CN114070741A - Topological graph generation method, system, equipment and storage medium - Google Patents

Topological graph generation method, system, equipment and storage medium Download PDF

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CN114070741A
CN114070741A CN202010739760.XA CN202010739760A CN114070741A CN 114070741 A CN114070741 A CN 114070741A CN 202010739760 A CN202010739760 A CN 202010739760A CN 114070741 A CN114070741 A CN 114070741A
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topological
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determining
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CN114070741B (en
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刘亚梅
姚路
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China Mobile Communications Group Co Ltd
China Mobile Suzhou Software Technology Co Ltd
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China Mobile Suzhou Software Technology Co Ltd
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/12—Discovery or management of network topologies
    • G—PHYSICS
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/08—Configuration management of networks or network elements
    • H04L41/085—Retrieval of network configuration; Tracking network configuration history
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management

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Abstract

The application provides a topological graph generation method, which relates to the technical field of information and comprises the following steps: determining first data; the first data is used for representing configuration data of each device for constructing the cloud platform; acquiring a trained topological model; the topological model is used for determining the layout information of each device in a topological graph; generating second data based on the first data and the topology model; and the second data is used for representing a topological graph corresponding to the cloud platform. The topological graph generation method can solve the problems of long drawing period, complicated processes and high labor cost caused by manual drawing of the cloud platform topological graph in the related technology, achieves automatic drawing of the cloud platform topological graph, shortens the drawing period, simplifies the processes and reduces the labor cost. The application also provides a topological graph generating system, a topological graph generating device and a computer readable storage medium.

Description

Topological graph generation method, system, equipment and storage medium
Technical Field
The present application relates to the field of information technology, and in particular, to a method, a system, a device, and a computer-readable storage medium for generating a topological graph.
Background
The cloud platform refers to a platform for providing computing, network and storage capabilities based on services of hardware resources and software resources. The realization of various functions in the cloud platform is realized by means of the cooperation among various devices in the cloud platform. Deployment of the cloud platform is usually realized based on a topological graph of the cloud platform, and the connection relation and the setting position between each device in the cloud platform can be clearly and intuitively displayed in the topological graph of the cloud platform.
In the related art, a topological graph of a cloud platform usually needs to be drawn manually.
However, the manual drawing method of the topological graph has a long drawing cycle, complicated processes, and high labor cost.
Disclosure of Invention
In order to solve the problems of long drawing period, complicated processes and high labor cost in manual drawing of topological graphs in the related art, the application provides the topological graph generation method, and the method can realize automatic drawing of cloud platform topological graphs, so that the drawing period of the topological graphs is shortened, the processes are simplified, and the labor cost is reduced.
The technical scheme provided by the application is as follows:
a method of generating a topology map, the method comprising:
determining first data; the first data is used for representing configuration data of each device for constructing the cloud platform;
acquiring a trained topological model; the topological model is used for determining the layout information of each device in a topological graph;
generating second data based on the first data and the topology model; and the second data is used for representing a topological graph corresponding to the cloud platform.
In some embodiments, said generating second data based on said first data and said topology model comprises:
determining a topological connection relation based on the first data; the topological connection relation comprises the connection relation among all the equipment sets;
and generating the second data based on the topological connection relation and the topological model.
In some embodiments, the generating the second data based on the topological connection relationship and the topological model includes:
acquiring a connection relation model and a space position relation model based on the topological model; the connection relation model is used for determining the connection relation among the devices; the spatial position relation model is used for determining spatial positions among the devices;
processing the topological connection relation through the connection relation model to obtain third data representing the connection relation among the devices;
processing the topological connection relation through the spatial position relation model to obtain fourth data representing the spatial position relation of each device;
and processing the third data and the fourth data to generate the second data.
In some embodiments, the processing the third data and the fourth data to generate the second data includes:
determining a graph processing algorithm; the graphic processing algorithm is used for performing layout processing on each device of the cloud platform;
and processing the third data and the fourth data based on the image processing algorithm to generate the second data.
In some embodiments, the processing the third data and the fourth data based on the graphics processing algorithm to generate the second data includes:
obtaining an equipment relation setting model and an equipment level setting model based on the graph processing algorithm; the device relationship setting model is used for setting the connection relationship of each device in at least one direction; the equipment level setting model is used for setting levels among the equipment;
and processing the third data and the fourth data based on the equipment relationship setting model and the equipment hierarchy setting model to generate the second data.
In some embodiments, the processing the third data and the fourth data based on the device relationship setting model and the device hierarchy setting model to generate second data includes:
processing the third data and the fourth data based on the equipment relationship setting model, and determining a horizontal connection relationship and a vertical connection relationship among the equipment;
based on the equipment level setting model, carrying out layout on the horizontal connection relation and the vertical connection relation to obtain a layout result;
generating the second data based on the layout result.
In some embodiments, the generating the second data based on the layout result comprises:
acquiring icon information and a graphic output module of each device; the graph output module is used for outputting a topological graph;
and generating the second data based on the icon information and the layout result through the graphic output module.
The present application further provides a topological graph generating system, which includes: a processor, a memory, and a communication bus; wherein:
the communication bus is used for realizing communication connection between the processor and the memory;
the processor is used for executing the program of the topological graph generation method in the memory so as to realize the following steps:
determining first data; the first data is used for representing configuration data of each device for constructing the cloud platform;
acquiring a trained topological model; the topological model is used for determining the layout information of each device in a topological graph;
generating second data based on the first data and the topology model; wherein the second data is used for representing a topological graph of the cloud platform.
The present application also provides a topology generating device, including: a determining module and a processing module; wherein:
the determining module is used for determining first data and acquiring a trained topology model; the first data is used for representing configuration data of each device constructing the cloud platform; the topology model is used for determining the layout information of each device in the topological graph;
the processing module is used for generating second data based on the first data and the topological model; wherein the second data is used for representing a topological graph of the cloud platform.
The present application also provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor of a map generation apparatus, implements any of the above-described topology map generation methods.
According to the topological graph generation method, first data used for representing configuration data of each device for building the cloud platform are determined, a trained topological model used for determining layout information of each device in the topological graph is obtained, and then second data used for representing the topological graph of the cloud platform are generated based on the first data and the topological model. Therefore, in the topological graph generating method provided by the application, the topological graph of the cloud platform can be automatically and quickly generated based on the configuration data of each device of the cloud platform and the trained topological model, so that the problems of long drawing period, low efficiency and high labor cost caused by manually drawing the topological graph in the related technology are solved.
Drawings
Fig. 1 is a flowchart of a first topology generation method provided in the present application;
FIG. 2 is a flowchart of a second topology generation method provided in the present application;
FIG. 3 is a detailed architecture diagram of a topology generation method according to the present application;
fig. 4 is a topological diagram of a government affair cloud platform obtained by the topological diagram generation method provided by the present application;
fig. 5 is a structural diagram of a topology map generation system according to an embodiment of the present application;
fig. 6 is a structural diagram of a topology map generation apparatus provided in the present application.
Detailed Description
The present application relates to the field of information technology, and in particular, to a method, a system, a device, and a computer-readable storage medium for generating a topological graph.
Due to the fact that the cloud platform is diverse in function implementation, diverse in service targets, high in frequency of service demand change and the like, when the cloud platform is deployed, the influence of the cloud platform on the cooperative computing among the devices in the cloud platform due to the factors such as the diversity in function implementation, the diverse in service targets, the speed of service demand change and the like needs to be fully considered.
Therefore, before the cloud platform is deployed, the deployment of each device in the platform needs to be comprehensively evaluated. In practical application, the evaluation of cloud platform deployment includes the evaluation of connection relation, deployment position, interaction mode between devices, interaction efficiency between devices and the like among devices constructing the cloud platform.
Because the cloud platform has a plurality of types and a large number of devices, the cloud platform deployment is evaluated in a topological graph drawing mode, and various types of devices are visually represented through the topological graph drawing, so that the evaluation speed can be increased, and the evaluation effect can be ensured. Therefore, the correct drawing of the topological graph is very important for the comprehensive evaluation of the cloud platform.
In the related art, the drawing of the topological graph in the cloud platform is usually realized by means of manual drawing. For example, with the help of certain drawing software such as Visio, icons of various types of equipment are drawn one by one according to the deployment requirement of the cloud platform, the equipment are connected one by one, and then the equipment with different levels, different functions and different types are labeled one by one.
In the process of drawing the topological graph, the topological graph is completely realized by manpower, so that the drawing time is long, the procedures are complicated, the labor cost is high, and errors are easy to occur.
In order to solve the above problem, an embodiment of the present application provides a topological graph generation method, which may be implemented by a topological graph generation device, which may be implemented by a processor of the topological graph generation device for example.
In practical applications, the processor may be at least one of an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a Central Processing Unit (CPU), a controller, a microcontroller, and a microprocessor.
As shown in fig. 1, the method for generating a topology map provided in the embodiment of the present application may include the following steps:
step 101, determining first data.
The first data is used for representing configuration data of each device for constructing the cloud platform.
In one embodiment, the first data may be data representing types of respective devices that build the cloud platform.
In one embodiment, the first data may be data representing types of respective devices constructing the cloud platform and the number of devices corresponding to each type.
In one embodiment, the first data may be used to represent configuration data for respective device sets that build the cloud platform. The device set may represent a set of a plurality of devices having the same function. Illustratively, a device set of services may represent a collection of servers of many different models.
In one embodiment, the first data may be used to represent configuration data for various devices that build a certain type of cloud platform.
In one embodiment, the first data may be used to represent configuration data of respective devices that construct the government cloud platform.
Specifically, the government affair cloud platform is a platform which utilizes a cloud computing technology, utilizes existing machine rooms, computing, storage, networks, safety, application support, information resources and the like in a comprehensive mode, exerts the characteristics of cloud computing virtualization, high reliability, high universality, high expandability, high speed, on-demand and elastic services and the like, and provides comprehensive services such as infrastructure, support software, application systems, information resources, operation guarantee and information safety for government industries.
During government cloud solution formulation, it is often necessary to draw a topological map to more intuitively present the solution to the user. Government cloud solutions often include complex resource requirements for computing, bare metal, storage, networking, security, Software Defined Networking (SDN), container cloud, desktop cloud, all-in-one, disaster recovery backup, and the like. In a topological graph, a plurality of service ranges are usually included, security information level protection requirements need to be met, and the topological graph has a large resource allocation and a complex topological structure.
In one embodiment, the first data may be data indicating a specific type of device and the number thereof in the government cloud platform.
In one embodiment, the first data may be data representing the model, name and number of various different types of devices in the government cloud platform.
In one embodiment, the first data may be determined according to construction requirements constructed by a government cloud platform.
And 102, acquiring a trained topological model.
The topological model is used for determining the layout information of each device in the topological graph.
In one embodiment, the layout information of each device in the topology map may indicate the connection relationship of each device in the topology map. Illustratively, it can be used to represent connection relationships between different types of device sets.
In one embodiment, the connection relationship between the devices may be used to represent the connection relationship between a device set of a specific type and a device set of another type.
In one embodiment, the connection relationship between the devices may be used to represent the connection relationship between the devices in a device set of a certain type. For example, the connection relationship between the devices in the device set may represent the connection relationship between the first switch device and the second switch device.
In one embodiment, the connection relationship between the devices may be used to represent the connection relationship between all the devices in the cloud platform.
In one embodiment, the layout information of each device in the topological graph may indicate a setting position of each device in the topological graph. The setting of the position may include a relative positional relationship and/or an absolute positional relationship between the respective devices, for example.
In one embodiment, the relative position relationship of each device in the topological graph may include a relative position relationship of each device in a vertical direction and/or a relative position relationship of each device in a horizontal direction in the topological graph.
In an embodiment, the trained topology model may be obtained by training according to sample data constructed by the cloud platform. Wherein, the sample data of the cloud platform member may include at least one of the following: the configuration parameters of various types of equipment and the layout relations of various types of equipment are used for constructing the cloud platform, and the configuration parameters of various types of equipment sets and the layout relations corresponding to the equipment sets are used for constructing the cloud platform.
In an embodiment, according to configuration parameters of various types of devices and/or layout relationships of various types of devices, a topological connection relationship between the devices can be obtained, and then a topological model is trained based on the topological connection relationship, so that a trained topological model is obtained.
In one embodiment, the topology model may be a neural network, and accordingly, the trained topology model may be obtained by adjusting parameters of the neural network based on the above sample data.
In an embodiment, the topology model may further include configuration parameters of a specific type of device in a cloud platform building process and a processing method of a connection relationship between the specific type of devices, and the configuration parameters of the specific type of device may be, for example, configuration parameters of a device set.
In an embodiment, the topology model may further include a processing method for configuration parameters of a specified type of device in a specific type of device in the cloud platform and a connection relationship between the specified type of device and any other device.
In an embodiment, the topology model may include a processing method for configuration parameters of any first-type device set and any other second-type device set in the cloud platform building process and a connection relationship between any first-type device set and any other second-type device set.
In one embodiment, the topology model may include recommended information and mandatory information. Wherein, the recommendation information may include: the position relation of each device contained in the cloud platform comprises the horizontal position and the vertical position of each device; the optional information may include a connection mode determined according to parameter information of each device in the cloud platform, and for example, the connection mode may be a vertical connection mode or a horizontal connection mode between the devices.
It should be noted that, in the embodiment of the present application, the order of step 101 and step 102 may be interchanged.
And 103, generating second data based on the first data and the topological model.
And the second data is used for representing a topological graph corresponding to the cloud platform.
In one embodiment, the second data may be used to represent a topology graph between different types of device sets in the cloud platform.
Accordingly, the second data is generated based on the first data and the topology model, and the configuration data of each device set in the first data can be input into the topology model, and the topology map of the device sets of different types is generated through the processing of the topology model.
In one embodiment, the second data may be used to represent a topological graph of a set of devices of a particular type and devices of other types in the cloud platform.
Accordingly, the second data is generated based on the first data and the topology model, and the configuration data of the device set of a specific type in the first data and the configuration data of the devices of other types are input into the topology model, and a topological graph of the device set of the specific type and the devices of other types in the cloud platform is generated through processing of the topology model.
In one embodiment, the second data may be used to represent a topology map within a device set of a certain type in the cloud platform.
Accordingly, the second data is generated based on the first data and the topology model, and the configuration data of a certain type of device set is input into the topology model, and a topological graph of a certain type of device in the cloud platform is generated through processing of the topology model.
In one embodiment, the second data may be used to represent a topology map that includes all devices in the cloud platform.
Accordingly, the second data is generated based on the first data and the topology model, and the configuration data of all the devices in the cloud platform may be input into the topology model, and the topology map of all the devices in the cloud platform may be generated through processing of the topology model.
In one embodiment, the second data may be used to represent a topology map of a particular type of cloud platform, such as a topology map of a government cloud platform.
Accordingly, the second data is generated based on the first data and the topology model, and the second data can be configuration data of a specific type of equipment representing the government affair cloud platform, which is input into the topology model, and a topological graph of the government affair cloud platform is generated through processing of the topology model.
The topological graph generating method provided by the embodiment of the application comprises the steps of firstly determining first data for representing configuration data of each device for constructing the cloud platform, obtaining a trained topological model for determining layout information of each device in the topological graph, and then generating second data for representing the topological graph of the cloud platform based on the first data and the topological model. Therefore, the topological graph generation method provided by the embodiment of the application can be used for quickly and automatically generating the topological graph of the cloud platform through the trained topological model on the basis of the configuration data of each device of the cloud platform, so that the problems of long drawing period, low efficiency and high labor cost caused by manually drawing the topological graph in the related technology are solved.
Based on the foregoing embodiments, an embodiment of the present application provides a topological graph generation method, including the following steps:
step 201, determining first data.
The first data is used for representing configuration data of each device for constructing the cloud platform.
And step 202, obtaining the trained topological model.
The topological model is used for determining the layout information of each device in the topological graph.
Step 203, determining the topological connection relation based on the first data.
The topological connection relation comprises the connection relation among all the equipment sets.
In one embodiment, the topological connection relationship may include a connection relationship between sets of devices having data transmission requirements. Illustratively, the topological connection relationship may represent a connection relationship between a server device set and a switch device set.
In one embodiment, the topological connectivity relationship may indicate that no connectivity relationship is established between the first set of devices and the second set of devices.
In one embodiment, the topological connection relationship may include a master-slave relationship or a data transmission relationship between the device set and the device set, but cannot embody information such as a hierarchy, a location, and the like of the device set.
In one embodiment, the topological connection relationship may be determined based on the first data and actual environment data of the built cloud platform.
In one embodiment, the topological connection relationship may be determined based on the first data and requirement data of at least one of power consumption, heat dissipation, security, load, and the like of the cloud platform.
And step 204, generating second data based on the topological connection relation and the topological model.
In an embodiment, the second data may be second data generated by inputting the topological connection relationship into a topological model, and analyzing and processing configuration data of each device set and configuration data of devices in each device set in the topological connection relationship through the topological model.
Illustratively, step 204 may be implemented by step A1-step A4:
and A1, acquiring a connection relation model and a spatial position relation model based on the topological model.
The connection relation model is used for determining the connection relation among all the devices; and the spatial position relation model is used for determining the spatial position among the devices.
In one embodiment, the connection relation model can be used for optimizing the connection relation among the device sets in the topological connection relation.
In one embodiment, a connection relationship model may be used to determine a connection relationship between devices in a first device set and devices in a second device set. Illustratively, it may comprise whether a device in the first device set needs to establish a connection relationship with a device in the second device set.
In one embodiment, the connection relation model may optimize the connection relation of the device set according to configuration parameters of the device set, the number of devices in the device set, and other parameters.
In one embodiment, the connection relation model may determine the connection relation of each device according to configuration parameters of each device in the device set.
In one embodiment, the spatial relationship model may optimize the setting positions of the device sets after the connection relationship is determined.
In one embodiment, the spatial relationship model may optimize the relative or absolute position of each device set or device after the connection relationship is determined.
Illustratively, the spatial position relationship model and the connection relationship model are obtained based on a topology model, and the spatial position relationship model and the connection relationship model can be obtained based on functional division of the topology model and control of functions of the topology model.
And A2, processing the topological connection relation through the connection relation model to obtain third data representing the connection relation among the devices.
In an embodiment, the third data may be obtained by analyzing, through the connection relationship model, configuration data of each device set in the topological connection relationship and/or configuration data of each device in the device set.
In one embodiment, the third data may be obtained by inputting the requirement data constructed by the cloud platform and the topological connection relation into the connection relation model.
And A3, processing the topological connection relation through the spatial position relation model to obtain fourth data representing the spatial position relation of each device.
In an embodiment, the fourth data may be obtained by analyzing, through a spatial location relationship model, configuration data of each device set in the topological connection relationship and/or configuration data of each device inside the device set.
In one embodiment, the fourth data may be obtained by inputting the demand data constructed by the cloud platform and the topological connection relationship into the spatial position relationship model.
Step a4, the third data and the fourth data are processed to generate second data.
In one embodiment, the second data may be generated by fusing the third data and the fourth data.
In one embodiment, the second data may be generated by fusing the third data and the fourth data and optimizing the fusion result.
Illustratively, step a4, may include step B1-step B2:
and step B1, determining a graphic processing algorithm.
The graphic processing algorithm is used for performing layout processing on each device of the cloud platform.
In an implementation manner, the graph processing algorithm may be used to perform optimization processing on data output by the topology model, so as to obtain a more intuitive and visual connection relationship and spatial position relationship between the devices.
In one embodiment, a graphics processing algorithm may be used to optimize the outputs of the connection relation model and the spatial location relation model, respectively.
In one embodiment, the graphics processing algorithm may be an algorithm designed and adjusted according to the requirement data of the cloud platform component.
In one embodiment, the graphics processing algorithm may be optimized for the source graphics processing algorithm.
In one embodiment, the graphics processing algorithm may be an open source algorithm library GraphViz.
In one embodiment, the layout process may optimize the spatial position relationship of each device on the basis of determining the connection relationship of each device.
In one embodiment, the layout process may be to optimize the connection relationship and/or the spatial position relationship of each device according to the requirement data of the cloud platform component.
And step B2, processing the third data and the fourth data based on a graphic processing algorithm to generate second data.
In one embodiment, the second data may be generated by:
and processing the third data and the fourth data in sequence based on a graph processing algorithm to generate second data.
In one embodiment, the second data may be generated by:
fusing the third data and the fourth data to obtain initial topological data containing the connection relation and the spatial position relation of each device; and processing the initial topological data based on a graph processing algorithm to generate second data.
In one embodiment, step B2 may be implemented by steps C1-C2:
and step C1, obtaining an equipment relation setting model and an equipment hierarchy setting model based on a graphic processing algorithm.
The device relationship setting model is used for setting the connection relationship of each device in at least one direction; and the equipment level setting model is used for setting levels among the equipment.
In one embodiment, the device relationship setting model may set the connection relationship of each device in at least one direction based on configuration data of each device.
In an embodiment, the device relationship setting model may set a connection relationship of each device in at least one direction based on demand data constructed by the cloud platform.
In one embodiment, the device relationship setting model may set the connection relationship of each device in at least one direction based on the optimization operation of the graphics processing algorithm itself.
In one embodiment, the device hierarchy setting model may set a hierarchy between devices based on configuration data of the devices.
In one embodiment, the device hierarchy setting model may set a hierarchy between devices based on demand data constructed by the cloud platform.
In one embodiment, the device hierarchy setting model may set the hierarchy between devices based on optimization operations of the graphics processing algorithm itself.
In one embodiment, the hierarchy between devices may include a relative hierarchy between sets of devices.
In one embodiment, the hierarchy between devices may include a relative hierarchy between devices within each device set.
And step C2, processing the third data and the fourth data based on the equipment relation setting model and the equipment hierarchy setting model to generate second data.
In one embodiment, step C2 may be implemented by steps D1-D3:
and D1, processing the third data and the fourth data based on the device relation setting model, and determining the horizontal connection relation and the vertical connection relation among the devices.
In one embodiment, the horizontal connection relationship between the devices may be a connection relationship in a horizontal direction in a topological graph of various different types of devices in the cloud platform.
In one embodiment, the horizontal connection relationship between the devices may be a connection relationship in a horizontal direction in a topological graph between a device set of a certain type and a device set of other types in the cloud platform.
In one embodiment, the horizontal connection relationship between the devices may be a connection relationship between a specific device and other devices in the cloud platform in a horizontal direction in the topological graph.
In one embodiment, the horizontal connection relationship between the devices may include devices connected in a horizontal direction and devices connected in a non-horizontal direction in the cloud platform.
In one embodiment, the vertical connection relationship between the devices may be a connection relationship in a vertical direction in the topological graph between different types of device sets in the cloud platform.
In one embodiment, the vertical connection relationship between the devices may be a connection relationship in a vertical direction in a topological graph between a device set of a certain type and a device set of other types in the cloud platform.
In one embodiment, the vertical connection relationship between the devices may be a connection relationship between a specific device and other devices in the cloud platform in a vertical direction in the topological graph.
In one embodiment, the vertical connection relationship between the devices may include a device with a vertical connection and a device without a vertical connection in the devices in the cloud platform.
In one embodiment, the horizontal connection relationship and the vertical connection relationship between the devices may be determined by:
and processing the third data and the fourth data in sequence based on the equipment relationship setting model, and determining the horizontal connection relationship and the vertical connection relationship among the equipment.
In one embodiment, the horizontal connection relationship and the vertical connection relationship between the devices may be determined by:
fusing the third data and the fourth data to obtain initial topological data containing the connection relation and the spatial position relation of each device; and optimizing the initial topological data through the equipment relation setting model, and further determining the horizontal connection relation and the vertical connection relation among the equipment.
And D2, setting a model based on the equipment hierarchy, and laying out the horizontal connection relation and the vertical connection relation to obtain a layout result.
In one embodiment, the layout result may include actual placement positions of the respective devices in a topology map of the cloud platform.
In one embodiment, the layout result may further include a deployment location of each device set in a topological graph of the cloud platform.
In an embodiment, the layout result may further include the strength of the connection relationship and/or the existence of the connection relationship between the devices in the cloud platform topology map.
In one embodiment, the layout result may include a hierarchical relationship of each device in the cloud platform topological graph, and may include a hierarchical relationship of each device set in the topological graph.
In one embodiment, the hierarchical relationship may be used to represent a master-slave relationship of devices and/or device sets in a topology graph.
In one embodiment, the hierarchical relationship may be used to represent a hierarchical relationship in which devices and/or device sets are laid out in a certain direction on a topological graph. Illustratively, a certain direction may mean a horizontal direction or a vertical direction.
And D3, generating second data based on the layout result.
In one embodiment, the second data may be generated by optimizing the layout result through a relevant module or interface in the graphics processing algorithm.
In one embodiment, the second data may be generated by a hierarchical representation of the layout result by a graphics processing algorithm.
In one embodiment, the second data may be generated by highlighting a specified area or a particular set of devices in the layout result.
Therefore, the hierarchical relationship in the finally obtained topological graph is clearer and the layout is more reasonable.
Illustratively, step D3 may be implemented by steps E1-E2:
and E1, acquiring icon information of each device and a graphic output module.
And the graph output module is used for outputting the topological graph.
Illustratively, the icon information may include information of icons representing respective devices in the topological graph space, including size, color, style, font, number, and the like of the icons.
In one embodiment, the icon information may be information of icons used to represent various types of device sets in a topology space.
In one embodiment, the icon information may be pre-configured.
In one embodiment, the icon information may be set according to the needs of the cloud platform construction.
In one embodiment, the icon information further includes connection lines of different styles and attribute information thereof.
In one embodiment, the graphics output module may be a function cut from a graphics processing algorithm.
In one embodiment, the Graphical output module may be a Graphical User Interface (GUI) in the Tkinter library. The GUI in the Tkinter library can adaptively add each icon information to the attribute of each device, and all the icon information is output together in the output topological graph. Illustratively, this may be achieved by inputting the layout results and icon information into a python Application Programming Interface (API) in the GUI module.
Based on the foregoing embodiments, fig. 3 is a diagram illustrating a specific implementation architecture of the topology generation method provided in the present application.
As shown in fig. 3, the method for generating a topological graph according to the embodiment of the present application is mainly implemented by the mutual cooperation between an apparatus configuration information reading module, an apparatus relationship establishing module, an apparatus relationship setting module, an apparatus hierarchy setting module, a drawing icon attribute setting module, and a topological graph output module.
In fig. 3, the device configuration information reading module is mainly used for reading a device configuration file. Illustratively, the device profile may be determined based on demand data for building the cloud platform. The device configuration file may include information such as the type, model, name, number, and specification of devices required for constructing the cloud platform. Optionally, after the information is determined based on the requirement data for constructing the cloud platform, the information is imported into an Excel file to form an equipment configuration file, so that the equipment configuration file can be read by an equipment configuration information reading module.
In fig. 3, a topology model is used to determine layout information between devices in a cloud platform based on demand data and configuration files for constructing the cloud platform. Specifically, the above function is realized by connecting the relationship model and the spatial position relationship model. The connection relation model is used for determining the connection relation among the devices based on the demand data and the configuration data among the devices in the configuration file. For example, the connection relation model may determine how each device has been connected before, and whether each device is connected. And the spatial position relation model is used for determining the spatial position of each device in the topological graph space.
In fig. 3, the device relationship setting module includes a horizontal relationship setting operation and a vertical relationship setting operation. The horizontal relation setting is used for determining the horizontal connection relation among all the devices; and the vertical relation setting is used for determining the vertical connection relation among the devices.
In fig. 3, the device hierarchy setting module is configured to set a hierarchical relationship between devices based on the set horizontal connection relationship and the set vertical connection relationship. In some embodiments, the hierarchical relationship between devices may be set based on horizontal connection relationships, vertical connection relationships, and a topology model.
In fig. 3, a drawing icon attribute setting module is used for managing and setting attributes of the shape, size, font, color, and the like of each device icon and each device set icon in the topological graph.
In fig. 3, a graphic output module for outputting a topology map, the functions of which may include a topology map preview and a topology map export. The topological graph previewing is used for checking and comparing the drawn topological graph; and exporting the topological graph, wherein the topological graph after drawing is output as a picture in a preset format. And for the drawing process of the topological graph, the self-adaptive layout can be carried out by using a Python API of an open source algorithm library GraphViz, and the formats of png, jpeg or bmp and the like which can be selected for deriving the topological graph can be used.
Illustratively, the specific implementation flow of the topology generation method provided by the embodiment of the present application is as follows:
firstly, based on the requirement data for constructing the cloud platform, an equipment configuration file is obtained, wherein the file can be an excel file, and relevant information in the configuration file, namely first data, is read through an equipment information reading module.
And secondly, obtaining the connection relation and the space position relation between the devices based on the first data and the required data for constructing the cloud platform through the device relation connection model and the device space position model in the device relation establishing module.
And thirdly, converting the connection relation among the devices into the horizontal connection relation and the vertical connection relation among the devices in the Python code through the horizontal relation setting operation and the vertical relation setting operation in the device relation setting module.
And fourthly, determining the hierarchical relationship between the devices by the device hierarchical setting module based on the horizontal connection relationship and the vertical connection relationship between the devices and combining a topological model in some embodiments, and setting the devices without the horizontal connection relationship in the same horizontal connection layer.
Fifthly, the attributes of the icon shape, size, characters, color and the like of each device or device set are configured through a drawing icon attribute setting module.
And finally, running a Python program, automatically laying out and typesetting to generate a topological graph, and selecting topological graph preview or topological graph export.
Taking the process of generating the topological graph of the government affair cloud as an example, the topological graph of the government affair cloud obtained by the topological graph generating method provided by the application shown in fig. 4 can be obtained through the above operation steps.
In fig. 4, the connection relationship between the respective devices is complicated, and the kinds and the number of the devices are large. However, in fig. 4, the horizontal connection relationship and the vertical connection relationship between the devices are clear, the layers are distinct, and the overall drawing is concise and intuitive.
The topological graph generation method provided by the embodiment of the application determines configuration data for representing each device for building the cloud platform, determines the connection relation based on the first data, and then generates second data based on the connection relation and the spatial position relation. Therefore, the topological graph generation method provided by the embodiment of the application realizes automatic drawing of the topological graph, and solves the problems of long drawing period, complex process and high labor cost caused by manual drawing of the topological graph in the related technology.
Based on the foregoing embodiments, an embodiment of the present application provides a topological diagram generation system 3, and as shown in fig. 5, a structural diagram of the topological diagram generation system is provided, where the topological diagram generation system 3 includes:
a processor 31, a memory 32 and a communication bus; wherein:
a communication bus for realizing communication connection between the processor 31 and the memory 32;
the processor 31 is configured to execute a program of a topology map generation method in the memory to implement the following steps:
determining first data; the first data is used for representing configuration data of each device for constructing the cloud platform;
acquiring a trained topological model; the topological model is used for determining the layout information of each device in a topological graph;
generating second data based on the first data and the topology model; and the second data is used for representing a topological graph of the cloud platform.
The processor 31 is configured to execute the program for generating the topology map in the memory to implement the following steps: determining a topological connection relation based on the first data; the topological connection relation comprises the connection relation among all the equipment sets;
and generating the second data based on the topological connection relation and the topological model.
The processor 31 is configured to execute a program of a topology map generation method in the memory to implement the following steps:
acquiring a connection relation model and a space position relation model based on the topological model; the connection relation model is used for determining the connection relation among the devices; the spatial position relation model is used for determining spatial positions among the devices;
processing the topological connection relation through the connection relation model to obtain third data representing the connection relation among the devices;
processing the topological connection relation through the spatial position relation model to obtain fourth data representing the spatial position relation of each device;
and processing the third data and the fourth data to generate the second data. .
The processor 31 is configured to execute a program of a topology map generation method in the memory to implement the following steps:
determining a graph processing algorithm; the graphic processing algorithm is used for performing layout processing on each device of the cloud platform;
and processing the third data and the fourth data based on the image processing algorithm to generate the second data.
The processor 31 is configured to execute a program of a topology map generation method in the memory to implement the following steps: obtaining an equipment relation setting model and an equipment level setting model based on the graph processing algorithm; the device relationship setting model is used for setting the connection relationship of each device in at least one direction; the equipment level setting model is used for setting levels among the equipment;
and processing the third data and the fourth data based on the equipment relationship setting model and the equipment hierarchy setting model to generate the second data.
The processor 31 is configured to execute a program of a topology map generation method in the memory to implement the following steps:
processing the third data and the fourth data based on the equipment relationship setting model, and determining a horizontal connection relationship and a vertical connection relationship among the equipment;
based on the equipment level setting model, carrying out layout on the horizontal connection relation and the vertical connection relation to obtain a layout result;
generating the second data based on the layout result.
The processor 31 is configured to execute a program of a topology map generation method in the memory to implement the following steps:
acquiring icon information and a graphic output module of each device; the graph output module is used for outputting a topological graph;
and generating the second data based on the icon information and the layout result through the graphic output module.
In practical applications, the processor 31 may be at least one of an application specific integrated circuit ASIC, a digital signal processor DSP, a PLD, an FPGA, a CPU, a controller, a microcontroller, and a microprocessor. The embodiment of the present application does not limit this.
The memory 32 may be a volatile memory (RAM); or a non-volatile memory (non-volatile memory) such as a ROM, a flash memory (flash memory), a Hard Disk (Hard Disk Drive, HDD) or a Solid-State Drive (SSD); or a combination of the above types of memories and provides instructions and data to the processor 31.
The topological graph generating system provided by the embodiment of the application firstly determines first data used for representing configuration data of each device for constructing the cloud platform, obtains a trained topological model used for determining layout information of each device in the topological graph, and then generates second data used for representing the topological graph of the cloud platform based on the first data and the topological model. Therefore, in the topological graph generating system provided by the embodiment of the application, the topological graph of the cloud platform can be quickly and automatically generated through the trained topological model on the basis of the configuration data of each device of the cloud platform, so that the problems of long drawing period, low efficiency and overhigh labor cost caused by manually drawing the topological graph in the related technology are solved.
Based on the foregoing embodiments, an embodiment of the present application provides a topology map generating device 4, and as shown in fig. 6, the topology map generating device 4 is a structure diagram of the topology map generating device, and includes: a determination module 41 and a processing module 42; wherein:
a determining module 41, configured to determine first data and obtain a trained topology model; the first data is used for representing configuration data of each device for constructing the cloud platform;
a processing module 42 for generating second data based on the first data and the topology model; and the second data is used for representing a topological graph of the cloud platform.
In some embodiments, the processing module 42 is configured to determine a topological connection relationship based on the first data; the topological connection relation comprises the connection relation among all the equipment sets;
the processing module 42 is further configured to generate the second data based on the topological connection relationship and the topological model.
In some embodiments, the processing module 42 is configured to obtain a connection relationship model and a spatial location relationship model based on the topology model; the connection relation model is used for determining the connection relation among the devices; the spatial position relation model is used for determining spatial positions among the devices;
processing the topological connection relation through the connection relation model to obtain third data representing the connection relation among the devices;
processing the topological connection relation through the spatial position relation model to obtain fourth data representing the spatial position relation of each device;
and processing the third data and the fourth data to generate the second data.
A processing module 42 for determining a graphics processing algorithm; the graphic processing algorithm is used for performing layout processing on each device of the cloud platform;
and processing the third data and the fourth data based on the image processing algorithm to generate the second data.
A processing module 42, configured to obtain an equipment relationship setting model and an equipment hierarchy setting model based on the graph processing algorithm; the device relationship setting model is used for setting the connection relationship of each device in at least one direction; the equipment level setting model is used for setting levels among the equipment;
and processing the third data and the fourth data based on the equipment relationship setting model and the equipment hierarchy setting model to generate the second data.
A processing module 42, configured to process the third data and the fourth data based on the device relationship setting model, and determine a horizontal connection relationship and a vertical connection relationship between the devices;
based on the equipment level setting model, carrying out layout on the horizontal connection relation and the vertical connection relation to obtain a layout result; generating the second data based on the layout result.
A processing module 42, configured to obtain icon information and a graphic output module of each device; the graph output module is used for outputting a topological graph;
and generating the second data based on the icon information and the layout result through the graphic output module.
In practical applications, the determining module 41 and the processing module 42 may be implemented by a processor in an electronic device, where the processor is at least one of an ASIC, a DSP, a DSPD, a PLD, an FPGA, a CPU, a controller, a microcontroller, and a microprocessor.
The topological graph generating device provided by the embodiment of the application firstly determines first data used for representing configuration data of each device for constructing the cloud platform, obtains a trained topological model used for determining layout information of each device in the topological graph, and then generates second data used for representing the topological graph of the cloud platform based on the first data and the topological model. Therefore, the topological graph generating device provided by the embodiment of the application can automatically and quickly generate the topological graph of the cloud platform based on the configuration data of each device of the cloud platform and the trained topological model, so that the problems of long drawing period, low efficiency and high labor cost caused by manually drawing the topological graph in the related technology are solved.
Based on the foregoing embodiments, the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program is executed by a processor of a topology map generation device to perform the topology map generation method according to any one of the foregoing embodiments.
In some embodiments, functions of or modules included in the apparatus provided in the embodiments of the present invention may be used to execute the method described in the above method embodiments, and specific implementation thereof may refer to the description of the above method embodiments, and for brevity, will not be described again here.
The foregoing description of the various embodiments is intended to highlight various differences between the embodiments, and the same or similar parts may be referred to each other, and for brevity, will not be described again herein.
The methods disclosed in the method embodiments provided by the present application can be combined arbitrarily without conflict to obtain new method embodiments.
Features disclosed in various product embodiments provided by the application can be combined arbitrarily to obtain new product embodiments without conflict.
The features disclosed in the various method or apparatus embodiments provided herein may be combined in any combination to arrive at new method or apparatus embodiments without conflict.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.

Claims (10)

1. A method for generating a topological graph, the method comprising:
determining first data; the first data is used for representing configuration data of each device for constructing the cloud platform;
acquiring a trained topological model; the topological model is used for determining the layout information of each device in a topological graph;
generating second data based on the first data and the topology model; and the second data is used for representing a topological graph corresponding to the cloud platform.
2. The method of claim 1, wherein generating the second data based on the first data and the topology model comprises:
determining a topological connection relation based on the first data; the topological connection relation comprises the connection relation among all the equipment sets;
and generating the second data based on the topological connection relation and the topological model.
3. The method of claim 2, wherein generating the second data based on the topological connection relationship and the topological model comprises:
acquiring a connection relation model and a space position relation model based on the topological model; the connection relation model is used for determining the connection relation among the devices; the spatial position relation model is used for determining spatial positions among the devices;
processing the topological connection relation through the connection relation model to obtain third data representing the connection relation among the devices;
processing the topological connection relation through the spatial position relation model to obtain fourth data representing the spatial position relation of each device;
and processing the third data and the fourth data to generate the second data.
4. The method of claim 3, wherein the processing the third data and the fourth data to generate the second data comprises:
determining a graph processing algorithm; the graphic processing algorithm is used for performing layout processing on each device of the cloud platform;
and processing the third data and the fourth data based on the image processing algorithm to generate the second data.
5. The method of claim 4, wherein the processing the third data and the fourth data based on the graphics processing algorithm to generate the second data comprises:
obtaining an equipment relation setting model and an equipment level setting model based on the graph processing algorithm; the device relationship setting model is used for setting the connection relationship of each device in at least one direction; the equipment level setting model is used for setting levels among the equipment;
and processing the third data and the fourth data based on the equipment relationship setting model and the equipment hierarchy setting model to generate the second data.
6. The method of claim 5, wherein the processing the third data and the fourth data based on the device relationship setting model and the device hierarchy setting model to generate the second data comprises:
processing the third data and the fourth data based on the equipment relationship setting model, and determining a horizontal connection relationship and a vertical connection relationship among the equipment;
based on the equipment level setting model, carrying out layout on the horizontal connection relation and the vertical connection relation to obtain a layout result;
generating the second data based on the layout result.
7. The method of claim 6, wherein generating the second data based on the layout result comprises:
acquiring icon information and a graphic output module of each device; the graph output module is used for outputting a topological graph;
and generating the second data based on the icon information and the layout result through the graphic output module.
8. A topological map generation system, comprising: a processor, a memory, and a communication bus; wherein:
the communication bus is used for realizing communication connection between the processor and the memory;
the processor is used for executing the program of the topological graph generation method in the memory so as to realize the following steps:
determining first data; the first data is used for representing configuration data of each device for constructing the cloud platform;
acquiring a trained topological model; the topological model is used for determining the layout information of each device in a topological graph;
generating second data based on the first data and the topology model; wherein the second data is used for representing a topological graph of the cloud platform.
9. A topology map generation apparatus, characterized in that the apparatus comprises: a determining module and a processing module; wherein:
the determining module is used for determining first data and acquiring a trained topology model; the first data is used for representing configuration data of each device constructing the cloud platform; the topology model is used for determining the layout information of each device in the topological graph;
the processing module is used for generating second data based on the first data and the topological model; wherein the second data is used for representing a topological graph of the cloud platform.
10. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor of a topology map generation apparatus, implements the topology map generation method of any one of claims 1 to 7.
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