CN109861869A - A kind of generation method and device of configuration file - Google Patents
A kind of generation method and device of configuration file Download PDFInfo
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- CN109861869A CN109861869A CN201910184533.2A CN201910184533A CN109861869A CN 109861869 A CN109861869 A CN 109861869A CN 201910184533 A CN201910184533 A CN 201910184533A CN 109861869 A CN109861869 A CN 109861869A
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Abstract
The application provides the generation method and device of a kind of configuration file, comprising: determines the facility information of each member device in the topological structure and the network of the network；The facility information of topological structure and each member device based on the network, generates the first network topological diagram of the network；The first network topological diagram is input in the neural network trained, to be identified by the neural network to the first network topological diagram, exports the first configuration file of each member device in the network；Obtain the first configuration file of each member device of the neural network output.The efficiency and accuracy that configuration file is generated and issued can be improved using method provided by the present application.
Description
Technical field
This application involves computer communication field more particularly to the generation methods and device of a kind of configuration file.
Background technique
User network is usually made of tens even up to a hundred network equipments.It is existing for the network equipment in user network
Configuration mode be: manually every network equipment in user network is configured.This human configuration mode allocative efficiency
It is low, and it is easy error.
Summary of the invention
In view of this, the application provides the generation method and device of a kind of configuration file, generated to improve configuration file
With the efficiency and accuracy issued.
Specifically, the application is achieved by the following technical solution:
According to a first aspect of the present application, a kind of generation method of configuration file is provided, the method is applied in network
Network Management Equipment, comprising:
Determine the facility information of each member device in the topological structure and the network of the network；
The facility information of topological structure and each member device based on the network, the first network for generating the network are opened up
Flutter figure；
The first network topological diagram is input in the neural network trained, with by the neural network to described
One network topological diagram is identified, the first configuration file of each member device in the network is exported；
Obtain the first configuration file of each member device of the neural network output.
Optionally, in the topological structure and the network of the determination network each member device facility information,
Include:
Topology, which is sent, to each member device collects message；
Receive topology information and facility information that each member device returns to each member device；
Topology information based on each member device calculates the topological structure of the network.
Optionally, it is generated in the network after the configuration file of each member device described, the method also includes:
The first configuration file for showing the first network topological diagram to user and being generated for each member device；
If the confirmation message for first configuration file of user's input is received, by what is generated for each member device
First configuration file is handed down to each member device.
Optionally, after showing the network topological diagram and the configuration file generated for each member device to user, institute
State method further include:
If receiving the modification message for first configuration file of user's input, obtains and carried in the modification message
The second network topological diagram；Second network topological diagram is that designated position of the user in first network topological diagram is added to pass
The network topological diagram formed after key information；
Second network topological diagram is input to the neural network, with by the neural network to the second network topology
Figure is identified, the second configuration file of each member device is exported；
It obtains the second configuration file of each member device and is handed down to each member device.
Optionally, the neural network forms training by the corresponding sample label of all types of networks；Each network
The sample of corresponding sample label centering is the network topological diagram of the network, and label is the configuration text of each member device in the network
Part.
According to a second aspect of the present application, a kind of generating means of configuration file are provided, described device is applied in network
Network Management Equipment, comprising:
Determination unit, the equipment letter of each member device in the topological structure and the network for determining the network
Breath；
Generation unit generates the net for the facility information of topological structure and each member device based on the network
The first network topological diagram of network；
Input unit, for the first network topological diagram to be input in the neural network trained, by the mind
The first network topological diagram is identified through network, exports the first configuration file of each member device in the network；
Acquiring unit, the first configuration file of each member device for obtaining the neural network output.
Optionally, the determination unit is specifically used for sending topology collection message to each member device；Each member is received to set
The standby topology information and facility information for returning to each member device；Topology information based on each member device calculates opening up for the network
Flutter structure.
Optionally, described device further include:
Issuance unit, the first configuration for showing the first network topological diagram to user and being generated for each member device
File；If receiving the confirmation message for first configuration file of user's input, the will generated for each member device
One configuration file is handed down to each member device.
Optionally, the issuing unit, if being also used to receive the modification for first configuration file of user's input
Message then obtains the second network topological diagram carried in the modification message；Second network topological diagram is user in the first net
Designated position in network topological diagram is added to the network topological diagram formed after key message；Second network topological diagram is inputted
The second of each member device is exported to the neural network to be identified by the neural network to the second network topological diagram
Configuration file；It obtains the second configuration file of each member device and is handed down to each member device.
Optionally, the neural network forms training by the corresponding sample label of all types of networks；Each network
The sample of corresponding sample label centering is the network topological diagram of the network, and label is the configuration text of each member device in the network
Part.
Since the application knows the network topological diagram that Network Management Equipment is automatically generated using the neural network trained
Not, the configuration file for obtaining each member device, without again by being manually that each member device inputs configuration file, it is possible to
The formation efficiency for greatly improving configuration file substantially reduces human configuration workload.
In addition, there is no be immediately handed down to configuration file Network Management Equipment after the configuration file for generating each member device
Each member device, but configuration file is shown into user, confirmed by user, this method, which can greatly improve, issues configuration
The accuracy of file.
Detailed description of the invention
Fig. 1 is a kind of schematic diagram of network topological diagram shown in one exemplary embodiment of the application；
Fig. 2 is a kind of flow chart of configuration file generation method shown in one exemplary embodiment of the application；
Fig. 3 is the schematic diagram of another network topological diagram shown in one exemplary embodiment of the application；
Fig. 4 is a kind of block diagram of configuration file generating means shown in one exemplary embodiment of the application；
Fig. 5 is the hardware structure diagram of the Network Management Equipment shown in one exemplary embodiment of the application.
Specific embodiment
Example embodiments are described in detail here, and the example is illustrated in the accompanying drawings.Following description is related to
When attached drawing, unless otherwise indicated, the same numbers in different drawings indicate the same or similar elements.Following exemplary embodiment
Described in embodiment do not represent all embodiments consistent with the application.On the contrary, they be only with it is such as appended
The example of the consistent device and method of some aspects be described in detail in claims, the application.
It is only to be not intended to be limiting the application merely for for the purpose of describing particular embodiments in term used in this application.
It is also intended in the application and the "an" of singular used in the attached claims, " described " and "the" including majority
Form, unless the context clearly indicates other meaning.It is also understood that term "and/or" used herein refers to and wraps
It may be combined containing one or more associated any or all of project listed.
It will be appreciated that though various information, but this may be described using term first, second, third, etc. in the application
A little information should not necessarily be limited by these terms.These terms are only used to for same type of information being distinguished from each other out.For example, not departing from
In the case where the application range, the first information can also be referred to as the second information, and similarly, the second information can also be referred to as
One information.Depending on context, word as used in this " if " can be construed to " ... when " or " when ...
When " or " in response to determination ".
In usual network can include: Network Management Equipment and member device.
1) above-mentioned Network Management Equipment can be used for managing member device, such as discovery member device, collect the net of each member device
Network topology information (for example member device is connected with which equipment, connection type, connectivity port etc.), the equipment of each member device
Information (such as device model etc.) etc..
The Network Management Equipment can be disposed on the physical equipment in the network, for example, when the network is SDN (Software
Defined Network, software defined network) network when, which can be SDN controller.
Certainly, which can also be configured with the network equipment of webmastering software in the network.Here, only to network management
Equipment is illustratively illustrated, without specifically defined.
2) above-mentioned member device (the also referred to as network equipment) may include forwarding device, such as interchanger, router etc.,
It is mainly used for message forwarding etc..
The facility information of topological structure and each member device of the Network Management Equipment based on the network in network generates the network
Network topological diagram, and the network topological diagram is input in the neural network trained, by neural network to the network topology
Figure is identified, the configuration file of each member device in the network is obtained.
Since the application knows the network topological diagram that Network Management Equipment is automatically generated using the neural network trained
Not, the configuration file for obtaining each member device, without again by being manually that each member device inputs configuration file, it is possible to
Greatly improve the formation efficiency of configuration file.
First the training of neural network is described in detail below.
The neural network can carry on an electronic device, which can be above-mentioned Network Management Equipment, be also possible to
Server, server cluster independently of Network Management Equipment.Here only the electronic equipment that neural network is carried is carried out exemplary
Ground explanation, without specifically defined.
The neural network forms training by all types of corresponding sample labels of network；Each network is corresponding
The sample of sample label centering is the network topological diagram of the network, and label is the configuration file of each member device in the network.
The training of neural network can be specifically achieved by the steps of.
Step 1: the equipment letter of each member device in the network topology of the available various types network of electronic equipment, network
The configuration file of each member device in breath and the key message for characterizing network attribute and each network is then based on each
The facility information and key message of each member device, generate preset format in the network topology of the network of seed type, network
Network topological diagram.
Concept involved in step 1 is explained first.
1) various types network may include: the network applied to different scenes, such as Campus Network, data center network
Etc., certain various types of networks can also include the ad hoc network set up by various network technologies, such as VXLAN
(Virtual eXtensible LAN, expansible Virtual Local Area Network) network, MPLS (Multi-protocol Label
Switching, multiprotocol label switching) L2VPN (2 Virtual Private Network of Layer, Layer 2 virtual private network
Network) network etc., certainly, which can also include two layers of common forwarding network and three layers of forwarding network.
Here only the network type of network is illustratively illustrated, without specifically defined.
Network type is abundanter, and the number networks are more, and the accuracy that the neural network trained generates configuration file is got over
It is high.
2) network topological diagram
In practical applications, it is possible that the situation of different types of network network topological diagram having the same, therefore
It in the embodiment of the present application, not only may include the company of each member device, each member device in network in generation network topological diagram
Relationship is connect, can also include the facility information of each member device and the key message of the network.
Wherein, facility information may include the information such as device model.What the network due to being applied to different scenes generallyd use
The equipment of different model.For example Campus Network is different with the device model of the network equipment used by data center network.Therefore
Neural network can be trained to distinguish the network for being applied to different scenes based on facility information.
Key message is used to characterize the attribute of network, for example it is special net that key message, which can be for identifying the network,
Network, such as VXLAN network or MPLS L2VPN network.It is distinguished by key message training neural network and is based on classical network
(such as common double layer network and three-layer network) and ad hoc network.
In addition it is also necessary to explanation, the network topological diagram of the application is the network topological diagram of preset format, is further come
Say that the icon of each network equipment in network topological diagram, line are all preset.The different types of network equipment corresponds to different
Icon.For example access switch, convergence switch, core switch, AP, AC etc. all correspond to different icons.The network equipment
Designated position near icon also configures the facility information of the network equipment.If the network is ad hoc network, whole network topological diagram
Designated position also configure above-mentioned key message.
For example, the network topological diagram schematic diagram of the application can be as shown in Figure 1.
It is convergence switch, equipment that equipment 101 to equipment 104 in Fig. 1, which is access switch, equipment 105 and equipment 106,
107 be core switch.Equipment 101 is configured with the device model of each equipment to 107 lower right corner of equipment.The upper left corner of Fig. 1 configures
There is key message (such as VXLAN).
Step 2: electronic equipment be directed to each network, using in the network configuration file of each member device as label,
Think that the network topological diagram for the preset format that the network generates as sample, generates the sample label pair of the network.
Step 3: the corresponding sample label of various types network can be used to the training neural network in electronic equipment.
When realizing, electronic equipment can be by the corresponding sample label of various types network to being input to neural network.For
Each sample label pair, neural network can identify sample, obtain the configuration file of each network equipment in sample.
Then neural network can calculate the configuration of each network equipment in the configuration file and label of each network equipment that identification obtains
The error of file, and by the error back propagation, each layer parameter of the neural network is adjusted, until neural network recognization sample obtains
To each network equipment configuration file and label in each network equipment configuration file error in a certain range when, determine
The neural metwork training is completed.
The method for using the neural network to generate configuration file is described in detail below.
Referring to fig. 2, Fig. 2 is a kind of flow chart of configuration file generation method shown in one exemplary embodiment of the application,
This method can be applicable on the Network Management Equipment in network, it may include step as described below.
Step 201: Network Management Equipment can determine setting for each member device in the topological structure and the network of the network
Standby information.
When realizing, Network Management Equipment can send topology to each member device and collect message.Member device is opened up receiving
It flutters after collecting message, the topology information and facility information of the member device can be returned to Network Management Equipment.
Network Management Equipment can be based on each member after the topology information for receiving each member device that each member device returns
The topology information of equipment calculates the topological structure of the network.
Wherein, topology information includes: interface message, neighbor information, stacking information of member device etc..It here is pair
Topology information is illustratively illustrated, without specifically defined.
It should also be noted that, above topology, which collects message, can be the message based on LLDP agreement, it is also possible to other
For collecting the message of the other types agreement of member device topology information and facility information, it is also possible to proprietary protocol message,
Here it only collects message to topology illustratively to be illustrated, without specifically defined.
Step 202: the facility information of topological structure and each member device of the Network Management Equipment based on the network, described in generation
The first network topological diagram of network.
When realizing, the facility information of topological structure and each member device of the network equipment based on calculated network is raw
At the first network topological diagram of preset format.
Step 203: the first network topological diagram is input in the neural network trained by Network Management Equipment, by described
Neural network identifies the first network topological diagram, exports the first configuration file of each member device in the network.
Step 204: Network Management Equipment can obtain the first configuration file of each member device of the neural network output.
When realizing, first network topological diagram can be input in the above-mentioned neural network trained by Network Management Equipment.Nerve
Network can identify that obtain each member device in the first network topological diagram first is matched to the first network topological diagram
File is set, and exports the first configuration file of each member device.
First configuration file of each member device of the available neural network output of Network Management Equipment.
In practical applications, ad hoc network (for example being VXLAN network, MPLS L2VPN network etc.) and common network (ratio
Such as common two layers of forwarding network and three layers of forwarding network) possibility network topology having the same, and ad hoc network and common net
The configuration file of each member device is different again in network.Therefore the key message of network is needed to distinguish ad hoc network and common
Network.
But Network Management Equipment can not collect the key message that message determines the network based on topology, therefore, in Network Management Equipment
After the first configuration file for getting each member device of neural network output, the first of each member device can be shown to user
Configuration file and the first network topological diagram, to carry out the confirmation operation of the first configuration file by user.
When user determine each member device the first configuration file it is correct after, user can be with input validation message.Work as network management
After equipment receives the confirmation message for first configuration file of user's input, Network Management Equipment can be by the of each member device
One configuration file is handed down to each member device.
When user determine the member device the first configuration file it is incorrect when, user can be shown in Network Management Equipment the
The designated position input key message of one network topological diagram forms the second network topological diagram.Then, user can be to Network Management Equipment
Message is modified in input, carries the second network topological diagram in the modification message.
After Network Management Equipment, which receives user, is directed to the modification message of first configuration file, the available modification message
Second network topological diagram of middle carrying, is then input to the neural network for the second network topological diagram.Neural network can be to this
Second network topological diagram is identified, the second configuration file of each member device is exported.
Network Management Equipment can will acquire the second configuration file of each member device of neural network output, then set each member
The second standby configuration file is handed down to each member device.
For example, it is assumed that the network is VXLAN network, but set since the Network Management Equipment in network is based on each member in network
Standby network topological information and facility information can not determine the key message (i.e. VXLAN) of the network, so Network Management Equipment base
It is as shown in Figure 3 in the first network topological diagram that the network topological information and facility information of each member device generate.
Network topological diagram shown in Fig. 3 is input to neural network by Network Management Equipment, with by neural network to net shown in Fig. 3
Network topological diagram identified, corresponding first configuration file of each member device in the network topological diagram is exported.
Then, network topological diagram shown in Fig. 3 and the first configuration file can be showed user by Network Management Equipment.
User has found that the designated position of the incorrect and shown in Fig. 3 network topological diagram of the first configuration file is added to pass
Key information (i.e. VXLAN) is formed the second network topological diagram (as shown in Figure 1).Then, user can input modification on Network Management Equipment
Message, the modification message carry network topological diagram shown in FIG. 1.
Network Management Equipment can obtain in the modification message and carry network topological diagram shown in FIG. 1, then by network shown in FIG. 1
Topological diagram is input in neural network, to be identified by neural network to network topological diagram shown in FIG. 1, is exported each member and is set
The second standby configuration file.Second configuration file of each member device of the available neural network output of Network Management Equipment, and will
Second configuration file is handed down to each member device.
Seen from the above description, confirmed by configuration file of the user to each member device of generation, be can be improved
Network Management Equipment is the accuracy that each member device issues configuration file.
The application proposes a kind of generation method of configuration file, topological structure of the Network Management Equipment based on the network in network
The network topological diagram of the network is generated with the facility information of each member device, and the network topological diagram is input to the mind trained
Through being identified by neural network to the network topological diagram, obtaining the configuration file of each member device in the network in network.
Since the application knows the network topological diagram that Network Management Equipment is automatically generated using the neural network trained
Not, the configuration file for obtaining each member device, without again by being manually that each member device inputs configuration file, it is possible to
The formation efficiency for greatly improving configuration file substantially reduces human configuration workload.
In addition, there is no be immediately handed down to configuration file Network Management Equipment after the configuration file for generating each member device
Each member device, but configuration file is shown into user, confirmed by user, this method, which can greatly improve, issues configuration
The accuracy of file.
In addition, present invention also provides configuration file generating means corresponding with above-mentioned configuration file generation method.
Referring to fig. 4, Fig. 4 is a kind of block diagram of configuration file generating means shown in one exemplary embodiment of the application.
The device can be applicable on Network Management Equipment, it may include unit as follows.
Determination unit 401, the equipment of each member device in the topological structure and the network for determining the network
Information；
Generation unit 402, for the facility information of topological structure and each member device based on the network, described in generation
The first network topological diagram of network；
Input unit 403, for the first network topological diagram to be input in the neural network trained, by described
Neural network identifies the first network topological diagram, exports the first configuration file of each member device in the network；
Acquiring unit 404, the first configuration file of each member device for obtaining the neural network output.
Optionally, the determination unit 401 is specifically used for sending topology collection message to each member device；Receive it is each at
Member's equipment returns to the topology information and facility information of each member device；Topology information based on each member device calculates the network
Topological structure.
Optionally, described device further include:
Issuance unit 405, first for showing the first network topological diagram to user and being generated for each member device
Configuration file；If receiving the confirmation message for first configuration file of user's input, will be generated for each member device
The first configuration file be handed down to each member device.
Optionally, the issuing unit 405, if being also used to receive the repairing for first configuration file of user's input
Change message, then obtains the second network topological diagram carried in the modification message；Second network topological diagram is user first
Designated position in network topological diagram is added to the network topological diagram formed after key message；Second network topological diagram is defeated
Enter to the neural network, to be identified by the neural network to the second network topological diagram, exports the of each member device
Two configuration files；It obtains the second configuration file of each member device and is handed down to each member device.
Optionally, the neural network forms training by the corresponding sample label of all types of networks；Each network
The sample of corresponding sample label centering is the network topological diagram of the network, and label is the configuration text of each member device in the network
Part.
It is the hardware structure diagram of the Network Management Equipment shown in one exemplary embodiment of the application referring to Fig. 5, Fig. 5.
The Network Management Equipment includes: communication interface 501, processor 502, machine readable storage medium 503 and bus 504；Its
In, communication interface 501, processor 502 and machine readable storage medium 503 complete mutual communication by bus 504.Processing
Device 502 can be held by reading and executing machine corresponding with configuration file generation control logic in machine readable storage medium 503
Row instruction, can be performed arrangements described above document generating method.
Machine readable storage medium 503 referred to herein can be any electronics, magnetism, optics or other physical stores
Device may include or store information, such as executable instruction, data, etc..For example, machine readable storage medium may is that easily
Lose memory, nonvolatile memory or similar storage medium.Specifically, machine readable storage medium 503 can be RAM
(Radom Access Memory, random access memory), flash memory, memory driver (such as hard disk drive), solid state hard disk,
Any kind of storage dish (such as CD, DVD) perhaps similar storage medium or their combination.
The function of each unit and the realization process of effect are specifically detailed in the above method and correspond to step in above-mentioned apparatus
Realization process, details are not described herein.
For device embodiment, since it corresponds essentially to embodiment of the method, so related place is referring to method reality
Apply the part explanation of example.The apparatus embodiments described above are merely exemplary, wherein described be used as separation unit
The unit of explanation may or may not be physically separated, and component shown as a unit can be or can also be with
It is not physical unit, it can it is in one place, or may be distributed over multiple network units.It can be according to actual
The purpose for needing to select some or all of the modules therein to realize application scheme.Those of ordinary skill in the art are not paying
Out in the case where creative work, it can understand and implement.
The foregoing is merely the preferred embodiments of the application, not to limit the application, all essences in the application
Within mind and principle, any modification, equivalent substitution, improvement and etc. done be should be included within the scope of the application protection.
Claims (10)
1. a kind of generation method of configuration file, which is characterized in that the method is applied to the Network Management Equipment in network, comprising:
Determine the facility information of each member device in the topological structure and the network of the network；
The facility information of topological structure and each member device based on the network generates the first network topology of the network
Figure；
The first network topological diagram is input in the neural network trained, with by the neural network to first net
Network topological diagram is identified, the first configuration file of each member device in the network is exported；
Obtain the first configuration file of each member device of the neural network output.
2. the method according to claim 1, wherein the topological structure of the determination network and described
The facility information of each member device in network, comprising:
Topology, which is sent, to each member device collects message；
Receive topology information and facility information that each member device returns to each member device；
Topology information based on each member device calculates the topological structure of the network.
3. the method according to claim 1, wherein in the configuration for generating each member device in the network
After file, the method also includes:
The first configuration file for showing the first network topological diagram to user and being generated for each member device；
If receiving the confirmation message for first configuration file of user's input, first will generated for each member device
Configuration file is handed down to each member device.
4. according to the method described in claim 3, it is characterized in that, showing the network topological diagram to user and being each member
After the configuration file that equipment generates, the method also includes:
If receiving the modification message for first configuration file of user's input, the carried in the modification message is obtained
Two network topological diagrams；Second network topological diagram is that designated position of the user in first network topological diagram is added to crucial letter
The network topological diagram formed after breath；
Second network topological diagram is input to the neural network, with by the neural network to the second network topological diagram into
Row identification, exports the second configuration file of each member device；
It obtains the second configuration file of each member device and is handed down to each member device.
5. the method according to claim 1, wherein the neural network passes through the corresponding sample of all types of networks
Label forms training；The sample of the corresponding sample label centering of each network is the network topological diagram of the network, and label is
The configuration file of each member device in the network.
6. a kind of generating means of configuration file, which is characterized in that described device is applied to the Network Management Equipment in network, comprising:
Determination unit, the facility information of each member device in the topological structure and the network for determining the network；
Generation unit generates the network for the facility information of topological structure and each member device based on the network
First network topological diagram；
Input unit, for the first network topological diagram to be input in the neural network trained, by the nerve net
Network identifies the first network topological diagram, exports the first configuration file of each member device in the network；
Acquiring unit, the first configuration file of each member device for obtaining the neural network output.
7. device according to claim 6, which is characterized in that the determination unit is specifically used for sending out to each member device
Topology is sent to collect message；Receive topology information and facility information that each member device returns to each member device；It is set based on each member
Standby topology information calculates the topological structure of the network.
8. device according to claim 6, which is characterized in that described device further include:
Issuance unit, the first configuration text for showing the first network topological diagram to user and being generated for each member device
Part；If receiving the confirmation message for first configuration file of user's input, first will generated for each member device
Configuration file is handed down to each member device.
9. device according to claim 8, which is characterized in that the issuing unit, if being also used to receive user's input
The modification message for first configuration file, then obtain the second network topological diagram carried in the modification message；Described
Two network topological diagrams are the network topology that user is formed after the designated position in first network topological diagram is added to key message
Figure；Second network topological diagram is input to the neural network, with by the neural network to the second network topological diagram into
Row identification, exports the second configuration file of each member device；Obtain the second configuration file of each member device and be handed down to it is each at
Member's equipment.
10. device according to claim 6, which is characterized in that the neural network passes through the corresponding sample of all types of networks
This label forms training；The sample of the corresponding sample label centering of each network is the network topological diagram of the network, label
For the configuration file of each member device in the network.
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| CN111787550A (en) * | 2020-04-17 | 2020-10-16 | 三个机器人公司 | Bluetooth network networking method and system based on BLE |
| CN113315655A (en) * | 2021-05-24 | 2021-08-27 | 恒隆通信技术有限公司 | Information configuration method of intelligent networking environment and intelligent networking system |
| CN115291963A (en) * | 2022-06-17 | 2022-11-04 | 芯华章科技股份有限公司 | Method for configuring hardware resources, electronic device and storage medium |
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| CN109861869B (en) | 2022-05-31 |
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