CN111240938A - Data congestion processing method and device based on face-brushing payment - Google Patents
Data congestion processing method and device based on face-brushing payment Download PDFInfo
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Abstract
The application provides a data congestion processing method and device based on face-brushing payment, which are applied to the technical field of quick payment, and the method comprises the following steps: the face brushing payment equipment is subjected to configuration permission butt joint with the database, the butt joint of the face brushing payment equipment and the database is realized, a face picture of a client acquired by the face brushing payment equipment can be uploaded to the database, so that a corresponding ID account is determined, and deduction is finally realized; acquiring a face picture of a client; after the face picture is obtained, monitoring the current CPU occupation ratio of the database, and determining an ID account pre-associated with the face picture from the database by adopting a corresponding preset rule according to the CPU occupation ratio, so that the face brushing payment equipment and the database do not need to participate in an intermediate server, and the problem that the interactive data transmission speed of a user is reduced due to the fact that the congestion is prevented by the mutual cooperation of a plurality of intermediate servers at present is effectively solved.
Description
Technical Field
The application relates to the technical field of quick payment, in particular to a data congestion processing method and device based on face-brushing payment.
Background
At present, an intermediate server for data processing usually performs corresponding memory slow release in the process of excessive user interaction data volume, and usually adopts a geographical method: determining the position of a user, and guiding the interactive data stream of the user into a server corresponding to the position of the user to realize slow release; monitoring the current CPU occupation amount of the server by adopting a monitoring drainage method, and when the current CPU occupation amount exceeds a set value, importing user interaction data streams corresponding to the exceeded CPU occupation amount into other servers, and the like;
for the current face-brushing payment field, all face data are necessarily stored in one database, and the database is connected with a plurality of intermediate servers through an admission agreement, so that all anti-congestion methods in the prior art adopt mutual cooperation of the plurality of intermediate servers to achieve the anti-congestion effect; although this type of solution solves the problem of intermediate servers crashing due to overload, the interaction of multiple intermediate servers substantially slows down the transmission speed of the interactive data of the user.
Disclosure of Invention
The application aims to solve the technical problem that the interactive data transmission speed of a user is reduced due to the fact that a plurality of intermediate servers are matched with each other to prevent congestion at present, and provides a data congestion processing method and device based on face-brushing payment.
The application adopts the following technical means for solving the technical problems:
the application provides a data congestion processing method based on face-brushing payment, which comprises the following steps:
carrying out configuration permission butt joint on the face brushing payment equipment and a database;
acquiring a face picture of a client;
monitoring the current CPU occupation ratio of the database, and determining an ID account pre-associated with the facial picture from the database by adopting a corresponding preset rule according to the CPU occupation ratio.
Further, when the CPU occupancy is in a first preset occupancy interval, the step of determining, from the database, an ID account pre-associated with the facial picture by using the corresponding preset rule includes:
hijacking and locking the ID account corresponding to the face picture and pre-associated by using the strand function in the linux kernel of the database, wherein,
the stride function is to apply a face picture and a ptrace function, and the ptrace function does not have the function of locking the pid and the ID account of the calling program, so that a calling frame script needs to be added to the tail of a syscall _ enter (structptrregs) function in a linux kernel of the database, and finally the calling frame script is led in through the face picture to output the pid calling program to hijack and lock the ID account from the database according to the face picture.
Further, the step of performing configuration approval docking of the face brushing payment device with the database comprises:
adding a calling frame script to the tail of a syscall _ enter (struct ptregs) function in a linux kernel of the database.
Further, when the CPU occupancy is in a second preset occupancy interval, the step of determining, from the database, an ID account pre-associated with the facial picture by using the corresponding preset rule includes:
converting the facial picture to a first base64 encoding;
a second base64 code, identical to the first base64 code, is determined from the database, thereby determining an ID account to which the second base64 code corresponds.
Further, the step of performing configuration approval docking of the face brushing payment device with the database comprises:
and configuring a picture transcoding script into a database, wherein the picture transcoding script is used for self-identifying base64 codes and calling pictures corresponding to similar codes of the base64 codes to code convert the pictures when the database acquires base64 codes.
The application provides a data processing apparatus that blocks up based on brush face payment, includes:
the docking unit is used for carrying out configuration permission docking on the face brushing payment equipment and the database;
an acquisition unit configured to acquire a facial picture of a customer;
and the identification unit is used for monitoring the current CPU occupation ratio of the database and determining an ID account pre-associated with the facial picture from the database by adopting a corresponding preset rule according to the CPU occupation ratio.
Further, the identification unit includes:
the hijacking module is used for carrying out hijacking locking on the ID account which is pre-associated with the face picture by utilizing the strand function in the linux kernel of the database, wherein,
the stride function is to apply a face picture and a ptrace function, and the ptrace function does not have the function of locking the pid and the ID account of the calling program, so that a calling frame script needs to be added to the tail of a syscall _ enter (structptrregs) function in a linux kernel of the database, and finally the calling frame script is led in through the face picture to output the pid calling program to hijack and lock the ID account from the database according to the face picture.
Further, the identification unit includes:
the coding conversion module is used for converting the facial picture into first base64 coding;
and the code locking module is used for determining a second base64 code which is the same as the first base64 code from the database, and further determining an ID account corresponding to the second base64 code.
The application also provides a face-brushing payment system, which comprises payment equipment, a merchant cash desk, an Internet database and a management center;
the payment equipment is used for acquiring a facial picture of a customer; the merchant cashier desk is used for being in butt joint with the payment equipment for payment; the Internet database is used for storing facial pictures of the clients; the management center is used for executing the data congestion processing method based on face brushing payment.
The application provides a data congestion processing method and device based on face-brushing payment, and the method and device have the following beneficial effects:
the face brushing payment equipment is subjected to configuration permission butt joint with the database, the butt joint of the face brushing payment equipment and the database is realized, a face picture of a client acquired by the face brushing payment equipment can be uploaded to the database, so that a corresponding ID account is determined, and deduction is finally realized; acquiring a face picture of a client; after the face picture is obtained, monitoring the current CPU occupation ratio of the database, and determining an ID account pre-associated with the face picture from the database by adopting a corresponding preset rule according to the CPU occupation ratio, so that the face brushing payment equipment and the database do not need to participate in an intermediate server, and the problem that the interactive data transmission speed of a user is reduced due to the fact that the congestion is prevented by the mutual cooperation of a plurality of intermediate servers at present is effectively solved.
Drawings
Fig. 1 is a schematic flow chart of a data congestion processing method based on face-brushing payment according to the present application;
fig. 2 is a block diagram of a data congestion processing apparatus based on face-brushing payment according to the present application;
fig. 3 is a block diagram of a structure of the face-brushing payment system according to the present application.
The implementation, functional features and advantages of the present application will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It is noted that the terms "comprises," "comprising," and "having" and any variations thereof in the description and claims of this application and the drawings described above are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus. In the claims, the description and the drawings of the specification of the present application, relational terms such as "first" and "second", and the like, may be used solely to distinguish one entity/action/object from another entity/action/object without necessarily requiring or implying any actual such relationship or order between such entities/actions/objects.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The technical problem solved by the application is to solve the technical problem that at present, congestion is prevented by mutual cooperation of a plurality of intermediate servers, so that the interactive data transmission speed of a user is reduced.
Referring to fig. 1, a schematic flow chart of a data congestion processing method based on face-brushing payment in an embodiment of the present application is shown;
a data congestion processing method based on face brushing payment comprises the following steps:
s1, carrying out configuration permission butt joint on the face brushing payment equipment and the database;
s2, acquiring a face picture of the client;
and S3, monitoring the current CPU occupation ratio of the database, and determining an ID account pre-associated with the facial picture from the database by adopting a corresponding preset rule according to the CPU occupation ratio.
The management center carries out configuration permission butt joint on the face brushing payment equipment and the database, adds a calling frame script to the tail of a syscall _ enter (struct ptregs) function in a linux kernel of the database, and configures a picture transcoding script in the database, wherein the picture transcoding script is used for carrying out code conversion on pictures by the database self-identification base64 coding and calling pictures corresponding to similar codes of the base64 coding when the database acquires the base64 coding; the storage occupation amount of the calling frame script and the image transcoding script is small and is between 1mb and 2mb, so the embodiment is specifically provided:
in one embodiment, the step of interfacing the face-brushing payment device with the database for configuration approval includes:
adding a calling frame script to the tail of a syscall _ enter (struct ptregs) function in a linux kernel of the database.
Specifically, the frame script is used for providing a frame for a facial picture of a customer, the facial picture is uploaded to a database after the facial picture of the customer is acquired by the face-brushing payment device, and the picture is loaded into the frame script after the facial picture is received by the database according to agreement permission.
In one embodiment, the step of interfacing the face-brushing payment device with the database for configuration approval includes:
and configuring a picture transcoding script into the database, wherein the picture transcoding script is used for self-identifying base64 codes and calling pictures corresponding to similar codes of the base64 codes to code-convert the pictures when the base64 codes are acquired by the database.
Specifically, the graph transcoding script is used to convert the picture into base64 code, and it should be noted that the base64 code is hexadecimal image code, for example: #00000, the hexadecimal base64 encodes, for example: the coding combination of #00000, #00001, and the like, which comprises a plurality of coding monomers, wherein each coding monomer indicates a hexadecimal color, and the colors are combined through the coding combination to form a picture, and the picture is converted into a base64 code in reverse principle, so that the storage occupancy of the picture can be effectively reduced, in the process of ID account identification, the base64 code determined by face brushing payment equipment is compared with the base64 code stored in a database, so that the ID account can be determined, and the data interaction speed of the face brushing payment equipment and the database is greatly improved through the identification of the base64 code.
In one embodiment, when the CPU occupancy is in the first preset occupancy interval, the step of determining the ID account pre-associated with the facial picture from the database by using the corresponding preset rule includes:
hijacking and locking the ID account corresponding to the face picture and pre-associated by using the strand function in the linux kernel of the database, wherein,
the stride function is to use a face picture and a ptrace function, and the ptrace function does not have the function of locking the pid and ID accounts of the calling program, so that a calling frame script needs to be added to the tail of a syscall _ enter (structptrregs) function in a linux kernel of the database, and finally the calling frame script is led in through the face picture to output the pid calling program to hijack and lock the ID accounts from the database according to the face picture.
It should be noted that, it is the current technology to call a system by using the strand function in the linux kernel, and in the present application, a call frame script is added to the tail code of the strand function, so that the call of the system is changed into the determination of the ID account based on the frame script.
Specifically, the first preset proportion interval is preferably 0% to 75%.
In one embodiment, when the CPU occupancy is in the second preset occupancy interval, the step of determining the ID account pre-associated with the facial picture from the database by using the corresponding preset rule includes:
converting the face picture into a first base64 encoding;
a second base64 code, identical to the first base64 code, is determined from the database, which in turn determines the ID account to which the second base64 code corresponds.
When the current CPU occupation ratio of the monitoring database of the management center is in a second preset occupation ratio interval, instructing the face brushing payment equipment to acquire the facial picture of the customer to perform base64 coding conversion, and realizing that the data uploaded by the face brushing payment equipment is base64 coding, wherein it needs to be explained that the storage occupation amount of the base64 coding is far less than that of the facial picture, the storage occupation amount of the general base64 coding is 50 bytes-100 kb, and the storage occupation amount of the facial image at least needs 500 kb. The face brushing payment device determines the ID account from the database in a base64 coding mode, and interaction speed of the payment device and the database is improved.
In specific implementation, the face-brushing payment device acquires a face image of a customer, meanwhile, the management center instructs the face-brushing payment device according to monitoring of the database, and when the current CPU occupation ratio of the database is in a second preset occupation ratio interval, the face-brushing payment device is instructed to convert the face image of the customer into a base64 code and send a first base64 code to the database; when the database receives a first base64 code, traversing the graph library according to a graph transcoding script, determining a facial image similar to a first base64 code expression color combination, transcoding the facial image to obtain a second base64 code, substantially, directly determining a corresponding facial image from the database through the first base64 code, improving the accuracy by comparing the first base64 code with the second base64 code, comparing the codes of human face parts in the first base64 code and the second base64 code, and determining a facial image corresponding to the second base64 code and determining an ID account corresponding to the facial image when the codes are consistent.
The second predetermined proportion interval is 75% to 100%.
Referring to fig. 2, a block diagram of a data congestion processing apparatus based on face-brushing payment is provided,
a data jam processing device based on face-brushing payment comprises:
the docking unit 1 is used for carrying out configuration permission docking on the face brushing payment equipment and the database;
an acquisition unit 2 for acquiring a face picture of a customer;
and the identification unit 3 is used for monitoring the current CPU occupation ratio of the database and determining an ID account pre-associated with the facial picture from the database by adopting a corresponding preset rule according to the CPU occupation ratio.
In one embodiment, the recognition unit 1 comprises:
the hijacking module is used for carrying out hijacking locking on the ID account which is pre-associated with the face picture by utilizing the strand function in the linux kernel of the database, wherein,
the stride function is to use a face picture and a ptrace function, and the ptrace function does not have the function of locking the pid and ID accounts of the calling program, so that a calling frame script needs to be added to the tail of a syscall _ enter (structptrregs) function in a linux kernel of the database, and finally the calling frame script is led in through the face picture to output the pid calling program to hijack and lock the ID accounts from the database according to the face picture.
In one embodiment, the recognition unit 1 comprises:
the coding conversion module is used for converting the face picture into first base64 coding;
and the code locking module is used for determining a second base64 code which is the same as the first base64 code from the database, and further determining an ID account corresponding to the second base64 code.
Referring to fig. 3, a block diagram of a face payment system according to the present application is shown.
A face-brushing payment system comprises payment equipment, a merchant cash desk, an Internet database and a management center;
the payment device is used for acquiring a facial picture of a customer; the merchant cashier desk is used for being in butt joint with the payment equipment for paying; the Internet database is used for storing facial pictures of the clients; the management center is used for executing the data congestion processing method based on face brushing payment.
In summary, the face-brushing payment device is subjected to configuration permission butt joint with the database, the butt joint of the face-brushing payment device and the database is realized, a face picture of a customer acquired by the face-brushing payment device can be uploaded to the database, so that a corresponding ID account is determined, and deduction is finally realized; acquiring a face picture of a client; after the face picture is obtained, monitoring the current CPU occupation ratio of the database, and determining an ID account pre-associated with the face picture from the database by adopting a corresponding preset rule according to the CPU occupation ratio, so that the face brushing payment equipment and the database do not need to participate in an intermediate server, and the problem that the interactive data transmission speed of a user is reduced due to the fact that the congestion is prevented by the mutual cooperation of a plurality of intermediate servers at present is effectively solved.
Although embodiments of the present application 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 application, the scope of which is defined in the appended claims and their equivalents.
Claims (9)
1. A data congestion processing method based on face-brushing payment is characterized by comprising the following steps:
carrying out configuration permission butt joint on the face brushing payment equipment and a database;
acquiring a face picture of a client;
monitoring the current CPU occupation ratio of the database, and determining an ID account pre-associated with the facial picture from the database by adopting a corresponding preset rule according to the CPU occupation ratio.
2. The data congestion processing method based on face-brushing payment according to claim 1, wherein when the CPU occupancy is in a first preset occupancy interval, the step of determining an ID account pre-associated with the facial picture from the database by using a corresponding preset rule comprises:
hijacking and locking the ID account corresponding to the face picture and pre-associated by using the strand function in the linux kernel of the database, wherein,
the stride function is to apply a face picture and a ptrace function, and the ptrace function does not have the function of locking the pid and the ID account of the calling program, so that a calling frame script needs to be added to the tail of a syscall _ enter (structptrregs) function in a linux kernel of the database, and finally the calling frame script is led in through the face picture to output the pid calling program to hijack and lock the ID account from the database according to the face picture.
3. The data congestion processing method based on face-brushing payment as claimed in claim 2, wherein the step of configuring the face-brushing payment device to interface with the database for permission comprises:
adding a calling frame script to the tail of a syscall _ enter (struct ptregs) function in a linux kernel of the database.
4. The data congestion processing method based on face-brushing payment according to claim 1, wherein when the CPU occupancy is in a second preset occupancy interval, the step of determining an ID account pre-associated with the facial picture from the database by using the corresponding preset rule comprises:
converting the facial picture to a first base64 encoding;
a second base64 code, identical to the first base64 code, is determined from the database, thereby determining an ID account to which the second base64 code corresponds.
5. The data congestion processing method based on face-brushing payment as claimed in claim 4, wherein the step of configuring the face-brushing payment device to interface with the database for permission comprises:
and configuring a picture transcoding script into a database, wherein the picture transcoding script is used for self-identifying base64 codes and calling pictures corresponding to similar codes of the base64 codes to code convert the pictures when the database acquires base64 codes.
6. A data jam processing apparatus based on face-brushing payment is characterized by comprising:
the docking unit is used for carrying out configuration permission docking on the face brushing payment equipment and the database;
an acquisition unit configured to acquire a facial picture of a customer;
and the identification unit is used for monitoring the current CPU occupation ratio of the database and determining an ID account pre-associated with the facial picture from the database by adopting a corresponding preset rule according to the CPU occupation ratio.
7. The device for processing data congestion based on face brushing payment according to claim 6, wherein the identification unit comprises:
the hijacking module is used for carrying out hijacking locking on the ID account which is pre-associated with the face picture by utilizing the strand function in the linux kernel of the database, wherein,
the stride function is to apply a face picture and a ptrace function, and the ptrace function does not have the function of locking the pid and the ID account of the calling program, so that a calling frame script needs to be added to the tail of a syscall _ enter (structptrregs) function in a linux kernel of the database, and finally the calling frame script is led in through the face picture to output the pid calling program to hijack and lock the ID account from the database according to the face picture.
8. The device for processing data congestion based on face brushing payment according to claim 6, wherein the identification unit comprises:
the coding conversion module is used for converting the facial picture into first base64 coding;
and the code locking module is used for determining a second base64 code which is the same as the first base64 code from the database, and further determining an ID account corresponding to the second base64 code.
9. A face-brushing payment system is characterized by comprising payment equipment, a merchant cash desk, an Internet database and a management center;
the payment equipment is used for acquiring a facial picture of a customer; the merchant cashier desk is used for being in butt joint with the payment equipment for payment; the Internet database is used for storing facial pictures of the clients; the management center is used for executing the data congestion processing method based on the face brushing payment according to any one of claims 1 to 5.
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