CN116471206A - Business network anomaly handling method and device - Google Patents

Business network anomaly handling method and device Download PDF

Info

Publication number
CN116471206A
CN116471206A CN202310369781.0A CN202310369781A CN116471206A CN 116471206 A CN116471206 A CN 116471206A CN 202310369781 A CN202310369781 A CN 202310369781A CN 116471206 A CN116471206 A CN 116471206A
Authority
CN
China
Prior art keywords
network
business
website
prediction data
point
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.)
Pending
Application number
CN202310369781.0A
Other languages
Chinese (zh)
Inventor
王飞
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Industrial and Commercial Bank of China Ltd ICBC
Original Assignee
Industrial and Commercial Bank of China Ltd ICBC
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Industrial and Commercial Bank of China Ltd ICBC filed Critical Industrial and Commercial Bank of China Ltd ICBC
Priority to CN202310369781.0A priority Critical patent/CN116471206A/en
Publication of CN116471206A publication Critical patent/CN116471206A/en
Pending legal-status Critical Current

Links

Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0805—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters by checking availability
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/06—Management of faults, events, alarms or notifications
    • H04L41/0654—Management of faults, events, alarms or notifications using network fault recovery
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/147—Network analysis or design for predicting network behaviour

Abstract

The embodiment of the application provides a business network anomaly processing method and device, which can be used in the financial field, and the method comprises the following steps: collecting network state information and business processing information of a target business website; determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information; according to the network operation condition, the network site business handling prediction data, the network site equipment operation prediction data and the network fluctuation prediction model, obtaining prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value; the method and the system can execute remedial measures when the network abnormality is monitored to ensure that the business network works normally.

Description

Business network anomaly handling method and device
Technical Field
The application relates to the field of network monitoring and also can be used in the field of finance, in particular to a business network anomaly processing method and device.
Background
As one of key technologies of the wireless network autonomous healing technology, interrupt detection has important significance for improving the wireless network operation and maintenance efficiency and reducing the operation and maintenance cost. However, wireless network outages are small probability events that can be collected with significantly smaller amounts of outage characteristic data than normal data, resulting in a serious imbalance in the data set. Furthermore, when there is more than one type of interruption in the network, there tends to be more severe inter-class overlap between the different types of interruption data. Both of these factors result in reduced wireless network outage detection performance.
In the prior art, monitoring on network abnormality of the business network is not advanced enough, normal operation of the business network is influenced when the network is abnormal, corresponding treatment measures aiming at the network abnormality are not available, and operation stability of the business network cannot be guaranteed.
The business network is generally in a wired network environment, when the network is interrupted due to sudden fault or incapacitation of the wired network, the 4G/5G wireless router is started in an emergency mode to take over the network, so that business handling of the business network is ensured not to be interrupted, and the state monitoring of the wireless network is quite practical.
Disclosure of Invention
Aiming at the problems in the prior art, the application provides a business network abnormality processing method and device, which can execute remedial measures when network abnormality is monitored so as to ensure that the business network operates normally.
In order to solve at least one of the above problems, the present application provides the following technical solutions:
in a first aspect, the present application provides a method for processing network anomalies in a business website, including:
collecting network state information and business processing information of a target business website;
determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information;
according to the network operation condition, the network site business handling prediction data, the network site equipment operation prediction data and the network fluctuation prediction model, and obtaining the prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value.
Further, the collecting network status information and service processing information of the target business website includes:
collecting wired network real-time state information of a business network through gateway equipment;
and collecting service processing information of the current business website through the management system of the business website.
Further, the determining the network point business transaction prediction data and the network point equipment operation prediction data of the target business network point according to the business processing information includes:
determining operation prediction data of the network point equipment according to the number of the current network point equipment, the bandwidth occupation amount of the current network point equipment and the current network point to-be-processed traffic;
and determining the site service handling prediction data according to the current site waiting service amount and the current site contemporaneous historical service handling total amount.
Further, when the predicted data of the network condition of the network point exceeds a threshold value, triggering a network abnormality early warning operation, including:
analyzing the change rate of the collected data in a set period, and determining a problem point causing network abnormality;
if the determined problem point belongs to the network equipment, starting the standby network equipment/port/interface, and then switching the network, or switching between the wired network and the wireless network, and judging whether the network is still abnormal or not again;
if the determined problem point belongs to the traffic volume to be handled of the network point, an early warning is sent to a network point manager end, and a corresponding device regulation strategy is determined according to the difference value between the network condition prediction data and the threshold value and the network point device condition.
In a second aspect, the present application provides a business website network exception handling apparatus, including:
the information acquisition module is used for acquiring network state information and service processing information of a target business website;
the data prediction module is used for determining the network operation condition of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information;
the abnormality early warning module is used for processing prediction data, network equipment operation prediction data and a network fluctuation prediction model according to the network operation condition and network point business, and obtaining the prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value.
Further, the information acquisition module includes:
the system comprises a wired network real-time state information acquisition unit, a gateway device and a network management unit, wherein the wired network real-time state information acquisition unit is used for acquiring wired network real-time state information of a business network through the gateway device;
and the business processing information acquisition unit is used for acquiring the business processing information of the current business website through the management system of the business website.
Further, the data prediction module includes:
the network point equipment operation prediction unit is used for determining network point equipment operation prediction data according to the number of the current network point network use equipment, the bandwidth occupation of the current network point network use equipment and the current network point to-be-processed traffic;
the network site business handling prediction unit is used for determining network site business handling prediction data according to the current network site waiting business volume and the current network site contemporaneous historical business handling total volume.
Further, the abnormality early warning module includes:
the abnormal positioning unit is used for analyzing the change rate of the acquired data in a set period and determining a problem point causing network abnormality;
the device exception handling unit is used for switching the network after starting the standby network device/port/interface or switching between the wired network and the wireless network if the determined problem point belongs to the network device itself, and re-judging whether the network is still abnormal;
and the business anomaly processing unit is used for sending an early warning to a website manager terminal if the determined problem point belongs to the website to-be-handled business volume, and determining a corresponding equipment regulation strategy according to the difference value between the network condition prediction data and the threshold value and the website equipment condition.
In a third aspect, the present application provides an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, where the processor implements the steps of the method for processing network anomalies in a business network when executing the program.
In a fourth aspect, the present application provides a computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of the method for handling network anomalies in a business network.
In a fifth aspect, the present application provides a computer program product comprising computer programs/instructions which when executed by a processor implement the steps of the method for handling network anomalies in a business network.
According to the technical scheme, the application provides a business network anomaly processing method and device, and network state information and business processing information of a target business network are acquired; determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information; obtaining the prediction data of the current network condition of the network according to the network operation condition, the network service transaction prediction data, the network equipment operation prediction data and the network fluctuation prediction model, and triggering network abnormality early warning operation when the predicted data of the network condition of the network point exceeds a threshold value, so that remedial measures can be executed when the network abnormality is monitored to ensure that the operation of the business network point is normal.
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 in the embodiments or the description of the prior art will be briefly described, and it is obvious that the drawings in the following description are some embodiments of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a method for handling network anomalies in a business website according to an embodiment of the present application;
FIG. 2 is a second flow chart of a method for handling network anomalies in a business website according to an embodiment of the present application;
FIG. 3 is a third flow chart of a method for handling network anomalies in a business website according to an embodiment of the present application;
FIG. 4 is a flowchart of a method for handling network anomalies in a business website according to an embodiment of the present application;
FIG. 5 is a block diagram of a network anomaly handling device for a business website in an embodiment of the present application;
FIG. 6 is a second block diagram of a network anomaly handling device for a business website in an embodiment of the present application;
FIG. 7 is a third block diagram of a network anomaly handling device for a business website in an embodiment of the present application;
FIG. 8 is a diagram illustrating a network anomaly handling device for a business website according to an embodiment of the present application;
fig. 9 is a schematic structural diagram of an electronic device in an embodiment of the present application.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the embodiments of the present application more clear, 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 apparent that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments herein without making any inventive effort, are intended to be within the scope of the present application.
The data acquisition, storage, use, processing and the like in the technical scheme meet the relevant regulations of national laws and regulations.
In consideration of the problems existing in the prior art, the application provides a business network anomaly processing method and device, which are implemented by collecting network state information and business processing information of a target business network; determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information; obtaining the prediction data of the current network condition of the network according to the network operation condition, the network service transaction prediction data, the network equipment operation prediction data and the network fluctuation prediction model, and triggering network abnormality early warning operation when the predicted data of the network condition of the network point exceeds a threshold value, so that remedial measures can be executed when the network abnormality is monitored to ensure that the operation of the business network point is normal.
In order to perform remedial measures to ensure that the operation of the business website is normal when the network anomaly is monitored, the present application provides an embodiment of a business website network anomaly processing method, referring to fig. 1, wherein the business website network anomaly processing method specifically includes the following contents:
step S101: network state information and business processing information of a target business website are collected.
Optionally, in this application, the service processing information includes: the method comprises the steps of current network usage equipment quantity, current network usage equipment bandwidth occupation quantity, current network usage equipment operation occupation ratio and current network to-be-processed (numbered) traffic.
Optionally, the method and the device can collect the real-time state information of the wired network of the business network through equipment such as a gateway.
Step S102: and determining the network operation condition of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information.
Optionally, in this application, the network operation condition includes, for example, a network load level and a network bandwidth ratio.
Optionally, in the present application, the operation prediction data of the network node device may be determined according to the number of devices used by the current network node, the bandwidth occupation of the devices used by the current network node, and the traffic to be processed by the current network node; and determining the site service handling prediction data according to the current site waiting service amount and the current site contemporaneous historical service handling total amount.
Step S103: according to the network operation condition, the network site business handling prediction data, the network site equipment operation prediction data and the network fluctuation prediction model, and obtaining the prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value.
Alternatively, the network fluctuation prediction model in the present application may use an existing artificial intelligence model, and the working process thereof is as follows: the flow prediction model can effectively judge the internet surfing behavior of the network user, predicts the application service, the watched program and the game which are possibly used by the user in a certain region and a certain period of time, further pushes the favorite content of the user to the network node closest to the user, even deploys the application program commonly used by the user on the node close to one end of the user, greatly reduces the network delay and improves the user experience. In addition, intelligent flow prediction can also provide more accurate basis for remote telecommunication 5G base station site selection.
The traditional prediction model can only conduct linear full-flow prediction aiming at a large core base station, only a small number of open source tools of a third party can conduct prediction aiming at specific network application flow, but the accuracy is not high, and effective guidance cannot be provided. The traffic prediction accuracy of different services on base stations of different levels is greatly improved through an AI technology.
As can be seen from the above description, the method for processing network anomalies in a business website provided by the embodiment of the present application can collect network status information and business processing information of a target business website; determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information; obtaining the prediction data of the current network condition of the network according to the network operation condition, the network service transaction prediction data, the network equipment operation prediction data and the network fluctuation prediction model, and triggering network abnormality early warning operation when the predicted data of the network condition of the network point exceeds a threshold value, so that remedial measures can be executed when the network abnormality is monitored to ensure that the operation of the business network point is normal.
In an embodiment of the method for handling network anomalies in a business network of the present application, referring to fig. 2, the step S101 may further specifically include the following:
step S201: and acquiring wired network real-time state information of the business network through gateway equipment.
Step S202: and collecting service processing information of the current business website through the management system of the business website.
In an embodiment of the method for handling network anomalies in a business network, referring to fig. 3, the step S102 may further specifically include the following:
step S301: and determining the running prediction data of the network point equipment according to the number of the current network point equipment, the bandwidth occupation amount of the current network point equipment and the current network point to-be-processed traffic.
Step S302: and determining the site service handling prediction data according to the current site waiting service amount and the current site contemporaneous historical service handling total amount.
In an embodiment of the method for handling network anomalies in a business network of the present application, referring to fig. 4, step S103 may further specifically include the following:
step S401: analyzing the change rate of the collected data in a set period, and determining the problem point causing network abnormality.
Step S402: if the determined problem point belongs to the network equipment, the standby network equipment/port/interface is started, then the network switching is carried out, or the switching between the wired network and the wireless network is carried out, and whether the network is still abnormal is judged again.
Step S403: if the determined problem point belongs to the traffic volume to be handled of the network point, an early warning is sent to a network point manager end, and a corresponding device regulation strategy is determined according to the difference value between the network condition prediction data and the threshold value and the network point device condition.
In order to perform remedial measures to ensure that the operation of the business network is normal when the network anomaly is detected, the present application provides an embodiment of a business network anomaly processing device for implementing all or part of the content of the business network anomaly processing method, referring to fig. 5, the business network anomaly processing device specifically includes the following contents:
the information acquisition module 10 is used for acquiring network state information and service processing information of the target business website.
The data prediction module 20 is configured to determine a network operation condition of the target business node according to the network state information, and determine node business handling prediction data and node equipment operation prediction data of the target business node according to the business processing information.
An anomaly early warning module 30 for providing a network fluctuation prediction model based on the network operation condition, the network point business transaction prediction data, the network point equipment operation prediction data and the network fluctuation prediction model, and obtaining the prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value.
As can be seen from the above description, the network anomaly handling device for a business website provided in the embodiment of the present application can collect network status information and service processing information of a target business website; determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information; obtaining the prediction data of the current network condition of the network according to the network operation condition, the network service transaction prediction data, the network equipment operation prediction data and the network fluctuation prediction model, and triggering network abnormality early warning operation when the predicted data of the network condition of the network point exceeds a threshold value, so that remedial measures can be executed when the network abnormality is monitored to ensure that the operation of the business network point is normal.
In one embodiment of the network anomaly handling device for a business website of the present application, referring to fig. 6, the information collecting module 10 includes:
and the wired network real-time state information acquisition unit 11 is used for acquiring the wired network real-time state information of the business network through the gateway equipment.
And the business processing information acquisition unit 12 is used for acquiring the business processing information of the current business website through the management system of the business website.
In one embodiment of the network anomaly handling device for a business website of the present application, referring to fig. 7, the data prediction module 20 includes:
the mesh point device operation prediction unit 21 is configured to determine mesh point device operation prediction data according to the number of current mesh point network usage devices, the bandwidth occupation amount of the current mesh point network usage devices, and the current mesh point pending traffic.
The site service transacting prediction unit 22 is configured to determine site service transacting prediction data according to the current site pending service volume and the current site contemporaneous historical service transacting total volume.
In an embodiment of the network anomaly handling device for a business website of the present application, referring to fig. 8, the anomaly early-warning module 30 includes:
an anomaly locating unit 31, configured to analyze the rate of change of the collected data in a set period, and determine a problem point that causes network anomaly.
The device exception handling unit 32 is configured to, if the determined problem point belongs to the network device itself, start the standby network device/port/interface and then switch the network, or switch between the wired network and the wireless network, and re-determine whether the network is still abnormal.
The business anomaly processing unit 33 is configured to send an early warning to a website administrator if the determined problem point belongs to the website to-do traffic, and determine a corresponding device regulation policy according to the difference between the predicted data of the network condition and the threshold value and the website device condition.
In order to perform remedial measures to ensure that a business node operates normally when a network abnormality is detected, the application provides an embodiment of an electronic device for implementing all or part of the content in the business node network abnormality processing method, where the electronic device specifically includes the following contents:
a processor (processor), a memory (memory), a communication interface (Communications Interface), and a bus; the processor, the memory and the communication interface complete communication with each other through the bus; the communication interface is used for realizing information transmission between the business network abnormality processing device and related equipment such as a core business system, a user terminal, a related database and the like; the logic controller may be a desktop computer, a tablet computer, a mobile terminal, etc., and the embodiment is not limited thereto. In this embodiment, the logic controller may refer to an embodiment of the business node network exception handling method and an embodiment of the business node network exception handling device in the embodiments, and the contents thereof are incorporated herein, and the repetition is omitted.
It is understood that the user terminal may include a smart phone, a tablet electronic device, a network set top box, a portable computer, a desktop computer, a Personal Digital Assistant (PDA), a vehicle-mounted device, a smart wearable device, etc. Wherein, intelligent wearing equipment can include intelligent glasses, intelligent wrist-watch, intelligent bracelet etc..
In practical application, part of the business network anomaly handling method may be executed on the electronic device side as described above, or all operations may be completed in the client device. Specifically, the selection may be made according to the processing capability of the client device, and restrictions of the use scenario of the user. The present application is not limited in this regard. If all operations are performed in the client device, the client device may further include a processor.
The client device may have a communication module (i.e. a communication unit) and may be connected to a remote server in a communication manner, so as to implement data transmission with the server. The server may include a server on the side of the task scheduling center, and in other implementations may include a server of an intermediate platform, such as a server of a third party server platform having a communication link with the task scheduling center server. The server may include a single computer device, a server cluster formed by a plurality of servers, or a server structure of a distributed device.
Fig. 9 is a schematic block diagram of a system configuration of an electronic device 9600 of an embodiment of the present application. As shown in fig. 9, the electronic device 9600 may include a central processor 9100 and a memory 9140; the memory 9140 is coupled to the central processor 9100. Notably, this fig. 9 is exemplary; other types of structures may also be used in addition to or in place of the structures to implement telecommunications functions or other functions.
In one embodiment, the business network anomaly handling method functionality may be integrated into the central processor 9100. The central processor 9100 may be configured to perform the following control:
step S101: network state information and business processing information of a target business website are collected.
Step S102: and determining the network operation condition of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information.
Step S103: according to the network operation condition, the network site business handling prediction data, the network site equipment operation prediction data and the network fluctuation prediction model, and obtaining the prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value.
As can be seen from the above description, the electronic device provided in the embodiment of the present application collects network status information and service processing information of a target business website; determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information; obtaining the prediction data of the current network condition of the network according to the network operation condition, the network service transaction prediction data, the network equipment operation prediction data and the network fluctuation prediction model, and triggering network abnormality early warning operation when the predicted data of the network condition of the network point exceeds a threshold value, so that remedial measures can be executed when the network abnormality is monitored to ensure that the operation of the business network point is normal.
In another embodiment, the abnormal processing device of the business network may be configured separately from the cpu 9100, for example, the abnormal processing device of the business network may be configured as a chip connected to the cpu 9100, and the function of the abnormal processing method of the business network is implemented by the control of the cpu.
As shown in fig. 9, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is noted that the electronic device 9600 need not include all of the components shown in fig. 9; in addition, the electronic device 9600 may further include components not shown in fig. 9, and reference may be made to the related art.
As shown in fig. 9, the central processor 9100, sometimes referred to as a controller or operational control, may include a microprocessor or other processor device and/or logic device, which central processor 9100 receives inputs and controls the operation of the various components of the electronic device 9600.
The memory 9140 may be, for example, one or more of a buffer, a flash memory, a hard drive, a removable media, a volatile memory, a non-volatile memory, or other suitable device. The information about failure may be stored, and a program for executing the information may be stored. And the central processor 9100 can execute the program stored in the memory 9140 to realize information storage or processing, and the like.
The input unit 9120 provides input to the central processor 9100. The input unit 9120 is, for example, a key or a touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used for displaying display objects such as images and characters. The display may be, for example, but not limited to, an LCD display.
The memory 9140 may be a solid state memory such as Read Only Memory (ROM), random Access Memory (RAM), SIM card, etc. But also a memory which holds information even when powered down, can be selectively erased and provided with further data, an example of which is sometimes referred to as EPROM or the like. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application/function storage portion 9142, the application/function storage portion 9142 storing application programs and function programs or a flow for executing operations of the electronic device 9600 by the central processor 9100.
The memory 9140 may also include a data store 9143, the data store 9143 for storing data, such as contacts, digital data, pictures, sounds, and/or any other data used by an electronic device. The driver storage portion 9144 of the memory 9140 may include various drivers of the electronic device for communication functions and/or for performing other functions of the electronic device (e.g., messaging applications, address book applications, etc.).
The communication module 9110 is a transmitter/receiver 9110 that transmits and receives signals via an antenna 9111. A communication module (transmitter/receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, as in the case of conventional mobile communication terminals.
Based on different communication technologies, a plurality of communication modules 9110, such as a cellular network module, a bluetooth module, and/or a wireless local area network module, etc., may be provided in the same electronic device. The communication module (transmitter/receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and to receive audio input from the microphone 9132 to implement usual telecommunications functions. The audio processor 9130 can include any suitable buffers, decoders, amplifiers and so forth. In addition, the audio processor 9130 is also coupled to the central processor 9100 so that sound can be recorded locally through the microphone 9132 and sound stored locally can be played through the speaker 9131.
The embodiments of the present application further provide a computer readable storage medium capable of implementing all the steps in the business network exception handling method in which the execution subject in the above embodiment is a server or a client, where the computer readable storage medium stores a computer program, and when the computer program is executed by a processor, the computer program implements all the steps in the business network exception handling method in which the execution subject in the above embodiment is a server or a client, for example, the processor implements the following steps when executing the computer program:
step S101: network state information and business processing information of a target business website are collected.
Step S102: and determining the network operation condition of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information.
Step S103: according to the network operation condition, the network site business handling prediction data, the network site equipment operation prediction data and the network fluctuation prediction model, and obtaining the prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value.
As can be seen from the above description, the computer readable storage medium provided in the embodiments of the present application collects network status information and service processing information of a target business website; determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information; obtaining the prediction data of the current network condition of the network according to the network operation condition, the network service transaction prediction data, the network equipment operation prediction data and the network fluctuation prediction model, and triggering network abnormality early warning operation when the predicted data of the network condition of the network point exceeds a threshold value, so that remedial measures can be executed when the network abnormality is monitored to ensure that the operation of the business network point is normal.
The embodiments of the present application further provide a computer program product capable of implementing all the steps in the business network exception handling method in which the execution subject in the above embodiments is a server or a client, where the computer program/instructions implement the steps of the business network exception handling method when executed by a processor, for example, the computer program/instructions implement the steps of:
step S101: network state information and business processing information of a target business website are collected.
Step S102: and determining the network operation condition of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information.
Step S103: according to the network operation condition, the network site business handling prediction data, the network site equipment operation prediction data and the network fluctuation prediction model, and obtaining the prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value.
As can be seen from the above description, the computer program product provided in the embodiments of the present application collects network status information and service processing information of a target business website; determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information; obtaining the prediction data of the current network condition of the network according to the network operation condition, the network service transaction prediction data, the network equipment operation prediction data and the network fluctuation prediction model, and triggering network abnormality early warning operation when the predicted data of the network condition of the network point exceeds a threshold value, so that remedial measures can be executed when the network abnormality is monitored to ensure that the operation of the business network point is normal.
It will be apparent to those skilled in the art that embodiments of the present invention may be provided as a method, apparatus, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (devices), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
The principles and embodiments of the present invention have been described in detail with reference to specific examples, which are provided to facilitate understanding of the method and core ideas of the present invention; meanwhile, as those skilled in the art will have variations in the specific embodiments and application scope in accordance with the ideas of the present invention, the present description should not be construed as limiting the present invention in view of the above.

Claims (11)

1. A business network anomaly handling method, the method comprising:
collecting network state information and business processing information of a target business website;
determining network operation conditions of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information;
according to the network operation condition, the network site business handling prediction data, the network site equipment operation prediction data and the network fluctuation prediction model, and obtaining the prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value.
2. The method for processing network anomalies of a business point according to claim 1, wherein the collecting network state information and business processing information of a target business point comprises:
collecting wired network real-time state information of a business network through gateway equipment;
and collecting service processing information of the current business website through the management system of the business website.
3. The business website network anomaly handling method of claim 1, wherein determining website business transaction prediction data and website equipment operation prediction data of the target business website according to the business processing information comprises:
determining operation prediction data of the network point equipment according to the number of the current network point equipment, the bandwidth occupation amount of the current network point equipment and the current network point to-be-processed traffic;
and determining the site service handling prediction data according to the current site waiting service amount and the current site contemporaneous historical service handling total amount.
4. The method for processing network anomalies of a business network according to claim 1, wherein triggering the network anomaly early warning operation when the predicted data of the network conditions of the network exceeds a threshold value comprises:
analyzing the change rate of the collected data in a set period, and determining a problem point causing network abnormality;
if the determined problem point belongs to the network equipment, starting the standby network equipment/port/interface, and then switching the network, or switching between the wired network and the wireless network, and judging whether the network is still abnormal or not again;
if the determined problem point belongs to the traffic volume to be handled of the network point, an early warning is sent to a network point manager end, and a corresponding device regulation strategy is determined according to the difference value between the network condition prediction data and the threshold value and the network point device condition.
5. A business network anomaly handling device, comprising:
the information acquisition module is used for acquiring network state information and service processing information of a target business website;
the data prediction module is used for determining the network operation condition of the target business website according to the network state information, and determining website business handling prediction data and website equipment operation prediction data of the target business website according to the business processing information;
the abnormality early warning module is used for processing prediction data, network equipment operation prediction data and a network fluctuation prediction model according to the network operation condition and network point business, and obtaining the prediction data of the current network condition of the network node, and triggering network abnormality early warning operation when the prediction data of the network condition of the network node exceeds a threshold value.
6. The business network anomaly processing device of claim 5, wherein the information acquisition module comprises:
the system comprises a wired network real-time state information acquisition unit, a gateway device and a network management unit, wherein the wired network real-time state information acquisition unit is used for acquiring wired network real-time state information of a business network through the gateway device;
and the business processing information acquisition unit is used for acquiring the business processing information of the current business website through the management system of the business website.
7. The business network anomaly processing device of claim 5, wherein the data prediction module comprises:
the network point equipment operation prediction unit is used for determining network point equipment operation prediction data according to the number of the current network point network use equipment, the bandwidth occupation of the current network point network use equipment and the current network point to-be-processed traffic;
the network site business handling prediction unit is used for determining network site business handling prediction data according to the current network site waiting business volume and the current network site contemporaneous historical business handling total volume.
8. The business network anomaly processing device of claim 5, wherein the anomaly early warning module comprises:
the abnormal positioning unit is used for analyzing the change rate of the acquired data in a set period and determining a problem point causing network abnormality;
the device exception handling unit is used for switching the network after starting the standby network device/port/interface or switching between the wired network and the wireless network if the determined problem point belongs to the network device itself, and re-judging whether the network is still abnormal;
and the business anomaly processing unit is used for sending an early warning to a website manager terminal if the determined problem point belongs to the website to-be-handled business volume, and determining a corresponding equipment regulation strategy according to the difference value between the network condition prediction data and the threshold value and the website equipment condition.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor performs the steps of the method for handling network anomalies in a point of sale according to any one of claims 1 to 4 when the program is executed.
10. A computer readable storage medium having stored thereon a computer program, which when executed by a processor, implements the steps of the business website network anomaly handling method of any one of claims 1 to 4.
11. A computer program product comprising computer programs/instructions which when executed by a processor implement the steps of the business node network anomaly handling method of any one of claims 1 to 4.
CN202310369781.0A 2023-04-07 2023-04-07 Business network anomaly handling method and device Pending CN116471206A (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202310369781.0A CN116471206A (en) 2023-04-07 2023-04-07 Business network anomaly handling method and device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202310369781.0A CN116471206A (en) 2023-04-07 2023-04-07 Business network anomaly handling method and device

Publications (1)

Publication Number Publication Date
CN116471206A true CN116471206A (en) 2023-07-21

Family

ID=87176427

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202310369781.0A Pending CN116471206A (en) 2023-04-07 2023-04-07 Business network anomaly handling method and device

Country Status (1)

Country Link
CN (1) CN116471206A (en)

Similar Documents

Publication Publication Date Title
CN109861856B (en) Method and device for notifying system fault information, storage medium and computer equipment
CN111782470B (en) Distributed container log data processing method and device
CN108804294A (en) Method, apparatus, equipment and the computer readable storage medium that electricity is reminded
CN111740860A (en) Log data transmission link monitoring method and device
CN104822174A (en) Calling mode adjusting method
CN113055479A (en) Self-adaptive processing method, device and system for distributed service cluster load
CN112764919A (en) Distributed service self-adaptive load balancing method and device
CN112965799A (en) Task state prompting method and device, electronic equipment and medium
CN115914375A (en) Disaster tolerance processing method and device for distributed message platform
CN116471206A (en) Business network anomaly handling method and device
CN113190516B (en) Data synchronization monitoring method and device
CN113808376B (en) Self-service teller machine equipment safety monitoring method and device
CN116185755A (en) Data processing method and device for distributed load balancing system
CN104571466A (en) Electricity saving method and device for multi-system terminal
CN104812033A (en) Terminal
CN108023741B (en) Monitoring resource use method and server
CN112994934B (en) Data interaction method, device and system
CN114697339A (en) Load balancing method and device under centralized architecture
CN116316983A (en) Network point power monitoring method and device
CN112101810A (en) Risk event control method, device and system
CN113612659A (en) Equipment networking test method and device, electronic equipment and storage medium
CN114338536B (en) Scheduling method, device, equipment and medium based on block chain
CN111352806B (en) Log data monitoring method and device
CN113839399B (en) New energy station high-frequency oscillation risk processing method and device
CN110996374B (en) Wireless network control method, device, equipment and medium

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