the feedback information data may be feedback information determined after the data to be verified is verified, and the feedback information data may be represented by binary or hexadecimal.
In this embodiment, the target parameter may be a parameter used to match the feedback information data, for example: when the feedback information data is binary data, only two parameters of 0 and 1 exist in the target parameter, and therefore, when data other than 0 and 1 exists in the feedback information data, the data is determined to be invalid data.
In this embodiment, the invalid data is the data not corresponding to the target parameter
In this embodiment, the target data processing request is a target data processing request determined by optimizing the target data processing request when invalid data exists.
In this embodiment, the service attribute may be a destination to be finally processed in the processing task.
In this embodiment, the first division is to divide the processing task according to the service attribute, and determine the sub-processing task.
In this embodiment, the data processing identifier of the sub-processing task may be used to mark the kind of requested data to be processed.
In this embodiment, the second division is to divide the request data according to the data processing identifier, so as to determine that one sub-processing task corresponds to one type of request data.
In this embodiment, the distributed processing node may be a processing node corresponding to a sub-processing task processing a type of request data.
In this embodiment, the synthesis node is a node used to summarize data processed by each distributed processing node.
In this embodiment, after the distributed processing nodes and the integrated nodes are distributed in the execution processing system, the method further includes:
determining communication topology among different distributed processing nodes, and determining a communication link between each distributed processing node and the summary node in the communication topology structure;
when the distributed processing nodes process the request data, calculating the similarity between the distributed processing nodes and the summary node based on the distributed processing nodes and the communication links between each distributed processing node and the summary node;
wherein D represents the similarity between the distributed processing node and the summary node; i represents the current distributed processing node; n represents the total number of the distributed processing nodes; m is i Representing a data communication link corresponding to the current distributed processing node; j represents a current communication link from a current distributed processing node to the summary node; q. q.s i,j Representing the data processing transmission state of the current distributed processing node in the current communication link; p (z) represents a probability density function corresponding to the distributed processing nodes; s (z) a probability density function representing the summary nodes;
analyzing the similarity between the distributed processing nodes and the summarizing nodes according to a following target formula, and determining the privacy protection degree of the distributed processing nodes and the summarizing nodes in the process of processing the request data;
wherein β represents the distributed processing node andthe privacy protection degree of the summary node in the process of processing the request data; d Z Representing a reference similarity;
based on the target formula, when beta is determined to be 0, determining that the privacy protection degree of the distributed processing nodes and the summary nodes in the process of processing the request data is low;
when the beta is 1, judging that the privacy protection degree of the distributed processing nodes and the summary nodes in the process of processing the request data is high;
when the privacy protection degree of the distributed processing nodes and the summary nodes in the process of processing the request data is low, Gaussian noise is obtained to interfere the distributed processing nodes and the summary nodes, and the privacy protection degree of the request data in the process of processing the request data is increased based on the interference result.
In the above, when the similarity between the distributed processing node and the summary node is higher, it is more difficult for a privacy attacker to distinguish the difference of data processing, so that the requested data sent by the user end is better protected, that is, the privacy protection degree of the distributed processing node and the summary node in the process of processing the requested data is higher.
The reference similarity is set in advance and is used for measuring the privacy protection degree of the distributed processing nodes and the summary nodes in the process of processing the request data.
The beneficial effects of the above technical scheme are: through identifying and verifying the data processing request, the target data processing request is obtained, the processing task for processing the request data can be acquired more accurately, the processing task can be classified based on the service attribute, distributed data processing can be realized accurately, the data processing accuracy is improved, the processing report is encrypted, the safety of client data after distributed data processing is facilitated, and the privacy degree of the client data is increased.
Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that changes, modifications, substitutions and alterations can be made in these embodiments without departing from the principles and spirit of the invention, the scope of which is defined in the appended claims and their equivalents.
Claims (10)
1. The invention provides a distributed data processing method, which is characterized by comprising the following steps: the method comprises the following steps:
the method comprises the following steps: a user side sends a request, and the request is converted into a data format through a data conversion module to generate request data;
step two: identifying the request data in a distributed database through a region identification module to generate a data processing request;
step three: sending the data processing request through a request sending module;
step four: performing risk assessment on the data processing request through a risk assessment module;
step five: the execution processing system passes the request data through the execution processor to work based on the evaluation result;
step six: the client server receives the execution information.
2. The distributed data processing method according to claim 1, wherein said step one includes:
when the sending request is converted into a data format, the sending request of the user side is temporarily stored in a data storage transfer station in a temporary data form.
3. A distributed data processing method according to claim 1, characterized in that: in the first step, the temporarily stored data is analyzed by the data analysis module during transmission, and if the data is abnormal, the data is processed by the gear-backing processing module to be transferred again.
4. A distributed data processing method according to claim 1, characterized in that: in the fourth step, the method comprises the following steps:
measuring an input variable r (k) and an output variable y (k) at the moment k of data transmission by a risk assessment system, and calculating a difference value of the input variable r (k) and the output variable y (k) at the moment k based on the input variable r (k) and the output variable y (k);
wherein e (k) is a difference between an input variable r (k) and an output variable y (k) at time k, and e (k) r (k) -y (k); x is the number of 1 (k)、x 2 (k)、x 3 (k) Expressing the values as stage influence values in the data transmission k moment, wherein e (k-1) is the difference value of an input variable r (k) and an output variable y (k) at the k-1 moment, and e (k-2) is the difference value of the input variable r (k) and the output variable y (k) at the k-2 moment;
calculating a risk coefficient of the data processing request based on a difference between the input variable r (k) and the output variable y (k) at the time k;
wherein u (k) is a risk coefficient of the data processing request at time k; phi is a p 、φ q 、φ d Is a proportional control coefficient; k is the current time; j is an initial time; u (k-1) represents a risk factor of the data processing request at time k-1;
calculating a risk coefficient threshold;
wherein, K in the formula B Is the maximum value of the risk factor u (k); k A Is the minimum value of the risk factor u (k); b is the maximum error value of e (k); a is the minimum error value of e (k);
and completing the risk evaluation of the data processing request based on the risk coefficient and the risk coefficient threshold value.
5. A distributed data processing method according to claim 4, wherein based on said risk factor threshold, a control variable for u (k) is calculated;
wherein ξ u(k) A control variable representing the risk coefficient u (k) at time k; xi u(k-1) A control variable representing the risk factor u (k-1) at time k-1; i represents the current variable influence factor; omega i (k) Representing the weight value corresponding to the current variable influence factor at the moment k; x is the number of i (k) The variable added value corresponding to the current variable influence factor at the moment k is represented;
and changing the risk coefficient based on the control variable of the u (k), and realizing the control of the risk coefficient based on the change result.
6. A distributed data processing method according to claim 1, characterized in that: and in the fifth step, based on the evaluation result, the execution processing system controls the execution processor to work according to the request data under the execution condition, and finally the execution processing result is fed back to the client server.
7. The distributed data processing method according to claim 1, wherein in the second step, the identifying the request data in the distributed database by the region identification module to generate the data processing request includes:
reading the request data based on the area identification module, and determining a data characteristic factor of the request data;
inputting the request data into the distributed database, and determining an identification node in the distributed database based on the data characteristic factor;
segmenting the request data according to the identification nodes to obtain a plurality of sub-identification data segments;
respectively reading segment head mark characters and segment tail mark characters of the plurality of sub-identification data segments, and meanwhile, determining network sub-nodes based on the segment head mark characters and the segment tail mark characters;
acquiring an incidence relation between the network sub-nodes, connecting the network sub-nodes based on the incidence relation, and generating a target data identification network in the distributed database according to a connection result;
mapping the sub-request data segments into the target identification network, and classifying the sub-request data segments by adopting a preset algorithm;
extracting a characteristic type sub-request data segment from the classification result, generating a sample sub-request data segment, and inputting the sample sub-request data segment into the target identification network again for identification;
outputting the identification result according to the distributed database, determining the characteristic parameters of the sample sub-request data segment according to the identification result, and determining a request generation instruction based on the characteristic parameters of the sample sub-request data segment;
generating the data processing request based on the request generation instruction.
8. The distributed data processing method according to claim 1, wherein in step five, the processing of the request data by the execution processor includes:
based on the execution processing system reading the data processing request, determining the request type of the data processing request;
matching a verification mode for verifying the data processing request in a preset database in the execution processing system according to the request type of the data processing request;
extracting to-be-verified data of the data processing request based on the verification mode, verifying the to-be-verified data based on the verification mode, and generating feedback information data based on a verification result;
matching the feedback information data in a target parameter file, and judging whether invalid data exists in the feedback information data based on a matching result;
when the feedback information data is matched with the corresponding parameters in the target parameters, judging that invalid data does not exist in the feedback information data;
when the feedback information data does not match with the corresponding parameters in the target parameters, judging that invalid data exists in the feedback information, and optimizing the data processing request based on the invalid data to obtain a target data processing request;
determining a processing task for processing the request data based on the target data processing request;
acquiring the service attribute of the processing task, performing first division on the processing task according to the service attribute, generating a sub-processing task based on a first division result, and simultaneously determining a data processing identifier of the sub-processing task;
performing second division on the request data according to the data processing identifier, and generating target data to be processed corresponding to the sub-processing tasks based on a second division result, wherein the target data to be processed belongs to the request data;
distributing distributed processing nodes and comprehensive nodes in the execution processing system according to the sub-processing tasks and the target to be processed corresponding to the sub-processing tasks;
meanwhile, the target data to be processed are processed respectively based on the sub-processing tasks based on the distributed processing nodes, and sub-processing results are obtained;
respectively summarizing and updating the sub-processing results based on the comprehensive node, and generating a processing report for processing the request data based on the comprehensive node;
and encrypting the processing report according to the data processing identifier to generate an encrypted processing report, and transmitting the encrypted processing report to the client server.
9. A device for a distributed data processing method according to any one of claims 1 to 8, comprising: the data processing device comprises a data processing device body (1) and a heat dissipation ventilating plate (5);
the data processing device comprises a data processing device body (1), wherein a data processing computer is arranged inside the data processing device body (1), a screen display (2) is arranged on the outer surface of the data processing device body (1), a state display lamp (3) and an adjusting switch (8) are arranged at the lower end of the screen display (2), a device protective door (4) is arranged on the outer side of the data processing device body (1), and a heat dissipation ventilating plate (5) is arranged on the outer surface of the data processing device body (1).
10. A distributed data processing method apparatus according to claim 9, wherein: the surface of the heat dissipation ventilating plate (5) is provided with a plurality of heat dissipation ventilating holes (6), and the lower end of the heat dissipation ventilating plate (5) is provided with a plurality of data connection sockets (7).
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210428827.7A CN114969178B (en) | 2022-04-22 | 2022-04-22 | Distributed data processing method and device |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210428827.7A CN114969178B (en) | 2022-04-22 | 2022-04-22 | Distributed data processing method and device |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN114969178A true CN114969178A (en) | 2022-08-30 |
| CN114969178B CN114969178B (en) | 2023-03-28 |
Family
ID=82979332
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210428827.7A Active CN114969178B (en) | 2022-04-22 | 2022-04-22 | Distributed data processing method and device |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN114969178B (en) |
Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN207503137U (en) * | 2017-12-19 | 2018-06-15 | 杨淑珍 | A kind of computer cabinet |
| CN109636607A (en) * | 2018-12-18 | 2019-04-16 | 平安科技（深圳）有限公司 | Business data processing method, device and computer equipment based on model deployment |
| CN110555779A (en) * | 2019-07-25 | 2019-12-10 | 深圳壹账通智能科技有限公司 | data processing method, data processing device, computer equipment and storage medium |
| CN111597160A (en) * | 2020-04-21 | 2020-08-28 | 中国人民财产保险股份有限公司 | Distributed database system, distributed data processing method and device |
| US20210133301A1 (en) * | 2019-11-06 | 2021-05-06 | Shuang Chen | System and Method for Enhancing IT System Access Security with Smart Cloud Service |
| WO2021217986A1 (en) * | 2020-04-30 | 2021-11-04 | 平安科技（深圳）有限公司 | Distributed message transmission method and apparatus, computer device and storage medium |
| CN113946862A (en) * | 2021-10-14 | 2022-01-18 | 中国平安财产保险股份有限公司 | Data processing method, device and equipment and readable storage medium |
| WO2022042301A1 (en) * | 2020-08-26 | 2022-03-03 | 腾讯科技（深圳）有限公司 | Data processing method and apparatus, smart device and storage medium |
-
2022
- 2022-04-22 CN CN202210428827.7A patent/CN114969178B/en active Active
Patent Citations (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN207503137U (en) * | 2017-12-19 | 2018-06-15 | 杨淑珍 | A kind of computer cabinet |
| CN109636607A (en) * | 2018-12-18 | 2019-04-16 | 平安科技（深圳）有限公司 | Business data processing method, device and computer equipment based on model deployment |
| CN110555779A (en) * | 2019-07-25 | 2019-12-10 | 深圳壹账通智能科技有限公司 | data processing method, data processing device, computer equipment and storage medium |
| US20210133301A1 (en) * | 2019-11-06 | 2021-05-06 | Shuang Chen | System and Method for Enhancing IT System Access Security with Smart Cloud Service |
| CN111597160A (en) * | 2020-04-21 | 2020-08-28 | 中国人民财产保险股份有限公司 | Distributed database system, distributed data processing method and device |
| WO2021217986A1 (en) * | 2020-04-30 | 2021-11-04 | 平安科技（深圳）有限公司 | Distributed message transmission method and apparatus, computer device and storage medium |
| WO2022042301A1 (en) * | 2020-08-26 | 2022-03-03 | 腾讯科技（深圳）有限公司 | Data processing method and apparatus, smart device and storage medium |
| CN113946862A (en) * | 2021-10-14 | 2022-01-18 | 中国平安财产保险股份有限公司 | Data processing method, device and equipment and readable storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN114969178B (en) | 2023-03-28 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11294744B2 (en) | Ensemble risk assessment method for networked devices | |
| US10884383B2 (en) | Advanced control systems for machines | |
| US20200211721A1 (en) | METHOD AND APPARATUS FOR DETERMINING AN IDENTITY OF AN UNKNOWN INTERNET-OF-THINGS (IoT) DEVICE IN A COMMUNICATION NETWORK | |
| CN112714093B (en) | Account abnormity detection method, device, system and storage medium | |
| WO2021184995A1 (en) | Data processing method and data standard management system | |
| KR101831604B1 (en) | Method for transmitting data, method for authentication, and server for executing the same | |
| CN111444072B (en) | Abnormality identification method and device for client, computer equipment and storage medium | |
| TW200849917A (en) | Detecting method of network invasion | |
| CN108632269A (en) | Detecting method of distributed denial of service attacking based on C4.5 decision Tree algorithms | |
| WO2022134911A1 (en) | Diagnosis method and apparatus, and terminal and storage medium | |
| KR102433831B1 (en) | System and method for supporting decision for security management | |
| CN116723136B (en) | Network data detection method applying FCM clustering algorithm | |
| CN108718298A (en) | Connect flow rate testing methods and device outside a kind of malice | |
| WO2022001924A1 (en) | Knowledge graph construction method, apparatus and system and computer storage medium | |
| CN113127904B (en) | Intelligent optimization system and method for access control strategy | |
| CN114969178B (en) | Distributed data processing method and device | |
| CN117834123B (en) | Industrial Internet equipment safety state early warning method based on encrypted data | |
| CN115174193B (en) | Data security intrusion detection method, device and equipment based on GA algorithm | |
| Sang et al. | Toward IoT device fingerprinting from proprietary protocol traffic via key-blocks aware approach | |
| US11601353B2 (en) | Device identification apparatus and method based on network behavior | |
| KR102665210B1 (en) | A anomaly detection system for cloud device based on xai and a method for anomaly detection | |
| CN114666282A (en) | 5G flow identification method and device based on machine learning | |
| CN112672301B (en) | Network data aggregation method for wireless sensor | |
| CN117938258B (en) | Intelligent adjusting method for working mode of optical module | |
| CN114679386B (en) | Cloud-edge cooperative Internet of things device role judgment and management method, system and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20230308 Address after: Room 207, Building 7, Phase I, Golden Olive City, Erdao District, Changchun City, Jilin Province, 130031 Applicant after: Zhizhu Technology (Jilin Province) Co.,Ltd. Address before: 510000 room 1809, No. 5, Huangpu East Road, Huangpu District, Guangzhou City, Guangdong Province (for office use only) Applicant before: Guangzhou master Ming Information Service Co.,Ltd. |
|
| TA01 | Transfer of patent application right | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |