CN114070741B - Topology graph generation method, system, equipment and storage medium - Google Patents
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Abstract
The application provides a topology graph generation method, which relates to the technical field of information, and comprises the following steps: determining first data; the first data are used for representing configuration data of each device constructing the cloud platform; obtaining a topology model after training; the topology model is used for determining layout information of each device in a topology graph; generating second data based on the first data and the topology model; the second data is used for representing a topological graph corresponding to the cloud platform. The topology map generation method can solve the problems of long drawing period, complicated working procedures and high labor cost caused by manual drawing of the topology map of the cloud platform in the related technology, realizes automatic drawing of the topology map of the cloud platform, shortens the drawing period, simplifies the working procedures and reduces the labor cost. The application also provides a topology map generation system, a topology map generation device and a computer readable storage medium.
Description
Technical Field
The present disclosure relates to the field of information technologies, and in particular, to a topology map generating method, system, device, and computer readable storage medium.
Background
Cloud platforms, which are platforms that provide computing, networking, 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 cooperation among various devices in the cloud platform. The deployment of the cloud platform is usually realized on the basis of a topological graph of the cloud platform, and the connection relation and the setting position of each device in the cloud platform can be clearly and intuitively shown in the topological graph of the cloud platform.
In the related art, a topology map of a cloud platform generally requires manual drawing.
However, the method of manually drawing the topological graph has long drawing period, complicated working procedure and high labor cost.
Disclosure of Invention
In order to solve the problems of long drawing period, complicated working procedures and high labor cost of manually drawing the topological graph in the related technology, the application provides a generation method of the topological graph, and the method can realize automatic drawing of the topological graph of the cloud platform, so that the drawing period of the topological graph is shortened, the working procedures are simplified, and the labor cost is reduced.
The technical scheme that this application provided is as follows:
a topology map generation method, the method comprising:
determining first data; the first data are used for representing configuration data of each device constructing the cloud platform;
obtaining a topology model after training; the topology model is used for determining layout information of each device in a topology graph;
generating second data based on the first data and the topology model; the second data is used for representing a topological graph corresponding to the cloud platform.
In some embodiments, the generating second data based on the first data and the topology model includes:
determining a topological connection relation based on the first data; the topological connection relation comprises connection relations among all 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 spatial position relation 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 the 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 graphic processing algorithm; the graphic processing algorithm is used for carrying out layout processing on each device of the cloud platform;
and processing the third data and the fourth data based on the graphic 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 a device relation setting model and a device hierarchy setting model based on the graphic processing algorithm; the device relation setting model is used for setting the connection relation of each device in at least one direction; the equipment hierarchy setting model is used for setting the hierarchy among the equipment;
And processing the third data and the fourth data based on the equipment relation 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 setup model and the device hierarchy setup model to generate second data includes:
processing the third data and the fourth data based on the equipment relation setting model, and determining a horizontal connection relation and a vertical connection relation between the equipment;
based on the equipment hierarchy setting model, laying out the horizontal connection relation and the vertical connection relation to obtain a layout result;
and generating the second data based on the layout result.
In some embodiments, the generating the second data based on the layout result includes:
the icon information and the graphic output module of each device are obtained; the graphic 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 application also provides a topology map generation system, which comprises: 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 configured to execute a program of the topology map generation method in the memory to implement the steps of:
determining first data; the first data are used for representing configuration data of each device constructing the cloud platform;
obtaining a topology model after training; the topology model is used for determining layout information of each device in a topology graph;
generating second data based on the first data and the topology model; the second data is used for representing a topological graph of the cloud platform.
The application also provides a topology map generation device, which comprises: a determining module and a processing module; wherein:
the determining module is used for determining first data and acquiring a trained topological model; the first data are used for representing configuration data of each device constructing the cloud platform; the topology model is used for determining layout information of each device in a topology graph;
The processing module is used for generating second data based on the first data and the topology model; 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 a topology map generation method of any of the above.
According to the topology map generation method, first data used for representing configuration data of each device constructing the cloud platform are determined, a topology model used for determining training completion of layout information of each device in the topology map is obtained, and then second data used for representing the topology map of the cloud platform are generated based on the first data and the topology model. Therefore, in the topology map generation method provided by the application, the topology map of the cloud platform can be automatically and rapidly generated based on the configuration data of each device of the cloud platform and the trained topology model, so that the problems of long drawing period, low efficiency and high labor cost caused by manually drawing the topology map in the related technology are solved.
Drawings
FIG. 1 is a flowchart of a first topology map generation method provided in the present application;
FIG. 2 is a flow chart of a second topology map generation method provided herein;
FIG. 3 is a schematic diagram of a specific implementation of a topology generating method provided in the present application;
fig. 4 is a topology diagram of a government cloud platform obtained by the topology diagram generation method provided by the application;
FIG. 5 is a block diagram of a topology map generation system provided in an embodiment of the present application;
fig. 6 is a block diagram of a topology generating apparatus provided in the present application.
Detailed Description
The present disclosure relates to the field of information technologies, and in particular, to a topology map generating method, system, device, and computer readable storage medium.
Due to the reasons of diversity of the cloud platform function implementation, diversity of the service targets, high frequency of service demand change and the like, when the cloud platform is deployed, the influence of factors such as the diversity of the cloud platform function implementation, the diversity of the service targets, the speed of service demand change and the like on cooperative calculation among all devices in the cloud platform needs to be fully considered.
Therefore, before cloud platform deployment, a comprehensive assessment of the deployment of each device in the platform is required. In practical application, the evaluation of cloud platform deployment comprises the evaluation of connection relation, deployment position, interaction mode between devices, interaction efficiency between devices and the like of each device for constructing the cloud platform.
Because the types and the number of the devices in the cloud platform are large, the cloud platform deployment is evaluated by drawing a topological graph, various types of devices are represented in an image and visual mode through drawing the topological graph, the evaluation speed can be increased, and the evaluation effect is ensured. Therefore, the correct drawing of the topological graph is very important to 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 a manual drawing mode. For example, by means of certain drawing software such as Visio, icons of various types of devices are drawn one by one according to the deployment requirement of a cloud platform, the devices are connected one by one, and then the devices with different layers, different roles and different types are labeled one by one.
In the process of drawing the topological graph, the drawing is realized completely by manpower, so that the drawing time is long, the working procedure is complicated, the labor cost is high, and the drawing is easy to make mistakes.
In order to solve the above problems, embodiments of the present application provide a topology map generation method, which may be implemented by a topology map generation apparatus, and may be implemented by a processor of the topology map generation apparatus, for example.
In practical applications, the processor may be at least one of an application specific integrated circuit (Application Specific Integrated Circuit, ASIC), a digital signal processor (digital signal processor), a DSP), a programmable logic device (programmable logic device, PLD), an on-chip programmable gate array (Field Programmable Gate Array, FPGA), a central processing unit (central processing unit, CPU), a controller, a microcontroller, and a microprocessor.
As shown in fig. 1, the topology map generating method provided by the embodiment of the present application may include the following steps:
step 101, determining first data.
The first data are used for representing configuration data of each device constructing the cloud platform.
In one embodiment, the first data may be used to represent data of the type of each device building the cloud platform.
In one embodiment, the first data may be used to represent the type of each device that constructs 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 each set of devices that build the cloud platform. Wherein, the device set may represent a set of a plurality of devices having the same function. By way of example, a set of devices served may represent a collection of servers of a variety of different models.
In one embodiment, the first data may be used to represent configuration data for each device building a cloud platform of some type.
In one embodiment, the first data may be used to represent configuration data for each device that constructs the government cloud platform.
Specifically, the government cloud platform is a platform which utilizes cloud computing technology, comprehensively utilizes the existing machine room, computing, storage, network, security, application support, information resources and the like, exerts the characteristics of cloud computing virtualization, high reliability, high universality, high expandability, rapidness, demand, elastic service and the like, and provides comprehensive services such as infrastructure, support software, application systems, information resources, operation guarantee, information security and the like for government industry.
In government cloud solution formulation, it is often necessary to draw a topological graph to more intuitively present the solution to the user. The government cloud solutions often include complex resource requirements such as computation, bare metal, storage, network, security, software defined network (Software Defined Network, SDN), container cloud, desktop cloud, all-in-one, disaster recovery backup, and the like. In the topology diagram, a plurality of service ranges are generally included, the security information level protection requirement is required to be met, and the resource configuration is numerous and the topology structure is complex.
In one embodiment, the first data may be data representing a specific type of device and the number thereof in the government cloud platform.
In one embodiment, the first data may be used to represent model, name, and quantity data for various different types of devices in the government cloud platform.
In one embodiment, the first data may be determined according to a construction requirement of government cloud platform construction.
Step 102, obtaining a trained topology model.
The topology model is used for determining layout information of each device in the topology graph.
In one embodiment, the layout information of each device in the topology map may represent the connection relationship of each device in the topology map. For example, it may be used to represent the connection relationship between different types of device sets.
In one embodiment, the connection relationship between devices may be used to represent the connection relationship between a specific type of device set and other types of device sets.
In one embodiment, the connection relationship between the devices may be used to represent the connection relationship between the devices in a certain type of device set. For example, the connection relationship between the respective 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 topology map may represent a setting position of each device in the topology map. Illustratively, the setting position may include a relative positional relationship and/or an absolute positional relationship between the respective devices.
In one embodiment, the relative positional relationship of each device in the topology map may include a relative positional relationship of each device in a vertical direction and/or a relative positional relationship in a horizontal direction in the topology map.
In one embodiment, the trained topology model may be trained from sample data constructed from a cloud platform. Wherein the sample data of the cloud platform component may include at least one of: configuration parameters of various types of equipment and layout relations of various types of equipment, configuration parameters of various types of equipment sets and layout relations corresponding to the equipment sets, which are used for constructing the cloud platform.
In one embodiment, according to configuration parameters of various types of devices and/or layout relations of various types of devices, a topology connection relation between the various devices can be obtained, and then a topology model is trained based on the topology connection relation, so that a trained topology 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 specific types of devices in the cloud platform construction process and a processing method of connection relationships between the specific types of devices, where, for example, the configuration parameters of the specific types of devices may be configuration parameters of a device set.
In an embodiment, the topology model may further include a processing method for configuration parameters of a designated number device in a specific type of device in the cloud platform and a connection relationship between the designated type of device and any other device.
In one embodiment, the topology model may include a method for processing configuration parameters of any one first type device set and any other second type device set in the cloud platform construction process, and a connection relationship between any one first type device set and any other second type device set.
In one embodiment, the topology model may include recommendation 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 necessary information may include a connection manner determined according to parameter information of each device in the cloud platform, and the connection manner may be, for example, a vertical connection manner or a horizontal connection manner between each device.
It should be noted that, in the embodiment of the present application, the order of the step 101 and the step 102 may be interchanged.
Step 103, 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 one embodiment, the second data may be used to represent a topology graph between different types of device sets in the cloud platform.
Correspondingly, 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 different types of device sets is generated through the processing of the topology model.
In one embodiment, the second data may be used to represent a topology of a particular type of device set and other types of devices in the cloud platform.
Correspondingly, the second data is generated based on the first data and the topology model, and the configuration data of a certain specific type of device set in the first data and the configuration data of other types of devices are input into the topology model, and a topological graph of the certain specific type of device set in the cloud platform and the other types of devices is generated through processing of the topology model.
In one embodiment, the second data may be used to represent a topology map inside a set of devices of a certain type in the cloud platform.
Correspondingly, the second data is generated based on the first data and the topology model, and the configuration data of a certain type of equipment set can be input into the topology model, and a topology diagram of a certain type of equipment 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.
Correspondingly, the second data is generated based on the first data and the topology model, and the configuration data of all devices in the cloud platform can be input into the topology model, and the topology map of all devices 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 of a particular type of cloud platform, such as a government cloud platform.
Correspondingly, the second data is generated based on the first data and the topology model, and can be a topological graph of the government cloud platform generated by inputting configuration data of a specific type of equipment representing the government cloud platform into the topology model and processing the topology model.
According to the topology map generation method, first data used for representing configuration data of each device constructing a cloud platform are determined, a topology model used for determining training completion of layout information of each device in the topology map is obtained, and then second data used for representing the topology map of the cloud platform are generated based on the first data and the topology model. Therefore, the topology map generation method provided by the embodiment of the application can quickly and automatically generate the topology map of the cloud platform by training the completed topology model on the basis of 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 topology map in the related technology are solved.
Based on the foregoing embodiments, embodiments of the present application provide a topology map generation method, including the following steps:
step 201, determining first data.
The first data are used for representing configuration data of each device constructing the cloud platform.
Step 202, obtaining a trained topology model.
The topology model is used for determining layout information of each device in the topology graph.
Step 203, determining a topological connection relation based on the first data.
The topological connection relation comprises connection relations among all equipment sets.
In one embodiment, the topological connection relationship may include a connection relationship between respective device sets having data transmission requirements. By way of example, the topological connection relationship may represent a connection relationship between a set of server devices and a set of switch devices.
In one embodiment, the topological connection may indicate that no connection 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 sets, but cannot embody information such as hierarchy, position, etc. of the device sets.
In one embodiment, the topological connection relationship may be determined based on the first data and actual environmental data of the build cloud platform.
In one embodiment, the topological connection relationship may be determined based on the first data and demand data for at least one of power consumption, heat dissipation, security, load, etc. of the build cloud platform.
Step 204, generating second data based on the topological connection relation and the topological model.
In one embodiment, the second data may be second data generated by inputting the topology connection relationship into a topology model, and analyzing and processing configuration data of each device set and configuration data of devices inside each device set in the topology connection relationship through the topology model.
Illustratively, step 204 may be implemented by steps A1-A4:
and A1, acquiring a connection relation model and a spatial position relation model based on the topology model.
The connection relation model is used for determining the connection relation among the devices; and the spatial position relation model is used for determining the spatial position between the devices.
In one embodiment, a connection relationship model may be used to optimize connection relationships between sets of devices in a topological connection relationship.
In one embodiment, a connection relationship model may be used to determine a connection relationship between a device in a first set of devices and a device in a second set of devices. For example, it may be included whether a device in the first set of devices needs to establish a connection with a device in the second set of devices.
In one embodiment, the connection relation model may optimize the connection relation of the device set according to parameters such as configuration parameters of the device set and the number of devices in the device set.
In one embodiment, the connection relationship model may determine the connection relationship of each device according to configuration parameters of each device in the device set.
In one embodiment, the spatial location relationship model may optimize the setting location of each device set after the connection relationship is determined.
In one embodiment, the spatial location relationship model may optimize the relative or absolute location of the respective device set or device after the connection relationship is determined.
The spatial positional relationship model and the connection relationship model are obtained based on the topology model, for example, and may be obtained based on functional division of the topology model and control of the functions of the topology model.
And A2, processing the topological connection relation through a connection relation model to obtain third data representing the connection relation among the devices.
In one embodiment, the third data may be obtained by analyzing, through a 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 and the topological connection relationship constructed by the cloud platform into the connection relationship model.
And A3, processing the topological connection relation through a spatial position relation model to obtain fourth data representing the spatial position relation of each device.
In one 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 in the device set.
In one embodiment, the fourth data may be obtained by inputting the requirement data and the topological connection relationship constructed by the cloud platform into a spatial location relationship model.
And A4, processing the third data and the fourth data 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 steps B1-B2:
and B1, determining a graphic processing algorithm.
The graphic processing algorithm is used for carrying out layout processing on each device of the cloud platform.
In one embodiment, the graphic processing algorithm can be used for optimizing the data output by the topology model, so that the connection relationship and the spatial position relationship among the devices are more visual and more vivid.
In one embodiment, a graphics processing algorithm may be used to optimize the output of the connection relationship model, the spatial location relationship model, respectively.
In one embodiment, the graphics processing algorithm may be an algorithm designed and adjusted according to the demand data of the cloud platform components.
In one embodiment, the graphics processing algorithm may be optimized for an open-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 positional relationship of each device based on determining the connection relationship of each device.
In one embodiment, the layout process may optimize the connection relationship and/or the spatial position relationship of each device according to the requirement data of the cloud platform component.
And B2, processing the third data and the fourth data based on a graph 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 turn 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 topology data containing the connection relation and the spatial position relation of each device; the initial topology data is processed based on a graphics processing algorithm to generate second data.
In one embodiment, step B2 may be implemented by steps C1-C2:
and step C1, obtaining a device relation setting model and a device hierarchy setting model based on a graphic processing algorithm.
The device relation setting model is used for setting the connection relation of each device in at least one direction; the device hierarchy setting model is used for setting the hierarchy among the devices.
In one embodiment, the device relation setting model may set the connection relation of the respective devices in at least one direction based on the configuration data of the respective devices.
In one embodiment, the device relation setting model may set a connection relation 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 the respective devices in at least one direction based on the optimization operation of the graphic processing algorithm itself.
In one embodiment, a 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 built by the cloud platform.
In one embodiment, the device hierarchy setting model may set the hierarchy between the devices based on the optimization operations of the graphics processing algorithm itself.
In one embodiment, the hierarchy between the devices may include a relative hierarchy between the sets of devices.
In one embodiment, the hierarchy between the devices may include a relative hierarchy between the devices within the respective device sets.
And 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 equipment relation setting model, and determining the horizontal connection relation and the vertical connection relation between the equipment.
In an embodiment, the horizontal connection relationship between the devices may be a connection relationship of a set of devices of different types in the cloud platform in a horizontal direction in the topology map.
In one embodiment, the horizontal connection relationship between each device may be a connection relationship between a specific type of device set and other types of device sets in the cloud platform in a horizontal direction in the topology map.
In one embodiment, the horizontal connection relationship between each device may be a connection relationship between a specific device and other devices in the cloud platform in a horizontal direction in the topology map.
In an embodiment, the horizontal connection relationship between the devices may include devices connected in a horizontal direction in each device in the cloud platform, and devices connected in a non-horizontal direction.
In one embodiment, the vertical connection relationship between the devices may be a connection relationship between different types of device sets in the cloud platform in a vertical direction in the topology graph.
In one embodiment, the vertical connection relationship between the devices may be a connection relationship between a specific type of device set and other types of device sets in the cloud platform in a vertical direction in the topology map.
In one embodiment, the vertical connection relationship between each device may be a connection relationship between a specific device and other devices in the cloud platform in a vertical direction in the topology map.
In one embodiment, the vertical connection relationship between the devices may include devices with a vertical connection in each device in the cloud platform, and devices without a vertical connection.
In one embodiment, the horizontal connection and the vertical connection between the respective devices may be determined by:
and based on the equipment relation setting model, processing the third data and the fourth data in sequence, and determining the horizontal connection relation and the vertical connection relation between the equipment.
In one embodiment, the horizontal connection and the vertical connection between the respective devices may be determined by:
fusing the third data and the fourth data to obtain initial topology data containing the connection relation and the spatial position relation of each device; and optimizing the initial topology data through a device relation setting model, and further determining the horizontal connection relation and the vertical connection relation between the devices.
And D2, laying out the horizontal connection relation and the vertical connection relation based on the equipment hierarchy setting model to obtain a layout result.
In one embodiment, the layout result may include an actual setting position of each device in the topology map of the cloud platform.
In one embodiment, the layout result may further include a deployment location of each device set in the topology map of the cloud platform.
In an embodiment, the layout result may further include the strength of the connection relationship between each device and/or whether there is a connection relationship between each device in the cloud platform topology map.
In one embodiment, the layout result may include a hierarchical relationship of each device in the cloud platform topology, and illustratively, may include a hierarchical relationship of each device set in the topology.
In one embodiment, the hierarchical relationship may be used to represent a master-slave relationship of individual devices and/or device sets in a topology graph.
In one embodiment, a hierarchical relationship may be used to represent a hierarchical relationship in which individual devices and/or sets of devices are laid out in a direction on a topology. Illustratively, a certain direction may represent 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 correlation module or interface in a graphics processing algorithm.
In one embodiment, the second data may be generated by layering the layout result by a graphics processing algorithm.
In one embodiment, the second data may be generated by highlighting a specified region or set of specific devices in the layout result.
Therefore, the hierarchical relationship in the finally obtained topological graph is more clear 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.
The graphic output module is used for outputting the topological graph.
By way of example, the icon information may include information for representing icons of respective devices in the topology map space, including information of the size, color, style, font, number, and the like of the icons.
In one embodiment, the icon information may be information of icons representing various types of device sets in the topology map space.
In one embodiment, the icon information may be pre-configured.
In one embodiment, the icon information may be self-set according to the requirements of the cloud platform construction.
In one embodiment, the icon information further includes links of different style styles and attribute information thereof.
In one embodiment, the graphics output module may be a clipping of functions in a graphics processing algorithm.
In one embodiment, the graphical output module may be a graphical user interface (Graphical User Interface, GUI) in a tkilter library. The GUI in the Tlater library can adaptively add each piece of icon information to the attribute of each device, and outputs each piece of icon information together in the output topological graph. Illustratively, this may be accomplished by entering layout results and icon information into the python application programming interface (Application Programming Interface, API) in the GUI module.
Based on the foregoing embodiments, fig. 3 shows a specific implementation architecture diagram of the topology generating method provided in the present application.
As shown in fig. 3, the topology map generating method provided in the embodiment of the present application is mainly implemented by the interaction among a device configuration information reading module, a device relationship establishing module, a device relationship setting module, a device hierarchy setting module, a drawing icon attribute setting module, and a topology map 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 a type, a model, a name, a number, and a specification of devices required for constructing the cloud platform. Optionally, after determining the above information based on the requirement data of the cloud platform, importing the information into an Excel file to form a device configuration file for reading by a device 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 for building the cloud platform and a configuration file. Specifically, the above functions are realized by a connection relationship model and a spatial position relationship model. The connection relation model is used for determining connection relations among the devices based on the demand data and configuration data among the devices in the configuration file. Illustratively, the connection relation model may determine how each device is connected before, and whether each device is connected or not, and the like. 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. Wherein, the horizontal relation is set up, is used for confirming the horizontal connection relation among every apparatus; 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 hierarchy relationship between devices based on the set horizontal connection relationship and vertical connection relationship. In some embodiments, the hierarchical relationship between devices may be set based on the horizontal connection relationship, the vertical connection relationship, and the topology model.
In fig. 3, a drawing icon attribute setting module is configured to manage and set the shape, size, font, color, and other attributes of each device icon and each device set icon in the topology map.
In fig. 3, the graphics output module is configured to output a topology map, and its functions may include two parts, a topology map preview and a topology map export. The topological graph previewing is used for checking and comparing the drawn topological graph; and the topology map is exported and is used for outputting the drawn topology map as a picture with a preset format. And for the drawing process of the topological graph, the Python API of the open source algorithm library GraphViz can be used for carrying out self-adaptive layout, and the topological graph can be derived to select the formats of. Png,. Jpeg or. Bmp.
The specific implementation flow of the topology map generation method provided by the embodiment of the application is as follows:
firstly, obtaining a device configuration file based on demand data for constructing a cloud platform, wherein the file can be an excel file, and reading related information, namely first data, in the configuration file through a device information reading module.
And secondly, a device relation connection model and a device space position model in the device relation building module are used for obtaining a connection relation and a space position relation between devices based on the first data and the demand data of the cloud platform.
Thirdly, converting the connection relation between the devices into a horizontal connection relation and a vertical connection relation between the devices in the Python code through the horizontal relation setting and the vertical relation setting operation in the device relation setting module.
Fourth, through the device hierarchy setting module, based on the horizontal connection relationship and the vertical connection relationship between devices, in some embodiments, the topology model may be combined, to determine the hierarchy relationship between devices, and set the devices without the horizontal connection relationship at the same horizontal connection layer.
Fifth, through the drawing icon attribute setting module, the icon shape, size, text, color and other attributes of each device or device set are configured.
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 topological graph generation process of the government cloud as an example, the topological graph of the government cloud, which is shown in fig. 4 and is obtained through the topological graph generation method provided by the application, can be obtained through the operation steps.
In fig. 4, the connection relationship between the respective devices is complex, and the kinds and the number of devices are numerous. However, in fig. 4, the horizontal connection relationship and the vertical connection relationship between the devices are clear, the hierarchy is clear, and the whole drawing is concise and visual.
According to the topology graph generation method, configuration data used for representing each device for constructing the cloud platform is determined, connection relation is determined based on the first data, and then second data are generated based on the connection relation and the spatial position relation. Therefore, the topology map generation method provided by the embodiment of the application realizes automatic drawing of the topology map, thereby alleviating the problems of long drawing period, complicated working procedures and high labor cost caused by manually drawing the topology map in the related technology.
Based on the foregoing embodiments, the embodiments of the present application provide a topology generating system 3, as shown in fig. 5, which is a structural diagram of the topology generating system, where the topology generating system 3 includes:
A processor 31, a memory 32, and a communication bus; wherein:
a communication bus for implementing a communication connection between the processor 31 and the memory 32;
the processor 31 is configured to execute a program of the topology map generation method in the memory to realize the steps of:
determining first data; the cloud platform comprises first data, second data and a cloud platform, wherein the first data is used for representing configuration data of each device constructing the cloud platform;
obtaining a topology model after training; the topology model is used for determining layout information of each device in a topology 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 a program for generating a topology map in a memory to implement the steps of: determining a topological connection relation based on the first data; the topological connection relation comprises connection relations among all 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 the topology map generation method in the memory to realize the steps of:
acquiring a connection relation model and a spatial position relation 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 the 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 the topology map generation method in the memory to realize the steps of:
determining a graphic processing algorithm; the graphic processing algorithm is used for carrying out layout processing on each device of the cloud platform;
and processing the third data and the fourth data based on the graphic processing algorithm to generate the second data.
The processor 31 is configured to execute a program of the topology map generation method in the memory to realize the steps of: obtaining a device relation setting model and a device hierarchy setting model based on the graphic processing algorithm; the device relation setting model is used for setting the connection relation of each device in at least one direction; the equipment hierarchy setting model is used for setting the hierarchy among the equipment;
And processing the third data and the fourth data based on the equipment relation setting model and the equipment hierarchy setting model to generate the second data.
The processor 31 is configured to execute a program of the topology map generation method in the memory to realize the steps of:
processing the third data and the fourth data based on the equipment relation setting model, and determining a horizontal connection relation and a vertical connection relation between the equipment;
based on the equipment hierarchy setting model, laying out the horizontal connection relation and the vertical connection relation to obtain a layout result;
and generating the second data based on the layout result.
The processor 31 is configured to execute a program of the topology map generation method in the memory to realize the steps of:
the icon information and the graphic output module of each device are obtained; the graphic 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 ASIC, a dsp DSP, PLD, FPGA, CPU, a controller, a microcontroller, and a microprocessor. The embodiments of the present application are not limited in this regard.
The memory 32 may be a volatile memory (RAM), for example; or a non-volatile memory (non-volatile memory), such as ROM, flash memory (flash memory), hard Disk (HDD) or Solid State Drive (SSD); or a combination of memories of the above kind and providing instructions and data to the processor 31.
According to the topology map generation system provided by the embodiment of the application, first data used for representing configuration data of each device constructing the cloud platform is determined, a topology model used for determining training completion of layout information of each device in the topology map is obtained, and then second data used for representing the topology map of the cloud platform is generated based on the first data and the topology model. Therefore, in the topology map generation system provided by the embodiment of the application, the topology map of the cloud platform can be rapidly and automatically generated by training the completed topology model based on 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 topology map in the related technology are solved.
Based on the foregoing embodiments, the embodiments of the present application provide a topology generating apparatus 4, as shown in fig. 6, which is a structural diagram of the topology generating apparatus, where the topology generating apparatus 4 includes: a determination module 41 and a processing module 42; wherein:
A determining module 41, configured to determine first data and acquire a trained topology model; the cloud platform comprises first data, second data and a cloud platform, wherein the first data is used for representing configuration data of each device 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 connection relations among all 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 the 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 carrying out layout processing on each device of the cloud platform;
and processing the third data and the fourth data based on the graphic processing algorithm to generate the second data.
A processing module 42, configured to obtain a device relationship setting model and a device hierarchy setting model based on the graphics processing algorithm; the device relation setting model is used for setting the connection relation of each device in at least one direction; the equipment hierarchy setting model is used for setting the hierarchy among the equipment;
and processing the third data and the fourth data based on the equipment relation 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 hierarchy setting model, laying out the horizontal connection relation and the vertical connection relation to obtain a layout result; and generating the second data based on the layout result.
A processing module 42, configured to obtain icon information of each device and a graphics output module; the graphic 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 located in an electronic device, where the processor is at least one of ASIC, DSP, DSPD, PLD, FPGA, CPU, a controller, a microcontroller, and a microprocessor.
The topology map generating device provided by the embodiment of the application firstly determines first data used for representing configuration data of each device constructing a cloud platform, acquires a topology model used for determining training completion of layout information of each device in the topology map, and then generates second data used for representing the topology map of the cloud platform based on the first data and the topology model. Therefore, the topology map generating device provided by the embodiment of the application can automatically and rapidly generate the topology map of the cloud platform based on the configuration data of each device of the cloud platform and the trained topology model, so that the problems of long drawing period, low efficiency and high labor cost caused by manually drawing the topology map in the related technology are solved.
Based on the foregoing embodiments, the embodiments of the present application further provide a computer-readable storage medium having stored thereon a computer program that is executed by a processor of a topology map generation apparatus to perform the topology map generation method as described in any of the foregoing embodiments.
In some embodiments, the functions or modules included in the apparatus provided by the embodiments of the present invention may be used to perform the methods described in the foregoing method embodiments, and specific implementations thereof may refer to descriptions of the foregoing method embodiments, which are not repeated herein for brevity.
The foregoing description of various embodiments is intended to highlight differences between the various embodiments, which may be the same or similar to each other by reference, and is not repeated herein for the sake of brevity.
The methods disclosed in the method embodiments provided by the application can be arbitrarily combined under the condition of no conflict to obtain a new method embodiment.
The features disclosed in the embodiments of the products provided by the application can be arbitrarily combined under the condition of no conflict, so as to obtain new embodiments of the products.
The features disclosed in the embodiments of the method or the apparatus provided in the application may be arbitrarily combined without conflict to obtain a new embodiment of the method or the apparatus.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The embodiments of the present invention have been described above with reference to the accompanying drawings, but the present invention is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present invention and the scope of the claims, which are to be protected by the present invention.
Claims (8)
1. A topology map generation method, the method comprising:
determining first data; the first data are used for representing configuration data of each device constructing the cloud platform;
obtaining a topology model after training; the topology model is used for determining layout information of each device in a topology graph;
generating second data based on the first data and the topology model; the second data is used for representing a topological graph corresponding to the cloud platform;
the generating the second data based on the first data and the topology model includes:
determining a topological connection relation based on the first data; the topological connection relation comprises connection relations among all equipment sets;
generating the second data based on the topological connection relationship and the topological model;
the generating the second data based on the topological connection relation and the topological model includes:
acquiring a connection relation model and a spatial position relation 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 the 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.
2. The method of claim 1, wherein the processing the third data and the fourth data to generate the second data comprises:
determining a graphic processing algorithm; the graphic processing algorithm is used for carrying out layout processing on each device of the cloud platform;
and processing the third data and the fourth data based on the graphic processing algorithm to generate the second data.
3. The method of claim 2, wherein the processing the third data and the fourth data based on the graphics processing algorithm to generate the second data comprises:
obtaining a device relation setting model and a device hierarchy setting model based on the graphic processing algorithm; the device relation setting model is used for setting the connection relation of each device in at least one direction; the equipment hierarchy setting model is used for setting the hierarchy among the equipment;
And processing the third data and the fourth data based on the equipment relation setting model and the equipment hierarchy setting model to generate the second data.
4. The method of claim 3, wherein the processing the third data and the fourth data based on the device relationship settings model and the device hierarchy settings model to generate the second data comprises:
processing the third data and the fourth data based on the equipment relation setting model, and determining a horizontal connection relation and a vertical connection relation between the equipment;
based on the equipment hierarchy setting model, laying out the horizontal connection relation and the vertical connection relation to obtain a layout result;
and generating the second data based on the layout result.
5. The method of claim 4, wherein generating the second data based on the layout result comprises:
the icon information and the graphic output module of each device are obtained; the graphic 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.
6. A topology generation system, the topology 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 configured to execute a program of the topology map generation method in the memory to implement the steps of:
determining first data; the first data are used for representing configuration data of each device constructing the cloud platform;
obtaining a topology model after training; the topology model is used for determining layout information of each device in a topology graph;
generating second data based on the first data and the topology model; the second data is used for representing a topological graph of the cloud platform;
determining a topological connection relation based on the first data; the topological connection relation comprises connection relations among all equipment sets; generating the second data based on the topological connection relationship and the topological model; acquiring a connection relation model and a spatial position relation 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 the 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.
7. A topology generation apparatus, the apparatus comprising: a determining module and a processing module; wherein:
the determining module is used for determining first data and acquiring a trained topological model; the first data are used for representing configuration data of each device constructing the cloud platform; the topology model is used for determining layout information of each device in a topology graph;
the processing module is used for generating second data based on the first data and the topology model; the second data is used for representing a topological graph of the cloud platform; determining a topological connection relation based on the first data; the topological connection relation comprises connection relations among all equipment sets; generating the second data based on the topological connection relationship and the topological model; acquiring a connection relation model and a spatial position relation 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 the 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.
8. 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 generation apparatus, implements the topology generation method of any of claims 1 to 5.
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