Circuit multi-route bearing analysis method and system, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a circuit multi-route bearing analysis method and system, electronic equipment and a storage medium, and belongs to the technical field of communication. According to the method, an actual transmission network topological graph is identified by using a neural network technology to obtain transmission network topological data which can be processed by a computer. For a group of target relay service data which comprises a plurality of relay circuits and has the same source and destination sites of each relay circuit and the same relay type, querying transmission network topology data according to the source and destination sites to obtain a plurality of pieces of second routing information capable of bearing corresponding circuits; the first routing information and the second routing information of the multiple relay circuits in the target relay service data are compared and analyzed, a circuit multi-routing bearing analysis result is obtained, and the multi-routing bearing analysis result comprises one of a routing construction requirement, a routing bearing reasonability or a routing bearing adjustment scheme. According to the invention, the transmission network bearer routing of the relay circuit can be automatically managed and reasonably distributed, and the service failure rate is reduced.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a circuit multi-route load analysis method, system, electronic device and storage medium. Background Art

[0002] As more and more important relay circuits are carried on transmission networks (such as optical transmission networks OTN), such as CN2 relays, IPTV relays, IPRAN relays, IDC relays, etc., various relay circuits are not configured with protection routes when they are opened on the OTN network. Therefore, when a single relay circuit is interrupted, its carrying traffic will be switched to other relay circuits for carrying.

[0003] At present, as the traffic volume of business transmission increases, the number of relay circuits opened increases. When manually managing OTN-bearing relay circuits, when there are many relay circuits opened, it is impossible to reasonably allocate relay circuit routes, and the load on each circuit is uneven. When a local relay circuit in the network fails, other relay circuits are prone to cause traffic congestion and business interruption, resulting in business risks. Summary of the invention

[0004] The main purpose of the embodiments of the present application is to propose a circuit multi-route bearer analysis method, system, electronic device and storage medium, which aims to automatically manage and reasonably allocate the transmission network bearer routes of the relay circuit and reduce the service failure rate.

[0005] To achieve the above object, an embodiment of the present application provides a circuit multi-route load analysis method, comprising the following steps:

[0006] Acquire transmission network topology data, wherein the transmission network topology data is obtained by identifying a transmission network topology map using a neural network technology, and the transmission network topology data includes connection relationships between sites of the transmission network;

[0007] Acquire target relay service data, wherein the target relay service data includes multiple relay circuits, each of the relay circuits has the same source and destination site and relay type, and each of the relay circuits includes first routing information and a bearer rate;

[0008] Querying the transmission network topology data according to the source and sink sites to obtain a plurality of second routing information;

[0009] The first routing information of multiple relay circuits in the target relay service data and the multiple second routing information are compared and analyzed to obtain a circuit multi-route bearer analysis result, wherein the multi-route bearer analysis result includes one of the route construction requirements, route bearer rationality or route bearer adjustment plan.

[0010] In some embodiments, the transmission network topology data is obtained by the following steps:

[0011] Obtain the transmission network topology map;

[0012] Using a trained convolutional neural network to identify site features in the transmission network topology map, and obtaining a site information set, wherein the site information set includes site coordinates, site visual connection features, and site area visual features;

[0013] Constructing a graph structure according to the site information set;

[0014] Using a trained graph neural network to identify site connection relationships in the graph structure, and obtaining site connection data in the transmission network topology graph;

[0015] The transmission network topology data is determined according to the site connection data and the site information set.

[0016] In some embodiments, the determining of the transmission network topology data according to the site connection data and the site information set comprises the following steps:

[0017] Determine a site type of each site according to the site information set, wherein the site type is one of a single-route site or a multi-route multiplexing site;

[0018] Determine the site with the most connections in the transmission network topology graph according to the site connection data, and determine the site as the traversal starting point;

[0019] Determine a target site that has a connection relationship with the traversal starting point according to the site connection data, and use an expected character to mark the connection relationship between the target site and the traversal starting point, wherein the expected character represents the site type with which the connection relationship exists and the target site;

[0020] The target site is determined as a new traversal starting point, and the steps of determining a target site having a connection relationship with the traversal starting point based on the site connection data and marking the connection relationship between the target site and the traversal starting point with expected characters are repeated to obtain transmission network topology data, wherein the target site has not been used as a traversal starting point in historical traversal rounds.

[0021] In some embodiments, the first routing information of the relay circuit in the target relay service data is obtained by the following steps:

[0022] Querying the corresponding media routing text according to the circuit name of the relay circuit in the target relay service data;

[0023] Using regular expressions to extract site information from the media routing text;

[0024] The first routing information of the relay circuit is determined according to the site information.

[0025] In some embodiments, the circuit multi-route load analysis method further includes the following steps:

[0026] According to the first routing information, merging multiple relay circuits with the same first routing information in the target relay service data into one relay circuit;

[0027] The sum of the carrying rates of the plurality of relay circuits having the same first routing information is determined as the carrying rate of the combined relay circuit.

[0028] In some embodiments, querying the transmission network topology data according to the source and destination sites to obtain a plurality of second routing information includes the following steps:

[0029] Traversing the transmission network topology data according to the source and destination sites, determining the sites along the way from the source end to the destination end;

[0030] A plurality of second routing information are determined according to the en route sites from the source end to the destination end and the site types of the en route sites.

[0031] In some embodiments, the comparing and analyzing the first routing information of the plurality of relay circuits and the plurality of the second routing information in the target relay service data to obtain the circuit multi-routing bearer analysis result includes the following steps:

[0032] Determining whether the amount of the second routing information is greater than a preset amount value;

[0033] When the amount of the second routing information is less than a preset amount value, determining that the multi-routing bearer analysis result is a routing construction requirement;

[0034] When the amount of the second routing information is greater than or equal to a preset amount value, determining whether the amount of the first routing information is the same as the amount of the second routing information;

[0035] When the number of the first routing information is the same as the number of the second routing information, judging whether the rate bearing is balanced according to the bearing rates of the multiple relay circuits in the target relay service data, and when the rate bearing is balanced, determining that the multi-route bearing analysis result is reasonable for the route bearing; when the rate bearing is unbalanced, determining that the multi-route bearing analysis result is a route bearing adjustment plan, and the route bearing adjustment plan includes adjusting the bearing rate of the route;

[0036] When the amount of the first routing information is less than the amount of the second routing information, the multi-route bearer analysis result is determined to be a route bearer adjustment scheme, wherein the route bearer adjustment scheme includes adjusting the relay circuit to a route that does not carry a circuit.

[0037] To achieve the above object, another aspect of the embodiment of the present application provides a circuit multi-route load analysis system, including:

[0038] The first module is used to obtain transmission network topology data, wherein the transmission network topology data is obtained by identifying a transmission network topology map using a neural network technology, and the transmission network topology data includes connection relationships between sites of the transmission network;

[0039] The second module is used to obtain target relay service data, wherein the target relay service data includes multiple relay circuits, each of the relay circuits has the same source and destination site and relay type, and each of the relay circuits includes first routing information and a bearer rate;

[0040] A third module is used to query the transmission network topology data according to the source and destination sites to obtain multiple second routing information;

[0041] The fourth module is used to compare and analyze the first routing information of multiple relay circuits in the target relay service data and the multiple second routing information to obtain the circuit multi-routing load analysis results, wherein the multi-routing load analysis results include one of the routing construction requirements, reasonable routing load or routing load adjustment solutions.

[0042] To achieve the above-mentioned purpose, another aspect of an embodiment of the present application proposes an electronic device, which includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection and communication between the processor and the memory, and the program implements the method described in the above embodiment when executed by the processor.

[0043] To achieve the above-mentioned purpose, another aspect of an embodiment of the present application proposes a storage medium, which is a computer-readable storage medium used for computer-readable storage, and the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the method described in the above embodiment.

[0044] The circuit multi-route load analysis method, system, electronic device and storage medium proposed in the present application obtain the transmission network topology data by using neural network technology to identify the actual transmission network topology map, and the transmission network topology data includes the connection relationship between the sites of the transmission network and the sites. For a group of target relay service data including multiple relay circuits, the source and destination sites of each relay circuit and the same relay type, query the transmission network topology data according to the source and destination sites to obtain multiple second routing information that can carry the corresponding circuits, compare and analyze the first routing information and multiple second routing information of the multiple relay circuits in the target relay service data, and obtain the circuit multi-route load analysis results, and the multi-route load analysis results include one of the route construction requirements, reasonable route load or route load adjustment scheme. The present application obtains the transmission network topology data by identifying the actual transmission network topology map through neural network technology, and then automatically compares and analyzes the relay circuits of the target relay service data based on the transmission network topology data, and determines the circuit multi-route load analysis results, so as to automatically manage and reasonably allocate the transmission network load routes of the relay circuits, and reduce the service failure rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is a flow chart of a circuit multi-route load analysis method provided in an embodiment of the present application;

[0046] Figure 2 yes Figure 1 Flow chart of the method for acquiring transmission network topology data in step S101;

[0047] Figure 3 yes Figure 2 Flow chart of step S205 in FIG.

[0048] Figure 4 yes Figure 1 Flow chart of step S102 in FIG.

[0049] Figure 5 is a flow chart of a circuit multi-route load analysis method provided by another embodiment of the present application;

[0050] Figure 6 yes Figure 1 Flow chart of step S103 in FIG.

[0051] Figure 7 It is a logical schematic diagram for comparing and analyzing resource-side routing and network management-side routing provided in an embodiment of the present application;

[0052] Figure 8 It is a schematic diagram of a circuit multi-route load analysis system provided in an embodiment of the present application;

[0053] Fig. 9 is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application;

[0054] Fig.10 It is a schematic diagram of a transmission network topology provided in an embodiment of the present application;

[0055] Fig.11 It is a logical schematic diagram of transmission network topology identification provided by an embodiment of the present application;

[0056] Fig.12 This is a text diagram of the media routing obtained through query provided in an embodiment of the present application. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0058] It should be noted that, although the functional modules are divided in the system and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the system or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0059] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0060] First, some nouns involved in this application are analyzed:

[0061] Convolutional Neural Networks (CNN): A type of feedforward neural network that includes convolution calculations and has a deep structure. It can perform supervised learning through labeled training data to complete tasks such as visual image recognition and target detection.

[0062] Graph structured data is a data structure composed of nodes and edges. In graph structured data, nodes represent entities and edges represent the relationship between entities. For example, in a social network, nodes can represent users and edges can represent the friendship between users.

[0063] Graph Neural Network (GNN) is a deep learning model that learns and infers on graph structured data. It can handle nodes, edges and complex relationships between them. The core idea of ​​​​graph neural network is to use the neighbor information of the node to update the state of the node, thereby capturing the structural information in the graph and realizing the prediction of the connection relationship in the graph.

[0064] Optical transmission technology: technology that transmits information in the form of optical signals between sender and receiver.

[0065] Optical Transport Network: Optical Transport Network (OTN for short) is a transmission network based on wavelength division multiplexing technology and organized at the optical layer. It is the next-generation backbone transmission network.

[0066] Optical transmission network topology: refers to the abstraction of the site equipment in the optical transmission network as a point, the abstraction of the transmission optical cable medium as a line, and the geometric figures composed of points and lines constitute the topological structure of the optical transmission network.

[0067] As the traffic volume of business transmission increases, the bandwidth of a single or a few relay circuits cannot meet the traffic carrying requirements, so the number of open relay circuits of each type will reach more than ten. The more relay circuits are opened, the more difficult it is to manually count them. It is no longer possible to evenly open the opened relay circuits on all reachable routes, resulting in traffic congestion and business obstruction after the traffic is switched to other relay circuits when some transmission routes are interrupted. Or there are multiple routes for relay circuit opening, but due to the long time interval between the relay circuits opened before and after, it is easy to ignore the route of the opened relay during manual opening, resulting in the route of the newly opened relay being the same as the previously opened relay. When the route fails, all relays are interrupted and all services are damaged, causing incalculable losses. It can be seen that when the transmission network carries relay circuits manually, when there are many relay circuits opened, the relay circuit routes cannot be reasonably allocated, and the circuits carry uneven loads. When a local relay circuit in the network fails, other relay circuits are prone to traffic congestion and service interruption, resulting in business risks.

[0068] Based on this, the embodiments of the present application provide a circuit multi-route bearer analysis method, system, electronic device and storage medium, which aim to automatically manage and reasonably allocate the transmission network bearer routes of the relay circuit to reduce the service failure rate.

[0069] The circuit multi-route load analysis method, system, electronic device and storage medium provided in the embodiments of the present application are specifically described through the following embodiments. First, the circuit multi-route load analysis method in the embodiments of the present application is described.

[0070] The circuit multi-route load analysis method provided in the embodiment of the present application relates to the field of artificial intelligence technology. The circuit multi-route load analysis method provided in the embodiment of the present application can be applied to a terminal, can also be applied to a server side, and can also be software running in a terminal or a server side. In some embodiments, the terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, etc.; the server side can be configured as an independent physical server, or a server cluster or a distributed system composed of multiple physical servers, and can also be configured as a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application that implements the circuit multi-route load analysis method, etc., but is not limited to the above forms.

[0071] The present application can be used in many general or special computer system environments or configurations. For example: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, distributed computing environments including any of the above systems or devices, etc. The present application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application can also be practiced in distributed computing environments, in which tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules can be located in local and remote computer storage media including storage devices.

[0072] Figure 1 is an optional flow chart of the circuit multi-route load analysis method provided in the embodiment of the present application. Figure 1 The method may include but is not limited to steps S101 to S104.

[0073] Step S101, acquiring transmission network topology data, wherein the transmission network topology data is obtained by identifying a transmission network topology map using a neural network technology, and the transmission network topology data includes connection relationships between sites of the transmission network;

[0074] Step S102, obtaining target relay service data, wherein the target relay service data includes multiple relay circuits, each relay circuit has the same source and destination site and relay type, and each relay circuit includes first routing information and a bearer rate;

[0075] Step S103, querying the transmission network topology data according to the source and destination sites to obtain a plurality of second routing information;

[0076] Step S104, compare and analyze the first routing information of multiple relay circuits and the multiple second routing information in the target relay service data to obtain a circuit multi-route load analysis result, wherein the multi-route load analysis result includes one of the route construction requirements, route load rationality or route load adjustment plan.

[0077] Steps S101 to S104 shown in the embodiment of the present application, by using neural network technology to identify the actual transmission network topology map to obtain transmission network topology data, the transmission network topology data includes the connection relationship between the sites of the transmission network and the sites. For a group of target relay service data including multiple relay circuits, the source and destination sites of each relay circuit and the same relay type, query the transmission network topology data according to the source and destination sites to obtain multiple second routing information that can carry the corresponding circuits, compare and analyze the first routing information and multiple second routing information of the multiple relay circuits in the target relay service data, and obtain the circuit multi-route bearing analysis results, and the multi-route bearing analysis results include one of the route construction requirements, reasonable route bearing or route bearing adjustment schemes. The embodiment of the present application uses neural network technology to identify the actual transmission network topology map to obtain transmission network topology data, and then automatically compares and analyzes the relay circuits of the target relay service data based on the transmission network topology data to determine the circuit multi-route bearing analysis results, so that the transmission network bearing routes of the relay circuits can be automatically managed and reasonably allocated to reduce the service failure rate.

[0078] In step S101 of some embodiments, the transmission network topology data is the description data of the transmission network topology map obtained by identifying the transmission network topology map using neural network technology, and the transmission network topology data records the connection relationship between the sites of the transmission network in the form of a matrix or a table. The site of the transmission network represents the location of the device with routing function, and the connection relationship between the sites represents the communication relationship between the routes, that is, data can be transmitted or not transmitted between the routes. The transmission network topology map can be saved on the network management side, and the transmission network topology map depicts the layout of the network equipment and the routing relationship between the devices in the real environment area. In this embodiment, the transmission network can be an optical transmission network, the transmission network topology map can be an optical transmission network topology map, and the transmission network topology data can be optical transmission network topology data. In this embodiment, the transmission network topology map that can only be recognized by humans is converted into a data form that can be recognized by a computer, so that when the source and destination sites are subsequently input, it is convenient to quickly identify all the reachable routing information between the two sites by traversing the graph.

[0079] See also Figure 2 In some embodiments, the transmission network topology data in step S101 may be obtained by including but not limited to steps S201 to S205:

[0080] Step S201, obtaining a transmission network topology map;

[0081] Step S202, using a trained convolutional neural network to identify site features in a transmission network topology map to obtain a site information set, wherein the site information set includes site coordinates, site visual connection features, and site area visual features;

[0082] Step S203, constructing a graph structure according to the site information set;

[0083] Step S204, using the trained graph neural network to identify the site connection relationship in the graph structure, and obtaining the site connection data in the transmission network topology graph;

[0084] Step S205: determining the transmission network topology data according to the site connection data and the site information set.

[0085] In this embodiment, the sites in the transmission network topology map and the connection relationship between them are identified, and the sites with connections are marked, which can be solved by combining computer vision and graph theory methods. In this embodiment, a deep learning model is used in combination with a convolutional neural network (CNN) and a graph neural network (GNN) to implement two processes: site detection and connection relationship identification, as follows:

[0086] First, the trained convolutional neural network is used to identify the site features in the transmission network topology map to obtain the site information set. Specifically, the transmission network topology map is as follows: Fig.10 As shown, the transmission network topology map is preprocessed, including standardization, resizing, etc., so that it can be subsequently input into the convolutional neural network. The preprocessed transmission network topology map is used to detect sites using a convolutional neural network (CNN). CNN is good at identifying features and objects in images. Site features are learned through training. Site features include but are not limited to site area visual features, site visual connection features, and site pixel positions (i.e., site coordinates), thereby obtaining a site information set. The site information set includes feature representations of each site and the names of each site. The training of the convolutional neural network can be trained using an image dataset annotated with site shapes and connection identifiers, and the annotated data contains the coordinates or bounding box information of the site.

[0087] Secondly, a graph neural network is used to identify the connection relationship between sites, and the site connection data in the network topology map is obtained. Specifically, a graph structure is constructed based on the detected site information set, and the sites in the site information set are used as nodes of the graph structure, and the edges of the graph structure are constructed based on the visual connection features of the sites (such as lines, paths, etc.). A feature vector is assigned to each node (site) and edge. The node features use the color and shape of the site, and the edge features use the connecting lines. The constructed graph structure is processed using a graph neural network to learn the dependencies and global features between nodes. The graph neural network can propagate and aggregate the information of neighboring nodes to determine whether there is a connection between the nodes. Through the output of the GNN model, the probability or certainty score of the connection between each node pair can be obtained. If the connection probability is higher than the threshold, it can be considered that there is a connection between the two nodes. If the connection probability is lower than the threshold, it can be considered that there is no connection between the two nodes, thereby obtaining site connection data.

[0088] Finally, the transmission network topology data is determined based on the site connection data and the site information set.

[0089] See also Figure 3 In some embodiments, in step S205, the step of determining the transmission network topology data according to the site connection data and the site information set may include but is not limited to steps S301 to S304:

[0090] Step S301, determining the site type of each site according to the site information set, wherein the site type is one of a single-route site or a multi-route multiplexing site;

[0091] Step S302, determining the site with the most connections in the transmission network topology diagram according to the site connection data, and determining the site as the traversal starting point;

[0092] Step S303, determining a target site that has a connection relationship with the traversal starting point according to the site connection data, and marking the connection relationship between the target site and the traversal starting point with an expected character, wherein the expected character represents the site type with which the connection relationship exists and the target site;

[0093] Step S304, determines the target site as a new traversal starting point, and repeats the steps of determining the target site that has a connection relationship with the traversal starting point based on the site connection data, and using expected characters to mark the connection relationship between the target site and the traversal starting point, to obtain the transmission network topology data, wherein the target site has not been used as a traversal starting point in historical traversal rounds.

[0094] In this embodiment, the site type of each site can be determined according to the site information set. The site type is one of a single-route site or a multi-route multiplexing site. The site type is described as follows:

[0095] Single-route site (also called OA site) can appear in one transmission route and is unique. If an OA site appears in two transmission routes, the two routes are considered to overlap and can only be counted as one transmission route.

[0096] Multi-route multiplexing site (also called OTM site) can appear in different transmission routes and is not unique.

[0097] In one example, the transmission network topology data can be obtained by traversing the site connection data. Fig.11 The transmission network topology diagram identifies the logic diagram, combined with Fig.10 The following is an example of the transmission network topology diagram, where: Fig.10 The square site is described by T, the triangular site is described by A, and a connection is represented by 1, and a connection is represented by 0:

[0098] Determine the site A with the most connections in the optical transmission topology according to the site connection data, such as Fig.10 The site with the most connecting lines in the graph is identified as 10011.

[0099] The site with the most connecting lines is taken as the traversal starting point, and the target site that has a connection relationship with the traversal starting point is determined, and the connection relationship between the target site and the traversal starting point is marked with an expected character. Exemplarily, taking 10011 as the traversal starting point, eight sites that have a connection relationship with 10011 are identified, namely 20008, 20016, 40007, 10010, 50013, 20014, 20015, and 50012, so the connection relationship between 10011 and the eight sites is recorded as 1 (indicating a connection relationship). Furthermore, the connection relationship can also be recorded according to the site type, and the target site whose site type is a single-route site is recorded as the expected character "1A", and the target site whose site type is a multi-route composite site is recorded as the expected character "1T".

[0100] The above target site is used as a new traversal starting point, and then the target site with a connection relationship with the traversal starting point is re-determined. It should be noted that the target site of the new traversal starting point has not been used as a traversal starting point in the historical traversal rounds, so as to avoid repeated recording of the connection relationship between the two sites. Exemplarily, the adjacent sites of the eight sites are identified in this way, and the sites that have a connection relationship are not recorded. The sites with a connection relationship with 20008 are identified as 10011 and 30006. Since the connection relationship between 10011 (used as a traversal starting point in the historical traversal rounds, so not as the target site of 20008) and 20008 has been stored, only the connection relationship between 30006 and 20008 is recorded as 1, and the eight sites are traversed in this way. Then, with the vertical column data 30006, 20005, 10010, and 10001 in the table as the center, the sites with a relationship with them are identified, and the connection relationship is recorded as 1, and the identification of the transmission network topology is gradually completed.

[0101] Furthermore, the connection relationship can be recorded according to the site type. The target site of a single-route site is recorded as the expected character "1A", and the target site of a multi-route composite site is recorded as the expected character "1T". The transmission network topology data obtained after traversal is shown in Table 1.

[0102] Table 1 Transmission network topology data

[0103] Site Name 20008 20016 40007 10010 50013 20014 20015 50012 10011 1A 1A 1T 1T 1A 1A 1A 1A 30006 1A 0 0 0 0 0 0 0 20005 0 1A 0 0 0 0 0 0 10010 0 0 1T 1T 0 0 0 0 10001 0 0 0 1T 0 0 0 0

[0104] Among them, 0 means that the route is unreachable (there is no connection between sites); 1A means that the route is reachable (there is a connection between sites) but the reachable site is an OA site. In multi-route analysis, this site can only appear in one transmission route and is unique. If an OA-type site appears in two transmission routes, it is judged that the two routes overlap and can only be counted as one transmission route; 1T means that the route is reachable and the reachable site is an OTM site. In multi-route analysis, this site can appear in different routes, that is, it is not unique; only traversal and storage of adjacent sites.

[0105] In step S102 of some embodiments, the network management side obtains the names and routing information of various types of service relay circuits from the resource system, and classifies the obtained relay circuits according to the same source destination site and the same type. The same type of relay circuits form relay service data, and the relay service data currently analyzed by the network management side is the target relay service data. In this embodiment, the same source destination site refers to the same sending site (source end) and receiving site (destination end) of the relay circuit, and the same type refers to the same fixed-line, broadband and other service types of the relay circuit. The target relay service data is the same type of relay circuit (same source and destination, same type) with at least three or more transmission routes opened, such as Chengdu-Luzhou 10GE0001 CN2, Chengdu-Luzhou 10GE0002CN2, Chengdu-Luzhou 10GE0003CN2. The circuits are all opened from Chengdu to Luzhou, and the circuit type is CN2. For the same type of service, these three circuits should be opened in three different transmission routes from Chengdu to Luzhou to achieve route balancing. When a single route fails, the traffic is switched to the other two routes.

[0106] Using the circuit name as a unique identifier, the data of the relay circuit obtained from the resource system is processed, and all the site information along the path of each relay circuit is recorded to obtain the first routing information of each relay circuit. At the same time, the carrying rate of the relay circuit is queried according to the circuit name.

[0107] See also Figure 4 In some embodiments, the first routing information of the relay circuit in the target relay service data in step S102 may be obtained by including but not limited to steps S401 to S403:

[0108] Step S401, querying the corresponding media routing text according to the circuit name of the relay circuit in the target relay service data;

[0109] Step S402, extracting site information from the media routing text using a regular expression;

[0110] Step S403: determine first routing information of the relay circuit according to the site information.

[0111] For example, taking the query of the 10GE0020CN2 relay circuit media route as an example, the obtained media route text is as follows: Fig.12 shown.

[0112] The exported relay circuit EXCEL routing table is read using the pandas library in Python to extract the circuit name and the content of the media routing field. The circuit rate is obtained from the circuit name as 10G. The media routing is matched using regular expressions. The starting site matches the site information starting with "Route:" or "Route 1:". The site name matches before "《" or after "》" and does not include "{" and "}" characters. The obtained site information is deduplicated, that is, if two adjacent sites have the same site name, only one is retained. The relay routing passes through the following sites: 10001, 10004, 20009, 110017, 110018, 110019, 110020, 110019, 110021, 110022, 110023. It should be noted that 10010 and 110024 are the starting sites of the route and are not recorded in the passing routing sites. The rates and routes of all similar relay circuits are extracted and saved in the above manner, thereby obtaining the first routing information.

[0113] See also Figure 5 In some embodiments, the circuit multi-route load analysis method of the embodiment of the present application may also include but is not limited to steps S501 to S502:

[0114] Step S501, according to the first routing information, merging multiple relay circuits with the same first routing information in the target relay service data into one relay circuit;

[0115] Step S502: Determine the sum of the bearer rates of multiple relay circuits with the same first routing information as the bearer rate of the combined relay circuit.

[0116] In this embodiment, the routing information of the same type of relay circuits belonging to the same target relay service data derived and screened in the resource system is parsed, the relay circuits with the same route through the site are classified and merged, the number of routes is re-counted, the route site information of each type of route is recorded (defined as resource-side route), and the sum of the carrying rates of each type of route is calculated. Among them, the number of merged relay circuits (i.e., the first routing information) in the target relay service data is greater than the preset number value, for example, the preset number value is 3, indicating that the target service to be analyzed needs to be carried on more than three transmission routes. If it is less than 3, it means that no subsequent analysis is required for this type of service.

[0117] In step S103 of some embodiments, the transmission network topology data is queried according to the source and destination sites of the target relay service data currently being analyzed to obtain a plurality of second routing information.

[0118] See also Figure 6 In some embodiments, step S103 includes but is not limited to steps S601 to S602:

[0119] Step S601, traversing the transmission network topology data according to the source and destination sites, and determining the sites along the way from the source end to the destination end;

[0120] Step S602: determining a plurality of second routing information according to the en route sites from the source end to the destination end and the site types of the en route sites.

[0121] In this embodiment, the source and destination sites of this type of relay are used as the starting and ending sites, and the identified transmission network topology data (which represents the connection relationship between actual sites) is traversed to automatically calculate the actual number of reachable routes from the source end to the destination end under this type of relay (OTM sites can be repeated, but OA sites cannot be repeated), and the sites passed by each route are recorded (defined as network management side routes), thereby obtaining multiple second routing information.

[0122] In step S104 of some embodiments, the first routing information of multiple relay circuits and the multiple second routing information in the target relay service data are compared and analyzed to obtain a circuit multi-route load analysis result. The multi-route load analysis result includes one of a route construction requirement, a reasonable route load, or a route load adjustment plan. The route construction requirement indicates that the actual route cannot carry this type of relay circuit service, and actual route construction is required. Reasonable route load means that the current route can evenly carry the relay circuit service. The route load adjustment plan indicates that the actual route can carry this type of relay circuit service, but the load route or route load rate of some relay circuits needs to be adjusted.

[0123] In some embodiments, step S104 may include but is not limited to steps S701 to S705:

[0124] Step S701, determining whether the amount of second routing information is greater than a preset amount value;

[0125] Step S702, when the amount of the second routing information is less than a preset amount value, determining the multi-route bearer analysis result as a routing construction requirement;

[0126] Step S703, when the amount of the second routing information is greater than or equal to the preset amount value, determining whether the amount of the first routing information is the same as the amount of the second routing information;

[0127] Step S704: when the number of the first routing information is the same as the number of the second routing information, judging whether the rate bearing is balanced according to the bearing rates of the multiple relay circuits in the target relay service data; when the rate bearing is balanced, determining the multi-route bearing analysis result as reasonable route bearing; when the rate bearing is unbalanced, determining the multi-route bearing analysis result as a route bearing adjustment plan, and the route bearing adjustment plan includes adjusting the bearing rate of the route;

[0128] Step S705: when the amount of the first routing information is less than the amount of the second routing information, determining the multi-route bearer analysis result as a route bearer adjustment scheme, wherein the route bearer adjustment scheme includes adjusting the relay circuit to a route that does not bear the circuit.

[0129] In this embodiment, please refer to Figure 7 , Python can be used to compare and analyze resource-side routing (i.e., multiple first routing information) and network management-side routing (i.e., multiple second routing information). The comparison content includes: whether the number of routes is greater than the preset value 3, and whether the number of routes is consistent.

[0130] The output analysis suggestions are as follows:

[0131] 1. If the number of routes is the same and the rate distribution is balanced, it means that the current opening method of this type of relay is reasonable; if the number of routes is the same but the rate distribution is uneven, adjust some circuit routes to make each route carry a balanced rate;

[0132] 2. If the number of routes automatically identified in the transmission network topology is greater than the number of routes with open relay circuits, it means that there are still physical routes that do not carry services in the transmission network management topology. Output route adjustment proposals, adjust some relay circuits to routes that do not carry relay circuits according to the preset calculation principle, so as to achieve balanced and shared load on multiple routes;

[0133] 3. If the number of routes automatically identified in the transmission network topology is 2 or less (including 2), it means that this type of relay circuit currently does not have the capacity to carry three or more routes and needs to be expanded. This proposal will be output to the relevant construction department for the construction of three routes.

[0134] In some embodiments, the specific scheme for performing multi-path balanced load bearing according to the preset calculation principle is as follows: integrate the routes with the same configured circuit rate, sort them according to the circuit rate configured for each route, and calculate the number of circuits to be configured for each type of route with the same circuit rate. Routes with the same circuit rate are calculated according to the principle of equalization. For example, the channel rates currently configured in the optical transmission network are 10G, 40G, 100G, 200G, and 400G, of which 10G and 100G are commonly used, and these two rates are taken as examples. Assume that route A is configured with a circuit rate of 100G and has 1 circuit, route B is configured with a circuit rate of 10G and has 2 circuits, route C is configured with a circuit rate of 10G and has 5 circuits, and the number of routes is 3, of which the number of 100G routes is 1 and the number of 10G routes is 7. Therefore, the number of circuits that should be configured for 100G = 100G / 1 = 100G, so route A should be configured with 1 wave, and the number of circuits that should be configured for 10G = 70G / 2 = 35G. Therefore, the number of circuits that should be configured for routes B and C is 3-4. Currently, route B is configured with 2 circuits, which is an unreasonable allocation. One route on route C needs to be adjusted to route B.

[0135] According to some embodiments of the present application, the multi-route circuit load analysis method of the embodiment of the present application is generally described as follows:

[0136] Save the optical transmission network topology diagram on the transmission network management, and use CNN+GNN technology to identify all site information and connection relationships and store them in the database.

[0137] Export all circuit information of the resource system, filter according to the trunk circuit name suffix ASON, CN2, EE, ELS, EB, IPTV, IDC, DCI, IPM, etc., and the circuit type can be flexibly increased.

[0138] After filtering by relay type, filter by source and destination sites in the circuit name to filter out multiple groups of similar relays.

[0139] Use Python to identify the rate and path site information (routing information) of all relay circuits in each group of similar relays.

[0140] Based on the source and destination site information in the same type of relay, the site and its connection relationship of the transmission network topology data stored in the database are automatically traversed, and all different actual routes of the same source and destination information are automatically calculated.

[0141] The first routing information of the relay circuit and the second routing information matched with the transmission network topology data are analyzed and compared. If the routes are the same and the rate sharing is balanced, it means that the opening method of this type of relay is reasonable and no adjustment is required; if the number of automatically calculated network management routes is greater than (3 or more) the number of routes obtained from resources, then according to the principle of balanced rate carrying, a solution is output to adjust some relay circuits to routes that have not yet carried relay circuits; if the number of automatically calculated network management routes is less than 2, it means that the relay circuit opened with the source and sink as the node does not meet the three-route carrying conditions, and a capacity expansion suggestion is output.

[0142] After the relevant parts are constructed, the topological image is re-identified, the sites and the connection relationships between sites are re-stored, and then re-analyzed.

[0143] For example, the IP circuit of Chengdu-Deyang in the resource system is exported. Assuming there are 4 circuits, 4 of them are 100G, and there are no other rates. The python tool is used to identify the routing information of the 4 100G circuits allocated in the resource system: Route 1: Chengdu-AB-Deyang (2 100G lines opened); Route 2: Chengdu-CD-Deyang; Route 3: Chengdu-DE-Deyang.

[0144] Identify the reachable route from Chengdu to Deyang on the network management, that is, based on the connection relationship table between sites and sites stored in the transmission network topology route based on the neural network identification, take Chengdu and Deyang as the starting points and traverse to find it in the relationship table. Traversal results show that route 1: Chengdu-AB-Deyang; route 2: Chengdu-CD-Deyang; route 3: Chengdu-DE-Deyang; route 4: Chengdu-FG-Deyang. Confirm whether the type of station D in the actual reachable route is A or T (A means OA station, T means OTM). If station D is an OA station, it means that route 2 and route 3 have the same route risk and can only be counted as one route; if station D is an OTM station, it means that route 2 and route 3 are different routes and can be counted as two routes.

[0145] After comparative analysis, the number of routes identified by the network management side is greater than 3, and there is no need to expand new routes. The number of routes on the network management side is 4, which is greater than the number of routes 3 identified by the resource side. According to the comparative analysis, the resource side and the network management side have consistent information on the first three routes, but route 4 does not carry any circuits. Therefore, according to the principle of route balancing, the output adjustment suggestion is: adjust one of the two 100G circuits carried by route 1 to route 4 for carrying.

[0146] See also Figure 8 The present application also provides a circuit multi-route load analysis system, including:

[0147] The first module is used to obtain transmission network topology data, wherein the transmission network topology data is obtained by identifying the transmission network topology map using neural network technology, and the transmission network topology data includes the connection relationship between sites of the transmission network and the sites;

[0148] The second module is used to obtain target relay service data, wherein the target relay service data includes multiple relay circuits, each relay circuit has the same source and destination site and relay type, and each relay circuit includes first routing information and a bearer rate;

[0149] The third module is used to query the transmission network topology data according to the source and destination sites to obtain multiple second routing information;

[0150] The fourth module is used to compare and analyze the first routing information of multiple relay circuits and multiple second routing information in the target relay service data to obtain the circuit multi-route load analysis results, wherein the multi-route load analysis results include one of the route construction requirements, route load rationality or route load adjustment solutions.

[0151] It can be understood that the contents of the above-mentioned circuit multi-route load bearing analysis method embodiment are all applicable to the present system embodiment, the functions specifically implemented by the present system embodiment are the same as those in the above-mentioned circuit multi-route load bearing analysis method embodiment, and the beneficial effects achieved are also the same as those achieved by the above-mentioned circuit multi-route load bearing analysis method embodiment.

[0152] The embodiment of the present application also provides an electronic device, the electronic device comprising: a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection and communication between the processor and the memory, and the program is executed by the processor to realize the above-mentioned circuit multi-route load analysis method. The electronic device can be any intelligent terminal including a tablet computer, a vehicle-mounted computer, etc.

[0153] See also Fig. 9 , Fig. 9 The hardware structure of an electronic device of another embodiment is illustrated, and the electronic device includes:

[0154] The processor 901 may be implemented by a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present application;

[0155] The memory 902 can be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 902 can store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 902, and the processor 901 calls and executes the circuit multi-route load analysis method of the embodiment of the present application;

[0156] Input / output interface 903, used to implement information input and output;

[0157] Communication interface 904, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WI FI, Bluetooth, etc.);

[0158] A bus 905 that transmits information between the various components of the device (e.g., the processor 901, the memory 902, the input / output interface 903, and the communication interface 904);

[0159] The processor 901 , the memory 902 , the input / output interface 903 and the communication interface 904 are connected to each other in communication within the device via a bus 905 .

[0160] An embodiment of the present application also provides a storage medium, which is a computer-readable storage medium used for computer-readable storage. The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the above-mentioned circuit multi-route load analysis method.

[0161] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0162] The embodiments described in the embodiments of the present application are intended to more clearly illustrate the technical solutions of the embodiments of the present application and do not constitute a limitation on the technical solutions provided in the embodiments of the present application. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided in the embodiments of the present application are also applicable to similar technical problems.

[0163] Those skilled in the art will appreciate that the technical solutions shown in the figures do not constitute a limitation on the embodiments of the present application, and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0164] The system embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the present embodiment.

[0165] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0166] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0167] It should be understood that in the present application, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0168] In the several embodiments provided in the present application, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are only schematic. For example, the division of the above units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of systems or units, which can be electrical, mechanical or other forms.

[0169] The units described above as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0170] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0171] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of various embodiments of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store programs.

[0172] The preferred embodiments of the present invention are described above with reference to the accompanying drawings, but the scope of the rights of the present invention is not limited thereto. Any modification, equivalent substitution and improvement made by a person skilled in the art without departing from the scope and essence of the present invention should be within the scope of the rights of the present invention.

Claims

1. A circuit multi-route load analysis method, characterized in that: The following steps are involved: Acquire transmission network topology data, wherein the transmission network topology data is obtained by identifying a transmission network topology map using a neural network technology, and the transmission network topology data includes connection relationships between sites of the transmission network; Acquire target relay service data, wherein the target relay service data includes multiple relay circuits, each of the relay circuits has the same source and destination site and relay type, and each of the relay circuits includes first routing information and a bearer rate; Querying the transmission network topology data according to the source and sink sites to obtain a plurality of second routing information; The first routing information of multiple relay circuits in the target relay service data and the multiple second routing information are compared and analyzed to obtain a circuit multi-route bearer analysis result, wherein the multi-route bearer analysis result includes one of the route construction requirements, route bearer rationality or route bearer adjustment plan.

2. The circuit multi-route load analysis method according to claim 1, characterized in that: The transmission network topology data is obtained by the following steps: Obtain the transmission network topology map; Using a trained convolutional neural network to identify site features in the transmission network topology map, and obtaining a site information set, wherein the site information set includes site coordinates, site visual connection features, and site area visual features; Constructing a graph structure according to the site information set; Using a trained graph neural network to identify site connection relationships in the graph structure, and obtaining site connection data in the transmission network topology graph; The transmission network topology data is determined according to the site connection data and the site information set.

3. The circuit multi-route load analysis method according to claim 2, characterized in that: The step of determining the transmission network topology data according to the site connection data and the site information set comprises the following steps: Determine a site type of each site according to the site information set, wherein the site type is one of a single-route site or a multi-route multiplexing site; Determine the site with the most connections in the transmission network topology graph according to the site connection data, and determine the site as the traversal starting point; Determine a target site that has a connection relationship with the traversal starting point according to the site connection data, and use an expected character to mark the connection relationship between the target site and the traversal starting point, wherein the expected character represents the site type with which the connection relationship exists and the target site; The target site is determined as a new traversal starting point, and the steps of determining a target site having a connection relationship with the traversal starting point based on the site connection data and marking the connection relationship between the target site and the traversal starting point with expected characters are repeated to obtain transmission network topology data, wherein the target site has not been used as a traversal starting point in historical traversal rounds.

4. The circuit multi-route load analysis method according to claim 1, characterized in that: The first routing information of the relay circuit in the target relay service data is obtained by the following steps: Querying the corresponding media routing text according to the circuit name of the relay circuit in the target relay service data; Using regular expressions to extract site information from the media routing text; The first routing information of the relay circuit is determined according to the site information.

5. The circuit multi-route load analysis method according to claim 1, characterized in that: The circuit multi-route load analysis method further comprises the following steps: According to the first routing information, merging multiple relay circuits with the same first routing information in the target relay service data into one relay circuit; The sum of the carrying rates of the plurality of relay circuits having the same first routing information is determined as the carrying rate of the combined relay circuit.

6. The circuit multi-route load analysis method according to claim 1, characterized in that: The step of querying the transmission network topology data according to the source and destination sites to obtain a plurality of second routing information includes the following steps: Traversing the transmission network topology data according to the source and destination sites, determining the sites along the way from the source end to the destination end; A plurality of second routing information are determined according to the en route sites from the source end to the destination end and the site types of the en route sites.

7. The circuit multi-route load analysis method according to claim 5, characterized in that: The step of comparing and analyzing the first routing information of the plurality of relay circuits in the target relay service data with the plurality of the second routing information to obtain a circuit multi-routing bearer analysis result comprises the following steps: Determining whether the amount of the second routing information is greater than a preset amount value; When the amount of the second routing information is less than a preset amount value, determining that the multi-routing bearer analysis result is a routing construction requirement; When the amount of the second routing information is greater than or equal to a preset amount value, determining whether the amount of the first routing information is the same as the amount of the second routing information; When the number of the first routing information is the same as the number of the second routing information, judging whether the rate bearing is balanced according to the bearing rates of the multiple relay circuits in the target relay service data, and when the rate bearing is balanced, determining that the multi-route bearing analysis result is reasonable for the route bearing; when the rate bearing is unbalanced, determining that the multi-route bearing analysis result is a route bearing adjustment plan, and the route bearing adjustment plan includes adjusting the bearing rate of the route; When the amount of the first routing information is less than the amount of the second routing information, the multi-route bearer analysis result is determined to be a route bearer adjustment scheme, wherein the route bearer adjustment scheme includes adjusting the relay circuit to a route that does not carry a circuit.

8. A circuit multi-route load analysis system, characterized in that: include: The first module is used to obtain transmission network topology data, wherein the transmission network topology data is obtained by identifying a transmission network topology map using a neural network technology, and the transmission network topology data includes connection relationships between sites of the transmission network; The second module is used to obtain target relay service data, wherein the target relay service data includes multiple relay circuits, each of the relay circuits has the same source and destination site and relay type, and each of the relay circuits includes first routing information and a bearer rate; A third module is used to query the transmission network topology data according to the source and destination sites to obtain multiple second routing information; The fourth module is used to compare and analyze the first routing information of multiple relay circuits in the target relay service data and the multiple second routing information to obtain the circuit multi-routing load analysis results, wherein the multi-routing load analysis results include one of the routing construction requirements, reasonable routing load or routing load adjustment solutions.

9. An electronic device, characterized in that: The electronic device includes a memory, a processor, a program stored in the memory and executable on the processor, and a data bus for realizing connection and communication between the processor and the memory. When the program is executed by the processor, the steps of the method described in any one of claims 1 to 7 are realized.

10. A storage medium, the storage medium being a computer-readable storage medium, used for computer-readable storage, characterized in that: The storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of any one of claims 1 to 7.

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