CN114417572A - Optical cable route planning method and device, terminal equipment and storage medium - Google Patents
Optical cable route planning method and device, terminal equipment and storage medium Download PDFInfo
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Abstract
The application provides an optical cable route planning method, an optical cable route planning device, terminal equipment and a storage medium. The method comprises the following steps: converting the service requirement acquired from the user input interface into a target parameter; carrying out search algorithm preference on the target parameters based on the optical cable resource data model to obtain a search preference result; carrying out planning algorithm preference on the search preference result to obtain a planning preference result; and outputting a planning preference result. The method reduces dependence on manual experience, and improves efficiency of optical cable routing planning.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to an optical cable routing planning method, apparatus, terminal device, and storage medium.
Background
With the continuous development of optical communication network technology, the composition of optical cable resources is becoming more and more complex, the number of resources is increasing, and the complexity of service provisioning for optical cables is also gradually increasing.
In possible implementation, the work of manual links is reduced to a certain extent, and automatic planning can be realized by manually configuring parameters in fewer optical cable resource node specifications. The technical scheme is based on the optical cable resource parameters manually input by technicians, and the optical cable routing planning efficiency is low compared with the experience of the technicians.
Disclosure of Invention
The application provides an optical cable route planning method and device, terminal equipment and a storage medium, which are used for reducing manual links, realizing automatic opening of an optical cable planning scheme and improving the efficiency of optical cable route planning.
In a first aspect, the present application provides an optical cable routing planning method, including:
converting the service requirement acquired from the user input interface into a target parameter; the target parameter is ID information in a cloud resource library corresponding to the service requirement; the service requirements include one or more of the following information for the cable route: the system comprises an initial position, a termination position, a must-pass node, an avoidance node, an approach optical cable, the maximum number of switching points, an optical fiber attenuation coefficient or the number of idle optical fibers;
carrying out search algorithm preference on the target parameters based on the optical cable resource data model to obtain a search preference result; the search algorithm comprises a depth priority algorithm and a breadth priority algorithm;
carrying out planning algorithm preference on the search preference result to obtain a planning preference result; the planning algorithm comprises an A-star algorithm and a Dijkstra algorithm;
and outputting a planning preference result.
Optionally, performing search algorithm preference on the target parameter based on the optical cable resource data model to obtain a search preference result, including:
if the target parameters include the necessary node parameters and the avoidance node parameters, preferentially selecting a search algorithm according to a depth-first algorithm to obtain a search preference result;
and if the target parameters have the optical cable parameters of the paths, preferentially selecting the search algorithm according to the breadth-first algorithm to obtain a search preferred result.
Optionally, the method for performing search algorithm preference on the target parameter based on the optical cable resource data model to obtain a search preference result further includes:
the target parameters include a necessary node parameter and an avoidance node parameter, if the depth-first algorithm cannot achieve a planning result, the search algorithm is selected preferentially according to the breadth-first algorithm to obtain a search preferred result;
and the target parameters have optical cable parameters, and if the breadth-first algorithm cannot achieve the planning result, the search algorithm is preferred according to the depth-first algorithm to obtain a search preferred result.
Optionally, performing planning algorithm preference on the search preference result to obtain a planning preference result, including:
respectively verifying the search preference result based on an A algorithm and a Dijkstra algorithm to obtain an A algorithm result and a Dijkstra algorithm result;
and obtaining a planning preferred result according to the A-star algorithm result, the Dijkstra algorithm result, the number of nodes, the path length and the result similarity.
Optionally, outputting a planning preference result, including:
and outputting the planning preference result in a display screen in the form of a list and a GIS map.
The application provides an optical cable routing planning method, which further comprises the following steps:
acquiring optical cable resource data from a cloud resource library;
simplifying the incidence relation and redundant data of the cable resource data to obtain original modeling data so as to establish an original data model;
performing secondary supplement on the original data model based on necessary service fields in the optical cable resource data to obtain
An optical cable resource data model; the necessary service field comprises optical fiber optical path name information, fiber core quality information and number information in the incidence relation in the redundant data.
In a second aspect, the present application provides an optical cable routing planning apparatus, including:
the service requirement processing module is used for converting the service requirement acquired from the user input interface into a target parameter; the target parameter is ID information in a cloud resource library corresponding to the service requirement; the service requirements include one or more of the following information for the cable route: the system comprises an initial position, a termination position, a must-pass node, an avoidance node, an approach optical cable, the maximum number of switching points, an optical fiber attenuation coefficient or the number of idle optical fibers;
the search algorithm preference module is used for carrying out search algorithm preference on the target parameters based on the optical cable resource data model to obtain a search preference result; the search algorithm comprises a depth priority algorithm and a breadth priority algorithm;
the planning algorithm preference module is used for carrying out planning algorithm preference on the search preference result to obtain a planning preference result; the planning algorithm comprises an A-star algorithm and a Dijkstra algorithm;
and the planning result output module is used for outputting a planning preference result.
In a third aspect, an embodiment of the present application provides a terminal device, including: a memory and a processor;
the memory is used for storing computer instructions; the processor is configured to execute the memory-stored computer instructions to implement the method of any of the first aspects.
In a fourth aspect, embodiments of the present application provide a computer-readable storage medium on which a computer program is stored, the computer program being executed by a processor to implement the method of any one of the first aspect.
In a fifth aspect, the present application provides a computer program product comprising a computer program that, when executed by a processor, implements the method of any one of the first aspects.
Note that the above-described computer program may be stored in whole or in part on a computer-readable storage medium. The computer readable storage medium may be packaged with the processor or packaged separately from the processor, which is not limited in this application.
According to the optical cable route planning method, the optical cable route planning device, the terminal equipment and the storage medium, the service requirement acquired from the user input interface is converted into the target parameter; carrying out search algorithm preference on the target parameters based on the optical cable resource data model to obtain a search preference result; carrying out planning algorithm preference on the search preference result to obtain a planning preference result; and outputting a planning preference result. A user can input fewer service requirements, and a better optical cable route planning scheme can be automatically planned. The method reduces dependence on manual experience, and improves the efficiency of optical cable routing planning.
Drawings
Fig. 1 is a schematic view of an application scenario provided in an embodiment of the present application;
fig. 2 is a schematic flow chart of an optical cable routing planning method according to an embodiment of the present application;
fig. 3 is a schematic flow chart of an optical cable routing planning method according to an embodiment of the present application;
fig. 4 is a path diagram illustrating an optical cable routing planning method according to an embodiment of the present application;
fig. 5 is a schematic flowchart of an optical cable route planning method according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of an optical cable route planning apparatus provided in an embodiment of the present application;
fig. 7 is a schematic structural diagram of an optical cable route planning terminal device according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present application. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present application, as detailed in the appended claims.
The terms referred to in this application are explained first:
the Optical Distribution Frame (ODF) is an Optical Distribution device specially designed for an Optical fiber communication machine room and has the functions of fixing and protecting Optical cables, terminating the Optical cables, adjusting wires and protecting Optical cable fiber cores and pigtails.
Optical cable distributing box: the optical cable end-forming and jumper connection device is used for providing optical cable end-forming and jumper connection for the optical cable of the trunk layer and the optical cable of the wiring layer. After the optical cable is introduced into the optical cable cross-connecting box, after fixing, terminating and fiber distribution, the main layer optical cable and the wiring layer optical cable are communicated by using the jump fiber.
In a possible implementation, the optical cable routing planning scheme still has the following problems:
with the development of optical communication technology, various optical communication data are increasing day by day, and higher requirements are put forward on information transmission. The composition of optical cable resources is becoming more and more complex, the number of resources is increasing day by day, and the complexity of service opening on the optical cable is also gradually rising. In the existing optical cable routing planning scheme, a scheme that large granularity selection is completed through a transmission system and then the optical cable section and the fiber core under the transmission system are automatically selected by manually configuring parameters is adopted, so that manual links are reduced to a certain extent. However, in this method, an optical cable planner needs to manually input a plurality of optical cable parameters to implement automatic planning, which depends on the manual experience of the technician. Meanwhile, in the optical cable routing planning scheme, the number of nodes is often large, the traversed information data is large, the time for outputting the planning result is influenced, the manual operation amount is increased, and the optical cable routing planning efficiency is low.
According to the optical cable route planning method based on the optical cable resource data model, all existing optical cable route conditions in a real scene are covered in the model, search algorithm preference and planning algorithm preference processing can be carried out according to service requests (initial positions, end positions and the like) of users, and a plurality of optical cable route planning schemes are automatically planned for the users. The method reduces the dependence on the manual experience, and non-technical personnel can also carry out optical cable routing planning according to the basic service requirements. The optical cable routing planning method can realize end-to-end simulation planning of the long-distance optical cable based on the optical cable resource data model, and the farthest distance can reach hundreds of thousands of kilometers.
The technical solution of the present invention and how to solve the above technical problems will be described in detail with specific embodiments. The following several specific embodiments may be combined with each other, and details of the same or similar concepts or processes may not be repeated in some embodiments. Embodiments of the present application will be described below with reference to the accompanying drawings.
Before describing the method provided by the embodiment of the present invention in detail, first, an application scenario of the optical cable routing planning method provided by the embodiment of the present invention is described in detail.
The method for planning the optical cable route provided by the application can be applied to an application scene graph of the optical cable route planning system shown in fig. 1. As shown in fig. 1, the optical cable routing planning system includes: the server 101 and the client 102, and the client 102 may be configured to receive a service requirement input by a user and display a search result of the optical cable routing plan. Illustratively, the client displays a manual light path emulation page based on which the user fills in service requirements, such as: filling in the starting point and the ending point, adding or deleting the avoiding place, the inevitable place and the like. The search results page of the client 102 provides a plurality of cable routing plans for viewing by the user. After the server 101 obtains and stores the optical cable resource data from the cloud resource library, an optical cable resource data model is established according to the optical cable resource data. The server 101 performs optical cable routing planning on the service requirement information input by the user based on the optical cable resource data model, and sends the search result to the client.
Based on the optical cable route planning system architecture, as shown in fig. 2, fig. 2 is a schematic flow chart of an optical cable route planning method provided in the embodiment of the present application. The method can comprise the following steps:
s201, converting the service requirement acquired from the user input interface into a target parameter; the target parameter is ID information in a cloud resource library corresponding to the service requirement. The service requirements include one or more of the following information for the cable route: the system comprises an initial position, a termination position, a must-pass node, an avoidance node, an approach optical cable, the maximum number of switching points, an optical fiber attenuation coefficient or the number of idle optical fibers.
The client can provide an interface for inputting the service requirement for the user and send the service requirement to the server. All data of the existing data model inquired from the cloud resource library are stored in the server. And the service end parameterizes the service requirement into ID information in a cloud resource library corresponding to the service requirement.
Illustratively, according to the service requirements input by the user at the client, such as: the method comprises the steps of carrying out parameterization processing on user service requirements on an initial position, a termination position, a must pass node, an avoidance node, an approach optical cable, the maximum transfer point number, an optical fiber attenuation coefficient, an idle optical fiber number and the like, and converting the initial position, the termination position, the must pass node, the avoidance node and the approach optical cable input by a user into corresponding ID information of the service requirements in a resource library to obtain target parameters. For example, the user inputs a start position and an end position in a text form, and the server converts the received start position and end position into corresponding latitude and longitude information or ID information. It is to be understood that the business requirements can be one or more of the above examples, which are not limited by this application.
According to the optical cable route planning method, a user can input fewer service requirements to realize rapid and convenient optical cable route planning. When the target parameters acquired by the server are less, the target parameters can be matched and combined through a matching strategy.
For example, a user inputs a start position in a text form, and the server converts the start position into a definition table of the area to query data information such as an ID number of the area where the start position is located, a corresponding machine room, an ODF, a terminal corresponding to the ODF, and a fiber core.
Illustratively, the default combination manner in the matching policy is: the system comprises an initial position parameter, a termination position parameter, a must pass node parameter, a avoidance node parameter, a maximum transit point number parameter, an optical fiber attenuation coefficient parameter and an idle optical fiber number parameter. If the path cable parameters exist, a new combination is generated besides the default combination, namely: the system comprises an initial position parameter, a termination position parameter, a must pass node parameter, a avoidance node parameter, an approach optical cable parameter, a maximum switching point number parameter, an optical fiber attenuation coefficient parameter and an idle optical fiber number parameter. If the path optical cable parameters do not exist, the server side inquires the path optical cables with the initial positions and the termination positions according to the initial position parameters and the termination position parameters except the default combination, generates corresponding number of combinations according to the number of the path optical cables, combines the corresponding number of combinations with the initial position parameters, the termination position parameters, the inevitable node parameters, the avoidance node parameters, the maximum transit point number parameters, the optical fiber attenuation coefficient parameters and the idle optical fiber number parameters, and uses the combinations in subsequent optical cable routing planning.
S202, carrying out search algorithm preference on the target parameters based on the optical cable resource data model to obtain a search preference result; the search algorithm includes a depth-first algorithm and a breadth-first algorithm.
Carrying out search algorithm preference on the target parameters by using a depth-first algorithm or a breadth-first algorithm to obtain a search preference result; the search and preference result comprises at least one planned path which can open the optical cable route between the starting position and the ending position. The search preference results are saved as surrogate data.
S203, carrying out planning algorithm preference on the search preference result to obtain a planning preference result; the planning algorithm comprises an A-algorithm and a Dijkstra algorithm.
And performing planning algorithm preference on the target parameters based on the A-algorithm and the Dijkstra algorithm to verify whether the planning path contained in the search preference result in the step S102 meets the target parameters. And if so, screening a better planning scheme from the plurality of planning paths for outputting.
And S204, outputting a planning preference result.
Illustratively, the planning preference result is output in the form of a list and a GIS map on a display screen of the client.
In the optical cable routing planning method provided by the embodiment, the service requirement acquired from the user input interface is converted into the target parameter; carrying out search algorithm preference on the target parameters based on the optical cable resource data model to obtain a search preference result; carrying out planning algorithm preference on the search preference result to obtain a planning preference result; and outputting a planning preference result. In the process, the user can input fewer service requirements, and the optical cable routing planning scheme can be automatically planned. The dependence on manual experience is reduced, and the efficiency of optical cable routing planning is improved.
Fig. 3 is a schematic flow chart of a method for planning an optical cable route according to an embodiment of the present application. On the basis of the embodiment shown in fig. 2, S202 includes:
optionally, if the target parameter has a must-pass node parameter and an avoidance node parameter, the search algorithm is preferentially selected according to the depth-first algorithm, so as to obtain a search preference result. And if the depth-first algorithm cannot achieve the planning result, carrying out search algorithm preference according to the breadth-first algorithm to obtain a search preference result.
And when the target parameters are subjected to search algorithm optimization, judging whether the target parameters comprise inevitable node parameters and avoidance node parameters. And when the necessary node parameter and the avoidance node parameter exist, the depth-first algorithm in the algorithm priority is prior to the breadth-first algorithm. And carrying out searching algorithm optimization on the target parameters based on a depth-first algorithm to obtain a plurality of planning paths.
Fig. 4 is an exemplary diagram of an optical cable routing path provided in an embodiment of the present application. As shown in fig. 4, circles represent nodes, and the numbers are node numbers.
The depth-first algorithm has a backtracking operation, and is realized through a multi-stage determination process. Each stage corresponds to a branch, if the branch path can not go deep, the node just searched is returned again, and another branch path of the node is selected. The depth-first algorithm searches slower for a single node, but may retain a portion of the nodes.
For example, if 1 is set as the starting position and 14 is set as the ending position, the search result sequence of the depth-first algorithm is:
route 1: 1-2-4-14
Route 2: 1-2-5
Route 3: 1-2-6-9
Path 4: 1-2-6-10-14
Path 5: 1-3-7-11-14
Path 6: 1-3-8-12-14
Path 7: 1-3-8-13
Where paths 1, 4, 5, and 6 are feasible paths to reach the end position 14.
Based on the depth-first algorithm, the characteristics of partial nodes can be reserved, when the target parameters comprise the requisite node parameters and the avoidance node parameters, the avoidance nodes are preferentially excluded, and the requirements of the requisite nodes are saved.
If the depth-first algorithm does not have a connected route, or the connected route cannot meet the requirements of the maximum switching point number, the optical fiber attenuation coefficient or the number of idle optical fibers, the planning result cannot be achieved, and at the moment, the breadth-first algorithm is performed on the target parameters.
Optionally, if the target parameter has an optical cable route parameter, the search algorithm is preferentially selected according to the breadth-first algorithm, so as to obtain a search preference result. And if the breadth-first algorithm cannot achieve the planning result, carrying out search algorithm preference according to the depth-first algorithm to obtain a search preference result.
And judging whether the target parameters contain the path optical cable parameters or not when the target parameters are subjected to search algorithm optimization. When the path optical cable parameters exist, the breadth-first algorithm is prior to the depth-first algorithm in the algorithm priority. And carrying out searching algorithm optimization on the target parameters based on the breadth-first algorithm to obtain a plurality of planning paths.
And the breadth first algorithm has no backtracking operation, accesses all adjacent nodes which are in an inaccessible state of the current node at one time, and accesses all secondary adjacent nodes which are in an inaccessible state of the adjacent node aiming at each adjacent node. Breadth-first algorithms search faster for a single node, but retain all nodes.
For example, if 1 is set as the starting position and 14 is set as the ending position, the search result sequence of the breadth first algorithm is:
<1,2>、<1,3>
<2,4>、<2,5>、<2,6>、<3,7>、<3,8>
<4,14>、<6,9>、<6,10>、<7,11>、<8,12>、<8,13>
<10,14>、<11,14>、<12,14>
after traversing all the nodes, obtaining an reachable path of the breadth-first algorithm: 1-2-4-14; 1-2-6-10-14; 1-3-7-11-14 and 1-3-8-12-14. If the target parameters do not have the avoidance node parameters, all nodes can be reserved. At the moment, according to the characteristics of the breadth-first algorithm, the optical cable can be found at the highest speed, and the searching process is accelerated.
If the breadth-first algorithm does not have a connected route, or the connected route cannot meet the requirements of the maximum switching point number, the optical fiber attenuation coefficient or the number of idle optical fibers, the planning result cannot be achieved, and at the moment, the depth-first algorithm is carried out on the target parameters.
According to the optical cable routing planning method provided by the embodiment, the target parameters are judged, and if the target parameters have the necessary node parameters and the avoidance node parameters, the searching algorithm is preferentially selected according to the depth-first algorithm, so that the searching and preferred result is obtained. And if the target parameters have the optical cable parameters of the paths, preferentially selecting the search algorithm according to the breadth-first algorithm to obtain a search preferred result. And establishing algorithm priority according to the characteristics of the breadth-first algorithm and the depth-first algorithm, and quickly traversing based on the characteristics of target parameters to generate a search preference result.
It can be understood that step S203 specifically includes:
optionally, the search preference result is verified based on the a-algorithm and the Dijkstra algorithm, respectively, to obtain an a-algorithm result and a Dijkstra algorithm result.
And part of planning paths in the search and preference result may not meet the requirement of the target parameters, and at the moment, the search and preference result can be verified through the A-star algorithm result and the Dijkstra algorithm result.
The Dijkstra algorithm principle is to visit the node with the lowest current cumulative cost g (n), which is the cumulative cost from the initial node to the current node. Dijkstra can ensure that the passed node is a path with the minimum cost g (n) from the starting position to the current position, so that the search is carried out according to the principle, and when the node discovers the target node, the backtraced path is a path with the minimum cost. The Dijkstra algorithm can verify the accuracy of the search and optimization result and obtain the minimum-cost planning path corresponding to the Dijkstra algorithm result.
The A-algorithm introduces a heuristic function h (n) on the basis of Dijkstra, wherein h (n) represents the estimated cost from the current node to the target node.
f(n)＝g(n)+h(n)
And the A-algorithm traverses each node to calculate the estimated cost, and ensures that the current node moves to the adjacent node with the minimum cost, thereby ensuring that the traversed path cost is minimum. The A-algorithm can verify the accuracy of the search and optimization result and simultaneously obtain the planning path with the minimum cost corresponding to the A-algorithm result.
Optionally, a planning preference result is obtained according to the result of the a-star algorithm, the result of the Dijkstra algorithm, the number of nodes, the path length and the similarity of the results.
Because the path-finding paths of the A-star algorithm and the Dijkstra algorithm are different, different characteristic results can be presented when more nodes have basic data. And according to the A-algorithm and the Dijkstra algorithm, excluding the planning path which does not meet the target parameters in the search and preference result. And simultaneously, screening a plurality of better planning schemes from the search and selection result, the A-x algorithm result and the Dijkstra algorithm result, and outputting the schemes to the user.
Illustratively, poor and repeated solutions may be eliminated based on the number of nodes, path length, similarity of planning solutions, etc. And when the similarity of the two planning schemes is too high, the planning scheme is determined to be a repeated planning scheme, and the repeated planning scheme is eliminated. In the rest planning schemes, a plurality of paths with the least number of nodes, the shortest path length or the minimum fiber core attenuation are respectively screened out as planning preference results. It is understood that the screening scheme of the optical cable routing planning path may be planned according to other screening rules.
In the optical cable routing planning method provided by this embodiment, the search preference result is verified based on the a-algorithm and the Dijkstra algorithm, respectively, so as to obtain an a-algorithm result and a Dijkstra algorithm result; and obtaining a planning preferred result according to the A-star algorithm result, the Dijkstra algorithm result, the number of nodes, the path length and the result similarity. The method verifies the search and preference result through the preference of the planning algorithm, and improves the accuracy of the reachable path in the optical cable routing planning method. And screening multiple paths with the least number of nodes, the shortest path length and the least fiber core attenuation from multiple planned paths of the search and selection result, the A-algorithm result and the Dijkstra algorithm result as a planned and selection result, enriching the selectivity of selectable planned paths and simultaneously providing multiple high-quality automatically-planned optical cable routes for users.
Fig. 5 is a schematic flowchart of establishing a cable resource data model according to an embodiment of the present application. As shown in fig. 5, the method includes:
s501, optical cable resource data are obtained from a cloud resource library.
The server side regularly obtains models such as a management area, a central office station, a machine room, an equipment placement point, an optical cable section, a fiber core, an ODF (optical distribution function), an optical cross-connecting box, a comprehensive box, an optical fiber splitting box, an optical cable joint, a provincial boundary, a column frame, a module, a terminal, a terminating end, a fused fiber, a local optical fiber route, an optical fiber light path, an optical link and an optical link route from a cloud resource library, and extracts all optical cable resource data in the existing models. Illustratively, the optical cable resource data can be queried and cached at the server by the server application in a period of every 24 hours, and updated in time.
S502, simplifying the incidence relation and the redundant data of the cable resource data to obtain original modeling data so as to establish an original data model.
The optical cable resource data is more and complicated, the first data reduction is firstly carried out on the optical cable resource data, and fields irrelevant to an optical cable routing planning scheme are removed. Such as manufacturer, property affiliation, etc. And simplifying the association relation of the optical cable resource data after the data are simplified according to the characteristics of the end-to-end connection of the optical cables. For example: the ODF, the optical cable cross connecting box, the comprehensive box and the optical cable fiber distributing box are simplified into a model that the ODF, the optical cable cross connecting box, the comprehensive box and the optical cable fiber distributing box are directly related to the terminal through a frame and module correlation model; the fiber core and the terminal which are related to the office direction optical fiber route and the optical link route are simplified into the direct relation between the terminal and the fiber core.
And processing redundant data according to the repeated and unavailable conditions of the optical cable resource state, the incidence relation, the node information and the like. For example: when the service state of the resources in the fiber core and the terminal is non-idle, the related resources are unavailable data in the application, and the whole incidence relation in head-to-tail connection can be inquired according to a model in which the terminal is directly associated with the fiber core, so that the data related to the optical cable is eliminated; when two pieces of model data formed by the fiber core and the terminal, the fiber core and the terminal passing through the inside of the model data sequentially belong to the same parent resource, the two pieces of data are regarded as repeated data, and the data can be simplified.
And after the incidence relation and the redundant data of the optical cable resource data are simplified, establishing an original data model.
S503, performing secondary supplement on the original data model based on necessary service fields in the optical cable resource data to obtain an optical cable resource data model; the necessary service field comprises optical fiber optical path name information, fiber core quality information and number information in the incidence relation in the redundant data.
In step S502, the number information of the simplified column frame and module related model exists; the ID and name information of the optical fiber light path exists in the simplified optical fiber light path; the conditions of fiber core quality information and the like exist in the repeated data of the fiber core and the terminal which are simplified, so that the original data model needs to be secondarily supplemented through necessary service fields in the optical cable resource data, the server application can inquire related results through the optical cable resource data, fill the related results into the original data model, finally output the optical cable resource data model which can be used for simulation, and store all resource information into the server in the form of a bidirectional linked list.
In the embodiment, optical cable resource data are acquired from a cloud resource library; simplifying the incidence relation and redundant data of the cable resource data to obtain original modeling data so as to establish an original data model; and performing secondary supplement on the original data model based on necessary service fields in the optical cable resource data to obtain the optical cable resource data model. The method provides an optical cable resource data modeling method, and the optical cable routing planning system can realize automatic path planning based on the optical cable resource data model, thereby reducing the dependence on manual experience.
Fig. 6 is a schematic structural diagram of an optical cable route planning apparatus according to an embodiment of the present application. As shown in fig. 6, the optical cable route planning apparatus 60 provided in this embodiment may include:
the service requirement processing module 601 is configured to convert a service requirement acquired in the user input interface into a target parameter; the target parameter is ID information in a cloud resource library corresponding to the service requirement; the service requirements include one or more of the following information for the cable route: the system comprises an initial position, a termination position, a must-pass node, an avoidance node, an approach optical cable, the maximum number of switching points, an optical fiber attenuation coefficient or the number of idle optical fibers.
A search algorithm preference module 602, configured to perform search algorithm preference on the target parameter based on the optical cable resource data model to obtain a search preference result; the search algorithm includes a depth-first algorithm and a breadth-first algorithm.
A planning algorithm preference module 603, configured to perform planning algorithm preference on the search preference result to obtain a planning preference result; the planning algorithm comprises an A-algorithm and a Dijkstra algorithm.
And a planning result output module 604 for outputting a planning preference result.
Optionally, the search algorithm preference module 602 is configured to perform search algorithm preference on the target parameter based on the optical cable resource data model to obtain a search preference result, and specifically includes:
and the depth-first algorithm module is used for preferentially selecting a search algorithm according to the depth-first algorithm to obtain a search preference result if the target parameter has the necessary node parameter and the avoidance node parameter.
And the breadth-first algorithm module is used for preferentially selecting the search algorithm according to the breadth-first algorithm to obtain a search preference result if the target parameter has the optical cable route parameter.
Optionally, the search algorithm preference module 602 is configured to perform search algorithm preference on the target parameter based on the optical cable resource data model to obtain a search preference result, and further includes:
and the breadth-first algorithm module is also used for obtaining a searching and preferred result by carrying out searching algorithm preference according to the breadth-first algorithm if the target parameters have the necessary node parameters and the avoidance node parameters and the depth-first algorithm cannot achieve the planning result.
And the depth-first algorithm module is also used for enabling the target parameters to exist in the optical cable parameters, and if the breadth-first algorithm cannot achieve the planning result, the search algorithm is preferentially selected according to the depth-first algorithm to obtain a search preference result.
Optionally, the planning algorithm preference module 603 is configured to perform planning algorithm preference on the search preference result to obtain a planning preference result, and specifically includes:
and the A-algorithm and Dijkstra algorithm module is used for verifying the search preference result respectively based on the A-algorithm and the Dijkstra algorithm to obtain an A-algorithm result and a Dijkstra algorithm result.
And the planning path preference module is used for acquiring a planning preference result according to the A-x algorithm result, the Dijkstra algorithm result, the number of nodes, the path length and the result similarity.
Optionally, the planning result output module 604 is configured to output a planning preference result, and specifically includes:
and outputting the planning preference result in a display screen in the form of a list and a GIS map.
The application provides an optical cable route planning device, still includes optical cable resource data simulation module 605, specifically includes:
and the optical cable data acquisition module is used for acquiring optical cable resource data from the cloud resource library.
And the optical cable data simplification module is used for simplifying the incidence relation and the redundant data of the optical cable resource data to obtain original modeling data so as to establish an original data model.
The optical cable model supplementing module is used for secondarily supplementing the original data model based on necessary service fields in the optical cable resource data to obtain an optical cable resource data model; the necessary service field comprises optical fiber optical path name information, fiber core quality information and number information in the incidence relation in the redundant data.
The optical cable route planning device according to the embodiment of the present application may be configured to implement the technical solution of the optical cable route planning method according to the embodiment of the present application, and the implementation principle and the technical effect are similar, which are not described herein again.
Fig. 7 is a schematic structural diagram of an optical cable route planning terminal device according to an embodiment of the present application. As shown in fig. 7, the optical cable route planning terminal device 70 provided in this embodiment may include:
a processor 701; and
a memory 702 for storing executable instructions of the terminal device;
the processor is configured to execute the technical solution of the above-described optical cable routing planning method embodiment by executing the executable instructions, and the implementation principle and technical effect are similar, which are not described herein again.
The embodiment of the present application further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the technical solution of the embodiment of the optical cable route planning method is implemented, and the implementation principle and the technical effect of the embodiment are similar, and are not described herein again.
The embodiment of the present application further provides a computer program product, which includes a computer program, and when the computer program is executed by a processor, the technical solution of the embodiment of the optical cable routing planning method is implemented, and the implementation principle and the technical effect of the embodiment are similar, and are not described herein again.
In the above Specific implementation of the terminal device or the server, it should be understood that the Processor may be a Central Processing Unit (CPU), other general purpose processors, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), etc. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present application may be directly implemented by a hardware processor, or may be implemented by a combination of hardware and software modules in a processor.
Those skilled in the art will appreciate that all or a portion of the steps of any of the above-described method embodiments may be performed by hardware associated with program instructions. The program may be stored in a computer-readable storage medium, and when executed, performs all or part of the steps of the above-described method embodiments.
The technical scheme of the application can be stored in a computer readable storage medium if the technical scheme is realized in a software form and is sold or used as a product. Based on this understanding, all or part of the technical solutions of the present application may be embodied in the form of a software product stored in a storage medium, including a computer program or several instructions. The computer software product enables a computer device (which may be a personal computer, a server, a network device, or a similar electronic device) to perform all or part of the steps of the method according to one embodiment of the present application. The storage medium may be various media capable of storing program codes, such as a usb disk, a removable hard disk, a ROM, a Random Access Memory (RAM), a magnetic disk, or an optical disk.
Finally, it should be noted that: the above embodiments are only used for illustrating the technical solutions of the present application, and not for limiting the same; although the present application has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art will understand that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present application.
Claims (10)
1. An optical cable routing planning method, comprising:
converting the service requirement acquired from the user input interface into a target parameter; the target parameter is ID information in a cloud resource library corresponding to the service requirement; the service requirements include one or more of the following information for the cable route: the system comprises an initial position, a termination position, a must-pass node, an avoidance node, an approach optical cable, the maximum number of switching points, an optical fiber attenuation coefficient or the number of idle optical fibers;
carrying out search algorithm preference on the target parameters based on an optical cable resource data model to obtain a search preference result; the search algorithm comprises a depth priority algorithm and a breadth priority algorithm;
carrying out planning algorithm preference on the search preference result to obtain a planning preference result; the planning algorithm comprises an A-star algorithm and a Dijkstra algorithm;
and outputting the planning preference result.
2. The method of claim 1, wherein the performing search algorithm preference on the target parameter based on the cable resource data model to obtain a search preference result comprises:
if the target parameters have the necessary node parameters and the avoidance node parameters, preferentially selecting a search algorithm according to the depth-first algorithm to obtain a search preferred result;
and if the target parameters have optical cable path parameters, preferentially selecting a search algorithm according to the breadth-first algorithm to obtain a search preferred result.
3. The method of claim 2, wherein the performing search algorithm preference on the target parameter based on the cable resource data model to obtain a search preference result further comprises:
the target parameters comprise the inevitable node parameters and the avoidance node parameters, and if the depth-first algorithm cannot achieve a planning result, the search algorithm is preferentially selected according to the breadth-first algorithm to obtain a search preferred result;
and the target parameters comprise the path optical cable parameters, and if the breadth-first algorithm cannot achieve a planning result, the search algorithm is preferred according to the depth-first algorithm to obtain the search preferred result.
4. The method of claim 3, wherein the performing planning algorithm preference on the search preference result to obtain a planning preference result comprises:
respectively verifying the search preference result based on an A algorithm and a Dijkstra algorithm to obtain an A algorithm result and a Dijkstra algorithm result;
and acquiring the planning preferred result according to the A-star algorithm result, the Dijkstra algorithm result, the number of nodes, the path length and the result similarity.
5. The method of claim 4, wherein outputting the planning preference result comprises:
and outputting the planning preference result in a display screen in the form of a list and a GIS map.
6. The method of claim 1, further comprising:
acquiring optical cable resource data from the cloud resource library;
simplifying the incidence relation and the redundant data of the optical cable resource data to obtain original modeling data so as to establish an original data model;
performing secondary supplement on the original data model based on necessary service fields in the optical cable resource data to obtain the optical cable resource data model; the necessary service field comprises optical fiber optical path name information, fiber core quality information and number information in the incidence relation in the redundant data.
7. An optical cable routing planning apparatus, comprising:
the service requirement processing module is used for converting the service requirement acquired from the user input interface into a target parameter; the target parameter is ID information in a cloud resource library corresponding to the service requirement; the service requirements include one or more of the following information for the cable route: the system comprises an initial position, a termination position, a must-pass node, an avoidance node, an approach optical cable, the maximum number of switching points, an optical fiber attenuation coefficient or the number of idle optical fibers;
the search algorithm preference module is used for carrying out search algorithm preference on the target parameters based on the optical cable resource data model to obtain a search preference result; the search algorithm comprises a depth priority algorithm and a breadth priority algorithm;
the planning algorithm preference module is used for carrying out planning algorithm preference on the search preference result to obtain a planning preference result; the planning algorithm comprises an A-star algorithm and a Dijkstra algorithm;
and the planning result output module is used for outputting the planning preference result.
8. A terminal device, comprising: a memory and a processor;
the memory is to store computer instructions; the processor is configured to execute the computer instructions stored by the memory to implement the method of any of claims 1-6.
9. A computer-readable storage medium, having stored thereon a computer program for execution by a processor to perform the method of any one of claims 1-6.
10. A computer program product, characterized in that it comprises a computer program which, when being executed by a processor, carries out the method of any one of claims 1-6.
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| CN115361063A (en) * | 2022-07-20 | 2022-11-18 | 卓信通信股份有限公司 | Intelligent optical fiber distribution management method and system |
| CN115514628A (en) * | 2022-09-25 | 2022-12-23 | 四川旅游学院 | Optical fiber wiring and fault locating method |
| CN115842584A (en) * | 2022-11-11 | 2023-03-24 | 国网安徽省电力有限公司合肥供电公司 | Method and system for bypassing power optical path protection service |
| CN115884017A (en) * | 2023-03-08 | 2023-03-31 | 联通（山东）产业互联网有限公司 | Method and system for analyzing path of optical cable access section |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115361063A (en) * | 2022-07-20 | 2022-11-18 | 卓信通信股份有限公司 | Intelligent optical fiber distribution management method and system |
| CN115361063B (en) * | 2022-07-20 | 2024-02-20 | 卓信通信股份有限公司 | Intelligent optical fiber wiring management method and system |
| CN115514628A (en) * | 2022-09-25 | 2022-12-23 | 四川旅游学院 | Optical fiber wiring and fault locating method |
| CN115514628B (en) * | 2022-09-25 | 2024-04-05 | 四川旅游学院 | Optical fiber wiring and fault positioning method |
| CN115842584A (en) * | 2022-11-11 | 2023-03-24 | 国网安徽省电力有限公司合肥供电公司 | Method and system for bypassing power optical path protection service |
| CN116260757A (en) * | 2022-12-02 | 2023-06-13 | 浪潮通信信息***有限公司 | Optical cable disconnection condition coping method, system and device based on resource topology |
| CN115884017A (en) * | 2023-03-08 | 2023-03-31 | 联通（山东）产业互联网有限公司 | Method and system for analyzing path of optical cable access section |
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