KR102638146B1 - Method and system for 5g network task automation - Google Patents

Abstract

A method of operating a network task automation system, comprising: setting a network task and at least one network task item constituting the network task; scripts for executing the task item on devices for each of the at least one network task item; Registering the scripts on a per-vendor basis, transmitting scripts registered on a per-vendor basis to devices of the corresponding manufacturer, and receiving execution results of the scripts from the devices, wherein the script Includes commands in a format supported by the manufacturer.

Description

5G network task automation method and system {METHOD AND SYSTEM FOR 5G NETWORK TASK AUTOMATION}

The present invention relates to a method and system for automating 5G network operations.

Network operators connect to numerous network devices and perform various operational tasks. Operational tasks are largely divided into tasks of retrieving specific information and tasks of setting specific information.

As the type and quantity of network equipment (e.g., PNF (Physical Network Function), VNF (virtual network function), Switch, etc.) in the 5G environment increases and manufacturers become more diverse, consistent work is performed with network equipment at once. It's difficult to do. This is because each manufacturer has different execution commands, formats, and methods for work items. Methods may include NetConf, API (Application Programming Interface), CLI (Command-line interface), etc.

To perform the same task with network equipment from different manufacturers, commands must be executed for each device. In the case of existing network equipment, the operator must directly access each equipment, go through a process such as logging in, and then perform tasks such as querying equipment information and setting equipment using different CLI commands for each equipment manufacturer.

If equipment, tasks, or work items from a manufacturer that did not previously exist are added, an upgrade of the system is necessary.

For each manufacturer, it is necessary to develop additional driver plug-ins suitable for the system or develop them for the corresponding task inside the system.

The problem to be solved is to provide a method and system to automatically perform the same task on network devices from different manufacturers by flexibly and easily accepting them without system changes or additional development even if a new task is added or a new manufacturer's network device is added. It is done.

According to one feature, a method of operating a network task automation system operated by at least one processor, comprising: setting a network task and at least one network task item constituting the network task; registering scripts for executing the work item on devices on a per-manufacturer basis, transmitting scripts created on a per-vendor basis to devices of the corresponding manufacturer, and transmitting the scripts from the devices. and receiving execution results of the scripts, and the scripts include commands in a format supported by the manufacturer.

The step of receiving the execution result includes receiving job execution result data in different formats for each manufacturer, and after receiving the execution result, extracting predefined essential item data from the job execution result data, extracted It may include converting essential item data into job execution result data in a generalized data format using regular expressions of each manufacturer, and outputting the converted job execution result data on an operator screen.

After receiving the execution result, determining whether the work result included in the execution result satisfies normal conditions, and if the normal condition is met, mapping the accuracy of the work items to the work items The step of storing and updating the normal judgment condition of the task based on the accuracy may be further included.

After the determining step, if the normal condition is not met, searching for at least one work item in the work list in order of high accuracy, and setting the priority of the searched work item based on the accuracy. Further comprising, the network task automation system transmits manufacturer-level scripts for the searched work items to the devices according to the set priority, receives execution results of the scripts from the devices, and receives execution results of the scripts from the devices. The operation of determining whether normal conditions are met can be repeated.

After the setting step, based on artificial intelligence technology, it may further include a step of preferentially executing the task selected from the task list based on the number of devices connected to the device that is the work target, the time required for the task, and the priority. there is.

According to another feature of the present invention, a network task automation system includes a communication device that performs communication using a pre-agreed protocol with a plurality of devices, a memory storing a program that performs network task automation, and at least one processor that executes the program. It includes, wherein the at least one processor sets a network task and at least one network work item constituting the network task, and executes the scripts on devices for each of the at least one network work item. Devices are registered on a per-vendor basis, the scripts registered on a per-vendor basis are transmitted to a device group of the same manufacturer at a designated time, and the execution results of the scripts are received and stored from the device group. The stored execution results are , it is output to the user's external device.

The processor executes a query task script including a command execution script, a data extraction script, and a data generalization script for each manufacturer, transmits the command execution script to a device, receives a script execution result, and executes the data extraction script. Executes to extract predetermined result data from the script execution results, executes the data generalization script to convert the extracted result data into result data in a common generalized format through a regular expression, and generates the result data in the generalized format. You can save it.

The processor may execute a setup work item script for creation format, deletion format, and update format on a per-manufacturer basis.

The processor sets conditions for determining whether the script execution result is normal or abnormal, sets at least one action task to be performed when it is determined to be abnormal according to the set conditions, and executes the received scripts. If the result is abnormal, a script corresponding to the at least one action task set above may be created, and the created script may be transmitted to the device.

The processor selects action tasks in order of high priority from a preset action task list, transmits a script corresponding to the selected action task to the device, and receives the script execution result from the device. This is the normal script execution result. This can be repeated until is received.

The processor determines whether the work result included in the execution result satisfies normal conditions, and if the normal condition is satisfied, maps the accuracy of the work item to the work item and stores it, and the accuracy of the work item is: It can be used to prioritize the above action tasks.

The processor may update the normal judgment condition of the task based on the accuracy.

According to the embodiment, a flexible structure is presented so that tasks can be performed as defined by the user, and the same tasks can be performed in batches on heterogeneous network devices without additional development of the system.

1 is a diagram schematically explaining the operation of a network task automation system according to an embodiment.
Figure 2 is a diagram explaining the operation of a conventional network task automation system.
3 shows a network task automation system according to an embodiment.
Figure 4 is a flowchart showing a method for automating network tasks according to an embodiment.
Figure 5 shows a script execution process according to one embodiment.
Figure 6 shows a script execution process according to another embodiment.
Figure 7 explains the data extraction process according to the embodiment.
Figure 8 is an example of work result data according to one embodiment.
Figure 9 is an example of work result data according to another embodiment.
Figure 10 is a block diagram showing the hardware configuration of a computing device according to an embodiment.

Below, with reference to the attached drawings, embodiments of the present invention will be described in detail so that those skilled in the art can easily implement the present invention. However, the present invention may be implemented in various different forms and is not limited to the embodiments described herein. In order to clearly explain the present invention in the drawings, parts that are not related to the description are omitted, and similar parts are given similar reference numerals throughout the specification.

Throughout the specification, when a part is said to “include” a certain element, this means that it may further include other elements rather than excluding other elements, unless specifically stated to the contrary.

In addition, terms such as “…unit”, “…unit”, and “…module” used in the specification refer to a unit that processes at least one function or operation, which may be implemented through hardware or software or a combination of hardware and software. You can.

The devices described in the present invention are composed of hardware including at least one processor, a memory device, a communication device, etc., and a program that is executed in conjunction with the hardware is stored in a designated location. The hardware has a configuration and performance capable of executing the method of the present invention. The program includes instructions that implement the operating method of the present invention described with reference to the drawings, and executes the present invention by combining it with hardware such as a processor and memory device.

In this specification, “transmission or provision” may include not only direct transmission or provision, but also indirect transmission or provision through another device or by using a circuitous route.

In this specification, expressions described as singular may be interpreted as singular or plural, unless explicit expressions such as “one” or “single” are used.

In this specification, the same reference numbers refer to the same elements regardless of the drawings, and “and/or” includes each and all combinations of one or more of the mentioned elements.

In this specification, terms including ordinal numbers, such as first, second, etc., may be used to describe various components, but the components are not limited by the terms. The above terms are used only for the purpose of distinguishing one component from another. For example, a first component may be referred to as a second component, and similarly, the second component may also be referred to as a first component without departing from the scope of the present disclosure.

In the flowcharts described herein with reference to the drawings, the order of operations may be changed, several operations may be merged, certain operations may be divided, and certain operations may not be performed.

In the specification, the terminal (Terminal/User equipment) connects to the base station of the Access Network/Radio Access network (RAN) and uses the network functions (NFs) of the Core Network. Here, the base station may include an eNB, gNB, AP, etc. depending on the access network. The terminal may be of various types and purposes, such as a portable terminal, IoT terminal, vehicle terminal, display terminal, broadcast terminal, and game terminal. The devices that make up the network may be implemented as hardware, software, or a combination of hardware and software.

Embodiments of the present invention are 3GPP, such as 3rd Generation Partnership Project (3GPP) Long Term Evolution (LTE), LTE-A, 3GPP2, Institute of Electrical and Electronics Engineers (IEEE) system, and Study on Architecture for Next Generation System (FS_NextGen) It may be supported by a standard document related to at least one of the 5G systems. That is, among the embodiments of the present invention, steps or parts not described in order to clearly reveal the technical idea of the present invention may be supported by the above document. Additionally, all terms disclosed in this document can be explained by the standard document.

FIG. 1 is a diagram schematically explaining the operation of a network task automation system according to an embodiment, and FIG. 2 is a diagram explaining the operation of a conventional network task automation system.

At this time, since no change to the device 200 is required in the embodiment of the present invention, the device 200 in FIGS. 1 and 2 uses the same reference numeral, and the network task automation systems 100 and 300 are used for their operation. Because these are different, the reference numerals are used differently.

Referring to FIG. 1, a network task automation system 100 according to an embodiment may be a computing device including a communication device, memory, and at least one processor.

The communication device may perform communication using a pre-agreed protocol with a plurality of devices 200. Here, the pre-agreed communication protocol may include a terminal connection method. For example, the terminal connection method may include telnet or SSH (Secure Shell) protocol.

The memory may store programs that perform network task automation. At least one processor executing the program may be a management engine 110 and an automation engine 130.

The management engine 110 defines the task and the items constituting the task, and the automation engine 130 transmits the task item script registered in the management engine 110 by the operator to the device group 200 of the same manufacturer, Network task automation can be performed in batches.

At this time, the automation engine 130 may transmit a work item script to the devices 200 and receive the results using a terminal connection method provided by default in the devices 200. In other words, by simply registering a work script containing commands that can be executed on a specific manufacturer (vendor) or the manufacturer's device 200 for each work item, blanket automation of network work is possible regardless of the manufacturer.

On the other hand, referring to FIG. 2, the conventional task automation system 300 requires a network task to be automatically performed to be developed in the system.

Additionally, work items constituting the work must also be defined in the work automation system 300. If there are multiple work items to be performed for each task, there is a command to perform each work item. That is, work item : instruction = 1 : (1…N). At this time, a driver program or plug-in program that can execute commands corresponding to each work item with devices 200 from different manufacturers must be installed in the network task automation system 300.

However, the plug-in program may not support all commands provided by the device 200. For example, task #1 may consist of item #1 and item #2. To perform item #1, each manufacturer has different commands. Manufacturer A's device 200 receives Manufacturer A's instructions, Manufacturer B's instructions, and Manufacturer C's instructions to perform item #1, and Manufacturer A's instructions, Manufacturer B's instructions, and Manufacturer C's instructions to perform Item #2. Each command may be required to be executed. Manufacturer A's device 200 may need to execute Manufacturer A's command to perform item #1 and Manufacturer B's command to perform item #2. Therefore, the network task automation system 300 must be installed with a plug-in program or driver program that supports commands for each manufacturer.

As such, conventionally, it is necessary to install a separate program, that is, a plug-in or driver, that supports commands for each manufacturer rather than a work item. Additionally, when manufacturer X is added, a plug-in or driver that supports manufacturer X's new command format must be added.

Additionally, when adding a new task, new task definition and additional development are required in the network task automation system 300. Additionally, since multiple items are set within one task, when new items are added, additional development of new items is required in the network task automation system 300. At this time, the command to perform the new item to be added must be supported by the plug-in or driver. If it is not supported, development of a plug-in, driver, or separate program is required to execute the command. Additionally, when adding a device from a new manufacturer, a plug-in or driver that supports commands recognized by the added device must be installed in the network task automation system 300.

In this way, if the existing plug-in or driver supports the instructions to perform the added item or the additional manufacturer's command format, only the work item and the manufacturer need to be developed additionally, but if it is not supported, additional development of the plug-in or driver itself is required. do.

However, as described in FIG. 1, in the embodiment of the present invention, the manufacturer command of the device 200 is accepted only by registering a script for each task and item of the task, so there is no need for separate program development. Additionally, even if a new manufacturer is added, the new manufacturer's device 200 can be controlled by simply registering the manufacturer's command format.

FIG. 3 is a diagram showing the detailed configuration of a network task automation system according to another embodiment. In particular, the detailed configuration of the management engine 110 and automation engine 130 of FIG. 1 is explained.

Referring to FIG. 3, the management engine 110 registers and stores work item scripts on a vendor basis at the operator's request. The automation engine 130 may transmit and execute a manufacturer-level work item script registered in the management engine 110 to the device 200 or device group 200 of the manufacturer at a specified period or at a specific time.

The management engine 110 is an engine that sets and/or manages information necessary for network task automation, and may be implemented in the form of a database server. The management engine 110 can manage information set by the user.

The automation engine 130 is connected to a plurality of devices 200. Here, the plurality of devices 200 are network work targets and may be network equipment. According to an embodiment, the plurality of devices 200 may include core equipment, base station equipment, etc. that constitute a 5G network.

Even though the plurality of devices 200 perform the same network function, they may be from different manufacturers. The plurality of devices 200 may be manufactured by different manufacturers for each device that performs different network functions. The plurality of devices 200 may be devices from the same manufacturer and form a group.

The automation engine 130 transmits a script to control the device 200 for each manufacturer based on information set by the management engine 110. The automation engine 130 collects and processes information according to script execution. The automation engine 130 stores the processed information in the database of the management engine 110. Information stored in the database is provided to the operator through an external device. The external device may be a display device.

The management engine 110 executes a plurality of functions, and the plurality of functions include task management, inquiry command management, setup command management, work item management, parsing rule definition, setup command execution, target equipment management, data generalization definition, and database ( DB) management, includes management of work item judgment criteria, management of action task mapping for each work item, and optimization management of work items and judgment criteria.

Here, the management engine 110 performs task management to register, modify, and delete tasks to be performed on a plurality of devices 200. The management engine 110 defines the execution type of the task to be performed on the plurality of devices 200. Execution types may include execution cycle settings and automatic/manual execution settings.

The management engine 110 manages query commands and setup commands to register, modify, and delete query commands and setup commands for work. At this time, the setup command includes a CREATE command, an UPDATE command, and a DELETE command.

The management engine 110 performs work item management including registration, modification, and deletion of work items constituting the work. Types of work items are divided into viewable items and configurable items. The management engine 110 defines a command execution script, parsing rule script, and data generalization script when registering a query item. Work commands are defined for each work item. Since work commands are different for each manufacturer and the results of executing work commands are also different for each manufacturer, work items must be defined for each manufacturer. Since the setting commands of the device 200 for each manufacturer are different, definition of work items for each manufacturer is necessary to perform the task even if it is the same task. Therefore, work item management includes management of work items by manufacturer.

The management engine 110 performs parsing rule definitions. Parsing rule definition is a function that defines regular expressions to extract the data required for each task from the results of executing the task command. Here, a regular expression refers to a formal language used to express a set of strings with specific rules.

The management engine 110 performs configuration command execution management. Executing configuration commands includes management functions such as registering, modifying, and deleting configuration command scripts.

When registering setting items, the management engine 110 performs script registration in the CREATE command format, DELETE command format, and UPDATE command format.

The management engine 110 performs target device management. Target device management includes management of registering, modifying, and deleting information on network devices that are the target of work.

Management engine 110 performs data generalization definition. Data generalization definition includes the function of defining a data generalization format to provide work command execution results in a unified form.

The management engine 110 may hold and manage a separate database. The database stores information necessary for the operation of the management engine 110 and automation engine 130. At this time, the database is operated according to the operation of the management engine 110, that is, query command management, setting command management, work item management, parsing rule definition, setting command execution, target equipment management, data generalization definition, work item judgment criteria management, You can save each information according to the action task mapping management for each work item and the optimization of work items and judgment criteria.

The management engine 110 manages work item judgment standards, manages action task mapping for each work item, and optimizes work items and judgment standards. At this time, the management engine 110 may perform management according to the request or control of the automation engine 130.

Management of work item judgment standards includes management such as registration, modification, and deletion of conditions for judging normal and abnormal conditions from work execution results. Action task mapping management for each work item includes management of mapping action tasks when the task execution result is judged to be abnormal. Optimization of work items and judgment standards includes management of optimizing action items and normal/abnormal judgment conditions by updating the work items and normal/abnormal judgment conditions after taking action on abnormal work execution results.

When a user selects or enters a queryable work item through a user interface device, the management engine 110 can perform work item management, query command management, parsing rule definition, and data generalization definition.

When a user selects or inputs a configurable work item through a user interface device, the management engine 110 can perform work item management, setup command management, and setup command execution management.

The automation engine 130 executes a job script that controls the device 200 for each manufacturer based on the database information of the management engine 110 and in conjunction with the management engine 110. Additionally, the automation engine 130 collects and processes information according to job script execution.

The automation engine 130 performs multiple functions, and the multiple functions may include script scheduler, script execution, data extraction, and data generalization.

The automation engine 130 executes a task command script and inputs a task command to be performed. The automation engine 130 executes a parsing rule script, selects a part to be extracted from the task command execution result, and writes it as a regular expression. The automation engine 130 executes a data generalization script and writes the extracted data into a generalization format for storing in the database.

The automation engine 130 performs script scheduling based on scheduling information according to task management of the management engine 110.

The automation engine 130 transmits and executes work commands to the device 200 using a terminal connection method provided by the device 200, which is the target of network work, without a separate device, and receives the results.

The automation engine 130 extracts only the desired data from the received results and determines whether the extracted data is normal or abnormal according to the judgment criteria defined for each work item.

If the task result is normal, the task result stored in the management engine 110 may be provided to the user.

If the work result is abnormal, the automation engine 130 can automatically perform the action tasks defined for each work item to successfully complete the work.

Additionally, depending on the task success rate, the management engine 110 may provide a high task success rate by optimizing the preset normal/abnormal judgment criteria. At this time, in the case of a numerical range as the judgment standard, continuous optimization can be performed to achieve a high success rate through subtle value changes.

Additionally, if the task result is abnormal, the management engine 110 searches for action tasks to be performed on the target task at the request of the automation engine 130 and provides the query result. The automation engine 130 automatically executes the action script queried by the management engine 110, extracts necessary data from the execution result, generalizes it, and stores it in the database.

The automation engine 130 performs accuracy calculation and judgment criteria optimization according to the action results. The automation engine 130 applies optimized judgment criteria according to accuracy.

Work items defined by the management engine 110 are executed on a work target device 200 in work units. The defined task is delivered to the automation engine 130, and based on the connection information of the device 200, the device 200 is connected to the device 200 using telnet or SSH (Secure Shell) protocol, each command is executed, and the results are received from the device 200. is received. That is, the registered task information is delivered to the script scheduler of the automation engine 130 according to the execution method. The script scheduler of the automation engine 130 is executed periodically/manually depending on the execution method. The automation engine 130 executes the command of the defined script on the device 200 and receives the execution result. Then, the automation engine 130 extracts necessary data from the execution result according to a parsing rule defined as a regular expression. Then, the extracted data is generalized to be managed as data of the same type, and then stored in the database.

Additionally, the automation engine 130 performs script scheduling to dynamically execute a command execution script registered in the management engine 110 to the device 200. The automation engine 130 executes the setup command script to the device 200.

The automation engine 130 processes task execution results, such as report alarms and statistical error information, and registers them in the database of the management engine 110.

Figure 4 shows a network task automation process according to one embodiment, Figure 5 shows a script execution process according to one embodiment, Figure 6 shows a script execution process according to another embodiment, and Figure 7 shows an embodiment. The data extraction process according to the present invention will be described, and FIG. 8 is an example of work result data according to one embodiment, and FIG. 9 is an example of work result data according to another embodiment.

Referring to FIG. 4, the management engine 110 of the network task automation system 100 sets tasks and task items (S101). For example, tasks may include inspection reports of 5G core equipment, SMF inspection reports, UPF inspection reports, AMF inspection reports, etc. One task consists of at least one work item. For example, a UPF inspection report may include a UPF traffic information collection work item.

The management engine 110 creates a task according to a user request or user input. It defines tasks grouped into a plurality of task items and sets the task name, execution method (cycle/manual), and target equipment. For example, when creating an AMF inspection report task, the management engine 110 may set the execution cycle to once a day and designate the work target equipment as Manufacturer A_AMF and Manufacturer B_AMF.

The management engine 110 sets conditions for determining whether the work result is normal or abnormal and an action to be taken if it is abnormal (S103). For example, if the work item is to collect UPF traffic information, the management engine 110 can set a condition that is normal or abnormal if the collected UPF traffic is below a certain level. Additionally, when UPF traffic increases, the management engine 110 may set a call bypass task for the national AMF to divert calls to another office as an action task. At this time, you can delete the SMF linked to the corresponding UPF from the existing AMF and set alternative SMF information to link again.

The management engine 110 sets inspection standards, that is, normal conditions/abnormal conditions, for each work item, and the automation engine 130 can generate a work result report according to the set standards. For example, if the CPU usage rate for 5 minutes is less than 70%, it can be set as normal, and if it is more than that, it can be set as abnormal.

The automation engine 130 executes a script for each work item (S105).

The automation engine 130 may periodically automatically execute scripts composed of commands for each work item and parser scripts to parse information to be reported, or execute them manually according to user input.

According to embodiments, the inquiry work item script may include a command execution script, a data extraction script, and a data generalization script.

The command execution script consists of commands for work items on the target device. The data extraction script may include regular expressions to extract the required data from the command execution results. The data generalization script may be configured in a format that generalizes the extracted data for the heterogeneous device 200. Manufacturer commands for each work item can be defined as shown in Table 1.

action item ManufacturerA_AMF command ManufacturerB_AMF command Port status inquiry RTRV-PORT-STS show port table Interlocking node status inquiry RTRV-NE-STS show egtpc peers

Referring to FIG. 5, the automation engine 130 extracts essential data (P11) from data (P1) as a result of executing a command script for a port status inquiry task targeting AMF of manufacturer A. The automation engine 130 may process the extracted essential data (P11) into generalized metadata (P5) using a regular expression (P3) and store it in a database.

Referring to FIG. 6, the automation engine 130 extracts essential data (P71) from data (P7) as a result of executing a command script for a port status inquiry task targeting Manufacturer B's AMF. The automation engine 130 may process the extracted essential data (P71) into generalized metadata (P11) using a regular expression (P9) and store it in a database.

Referring to Figures 5 and 6, the required data (P11, P71) extracted as the result data (P1, P7) is different for each manufacturer, but it is processed into generalized data by processing it through regular expressions. At this time, the generalized data format is the same for all manufacturers.

According to an embodiment, the setup work item script may include a CREATE format, a DELETE format, and an UPDATE format. The CREATE format includes a command format for making new settings. The DELETE format includes a command format to erase existing settings. The UPDATE format includes a command format to change existing settings to new settings.

In this way, task types are defined as configurable tasks and viewable tasks. Accordingly, the automation engine 130 executes a setup task script composed of setup commands or automatically executes a query task script composed of query commands.

In order to perform the same setup task with equipment from all manufacturers, setup work item scripts for each manufacturer must be defined separately. For example, in the case of VLAN creation, manufacturer A's command is "CREATE vlan_id: 10", and manufacturer B's command is "vlan 10", so the command format is different. Therefore, define the VLAN creation task item for manufacturer A (A_VLAN_Creation) and define the VLAN creation task for manufacturer B (B_VLAN_Creation). Each work item is defined as a VLAN creation work item. When the operator executes the VLAN creation task, the A_VLAN_Creation/B_VLAN_Creation task items are actually performed. Conventionally, a separate program, i.e., a plug-in program or driver program, must be developed to support each command format for each manufacturer. However, according to an embodiment of the present invention, command formats from various manufacturers are accepted simply by specifying a work item. can do.

The automation engine 130 executes a script for each work item (S107). In other words, the script is transmitted and executed to the device 200, which is the target equipment, using the script for each work item generated in S105. For example, the automation engine 130 may execute a script that checks the CPU usage rate of Manufacturer A's AMF (Show CPU table).

The automation engine 130 periodically performs scripts of defined tasks and work items, extracts necessary data from the results, and generalizes them (S109). For example, UPF traffic information can be extracted and stored in a database. The automation engine 130 can only parse the 5-minute average CPU usage rate (P13) from the show cpu table in FIG. 7.

The automation engine 130 generates work result data for each work item based on the data generalized in S109 (S109). That is, the automation engine 130 extracts each essential data from the task performance result data for each manufacturer and converts it into generalized metadata, as shown in the examples described in FIGS. 5 and 6.

The automation engine 130 generates task result data (S111) based on generalized metadata and stores it in a database. Work result data may be in the form of a report.

The automation engine 130 determines whether the operation result data stored in the database meets normal conditions (S113).

If normal, the work result data stored in the DB of the management engine 110 can be output to the outside (S115) through a connected user interface device so that the operator can check it. Work result data output externally may be structured as shown in the examples in FIGS. 8 and 9.

The automation engine 130 may determine whether the execution task is an action task (S117), and if so, update the accuracy of the action task items (S119). The automation engine 130 may reflect the updated accuracy in S119 and optimize the normal/abnormal judgment conditions according to the action results (S121). In other words, it can reflect judgment conditions optimized for the task in question.

Meanwhile, if it is determined in S113 that the automation engine 130 does not meet the normal conditions, that is, if it is determined to be abnormal, the automation engine 130 determines whether the currently executing task is an action task (S123). If it is determined to be an action task, the automation engine 130 may update the abnormal accuracy for the action task items (S125).

The automation engine 130 searches the action task list for the corresponding task in order of high accuracy (S127), sets the task priority according to accuracy (S129), and performs the task starting from S105. At this time, in S129, work items with low accuracy can be excluded from the work depending on the presence or absence of related work items in the work. This means you can auto-tune your work items. That is, the automation engine 130 repeats action tasks according to priority until normal conditions are met.

Additionally, if it is determined in S117 and S123 that it is not an action operation, the step is terminated.

As described above, network task automation can be applied to 5G core network control. In other words, if a failure occurs in Manufacturer A's SMF, call bypass can be automatically taken.

At this time, the call bypass task is a task of changing control data processing to another SMF when a problem occurs in the SMF that processes control data such as billing or a new SMF is added or removed. These settings are performed in the AMF. The SMF for processing control data of the corresponding UPF can be changed. Manufacturer A's AMF is adjusted by the CAPA value, CISCO AMF can add and delete SMF information, and data is transferred by reattaching to a new SMF.

An example of applying the network task automation described in FIGS. 1 to 9 to the SMF failure task is as follows.

1) First, the management engine 110 defines tasks and work items. For example, the management engine 110 defines the task of collecting node status information of Manufacturer A's SMF, and the work item is defined as extracting status information from a command (RTRV-NODE-STS) to query node status information. You can. At this time, the node status information may include node name (NODE), operation status (ACT_STS), administrator status (ADM_STS), operation status (OPR_STS), service status (SVC_STS) information, etc.

2) When a defined work item is executed, the management engine 110 sets conditions to determine whether the work and the execution result of the work item are normal/abnormal. For example, the management engine 110 may define the extracted data as normal or abnormal when ACT_STS of the extracted data is Active/Standby or OPR_STS is ENABLE. Condition settings are largely divided into eight types, and can include the presence or absence of data, comparison of the number of data, presence or absence of differences in the data, data to be compared, inequality and four-rule operation, presence or absence of the same data, setting conditional statements, etc.

3) The management engine 110 can define tasks to take action in case of abnormalities depending on conditions. If a problem occurs in the SMF, the management engine 110 can define a call bypass operation for the nationwide AMF in order to divert the call to another office. In other words, before taking action on the SMF where a problem occurs, the settings of the AMF can be changed to ensure service continuity, and after providing continuous service, action on the SMF when the problem occurs can be taken. For example, you can perform SMF actions such as system restart.

At this time, the management engine 110 can query and store new SMF information to be changed. The commands executed in AMF, whose manufacturer is CISCO, consist of three command groups. For existing SMF information deletion work items, the command may include a parameter SMF consisting of an SMF deletion command in APN-Profile, an SMF deletion command in LTE-EMERGENCY, and an SMF deletion command in TAIDB. For the Add new SMF information work item, the command may include a parameter new SMF consisting of Add SMF in APN-Profile, Add SMF in LTE-EMERGENCY, and Add SMF in TAIDB. At this time, new SMF selection is selected according to priority.

In addition, the command executed in AMF, manufactured by Samsung, consists of one command, and in the SMF group there is a command (CHANGE-SMF-CAPA) to adjust CAPA. These commands include the parameter SMF, which changes the CAPA value of the existing SMF to low, and the parameter new SMF, which changes the CAPA value of the new SMF to high.

Additionally, the management engine 110 defines a system restart operation for SMF. The management engine 110 may define a restart task for SMF physical servers and virtual machines (VMs).

In addition, the management engine 110 can define other tasks, and artificial intelligence (AI) makes a comprehensive judgment about the current situation by considering task impact (number of devices connected to the task)/task time/task priority. This can be defined to carry out and select the best action to execute first.

The automation engine 130 periodically performs tasks and work items defined by the management engine 110 and extracts necessary data from the results. The automation engine 130 may perform the task of collecting node status information of the SMF. If ACT_STS of the data extracted from the node status information collected by the automation engine 130 is Active and OPR_STS is ENABLE, it can be judged as normal, and if ACT_STS is Standby and OPR_STS is not ENABLE, it can be judged as abnormal.

The automation engine 130 compares the extracted data with defined normal/abnormal judgment criteria. At this time, the extracted data is character string or numeric data. If it is character data, a comparison operator can be performed, and if it is numeric data, normal/abnormality can be determined by comparing it with a reference value through the 4th rule operation.

If normal, the automation engine 130 may update the priority of action work items to be higher if the currently executing task is an action. In the case of abnormality, the automation engine 130 may update the priority of action work items to be lower if the currently executing task is an action. Periodically perform the next priority action task in the action task list for the task and extract the necessary data from the results.

Additionally, low-priority work items are automatically adjusted by excluding them from the work depending on the presence or absence of related work items within the work.

The series of network task automation described above is not limited to SMF failure tasks and can be commonly applied to multiple network tasks.

Meanwhile, the network task automation system described in FIGS. 1 to 9 may be implemented with a computing device such as that of FIG. 10 .

Figure 10 is a block diagram showing the hardware configuration of a computing device according to an embodiment.

Referring to FIG. 10, the network task automation system 100 described in FIGS. 1 to 9 may be implemented as a computing device 400, a computer that includes instructions described to execute the operations of the present disclosure. You can run the program.

The hardware of the computing device 400 may include at least one processor 410, memory 420, storage 430, and communication device 440, and may be connected through a bus. The computer program includes instructions described to execute the operations of the present disclosure. A computer program may be stored on a non-transitory computer readable storage medium.

The processor 410 is a device that controls the operation of the network task automation system 100 and may be various types of processors that process instructions included in a computer program, for example, a CPU (Central Processing Unit), MPU ( It may be a Micro Processor Unit (Micro Processor Unit), Micro Controller Unit (MCU), Graphic Processing Unit (GPU), etc. The memory 420 stores various data, commands and/or information.

Memory 420 may load a corresponding computer program from storage 430 so that instructions described to execute operations of the present disclosure are processed by processor 410.

The memory 420 may be, for example, read only memory (ROM), random access memory (RAM), etc.

The storage 430 can store various data, computer programs, etc. required to execute the operations of the present disclosure. Storage 430 may non-temporarily store computer programs. Storage 430 may be implemented as non-volatile memory.

Setting information of the management engine 110 and job execution result data received and processed by the automation engine 130 may be stored in a designated location of the storage 430.

The communication device 440 may be a wired/wireless communication module. The communication device 440 may perform communication using a pre-agreed protocol with a plurality of devices (200 in FIGS. 1 to 9).

At this time, the memory 420 may store a program containing instructions for driving the management engine 110 and the automation engine 130 respectively described in FIGS. 1 to 9, and this program is executed by at least one processor. .

The processor 410 sets a network task and at least one network work item constituting the network task, and registers scripts for executing the work item on devices for each at least one network work item on a per device manufacturer basis. You can.

The processor 410 may transmit scripts registered per manufacturer to the device group 200 of the same manufacturer at a designated time, receive execution results of the scripts from the device group 200, and store them in the storage 430. At this time, the execution result stored in the storage 430 may be output to an external device.

The processor 410 may execute a query task script including a command execution script, data extraction script, and data generalization script on a per-manufacturer basis.

The processor 410 may transmit a command execution script to the device 200 and receive a script execution result.

The processor 410 may execute a data extraction script and extract predetermined result data from the script execution results.

The processor 410 may execute the data generalization script, convert the extracted result data into result data in a common generalized format using a regular expression, and store the result data in the generalized format in the storage 430 .

The processor 410 may execute setup work item scripts for creation format, deletion format, and update format on a per-manufacturer basis.

The processor 410 may set conditions for determining whether the script execution result is normal or abnormal, and may set at least one action task to be performed if it is determined to be abnormal according to the set conditions. At this time, if the execution results of the received scripts are abnormal, the processor 410 may generate a script corresponding to at least one set action task and transmit the generated script to the device 200.

The processor 410 selects action tasks in order of high priority from a preset action task list, transmits the script corresponding to the selected action task to the device 200, and receives the script execution result from the device 200. This operation can be repeated until normal script execution results are received.

The processor 410 determines whether the work result included in the script execution result satisfies normal conditions, and if it satisfies the normal condition, the accuracy of the work item may be mapped to the work item and stored. The processor 410 may update the normal judgment condition of the task based on the accuracy mapped to the task item. At this time, the accuracy of the work item can be used to prioritize the action task.

A computer program including instructions for executing the operations of the present disclosure described above is stored in a medium readable by a computing device, and the medium readable by the computing device may be a removable recording medium or a fixed recording medium. A computer program can be transmitted to another computing device through a network such as the Internet, installed on the other computing device, and executed.

The embodiments of the present invention described above are not only implemented through devices and methods, but can also be implemented through programs that implement functions corresponding to the configurations of the embodiments of the present invention or recording media on which the programs are recorded.

Although the embodiments of the present invention have been described in detail above, the scope of the present invention is not limited thereto, and various modifications and improvements made by those skilled in the art using the basic concept of the present invention defined in the following claims are also possible. It falls within the scope of rights.

Claims (12)

A method of operating a network task automation system operated by at least one processor, comprising:
setting a network task and at least one network task item constituting the network task;
Registering scripts for executing the work item on devices for each of the at least one network work item on a vendor basis of the devices,
A step of transmitting the scripts generated for each manufacturer to the devices of the corresponding manufacturer, and
Receiving execution results of the scripts from the devices,
These scripts are:
Contains instructions in a format supported by the manufacturer,
The devices are,
It is a network equipment that includes at least one of the core equipment or base station equipment that constitutes the network,
After receiving the execution result,
determining whether the work result included in the execution result satisfies normal conditions; and
If the normal conditions are not met, based on artificial intelligence technology, preferentially executing the task selected from the task list based on at least one of the number of devices connected to the device being the task, the time required for the task, and task priority.
A method further comprising: In paragraph 1:
The step of receiving the execution result is,
Receive task execution result data in different formats for each manufacturer,
After receiving the execution result,
Extracting predefined essential item data from the job execution result data,
Converting the extracted essential item data into job execution result data in a generalized data format using regular expressions from each manufacturer, and
Step of outputting the converted task execution result data to the operator screen
A method further comprising: In paragraph 1:
After the above judgment step,
If the normal condition is met, mapping the accuracy of the work items to the work items and storing the work items, and updating the normal judgment condition of the work based on the accuracy.
A method further comprising: In paragraph 3,
After the above judgment step,
If the normal condition is not met, searching for at least one work item in the work list in order of high accuracy, and setting a priority of the searched work item based on the accuracy,
The network task automation system,
The operation of transmitting manufacturer-level scripts for the searched work items to the devices according to the set priority, receiving execution results of the scripts from the devices, and determining whether the normal conditions are met is repeated. How to. delete A communication device that performs communication using a pre-agreed protocol with a plurality of devices that are network equipment including at least one of the core equipment or base station equipment constituting the network,
Memory in which programs that perform automation of network operations are stored,
At least one processor executing the program,
The at least one processor,
Setting a network task and at least one network task item constituting the network task, registering scripts for executing the task item on devices for each of the at least one network task item on a per manufacturer basis of the devices,
Transmitting scripts registered on a per-manufacturer basis to a device group of the same manufacturer at a designated time and receiving and storing the execution results of the scripts from the device group,
If the task result included in the execution result does not meet the normal conditions, based on artificial intelligence technology, a task is selected from the task list based on at least one of the number of devices connected to the device being worked on, the time required for the task, and the task priority. Executes tasks first,
The saved execution results are,
A network task automation system that outputs to the user's external device. In paragraph 6:
The processor,
Executing a query task script including a command execution script, data extraction script, and data generalization script for each manufacturer,
Transmit the command execution script to the device and receive the script execution result,
Executing the data extraction script to extract predetermined result data from the script execution results,
Executing the data generalization script to convert the extracted result data into result data in a common generalized format through regular expressions,
A network task automation system that stores result data in the generalized format. In paragraph 6:
The processor,
A network task automation system that executes setup work item scripts for creation format, deletion format, and update format on a manufacturer-by-manufacturer basis. In paragraph 6:
The processor,
Setting conditions for determining whether the script execution result is normal or abnormal, and setting at least one action to be performed when it is determined to be abnormal according to the set conditions,
If the execution results of the received scripts are abnormal, a network task automation system that generates a script corresponding to the at least one action task set and transmits the generated script to the device. In paragraph 9:
The processor,
Select action tasks in order of high priority from the preset action task list, transmit the script corresponding to the selected action task to the device, and receive script execution results from the device until a normal script execution result is received. A repetitive, network task automation system. In paragraph 10:
The processor,
Determine whether the work result included in the execution result satisfies normal conditions, and if the normal condition is met, map the accuracy of the work item to the work item and store it;
The accuracy for the above work items is:
Network task automation system, used for prioritization of the above action tasks. In paragraph 11:
The processor,
A network task automation system that updates normal judgment conditions of the task based on the accuracy.

Images