CN115273356B - Data processing method and system of self-service equipment - Google Patents
Data processing method and system of self-service equipment Download PDFInfo
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- CN115273356B CN115273356B CN202210909608.0A CN202210909608A CN115273356B CN 115273356 B CN115273356 B CN 115273356B CN 202210909608 A CN202210909608 A CN 202210909608A CN 115273356 B CN115273356 B CN 115273356B
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F19/00—Complete banking systems; Coded card-freed arrangements adapted for dispensing or receiving monies or the like and posting such transactions to existing accounts, e.g. automatic teller machines
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/52—Surveillance or monitoring of activities, e.g. for recognising suspicious objects
- G06V20/53—Recognition of crowd images, e.g. recognition of crowd congestion
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07F—COIN-FREED OR LIKE APPARATUS
- G07F19/00—Complete banking systems; Coded card-freed arrangements adapted for dispensing or receiving monies or the like and posting such transactions to existing accounts, e.g. automatic teller machines
- G07F19/20—Automatic teller machines [ATMs]
- G07F19/207—Surveillance aspects at ATMs
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V2201/00—Indexing scheme relating to image or video recognition or understanding
- G06V2201/07—Target detection
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Abstract
The embodiment of the application discloses a data processing method and a system of self-service equipment, which can be applied to the field of cloud computing, the field of big data, the field of Internet of things or the field of finance, and the method comprises the steps of receiving a service request for handling target service sent by target self-service equipment, and determining a first fog node corresponding to an identifier of the target self-service equipment; the first fog node is used for establishing connection with the target self-service equipment in a fog computing network and providing computing resources, and the fog computing network comprises a plurality of fog nodes; transmitting the service data to the first cloud node; and receiving a processing result of the service data returned by the first fog node, and returning the processing result to the target self-service equipment according to the identification of the target self-service equipment. Based on the fact that the mist calculation is introduced, data and data are processed in the equipment at the network edge, the network calculation is expanded from the network center to the network edge, and the processing efficiency of the self-service equipment is improved.
Description
Technical Field
The present application relates to the field of information processing technologies, and in particular, to a data processing method and system for a self-service device.
Background
With the development of technology, banking outlets do not rely on website personnel to conduct business handling, more and more self-service devices enter the website, the intelligent degree of the self-service devices is continuously improved, but the intelligent means that the self-service devices need better performance to calculate and process data, the data processing speed of the self-service devices is limited due to the performance, the customer experience is poor, and the problem that the processing efficiency of the banking self-service devices is low exists in the prior art is seen.
Disclosure of Invention
The application aims to provide a data processing method and a system of self-service equipment, which are used for centralizing data and data processing in equipment at the network edge by introducing fog calculation, expanding the network calculation from a network center to the network edge and improving the processing efficiency of the self-service equipment.
To achieve the above object, in a first aspect, the present application provides a data processing method of a self-service device, the method including:
Receiving a service request for handling a target service sent by target self-service equipment, wherein the service request comprises: the identification and business data of the target self-service equipment; the target self-service equipment is any self-service equipment in a target banking website;
Determining a first fog node corresponding to the identification of the target self-service equipment; the first fog node is one fog node in a fog computing network for providing computing resources for the target self-service device, and the fog computing network comprises a plurality of fog nodes;
the service data is sent to the first fog node, and a processing result of the service data returned by the first fog node is received;
And returning the processing result to the target self-service equipment according to the identification of the target self-service equipment.
Optionally, before the receiving the service request sent by the target self-service device for transacting the target service, the method further includes:
Setting up a fog computing network at the target bank website, distributing a first fog node for the target bank website, creating a mapping relation between the target bank website and the first fog node in a preset mapping table of the bank website and the fog node, and generating an updated mapping table of the bank website and the fog node;
and determining the self-service equipment and the identification of the self-service equipment included in the target banking website, and establishing a mapping relation between the identification of the self-service equipment and the target banking website.
Optionally, the determining the first fog node corresponding to the identifier of the target self-service device includes:
Determining a target banking website corresponding to the identification of the target self-service equipment;
Acquiring the updated mapping table of the banking outlets and the fog nodes;
and determining a first fog node corresponding to the target bank node according to the updated mapping table of the bank node and the fog node.
Optionally, the method further comprises:
acquiring a picture data set shot by a camera of the target bank website;
generating a network point traffic monitoring model according to the picture data set and a target detection algorithm;
Determining the people flow detection data of the target banking website according to the website people flow monitoring model;
And scheduling the quantity of the edge network equipment resources serving the first fog node in the fog computing network according to the people flow detection data of the target banking website.
Optionally, the scheduling, according to the people flow detection data of the target banking website, the number of edge network device resources serving the first fog node in the fog computing network specifically includes:
If the people flow detection data of the target banking website is larger than a first preset threshold value, increasing the number of edge network equipment resources serving the first fog node in the fog computing network;
If the people flow detection data of the target banking website is smaller than a second preset threshold value, reducing the number of edge network equipment resources serving the first fog node in the fog computing network; the second preset threshold value is smaller than the first preset threshold value;
If the people flow detection data of the target banking website is larger than a second preset threshold value and smaller than a first preset threshold value, the first fog node is allocated with the quantity of the edge network equipment resources according to preset resource allocation parameters.
In a second aspect, the present application also provides a data processing system of a self-service device, the system comprising:
the request receiving module is used for receiving a service request for handling a target service sent by the target self-service equipment, wherein the service request comprises the following components: the identification and business data of the target self-service equipment; the target self-service equipment is any self-service equipment in a target banking website;
The fog node determining module is used for determining a first fog node corresponding to the identification of the target self-service equipment; the first fog node is one fog node in a fog computing network for providing computing resources for the target self-service device, and the fog computing network comprises a plurality of fog nodes;
the fog calculation interaction module is used for sending the service data to the first fog node and receiving a processing result of the service data returned by the first fog node;
And the data sending module is used for returning the processing result to the target self-service equipment according to the identification of the target self-service equipment.
Optionally, the system further comprises:
The fog computing network creation module is used for building a fog computing network at the target bank website, distributing a first fog node for the target bank website, creating a mapping relation between the target bank website and the first fog node in a preset mapping table of the bank website and the fog node, and generating an updated mapping table of the bank website and the fog node; and determining the self-service equipment and the identification of the self-service equipment included in the target banking website, and establishing a mapping relation between the identification of the self-service equipment and the target banking website.
Optionally, the fog node determining module is specifically configured to:
Determining a target banking website corresponding to the identification of the self-service equipment; acquiring the updated mapping table of the banking outlets and the fog nodes; and determining a first fog node corresponding to the target bank node according to the updated mapping table of the bank node and the fog node.
Optionally, the system further comprises:
The data acquisition module is used for acquiring a picture data set shot by a camera of the target bank website;
The data processing module is used for generating a network point traffic monitoring model according to the picture data set and a target detection algorithm; determining the people flow detection data of the target banking website according to the website people flow monitoring model;
and the dynamic scheduling module is used for scheduling the quantity of the edge network equipment resources serving the first fog node in the fog computing network according to the people flow detection data of the target banking website.
Optionally, the dynamic scheduling module is specifically configured to:
If the people flow detection data of the target banking website is larger than a first preset threshold value, increasing the number of edge network equipment resources serving the first fog node in the fog computing network;
If the people flow detection data of the target banking website is smaller than a second preset threshold value, reducing the number of edge network equipment resources serving the first fog node in the fog computing network; the second preset threshold value is smaller than the first preset threshold value;
If the people flow detection data of the target banking website is larger than a second preset threshold value and smaller than a first preset threshold value, the first fog node is allocated with the quantity of the edge network equipment resources according to preset resource allocation parameters.
The embodiment of the application provides a data processing method and a system of self-service equipment, wherein the method receives a service request for handling target service sent by target self-service equipment and determines a first fog node corresponding to an identifier of the target self-service equipment; the first fog node is used for establishing connection with the target self-service equipment in a fog computing network and providing computing resources, and the fog computing network comprises a plurality of fog nodes; transmitting the service data to the first cloud node; and receiving a processing result of the service data returned by the first fog node, and returning the processing result to the target self-service equipment according to the identification of the target self-service equipment. Based on the fact that the mist calculation is introduced, data and data are processed in the equipment at the network edge, the network calculation is expanded from the network center to the network edge, and the processing efficiency of the self-service equipment is improved.
Drawings
In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present application, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flowchart of a data processing method of a self-service device according to an embodiment of the present application;
FIG. 2 is a schematic diagram of a data processing system of a self-service device according to an embodiment of the present application.
Detailed Description
The following description of the embodiments of the present application will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.
Along with the development of technology, the intelligent degree of the self-service equipment of the banking website is also continuously improved, but the intelligent means that the self-service equipment needs better performance to calculate and process data, and the data processing speed of the self-service equipment is also limited due to the limitation of the performance, so that the processing efficiency of the self-service equipment of the banking website is low.
The embodiment of the application provides a data processing method and a system of self-service equipment, which are used for centralizing data and data processing in equipment at the network edge by introducing fog calculation, expanding the network calculation from a network center to the network edge and improving the processing efficiency of the self-service equipment.
It should be noted that the data processing method and system of the self-service device provided by the application can be applied to the field of cloud computing, the field of big data, the field of internet of things or the field of finance. The foregoing is merely exemplary, and is not intended to limit the application of the present application.
The following describes a data processing method of the self-service device in detail:
Fig. 1 is a flowchart of a data processing method of a self-service device according to an embodiment of the present application. As shown in fig. 1, the data processing method of the self-service device in the embodiment of the application includes:
S10: receiving a service request for handling a target service sent by target self-service equipment, wherein the service request comprises: identification of the target self-service device and business data; the target self-service equipment is any self-service equipment in a target banking website;
It should be noted that, the user transacts the service through the self-service device at the banking website, and the self-service device responds to the target service transacting click selection operation of the user, and generates a service request of the corresponding target service and sends the service request to the data processing system of the self-service device.
S11: determining a first fog node corresponding to the identification of the target self-service equipment; the first fog node is one fog node in a fog computing network for providing computing resources for the target self-service device, and the fog computing network comprises a plurality of fog nodes;
Specifically, the determining the first fog node corresponding to the identifier of the target self-service device includes: determining a target banking website corresponding to the identification of the target self-service equipment according to the identification of the target self-service equipment; acquiring a mapping table of banking outlets and fog nodes; and determining a first fog node corresponding to the target bank node according to the mapping table of the bank node and the fog node.
It should be noted that, each self-service device in the banking website has a corresponding identifier, and the identifier is used for distinguishing each self-service device to determine which self-service device the user operates on, and the processing result of the mist computing network should be returned to which self-service device. The identifier may be set empirically by those skilled in the art, and may be an ID, a manufacturer identification code, etc., which is not limited herein, and is within the scope of the present application.
S12: transmitting the service data to the first cloud node; receiving a processing result of the service data returned by the first fog node;
It should be noted that, the fog node is a core component of the fog computing architecture, and the fog node may be a physical component, such as a gateway, a switch, a router, a server, and the like; the cloud node may also be a virtual component that is tightly coupled to the intelligent terminal device or access network and provides computing resources, such as virtual machines, for these devices. In addition, the cloud nodes provide some form of data management and communication services between the network edge layers, through which the terminal devices reside the cloud computing service computing resources. The fog node deployment model can be a private fog node and a public fog node, and is not limited here, and is within the scope of the application.
It should be noted that Fog Computing (Fog Computing), also known as networking of Fog or Fog, extends the traditional Cloud Computing paradigm to network edges, where data, data processing, and applications are concentrated in devices at the network edge, rather than being almost entirely stored in the Cloud, an extended concept of Cloud Computing (Cloud Computing); the goal is to improve the efficient atomization and reduced data transfer to the cloud for processing, analysis and storage.
Specifically, in the embodiment of the application, service data is sent to a first fog node; the first fog node processes the service data by utilizing the number of the edge network equipment resources providing service in the fog computing network to generate a corresponding processing result, and then the first fog node returns the processing result aiming at the service data to the data processing system of the self-service equipment, and the data processing system of the self-service equipment receives the processing result of the service data returned by the first fog node.
It should be noted that, the processing result of the service data corresponds to an operation request of the user on the self-service device, for example, the user performs an operation of inquiring funds of the account on the self-service device, and the processing result is the funds data of the account inquired by the user.
It should be noted that, when the first fog node returns the processing result of the service data, the processing result is bound with the service data, so that the system clearly aims at the processing result of which service data, and thus the processing result is accurately fed back to the corresponding target device. The specific binding may be that the processing result carries the corresponding service data required to be processed, or the system binds the service identifier for identifying the service data required to be processed, and then sends the service identifier to the first fog node for processing, and the first fog node binds the processing result with the service identifier when returning the processing result, so as to provide system identification. Specifically, the service identifier used for identification may be a newly set identifier (for example, an identifier set according to an uploading sequence), or may be an identifier of the target self-service device, where the service identifier is not specifically limited, and may be any service identifier as required in actual situations, and all service identifiers are within the protection scope of the present application.
S13: and returning the processing result to the target self-service equipment according to the identification of the target self-service equipment.
The system can clearly know the corresponding target self-service equipment of the service data when the target self-service equipment sends the service request for handling the target service, and after the data processing system of the self-service equipment receives the processing result, the processing result of the service data for which the service request is processed can be determined according to the service identifier because the processing result is bound with the service identifier, and then the system can determine the returned target self-service equipment according to the identifier of the corresponding target self-service equipment of the service data.
In this embodiment of the present application, before the receiving the service request for handling the target service sent by the target self-service device, the method further includes:
Setting up a fog computing network at the target bank website, distributing a first fog node for the target bank website, creating a mapping relation between the target bank website and the first fog node in a preset mapping table of the bank website and the fog node, and generating an updated mapping table of the bank website and the fog node; and determining the self-service equipment and the identification of the self-service equipment included in the target banking website, and establishing a mapping relation between the identification of the self-service equipment and the target banking website.
It should be noted that, the preset mapping table of the banking website and the fog node is an initial mapping table of the banking website and the fog node, after the banking website newly builds the fog computing network, new mapping care of the banking website and the fog node is built, the mapping care is added into the mapping table of the banking website and the fog node updated last time, the mapping table of the banking website and the fog node updated each time is stored in the data processing system of the self-service equipment, the storage can be stored in an overlay storage mode, namely, the mapping table of the banking website and the fog node updated each time can overlay the mapping table stored last time; the number of the stored mapping tables can be limited, the mapping tables of the banking outlets and the fog nodes after updating are stored in the storage unit of the system every time, and the mapping tables stored in the previous storage unit are deleted according to the storage sequence when the number reaches the threshold value.
In the embodiment of the application, the data processing method and system of the self-service equipment are provided, and the fog computing network is built at a banking website, so that data and data processing are distributed and deployed at the edge network equipment to provide service for the self-service equipment, and the network computing of the self-service equipment is expanded from a network center to a network edge, so that the processing efficiency of the self-service equipment is improved.
Preferably, according to the data processing method of the self-service device provided by the other embodiment of the application, the number of the edge network device resources providing the service in the mist computing network can be dynamically scheduled according to the monitoring condition of the network point traffic.
Specifically, the data processing method of the self-service device further comprises the following steps:
acquiring a picture data set shot by a camera of the target bank website; generating a network point traffic monitoring model according to the picture data set and a target detection algorithm; determining the people flow detection data of the target banking website according to the website people flow monitoring model; and scheduling the quantity of the edge network equipment resources serving the first fog node in the fog computing network according to the people flow detection data of the target banking website.
It should be noted that, the camera used for acquiring the image dataset may be an infrared camera, a wide-angle camera, a panoramic camera, etc., and the image in the acquired image dataset needs to be as consistent as possible with the shooting angle of the camera actually used for monitoring the traffic, i.e. the shooting angle of the camera needs to monitor the traffic information as much as possible. The specific form of the camera for acquiring the picture data set is not limited, and the camera can be determined according to actual conditions and belongs to the protection scope of the application.
It should be noted that, in the generating of the mesh point traffic monitoring model according to the image dataset and the target detection algorithm, the target detection algorithm used may be a YOLO v5 target detection algorithm, specifically, according to the image dataset, the mesh point traffic monitoring model may be trained by using the YOLO v5 target detection algorithm, or may be another target detection algorithm related to deep learning, which is not limited to a specific form of the target detection algorithm, and may be determined according to the actual situation, and all belong to the protection scope of the present application.
Specifically, according to the people flow detection data of the target banking website, the method for scheduling the number of the edge network equipment resources serving the first fog node in the fog computing network specifically includes: if the people flow detection data of the target banking website is larger than a first preset threshold value, increasing the number of edge network equipment resources serving the first fog node in the fog computing network; if the people flow detection data of the target banking website is smaller than a second preset threshold value, reducing the number of edge network equipment resources serving the first fog node in the fog computing network; the second preset threshold value is smaller than the first preset threshold value; if the people flow detection data of the target banking website is larger than a second preset threshold value and smaller than a first preset threshold value, the first fog node is allocated with the quantity of the edge network equipment resources according to preset resource allocation parameters.
It should be noted that, the first preset threshold and the second preset threshold may be set according to experience of a person skilled in the art, and are not limited herein specifically, for example, the first preset threshold may be 100, the second preset threshold may be 50, and when the detected data of the traffic of people at the target banking website is 120 people, the number of edge network equipment resources serving the first fog node in the fog computing network is increased; and when the people flow detection data of the target banking website is 20 people, reducing the number of edge network equipment resources for providing services for the first fog node in the fog computing network. If the people flow detection data of the target banking website is 60 people, distributing the quantity of the edge network equipment resources providing service in the fog computing network to the first fog node according to the preset resource distribution parameters.
It should be noted that, for each mist node in the mist computing network, the preset resource allocation parameter for providing the number of service edge network device resources may be confirmed according to experience of the person skilled in the art, and for each mist node in the mist computing network, the preset resource allocation parameter for providing the number of service edge network device resources may be fixed, for example, the preset resource allocation parameter for each mist node is 1%, that is, 1% of the number of service edge network device resources in the mist computing network is used as the number of service edge network device resources pre-allocated to each mist node. The number of the cloud nodes in the cloud computing network may also be determined according to the number of the cloud nodes in the cloud computing network, so as to determine the number of the edge network device resources serving the first cloud node in the cloud computing network. The specific determination mode of the preset resource allocation parameters is not limited, and the specific determination mode can be determined according to actual conditions and is within the protection scope of the application.
According to the embodiment of the application, the edge network resources providing service in the fog computing network can be dynamically scheduled according to the traffic monitoring condition of the network points, so that more people can be involved, the resource utilization rate of the edge network equipment can be improved when the utilization rate of the network point self-service equipment is high, and otherwise, the utilization rate of the edge network equipment is reduced; therefore, the edge network equipment for mist calculation can be intelligently scheduled by monitoring the number of people in the network points, so that resource waste is prevented, and the processing efficiency of the mist calculation is improved.
Referring to fig. 2, referring to a description of a data processing system of a self-service device in an embodiment of the present application, based on a data processing method of a self-service device in the foregoing embodiment, in an embodiment of the present application, the data processing method of the self-service device is implemented by using the data processing system of the self-service device, where the data processing system of the self-service device in the embodiment of the present application includes:
A request receiving module 201, configured to receive a service request sent by a target self-service device for handling a target service, where the service request includes: the identification and business data of the target self-service equipment; the target self-service equipment is any self-service equipment in a target banking website;
A fog node determining module 202, configured to determine a first fog node corresponding to an identifier of the target self-service device; the first fog node is one fog node in a fog computing network for providing computing resources for the target self-service device, and the fog computing network comprises a plurality of fog nodes;
The fog calculation interaction module 203 is configured to send the service data to the first fog node, and receive a processing result of the service data returned by the first fog node;
And the data sending module 204 is configured to return the processing result to the target self-service device according to the identifier of the target self-service device.
Preferably, the system further comprises:
The fog computing network creation module is used for building a fog computing network at the target bank website, distributing a first fog node for the target bank website, creating a mapping relation between the target bank website and the first fog node in a preset mapping table of the bank website and the fog node, and generating an updated mapping table of the bank website and the fog node; and determining the self-service equipment and the identification of the self-service equipment included in the target banking website, and establishing a mapping relation between the identification of the self-service equipment and the target banking website.
Specifically, the fog node determining module is specifically configured to:
Determining a target banking website corresponding to the identification of the self-service equipment; acquiring the updated mapping table of the banking outlets and the fog nodes; and determining a first fog node corresponding to the target bank node according to the updated mapping table of the bank node and the fog node.
Preferably, the system further comprises:
The data acquisition module is used for acquiring a picture data set shot by a camera of the target bank website;
The data processing module is used for generating a network point traffic monitoring model according to the picture data set and a target detection algorithm; determining the people flow detection data of the target banking website according to the website people flow monitoring model;
and the dynamic scheduling module is used for scheduling the quantity of the edge network equipment resources serving the first fog node in the fog computing network according to the people flow detection data of the target banking website.
The dynamic scheduling module is specifically configured to: if the people flow detection data of the target banking website is larger than a first preset threshold value, increasing the number of edge network equipment resources serving the first fog node in the fog computing network; if the people flow detection data of the target banking website is smaller than a second preset threshold value, reducing the number of edge network equipment resources serving the first fog node in the fog computing network; the second preset threshold value is smaller than the first preset threshold value; if the people flow detection data of the target banking website is larger than a second preset threshold value and smaller than a first preset threshold value, the first fog node is allocated with the quantity of the edge network equipment resources according to preset resource allocation parameters.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (6)
1. A method of data processing for a self-service device, the method comprising:
Receiving a service request for handling a target service sent by target self-service equipment, wherein the service request comprises: the identification and business data of the target self-service equipment; the target self-service equipment is any self-service equipment in a target banking website;
Determining a first fog node corresponding to the identification of the target self-service equipment; the first fog node is one fog node in a fog computing network for providing computing resources for the target self-service device, and the fog computing network comprises a plurality of fog nodes;
the service data is sent to the first fog node, and a processing result of the service data returned by the first fog node is received;
Returning the processing result to the target self-service equipment according to the identification of the target self-service equipment;
Wherein the method further comprises:
acquiring a picture data set shot by a camera of the target bank website;
generating a network point traffic monitoring model according to the picture data set and a target detection algorithm;
Determining the people flow detection data of the target banking website according to the website people flow monitoring model;
Scheduling the number of edge network equipment resources serving a first fog node in the fog computing network according to the people flow detection data of the target banking website;
the scheduling, according to the people flow detection data of the target banking website, the number of edge network equipment resources serving the first fog node in the fog computing network specifically includes:
If the people flow detection data of the target banking website is larger than a first preset threshold value, increasing the number of edge network equipment resources serving the first fog node in the fog computing network;
If the people flow detection data of the target banking website is smaller than a second preset threshold value, reducing the number of edge network equipment resources serving the first fog node in the fog computing network; the second preset threshold value is smaller than the first preset threshold value;
If the people flow detection data of the target banking website is larger than a second preset threshold value and smaller than a first preset threshold value, the first fog node is allocated with the quantity of the edge network equipment resources according to preset resource allocation parameters.
2. The method of claim 1, wherein prior to receiving the service request for transacting the target service sent by the target self-service device, the method further comprises:
Setting up a fog computing network at the target bank website, distributing a first fog node for the target bank website, creating a mapping relation between the target bank website and the first fog node in a preset mapping table of the bank website and the fog node, and generating an updated mapping table of the bank website and the fog node;
and determining the self-service equipment and the identification of the self-service equipment included in the target banking website, and establishing a mapping relation between the identification of the self-service equipment and the target banking website.
3. The method of claim 2, wherein the determining the first fog node corresponding to the identity of the target self-service device comprises:
Determining a target banking website corresponding to the identification of the target self-service equipment;
Acquiring the updated mapping table of the banking outlets and the fog nodes;
and determining a first fog node corresponding to the target bank node according to the updated mapping table of the bank node and the fog node.
4. A data processing system for a self-service device, the system comprising:
the request receiving module is used for receiving a service request for handling a target service sent by the target self-service equipment, wherein the service request comprises the following components: the identification and business data of the target self-service equipment; the target self-service equipment is any self-service equipment in a target banking website;
The fog node determining module is used for determining a first fog node corresponding to the identification of the target self-service equipment; the first fog node is one fog node in a fog computing network for providing computing resources for the target self-service device, and the fog computing network comprises a plurality of fog nodes;
the fog calculation interaction module is used for sending the service data to the first fog node and receiving a processing result of the service data returned by the first fog node;
The data sending module is used for returning the processing result to the target self-service equipment according to the identification of the target self-service equipment;
wherein the system further comprises:
The data acquisition module is used for acquiring a picture data set shot by a camera of the target bank website;
The data processing module is used for generating a network point traffic monitoring model according to the picture data set and a target detection algorithm; determining the people flow detection data of the target banking website according to the website people flow monitoring model;
The dynamic scheduling module is used for scheduling the quantity of the edge network equipment resources serving the first fog node in the fog computing network according to the people flow detection data of the target banking website;
the dynamic scheduling module is specifically configured to:
If the people flow detection data of the target banking website is larger than a first preset threshold value, increasing the number of edge network equipment resources serving the first fog node in the fog computing network;
If the people flow detection data of the target banking website is smaller than a second preset threshold value, reducing the number of edge network equipment resources serving the first fog node in the fog computing network; the second preset threshold value is smaller than the first preset threshold value;
If the people flow detection data of the target banking website is larger than a second preset threshold value and smaller than a first preset threshold value, the first fog node is allocated with the quantity of the edge network equipment resources according to preset resource allocation parameters.
5. The system of claim 4, wherein the system further comprises:
The fog computing network creation module is used for building a fog computing network at the target bank website, distributing a first fog node for the target bank website, creating a mapping relation between the target bank website and the first fog node in a preset mapping table of the bank website and the fog node, and generating an updated mapping table of the bank website and the fog node; and determining the self-service equipment and the identification of the self-service equipment included in the target banking website, and establishing a mapping relation between the identification of the self-service equipment and the target banking website.
6. The system of claim 5, wherein the foggy node determination module is specifically configured to:
Determining a target banking website corresponding to the identification of the self-service equipment; acquiring the updated mapping table of the banking outlets and the fog nodes; and determining a first fog node corresponding to the target bank node according to the updated mapping table of the bank node and the fog node.
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| CN107767080A (en) * | 2017-11-14 | 2018-03-06 | 中国银行股份有限公司 | A kind of bank outlets' Service Source dispatching method and device |
| CN111401711A (en) * | 2020-03-09 | 2020-07-10 | 刘振 | Intelligent scheduling method, device, equipment and storage medium |
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| CN109286645A (en) * | 2017-07-21 | 2019-01-29 | 中兴通讯股份有限公司 | A kind of moving method and device of business |
| CN111985851B (en) * | 2020-09-07 | 2023-09-19 | 中国银行股份有限公司 | Bank outlet resource scheduling method and device |
| CN114783121B (en) * | 2022-04-13 | 2024-06-25 | 中国银行股份有限公司 | Fault processing method, device and equipment of self-service equipment and readable storage medium |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN107767080A (en) * | 2017-11-14 | 2018-03-06 | 中国银行股份有限公司 | A kind of bank outlets' Service Source dispatching method and device |
| CN111401711A (en) * | 2020-03-09 | 2020-07-10 | 刘振 | Intelligent scheduling method, device, equipment and storage medium |
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