Network service management method, apparatus, device, medium, and program product

Abstract

The present disclosure provides a network service management method, device, equipment, medium and program product. Including dividing the end grid into different area types; each area type corresponds to a FAP box coverage radius range; performing Thiessen polygon algorithm division on potential FAP boxes in the end grid to obtain the potential coverage range of each potential FAP box; setting the FAP box in the end grid according to the potential coverage range corresponding to each potential FAP box and the set coverage range of each potential FAP box; determining the optical path information from each FAP box to the convergence machine room according to the preset optical path rule through graph traversal algorithm to obtain the optical path information set from the FAP box to the convergence machine room; and selecting target optical path information in the optical path information set from the FAP box to the convergence machine room according to the service demand of the access service. The method provided by the embodiment of the present disclosure can improve the efficiency and accuracy of the network service management method.

Description

Technical Field

[0001] This disclosure relates to the field of big data technology, and in particular to a network service management method, apparatus, equipment, medium, and program product. Background Technology

[0002] In related technologies, network service management methods, including the planning and construction of end-user access grids and Fiber Access Points (FAPs), primarily utilize traditional CAD (Computer-Aided Design) platforms and Google Earth platforms for layered, grid-based display and management. Points, lines, and blocks are labeled using latitude and longitude coordinates to plan, construct, and manage service points, FAPs, pipeline resources, and physical data center locations. However, currently, the end-user access grid is mainly divided manually on traditional platforms, relying on business needs and subjective experience to set up FAPs. This leads to low efficiency and accuracy in network service management methods. Summary of the Invention

[0003] This disclosure provides a network service management method, apparatus, device, medium, and program product. The technical solution of this disclosure is as follows:

[0004] Firstly, this disclosure provides a method for managing network services, including:

[0005] Based on the latitude and longitude layers divided by the terminal grid, and combined with the terminal grid data, the terminal grid is divided into different region types; wherein, the terminal grid data includes at least one of the following: terminal grid information, optical distribution box information, ODB box information, relationship between terminal network and optical distribution box, and relationship between terminal network and ODB box; each region type corresponds to a FAP box coverage radius range;

[0006] The potential FAP boxes within the end grid are divided using the Thiessen polygon algorithm to obtain the potential coverage area of ​​each potential FAP box.

[0007] Based on the potential coverage area corresponding to each potential FAP box and the set coverage area of ​​each potential FAP box, FAP boxes are set within the terminal grid; wherein, the set coverage area is determined based on the coverage radius range of the FAP box corresponding to each area type;

[0008] The optical path information from each FAP enclosure to the aggregation room is determined by a graph traversal algorithm according to a preset optical path rule, thus obtaining a set of optical path information from the FAP enclosure to the aggregation room.

[0009] Based on the service requirements of the access service, select the target optical path information from the optical path information set from the FAP cabinet to the aggregation room.

[0010] Secondly, this disclosure discloses a network service management device, comprising:

[0011] The region division module is used to divide the terminal grid into different region types based on the latitude and longitude layer of the terminal grid and in combination with the terminal grid data; wherein, the terminal grid data includes at least one of the following: terminal grid information, optical distribution box information, ODB box information, relationship between terminal network and optical distribution box, and relationship between terminal network and ODB box; each region type corresponds to a FAP box coverage radius range;

[0012] The polygon partitioning module is used to perform Thiessen polygon algorithm partitioning on the potential FAP boxes within the end grid to obtain the potential coverage area of ​​each potential FAP box.

[0013] The enclosure setting module is used to set FAP enclosures within the end grid according to the potential coverage range corresponding to each potential FAP enclosure and the set coverage range of each potential FAP enclosure; wherein, the set coverage range is determined based on the FAP enclosure coverage radius range corresponding to each area type;

[0014] The optical path module is used to determine the optical path information from each FAP enclosure to the aggregation room according to a preset optical path rule through a graph traversal algorithm, thereby obtaining a set of optical path information from the FAP enclosure to the aggregation room.

[0015] The optical path selection module is used to select the target optical path information from the optical path information set from the FAP cabinet to the aggregation room according to the service requirements of the access service.

[0016] Thirdly, this disclosure discloses an electronic device, comprising:

[0017] processor;

[0018] Memory used to store the processor's executable instructions;

[0019] The processor is configured to execute the instructions to implement the method described in the first aspect.

[0020] Fourthly, this disclosure provides a computer-readable storage medium having a computer program stored thereon, characterized in that the computer program, when executed by a processor, implements the method described in the first aspect.

[0021] Fifthly, this disclosure provides a computer program product, including a computer program / instructions, characterized in that the computer program / instructions, when executed by a processor, implement the method described in the first aspect.

[0022] The technical solution disclosed herein brings at least the following beneficial effects:

[0023] In this embodiment, based on the latitude and longitude layer divided by the terminal grid, and combined with the terminal grid data, the terminal grid is divided into different region types. The terminal grid data includes at least one of the following: terminal grid information, optical distribution box information, ODB box information, relationship between the terminal network and the optical distribution box, and relationship between the terminal network and the ODB box. Each region type corresponds to a coverage radius range of an FAP box. The potential FAP boxes within the terminal grid are divided using the Thiessen polygon algorithm to obtain the potential coverage range of each potential FAP box. Based on the potential coverage range corresponding to each potential FAP box and the set coverage range of each potential FAP box, FAP boxes are set within the terminal grid. The set coverage range is determined based on the coverage radius range of the FAP box corresponding to each region type. The optical path information from each FAP box to the aggregation room is determined using a graph traversal algorithm according to preset optical path rules, resulting in a set of optical path information from the FAP box to the aggregation room. Target optical path information is selected from the set of optical path information from the FAP box to the aggregation room according to the service requirements of the access service. In this way, the Thiessen polygon algorithm can be used to evaluate the coverage density and layout rationality of FAPs within the end-grid. By calculating the Thiessen polygons of each FAP cabinet, the potential coverage area of ​​the FAPs within the end-grid can be determined, and FAP cabinets can be set up within the end-grid. Furthermore, intelligent end-to-end resource analysis can be achieved through graph traversal algorithms to optimize dynamic routing schemes for service access. Additionally, based on the service requirements of access services, optimal target optical path information can be automatically output, and optimal access optical path routing schemes can be developed. Thus, the Thiessen polygon algorithm and traversal algorithm can be applied to FAP point selection and routing decisions, enabling scientific planning of FAP points and intelligent end-to-end resource analysis in optical fiber networks, thereby effectively improving the efficiency and accuracy of network service management methods.

[0024] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0025] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure, and are not intended to unduly limit this disclosure.

[0026] Figure 1A flowchart illustrating a network service management method provided in an embodiment of this disclosure;

[0027] Figure 2 This is a logical schematic diagram of a Thiessen polygon algorithm provided in an embodiment of this disclosure;

[0028] Figure 3 This is a schematic diagram of a concave polygon provided in an embodiment of this disclosure;

[0029] Figure 4 This is a logical schematic diagram of a network service management method provided in an embodiment of this disclosure;

[0030] Figure 5 This is a schematic diagram of the structure of a network service management device provided in an embodiment of this disclosure;

[0031] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Detailed Implementation

[0032] To enable those skilled in the art to better understand the technical solutions of this disclosure, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings.

[0033] It should be noted that the terms "first," "second," etc., used in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this disclosure. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this disclosure as detailed in the appended claims.

[0034] It should be noted that the information (including but not limited to user device information, user personal information, etc.), data (including but not limited to data used for analysis, data stored, data displayed, etc.) and signals involved in this disclosure are all authorized by the user or fully authorized by all parties, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0035] The acquisition, storage, use, and processing of data in this disclosed technical solution all comply with the relevant provisions of national laws and regulations.

[0036] It should be noted that in the embodiments disclosed herein, there may be some existing solutions in the industry such as software, components, and models. These should be considered as exemplary, and their purpose is only to illustrate the feasibility of implementing the technical solutions disclosed herein. However, it does not mean that the applicant has used or necessarily used such solutions.

[0037] In related technologies, the planning and construction of end-point access grids and FAPs (Functional Application Profiles) are mainly carried out through traditional CAD (Computer-Aided Design) platforms and Google Earth platforms for layered, gridded display and resource planning management. These platforms have difficulties in obtaining basic maps, especially in suburban areas and new planning areas. The planning of suburban and rural areas can easily become blind spots in planning, and the accuracy of information points is not high. Online editing on specific platforms like Google Earth is required, and the display and output of results are inconvenient, making it difficult to form a unified platform that can be integrated into the entire production process. Moreover, at present, there is still a lack of systems for evaluating the coverage density and layout rationality of FAPs within the end-point grid. The main approach involves manually dividing the end-user access mesh on traditional platforms, relying on business needs and subjective experience to set up unified fiber distribution points (FAPs). This lacks scientific and objective algorithms for evaluation, particularly regarding the density and distribution rationality of FAPs, which lacks closed-loop post-evaluation, leading to uneven resource distribution or redundant deployment. Service activation relies on manual route design, resulting in low automation levels. It depends on manual processing of large amounts of data and information, which can lead to suboptimal route design due to human factors. There is a lack of end-to-end resource evaluation and early warning, and timely resource reserves, which can affect the efficiency of service activation due to resource deployment.

[0038] Based on this, embodiments of this disclosure provide a network service management method, apparatus, device, medium, and program product. It can utilize the Thiessen polygon algorithm to evaluate the coverage density and layout rationality of FAPs within the end-point grid. By calculating the Thiessen polygons of each FAP enclosure, the potential coverage area of ​​the FAP within the end-point grid can be determined and compared with the coverage areas of other FAP enclosures to assess coverage density. It automatically selects FAPs using a three-point estimation algorithm to predict FAP demand and coverage area, providing decision support for FAP site selection and resource allocation. It can also achieve intelligent end-to-end resource analysis through a graph traversal algorithm to optimize dynamic routing schemes for service access. Furthermore, by setting access optical path length, optical path hop count, and fiber core resource rules, it evaluates the resource utilization and compliance of each optical path through algorithms, assessing the optical path resource situation from potential FAP enclosures to the aggregation room, ensuring the accessibility of the unified bearer point. Moreover, it can automatically output optimal and suboptimal access optical path routing schemes based on service requirements. By combining the FAP optical path information database and service access point location information, the system automatically selects the FAP access point within the terminal grid and generates the route scheme with the shortest optical path reachability.

[0039] As can be seen, the network service management method provided in this disclosure solves the scientific planning of unified FAP bearer points and intelligent end-to-end resource analysis in the operation of an optical cable network by using a "terminal grid FAP coverage density assessment method," "end-to-end resource reserve capacity assessment method," and "FAP point selection and dynamic routing decision method" based on business logic and utilizing known algorithms, thus filling a gap in the industry. It uses Thiessen polygons and corresponding algorithmic rules to assess the FAP coverage density and layout rationality within the terminal grid, providing supplementary suggestions to guide micro-planning; it pioneered the development of rules for access optical path length, optical path hop count, and fiber core resources based on practical experience, thereby achieving end-to-end optical path resource assessment from potential FAP enclosures to the aggregation room, ensuring the accessibility of unified bearer points. The network service management method provided in this disclosure can apply the Thiessen polygon algorithm to FAP coverage assessment, and apply three-point estimation and traversal algorithms to resource assessment and routing decisions, integrating these algorithms into a sandbox support system to form a complete solution for the scientific planning of FAPs and intelligent end-to-end resource analysis in optical cable networks.

[0040] The technical solutions provided by the embodiments of this disclosure are described in detail below with reference to the accompanying drawings.

[0041] Figure 1 This flowchart illustrates a network service management method provided in an embodiment of the present disclosure. This method can be applied to servers, such as a single server or a server cluster. Figure 1 As shown, the network service management method may include the following steps:

[0042] S101, based on the latitude and longitude layers divided by the end grid, and combined with the end grid data, divides the end grid into different region types.

[0043] The terminal grid data includes at least one of the following: terminal grid information, optical distribution box information, ODB (On-Board Diagnostics) box information, relationship between terminal network and optical distribution box, and relationship between terminal network and ODB box; each region type corresponds to a FAP box coverage radius.

[0044] In the embodiments of this disclosure, when performing network service management, a finely divided latitude and longitude layer of the end grid can be used as the calculation basis. Input end grid data includes end grid information, optical distribution box / ODB box information, and the relationship between the end grid and the optical distribution box / ODB box. Then, the end grid can be divided into different region types according to geographical location and service characteristics. As an example, the region types can be set as six categories: "dense urban area," "general urban area," "county town," "township," "rural area," and "other." A coverage radius range for each region type is defined. For example, the coverage radius range of the FAP box in a dense urban area is less than 150m; the coverage radius range in a general urban area is less than 250m; the coverage radius range in suburban counties and developed townships is less than 300m; and the coverage radius range in rural areas and mountainous areas is not limited, with a value of -1 representing no limitation on the coverage radius. Understandably, geographic information includes the boundaries of the end grid, the location of FAP boxes, optical distribution box information, and optical path resources of repeater segments, which can be collected, stored, analyzed, and displayed through GIS (Geographic Information System). Based on the system's optical distribution box and ODB data, aggregation room information, optical cable repeater segment data, etc., a Java-based data model can be used to develop an intelligent sand table system, and network service management methods can be executed based on the intelligent sand table system.

[0045] S102, the potential FAP boxes within the end grid are divided using the Thiessen polygon algorithm to obtain the potential coverage area of ​​each potential FAP box.

[0046] In the embodiments of this disclosure, potential FAP boxes in the end-point grid can be determined. For example, PX (Patch Panel) and FG (Fiber Optic Distribution Box) boxes with uplink optical path resources can be selected as suitable potential FAP boxes for selection as FAP objects. Alternatively, ODB boxes can be selected as backup box resources for supplementary coverage. Then, the potential FAP boxes in the end-point grid can be trained and partitioned using the Voronoi Diagrams algorithm. A Voronoi polygon is generated with each potential FAP box as the center. That is, there is one Voronoi polygon for each potential FAP box. These Voronoi polygons collectively cover the entire end-point grid area, and each Voronoi polygon represents the potential coverage area of ​​a corresponding potential FAP box.

[0047] S103, based on the potential coverage area corresponding to each potential FAP box and the set coverage area of ​​each potential FAP box, set the FAP box in the end grid.

[0048] The coverage range is determined based on the coverage radius of the FAP box corresponding to each area type.

[0049] In the embodiments of this disclosure, after obtaining the potential coverage range of each potential FAP cabinet, the set coverage range of each potential FAP cabinet can be determined centered on each potential FAP cabinet, based on the coverage radius range of the FAP cabinet corresponding to the area type where the potential FAP cabinet is located. Then, based on the potential coverage range and set coverage range of each potential FAP cabinet, the FAP points to be set within the end grid can be determined, and FAP cabinets can be set at the corresponding FAP points. It is understood that the FAP cabinet can be an optical distribution box, such as a PX or FG with uplink optical path resources, or an ODB cabinet can be used as the FAP cabinet. In this way, the FAP coverage density assessment of the end grid and the setting of FAP cabinets can be realized.

[0050] S104. Using a graph traversal algorithm according to preset optical path rules, determine the optical path information from each FAP enclosure to the aggregation room, and obtain the set of optical path information from the FAP enclosure to the aggregation room.

[0051] In the embodiments of this disclosure, after setting up the FAP enclosure, the set of optical path information from the FAP enclosure to the aggregation room can be determined, i.e., the optical path information database. For example, preset optical path rules can be set, and a graph traversal algorithm can be used to obtain the optical path information from the FAP enclosure to the aggregation room. Thus, the optical path information from each FAP enclosure to the aggregation room can be obtained. Based on the optical path information from each FAP enclosure to the aggregation room, the set of optical path information from the FAP enclosure to the aggregation room can be obtained, i.e., the optical path information database from the FAP enclosure to the aggregation room.

[0052] S105: Select the target optical path information from the optical path information set from the FAP cabinet to the aggregation room according to the service requirements of the access service.

[0053] In the embodiments of this disclosure, after obtaining the optical path information set from the AP enclosure to the aggregation room, if an access service request is received, the service requirements of the access service can be obtained, such as the location information and type of the access service, to determine the target FAP point and the target aggregation room. Then, based on the target FAP point and the target aggregation room, target optical path information can be selected from the optical path information set from the FAP enclosure to the aggregation room. The target optical path information can be one or more paths, and the target optical path information can be the route scheme with the shortest optical path reachable from the target FAP point to the target aggregation room from the optical path information set from the FAP enclosure to the aggregation room.

[0054] In this embodiment, based on the latitude and longitude layer divided by the terminal grid, and combined with the terminal grid data, the terminal grid is divided into different region types. The terminal grid data includes at least one of the following: terminal grid information, optical distribution box information, ODB box information, relationship between the terminal network and the optical distribution box, and relationship between the terminal network and the ODB box. Each region type corresponds to a coverage radius range of an FAP box. The potential FAP boxes within the terminal grid are divided using the Thiessen polygon algorithm to obtain the potential coverage range of each potential FAP box. Based on the potential coverage range corresponding to each potential FAP box and the set coverage range of each potential FAP box, FAP boxes are set within the terminal grid. The set coverage range is determined based on the coverage radius range of the FAP box corresponding to each region type. The optical path information from each FAP box to the aggregation room is determined using a graph traversal algorithm according to preset optical path rules, resulting in a set of optical path information from the FAP box to the aggregation room. Target optical path information is selected from the set of optical path information from the FAP box to the aggregation room according to the service requirements of the access service. In this way, the Thiessen polygon algorithm can be used to evaluate the coverage density and layout rationality of FAPs within the end-grid. By calculating the Thiessen polygons of each FAP cabinet, the potential coverage area of ​​the FAPs within the end-grid can be determined, and FAP cabinets can be set up within the end-grid. Furthermore, intelligent end-to-end resource analysis can be achieved through graph traversal algorithms to optimize dynamic routing schemes for service access. Additionally, based on the service requirements of access services, optimal target optical path information can be automatically output, and optimal access optical path routing schemes can be developed. Thus, the Thiessen polygon algorithm and traversal algorithm can be applied to FAP point selection and routing decisions, enabling scientific planning of FAP points and intelligent end-to-end resource analysis in optical fiber networks, thereby effectively improving the efficiency and accuracy of network service management methods.

[0055] In some possible implementations, the potential FAP boxes within the end grid are divided using the Thiessen polygon algorithm to obtain the potential coverage area of ​​each potential FAP box, including:

[0056] Boxes with uplink optical path resources within the terminal grid are selected as potential FAP boxes;

[0057] Each potential FAP box is abstracted as an object point on a plane;

[0058] The Thiessen polygon algorithm is used to divide each potential FAP box into Thiessen polygons based on the object points corresponding to each potential FAP box; the Thiessen polygons corresponding to each potential FAP box are used to indicate the potential coverage area of ​​each potential FAP box.

[0059] In this embodiment, when dividing the potential FAP boxes within the end grid using the Thiessen polygon algorithm to obtain the potential coverage area of ​​each potential FAP box, boxes with uplink optical path resources within the end grid can be selected as potential FAP boxes first. For example, PX and FG boxes with uplink optical path resources are selected as suitable potential FAP boxes for selection as FAP objects, while ODB boxes are listed as backup box resources for supplementary coverage. Then, the potential FAP box objects within the same end access grid can be abstracted into all n object points in the grid plane. The plane is then divided based on the object points corresponding to each potential FAP box using the Thiessen polygon algorithm, so that any object point in the plane is closest to its nearest object point. The space around each object point forms a Thiessen polygon, which contains all points that are closer to that point than any other point, thus obtaining the Thiessen polygon corresponding to each potential FAP box. These Thiessen polygons collectively cover the entire grid area, and each Thiessen polygon represents the potential coverage area of ​​an FAP box.

[0060] As an example, Voronoi Diagrams are a spatial analysis tool used to divide a plane based on a set of points (here, potential FAP boxes) such that any point in the plane is closest to its nearest neighbor. The space around each point forms a Voronoi Diagram, which contains all points that are closer to that point than any other point. Its implementation rules can be set by combining the specific physical environment characteristics of the end-grid and the FAP resource objects, including: a. Using a finely divided latitude and longitude layer of the end-grid as the calculation basis. Input end-grid information, optical junction box / OBD box information, and the relationship between the end-grid and the optical junction box / OBD box. b. According to geographical location and business characteristics, the end-grid type is set into six categories: "Dense Urban Area," "General Urban Area," "County Town," "Township," "Rural Area," and "Other." The coverage radius of the FAP is defined for different attributes: less than 150m in dense urban areas; less than 250m in general urban areas; less than 300m in suburban counties and developed townships; no restrictions for rural and mountainous areas, with a value of -1 representing no restriction on the coverage radius. PX and FG boxes with uplink optical path resources were selected as potential FAP boxes suitable for selection as FAP objects, and ODB boxes were listed as backup box resources for supplementary coverage.

[0061] The algorithm abstracts the FAP boxes within the end grid as points on a plane, generating a Thiessen polygon centered on each FAP box. For each point, the perpendicular bisectors (i.e., the perpendicular bisectors) between it and other points are calculated; the closed region formed by the intersection of these perpendicular bisectors is the Thiessen polygon for that point. These Thiessen polygons collectively cover the entire grid area, with each Thiessen polygon representing the potential coverage area of ​​an FAP box. As a concrete example, combined with... Figure 2 The specific implementation process can be as follows: a. Connect the mesh inside the same end to abstract the potential FAP box object suitable for FAP into all n object points in the mesh plane; b. Select one point P1 as the reference point, and connect the other n-1 points with P1 as the starting point; c. For each line segment, draw its perpendicular bisector, so that there are n-1 perpendicular bisectors intersecting to form some polygons; d. The polygon enclosed by the perpendicular bisector closest to the reference point P1 is the Voronoi polygon of point P1, which does not include other reference points; e. Select other points as reference points in turn to calculate their Voronoi polygons.

[0062] In some possible implementations, FAP boxes are set within the end grid according to the potential coverage area corresponding to each potential FAP box and the set coverage area of ​​each potential FAP box, including:

[0063] Determine the designated FAP enclosure coverage radius range corresponding to the area type where each potential FAP enclosure is located;

[0064] Based on the set coverage radius of each potential FAP enclosure, calculate the set coverage range for each potential FAP enclosure;

[0065] Based on the potential coverage area corresponding to each potential FAP box and the set coverage area of ​​each potential FAP box, determine the FAP coverage within the terminal grid;

[0066] Based on the FAP coverage within the end grid, FAP enclosures are set up within the end grid.

[0067] In this embodiment, when setting up FAP boxes within the end grid based on the potential coverage area corresponding to each potential FAP box and the set coverage area of ​​each potential FAP box, the set coverage radius of the area type where each potential FAP box is located can be determined first. Based on this set coverage radius, the set coverage area of ​​each potential FAP box is calculated. For example, the set coverage area of ​​each potential FAP box can be calculated with the FAP box as the center and the set coverage area of ​​the potential FAP box as the radius. Then, based on the potential coverage area corresponding to each potential FAP box and the set coverage area of ​​each potential FAP box, the FAP coverage situation within the end grid can be determined. For example, the intersection area of ​​the set coverage area of ​​each potential FAP box with the Thiessen polygon of each potential FAP box can be calculated, and the FAP coverage situation within the end grid can be determined by calculating the proportion of the intersection area within the set coverage area. Afterwards, FAP boxes can be set up within the end grid according to the FAP coverage situation within the end grid.

[0068] As an example, the implementation process of this embodiment may include the following steps: f. In actual business operations, if the end grid is a convex polygon, according to the Thiessen polygon generation algorithm, each FAP box point corresponds to a polygon containing only that FAP box point, simulating the coverage area of ​​the FAP box point. However, if the end grid is a concave polygon, then for one FAP box, it may correspond to multiple different Thiessen polygons (see...). Figure 3 , Figure 3 The black dot represents a FAP (Functional Apparatus) box point. From a business logic perspective, polygons are defined that do not contain any FAP box points, except for those containing the specified FAP box point. The algorithm output is the area that needs to be supplemented with additional box coverage. See also... Figure 3 The Thiessen polygon in the lower left corner represents the area where FAP coverage points need to be increased. g. For cases where there are no potential FAP boxes in the end grid, or where there is only one FAP box but the FAP coverage area is limited, and the coverage area of ​​the end grid is less than the preset percentage (e.g., 70%), ODB boxes can be considered as alternatives. h. For different attribute definitions of the end grid, the coverage radius of each potential FAP box can be obtained. A circle can be generated with the FAP box as the center. Using the intersection area of ​​the circle and the Voronoi polygon corresponding to the box, the proportion of the intersection area relative to the Thiessen polygon can be calculated to assess whether FAP coverage needs to be increased. For each end grid, the FAP box coverage calculation results can be defined as follows: ① The optical distribution box is selected as the FAP box to meet the coverage requirements; ② The optical distribution box in the Thiessen polygon area cannot meet the coverage requirements, and an additional FAP box needs to be added; ③ There is no optical distribution box available, so an ODB box is considered as the FAP box; ④ The optical distribution box cannot meet the coverage requirements, so an ODB box can be considered as the FAP box; ⑤ The optical distribution box cannot meet the coverage requirements, and no ODB box is available.

[0069] In some possible implementations, a graph traversal algorithm is used to determine the optical path information from each FAP enclosure to the aggregation room according to a preset optical path rule, resulting in a set of optical path information from the FAP enclosure to the aggregation room, including:

[0070] Set the optical path length range from the FAP cabinet to the aggregation room according to the area type of the end grid where the FAP cabinet is located; each area type corresponds to one optical path length range.

[0071] Set the maximum allowed number of hops in the optical path and the fiber core resource rules; among which, the fiber core resource rules include the number of idle fiber core resources in the entire optical path being greater than or equal to the preset number;

[0072] The optical path length range, maximum allowable number of hops, and fiber core resource rules corresponding to each region type are determined as preset optical path rules;

[0073] For relay segments between facility IDs and between facility IDs and aggregation site IDs, if the number of relay segments is less than 3, the average distance of the relay segments shall be taken as the relay segment length.

[0074] If the number of relay segments is greater than or equal to 3, the relay segment length is calculated using a three-point estimation algorithm.

[0075] Based on the relay segment length, a graph traversal algorithm is used to select nodes that satisfy the preset optical path rules as aggregation site nodes;

[0076] Based on the aggregation site nodes, the optical path information from each FAP box in each terminal grid to the aggregation room is generated, resulting in a set of optical path information from the FAP box to the aggregation room.

[0077] In this embodiment, the optical path information from each FAP enclosure to the aggregation room is determined using a graph traversal algorithm according to preset optical path rules. When obtaining the set of optical path information from the FAP enclosure to the aggregation room, the optical path length range limit from the FAP enclosure to the aggregation room can be set according to the region type of the end grid where the FAP enclosure is located. For example, it can be set as follows: optical path length ≤ 3000m in dense urban areas; optical path length ≤ 5000m in general urban areas; optical path length ≤ 6000m in county towns and townships; and optical path length ≤ 12000m in rural areas. A maximum allowed number of hops for the optical path is set, for example, 5 hops, 4 hops, 3 hops, etc., with a hop count less than or equal to 5 hops. Furthermore, fiber core resource rules are set, including the number of idle fiber core resources throughout the optical path being greater than or equal to a preset number. For example, it can be set to at least one of the following: idle fiber core resources throughout the optical path ≥ 2 cores, and the fiber core resource utilization rate of the optical path being less than or equal to a preset percentage. The preset percentage could be, for example, 70%. Then, the optical path length range, maximum allowed number of hops, and fiber core resource rules corresponding to each area type can be determined as preset optical path rules. After that, the number of repeater segments between facility ID (IdentityDocument, unique identifier) ​​and facility ID, and the number of repeater segments between facility ID and aggregation site ID can be determined. For cases where the number of repeater segments is less than 3, the average of the repeater segments is directly taken as the estimated distance of the repeater segment, that is, the repeater segment length. For cases where the number of repeater segments is greater than or equal to 3, the average repeater segment length information can be obtained through three-point estimation. The fiber core and remaining resource quantity are accumulated. As an example, for cases where there are multiple repeater segments between two IDs, the estimated distance is obtained by merging the three-point estimation formula. The average distance is the average value obtained after removing the longest and shortest distances. The calculation formula is as shown in formula (1). If there are fewer than 3 repeater segments, the average value is directly taken.

[0078] (Longest distance + Shortest distance + 4 * Average distance) / 6 = Repeater segment length (1)

[0079] Then, based on the relay segment length, a graph traversal algorithm, such as BFS (Breadth First Search), can be used to select nodes that meet the preset optical path rules as aggregation site nodes (e.g., aggregation equipment rooms). For example, a one-dimensional array can be used to record the possible path information from each FAP box to the aggregation equipment room. Each element node of the one-dimensional array represents the endpoint of a relay segment. Each node needs to record the index of its parent node, the cumulative length of the relay segment, and the fiber core information of the current relay segment. When a node is reached, if it exceeds 5 hops, or the cumulative distance of the relay segment exceeds the maximum distance allowed by the end grid definition, the node is marked as the end of the search. If the node belongs to the aggregation site and meets the requirements of no more than 5 hops and a length that does not exceed the maximum distance allowed by the end grid, the node is marked as an aggregation site node, i.e., the aggregation equipment room. Then, based on the aggregation site nodes, optical path information from each FAP enclosure in each end grid to the aggregation room can be generated, obtaining the possible path information from the FAP enclosure to the aggregation room, i.e., the optical path information. The resulting set of possible path information for each FAP enclosure in each end grid to the aggregation room can be obtained. For example, based on the one-dimensional array obtained by the graph traversal algorithm, site nodes can be retrieved from back to front, and based on each site node, the optical path information from each potential FAP enclosure in each end grid to the aggregation site can be generated in reverse order.

[0080] In one possible implementation, after determining the optical path information from each FAP enclosure to the aggregation room using a graph traversal algorithm according to preset optical path rules, and obtaining the set of optical path information from the FAP enclosure to the aggregation room, the system further includes at least one of the following:

[0081] Based on the optical path distance from each FAP enclosure to the aggregation room, fiber core resources, and hop count data, the data is normalized and weighted to obtain the optical path priority sorting table corresponding to the end grid.

[0082] Based on the optical path distance from each FAP enclosure to the aggregation room, fiber core resources, and whether the hop count data meets the preset optical path rules, a potential FAP optical path information database and an optical path early warning information database to be optimized are obtained.

[0083] In this embodiment, after obtaining the optical path information set from the FAP enclosure to the aggregation room, the optical path information set can be processed to obtain an optical path priority ranking table. For example, based on the optical path distance, fiber core resource status, and hop count data from each FAP enclosure to the aggregation room, data normalization and weighting configuration (e.g., adjusting weight parameters through final service testing and evaluation) can be performed to obtain the optical path priority ranking table corresponding to the end grid. The main function of the priority ranking table is, for example, to provide information on optical paths with sufficient resources and to provide construction suggestions for optical paths with limited resources. Furthermore, based on whether the optical path distance, fiber core resource status, and hop count data from each FAP enclosure to the aggregation room meet preset optical path rules, a potential FAP optical path information database and a pre-optimized optical path warning information database can be obtained. For example, optical path information whose total optical path distance and hop count meet the set rules and whose total optical path has ≥2 idle fiber cores can be included in the "potential FAP optical path information database," while optical path information that does not meet the set rules or whose optical path fiber core resource utilization exceeds 70% can be included in the "pre-optimized optical path warning information database."

[0084] In one possible implementation, target optical path information is selected from the set of optical path information from the FAP enclosure to the aggregation room based on the service requirements of the access service, including:

[0085] Based on the location information of the access service, calculate the end grid to which the service point of the access service belongs;

[0086] Select the FAP enclosure access point and aggregation room within the terminal grid based on the regional attributes of the terminal grid;

[0087] Select the target optical path information from the optical path information set from the FAP enclosure to the aggregation room based on the FAP enclosure access point and aggregation room.

[0088] In this embodiment of the disclosure, upon receiving an access service, the target optical path information can be selected from the set of optical path information from the FAP cabinet to the aggregation room according to the service requirements of the access service. For example, based on the FAP cabinet access point selection and routing design according to the access service requirements, the target room can be selected according to the access service type (wireless, home broadband, enterprise), and an access optical path routing scheme (providing both optimal and suboptimal schemes) can be automatically output based on the potential FAP cabinet optical path information. As an example, the location information of the access service can be obtained, and based on this information, the end grid to which the access service point belongs can be calculated. A list of corresponding aggregation rooms can be filtered from the service access area corresponding to the service point, and the FAP cabinet access point can be automatically selected based on the service access point location information. Then, the target optical path information can be selected from the set of optical path information from the FAP cabinet to the aggregation room based on the FAP cabinet access point and the aggregation room. For example, based on the "potential FAP optical path information database," which is the set of optical path information from the FAP enclosure to the aggregation room, a routing scheme with the shortest optical path reachability can be automatically generated as the target optical path information. The target optical path information can be one, two, or more.

[0089] Furthermore, loop checks can be performed on the target optical path information. For example, it can be checked whether there are duplicate jump points. If there are duplicate jump points, the corresponding target optical path information can be deleted to avoid generating loops.

[0090] Understandably, the following processing can also be performed: Based on the comprehensive sorting of the optical path information set from the FAP enclosure to the aggregation room, staff will determine the FAP enclosure to be used according to business rules. Simultaneously, resource usage will be synchronized to the system's resource database, including registering the number of reserved fiber cores in the pipeline system's repeater information; for data clearly already occupied, the enclosure information and site resource information will be updated synchronously. For newly added FAP enclosure data and repeater information after supplementary construction and completion, the calculations in the above method embodiment will be triggered to update the Thiessen polygon information of the grid. Furthermore, after each FAP enclosure selection, resource reservation, and resource occupation is completed according to business rules, the algorithm model in the above embodiment will be activated. Based on the latest resource changes, the optical path information from the FAP enclosure to the aggregation site in the end grid will be recalculated, and the FAP enclosure priority sorting result corresponding to the end grid will be recalculated. The result table data will then be updated.

[0091] To make the network service management method provided in this disclosure clearer, it will be described below with reference to specific examples. Figure 4This disclosed embodiment primarily utilizes data from optical distribution boxes, equipment rooms, optical cable repeater segments, and locally defined terminal network layers. It employs Java architecture for data modeling and leverages various algorithms to achieve terminal grid FAP coverage density assessment, end-to-end resource reserve capacity assessment, FAP site selection based on service requirements, and automatic route design. Horizontally, the three functional modules work collaboratively, while vertically, they encompass the entire production process of planning and construction, optimized operation, and resource management.

[0092] The network service management method disclosed herein mainly includes the following three parts:

[0093] 1. Implementation of end-grid FAP coverage density assessment.

[0094] The technical principle of end-grid FAP coverage density assessment mainly revolves around the quantitative analysis of the rationality of the layout and coverage density of FAPs (Unified Access Fiber Points) within the end-grid. This assessment process involves Geographic Information System (GIS) technology, spatial analysis methods, and especially the concept and algorithm of Voronoi Diagrams. The relevant technical principles are as follows:

[0095] Geographic Information System (GIS) technology is a system used to collect, store, analyze, and display geospatial data. In this scenario, GIS is used to manage and analyze geographic information related to the end grid, including grid boundaries, FAP locations, optical distribution box information, and repeater optical path resources.

[0096] Voronoi Diagrams are a spatial analysis tool used to divide a plane based on a set of points (in this case, the potential FAP box) such that any point in the plane is closest to its nearest neighbor. The space around each point forms a Voronoi Diagram, which contains all points that are closer to that point than to any other point.

[0097] (1) To implement the rules, the first step is to combine the specific physical environment characteristics of the end grid with the FAP resource objects to set the rules, as follows:

[0098] a. The calculation is based on a latitude and longitude layer with finely divided end grids. Input end grid information, optical junction box / OBD box information, and the relationship between the end grid and the optical junction box / OBD box.

[0099] b. Based on geographical location and business characteristics, the terminal grid type is set into six categories: "Dense Urban Area", "General Urban Area", "County Town", "Township", "Rural Area" and "Other". The coverage radius of FAP is defined for different attributes: less than 150m in dense urban area; less than 250m in general urban area; less than 300m in suburban counties and developed townships; no limit for rural and mountainous areas, with a value of -1 representing no limit on coverage radius.

[0100] c. Select PX and FG with uplink optical path resources as potential FAP boxes suitable for selection as FAP objects, and list ODB boxes as backup box resources for supplementary coverage.

[0101] (2) Algorithm Design

[0102] The Thiessen polygon generation algorithm abstracts the FAP boxes inside the end grid as points on a plane. A Thiessen polygon is generated centered on each FAP box. For each point, the perpendicular bisectors (i.e., the perpendicular bisectors) between it and other points are calculated; the closed region formed by the intersection of these perpendicular bisectors is the Thiessen polygon for that point. These Thiessen polygons collectively cover the entire grid area, and each Thiessen polygon represents the potential coverage area of ​​one FAP box.

[0103] a. Connect the mesh at the same end, and abstract the box object suitable for FAP into all n object points in the mesh plane;

[0104] b. Select one point P1 as a reference point, and use P1 as the starting point to connect the other n-1 points;

[0105] c. For each line segment, draw its perpendicular bisector, so that there are n-1 perpendicular bisectors intersecting to form some polygons;

[0106] d. The polygon formed by the perpendicular bisectors closest to the reference point P1 is the Voronoi polygon of point P1, which does not include other reference points;

[0107] e. Select other points sequentially as reference points to calculate their Voronoi polygons. (An example of the ae algorithm process is shown below.) Figure 2 (As shown).

[0108] f. In actual business applications, if the end grid is a convex polygon, according to the Thiessen polygon generation algorithm, each FAP box point corresponds to a polygon containing only that FAP box point, simulating the coverage area of ​​the FAP box point. If the end grid is a concave polygon, then for one FAP box, it will correspond to multiple different Thiessen polygons (e.g., ...). Figure 3As shown in the diagram, from a business logic perspective, polygons are defined that do not contain FAP box points, except for those containing the FAP box point. The algorithm outputs these polygons as the areas that need to be covered by additional boxes. For example, in the lower left corner of the diagram below, the Thiessen polygon represents the area where FAP coverage points need to be added.

[0109] g. In cases where there are no potential FAP boxes in the end grid, or where there is only one FAP box but the FAP has a limited range and covers less than 70% of the end grid area, consider finding ODB boxes as alternatives.

[0110] h. For different attribute definitions of the end grid, the coverage radius of each potential FAP box can be obtained. A circle is generated centered on the FAP box. The proportion of the intersection area between the circle and the Voronoi polygon corresponding to the box is calculated relative to the Thiessen polygon, thereby assessing whether the FAP needs increased coverage. The FAP coverage calculation result is defined as follows for each end grid:

[0111] ① The optical distribution box is selected as the FAP to meet coverage requirements;

[0112] ② The optical distribution box within the Thiessen polygon area cannot meet the coverage requirements, so an additional FAP is needed;

[0113] ③ If no optical junction box is available, consider using ODB as FAP;

[0114] ④ If the optical distribution box cannot meet the coverage requirements, ODB can be considered as FAP;

[0115] The optical distribution box cannot meet the coverage requirements, and there is no ODB option.

[0116] 2. End-to-end resource reserve capacity assessment achieved

[0117] The technical principle of end-to-end resource reserve capacity assessment mainly revolves around the three-point estimation algorithm and graph traversal algorithm to assess the end-to-end optical path resource status from potential FAP enclosures to aggregation equipment rooms. By setting access optical path length, optical path hop count and fiber core resource rules, it outputs a potential FAP optical path information table that meets access requirements and an early warning information table of optical paths that need optimization, thereby guiding the micro-planning team to design optical path routes, optimize end-to-end resources and plan reserves in advance for service access requirements.

[0118] (1) Implementation rules

[0119] a. Based on the end-to-end grid category where the FAP is located, set the end-to-end optical path length limit from the FAP to the aggregation site: optical path length in dense urban areas ≤ 3000m; optical path length in general urban areas ≤ 5000m; optical path length in county towns and townships ≤ 6000m; optical path length in rural areas ≤ 12000m;

[0120] b. Set the optical path hop count to ≤ 5 hops;

[0121] c. If the total optical path distance and hop count meet the set rules and the total optical path has ≥2 idle fiber cores, it will be included in the "Potential FAP Optical Path Information Database". If it does not meet the set rules or the optical path fiber core resource utilization rate exceeds 70%, it will be included in the "Optical Path Optimization Warning / Hidden Danger Database".

[0122] (2) Algorithm design: Calculations are performed based on potential FAP basic information (optical distribution box, ODB box basic information), repeater segment information (recording facility ID, length, fiber core quantity, and remaining resource information between adjacent hop points on the entire network link), and the relationship data between the grid and optical distribution boxes and ODB boxes.

[0123] a. Based on relay segment information: Generate the relationship information of each facility ID with other facility IDs, and between facility IDs and aggregation site IDs, including length, total number of fiber cores, used fiber cores, reserved fiber cores, and remaining fiber cores. During the algorithm calculation process, the data undergoes the following transformation calculations:

[0124] (1) There is only one record for a relay segment, without direction information. The algorithm needs to consider the link direction. Therefore, each relay segment needs to be converted into two relay segments with direction attributes. The two facility IDs are the start and end points of each other.

[0125] (2) In the case of multiple paths in the relay segment between facility IDs and between facility ID and aggregation site ID, the algorithm obtains the average length information through three-point estimation, and the fiber core and remaining resource quantity are accumulated.

[0126] (3) Three-point estimation algorithm: When there are multiple relay segments between two IDs, the three-point estimation formula is used to combine them to obtain the estimated distance. The average distance is the average value obtained after removing the longest and shortest distances. The formula is as follows:

[0127] (Longest distance + Shortest distance + 4 * Average distance) / 6 = Repeater segment length

[0128] If there are fewer than 3 relay segments, the average value is taken directly.

[0129] b. Based on the corresponding potential FAP information in the grid, calculate the route from each FAP to the aggregation room. Specifically, using the trunk segment information obtained in step 1, the Breadth-First Search (BFS) algorithm in graph traversal is adopted. A one-dimensional array is used to record the possible path information from each FAP to the aggregation room. Each element node of the one-dimensional array represents the endpoint of a trunk segment. Each node needs to record the index of its parent node, the cumulative length of the trunk segment, and the fiber core information of the current trunk segment. When reaching a node, if it exceeds 5 hops or the cumulative distance of the trunk segment exceeds the maximum distance allowed by the grid definition, the node is marked as the end of the search. If the node belongs to the aggregation site and satisfies the conditions of not exceeding 5 hops and the length not exceeding the maximum distance allowed by the grid, the node is marked as an aggregation site node.

[0130] c. Based on the one-dimensional array obtained by the graph traversal algorithm in the previous step, retrieve the site nodes from back to front. Based on each site node, generate the optical path information from each grid and each potential FAP to the site in reverse order.

[0131] d. Within the grid, based on the optical path distance from the FAP to the aggregation room, fiber core resources, and hop count data, data normalization and weighting configuration are performed (weight parameters need to be adjusted through final service testing and evaluation) to obtain the corresponding optical path priority ranking table for the grid. The main function of the priority ranking table is to provide information on optical paths with sufficient resources and to provide construction suggestions for optical paths with limited resources. Paths with the following characteristics are listed in the "Potential FAP Optical Path Information Database": those with the total optical path distance and hop count meeting the set rules and having ≥2 idle fiber cores throughout the optical path; and those that do not meet the set rules or have a fiber core resource utilization rate exceeding 70% are listed in the "Optimization Required Early Warning Information Database".

[0132] 3. Implementation of FAP site selection and dynamic routing decision based on business needs. This mainly implements FAP access site selection and routing design based on access service needs. It selects the target equipment room according to the access service type (wireless, home broadband, enterprise customers) and automatically outputs access optical path routing schemes based on potential FAP optical path information (providing two schemes, optimal and suboptimal, for selection).

[0133] (1) Implementation rules

[0134] a. Based on the location information of the access service, first filter out the corresponding aggregation data center list from the service access area corresponding to the service point; then, based on the type of access service, filter out the targets suitable for access (the relevant equipment resources in the data center are ready for production).

[0135] b. Automatically select FAP access points within the end-mesh based on the service access point location information;

[0136] c. Automatically generate the shortest and most reachable optical path routing scheme based on the "Potential FAP Optical Path Information Database";

[0137] d. Loop check: The output scheme must be checked for duplicate jump points. If any are found, they should be deleted to avoid generating loops.

[0138] (2) Algorithm Design

[0139] a. Calculate the end grid to which the business point belongs based on the latitude and longitude selected for the business.

[0140] b. Define the FAP range based on the area attributes of the grid itself, determine the available FAP information corresponding to the current service point, and the optical path information from the FAP to the aggregation site.

[0141] c. Based on the comprehensive sorting of available FAP optical path information, business personnel, in accordance with existing business rules, determine the FAP enclosures to be used, and simultaneously synchronize resource usage to the system's resource database, including the number of fiber cores reserved, and register them in the pipeline system's repeater section information. For data that is clearly already occupied, synchronize and update the enclosure information and site resource information.

[0142] d. For the completed supplementary construction and finished FAP box data information, the relay section information is newly entered into the system, which should trigger the calculation of module one to update the Thiessen polygon information of the mesh.

[0143] e. Each time the business process of selecting, reserving, and occupies FAP resources is completed according to the business rules, the corresponding algorithm model of Activation Module 2 is activated. Based on the latest resource changes, the optical path resources from the FAPs in the grid to the aggregation site are recalculated, and the FAP priority ranking results for the corresponding grid are recalculated. The result table data is then updated.

[0144] As a concrete example, the functions can be implemented as follows:

[0145] 1. Implementation of end-grid FAP coverage density assessment.

[0146] By collecting usage data from each port resource and using a port resource heatmap algorithm (the algorithm steps are as follows), the generated port resource heatmap can visually show the resource utilization rate. The color intensity in the heatmap represents the port utilization rate, which can intuitively show the resource usage situation. At the same time, by applying the Voronoi diagram algorithm of this proposal, the areas that need to be supplemented with FAP boxes can be calculated and marked (the black arrow area in the figure below). By calculating the Thiessen polygon of each FAP box, its potential coverage area is determined, and the coverage area is compared with the coverage area of ​​other FAP boxes to evaluate the coverage density, providing guidance and reference for planners.

[0147] The steps for generating the port resource heat map algorithm are as follows:

[0148] (1) Obtain the location and resource information of the beam splitter boxes in the park and user buildings;

[0149] (2) Calculate the actual service volume of the box by dividing the number of broadband addresses in use bound to the box by the total number of broadband addresses bound to the box;

[0150] (3) The map front end generates a grid heat map of the area based on the actual percentage of business volume;

[0151] (4) Based on the distribution of thermal values ​​within the region, find the thermal region polygon within the region using the well-known density algorithms Kmeans or DBScan (Density-Based Spatial Clustering of Applications with Noise);

[0152] (5) Find the intersection of the thermal region polygon and the FAP to be supplemented region polygon to obtain the location of the region where additional FAP convergence points need to be added.

[0153] 2. End-to-end resource reserve capacity assessment and dynamic routing decision implementation.

[0154] As a concrete example, Case 1, suppose an account manager initiates a request for a leased internet line access service. The coordinates are: longitude: 116.76783751, latitude: 23.48373617 (GPS), and the service type is PON (Passive Optical Network). After inputting the latitude, longitude, and service type into the algorithm tool's front-end interface, the algorithm locates the end grid to which the service point belongs based on the latitude and longitude. The FAP range is defined according to the grid's regional attributes, and the available FAP information corresponding to the current service point is determined. Based on the potential FAP information in the grid, the Breadth-First Search (BFS) algorithm in graph traversal is used. A one-dimensional array is used to record the possible path information from each FAP to the aggregation room. Site nodes are searched from back to front. Based on each site node, the optical path information from each grid and each potential FAP to the site is generated in reverse order, thus outputting candidate FAPs and their corresponding candidate routes. Based on the principle of shorter route length and fewer hops, the first route is selected as the summary route for this service.

[0155] Case 2: Assume that aggregation room A needs to be dismantled, and its base station service "A1" needs to be transferred to another service aggregation. Longitude: 116.72556, Latitude: 23.39562 (GPS), Service transfer type: PTN (PTN). Routing information before the transfer: Wireless equipment room 01, xx building, xx district → Axxx1 → Axxx2 → A aggregation point, x building, equipment room, transmission 1. The recommended FAP obtained through end-to-end resource reserve capacity assessment and dynamic routing decision function (the algorithm process in Case 1) is consistent with that before the transfer; no change to the access point is required, only the last hop needs to be changed to the replacement station of the dismantled equipment room: B. Routing information after the transfer: Wireless equipment room 01, xx building, xx district → Axxx1 → Axxx2 → B aggregation equipment room 01.

[0156] In summary, this disclosure addresses the scientific planning of unified FAP bearer points and intelligent end-to-end resource analysis in the operation of an optical cable network by employing a "terminal grid FAP coverage density assessment method," a "end-to-end resource reserve capacity assessment method," and a "FAP point selection and dynamic routing decision method" designed based on business logic and utilizing known algorithms, thus filling a gap in the industry. It is the first to use Voronoi diagrams and corresponding algorithmic rules to assess the FAP coverage density and layout rationality within the terminal grid, providing supplementary suggestions to guide micro-planning; and it is the first to combine practical experience to formulate rules for access optical path length, optical path hop count, and fiber core resources, thereby achieving end-to-end optical path resource assessment from potential FAP enclosures to the aggregation equipment room, ensuring the accessibility of unified bearer points. Specifically:

[0157] 1. Application of Voronoi Diagram Algorithm: Voronoi diagrams are used to evaluate the coverage density and layout rationality of FAPs (Unified Access Fiber Distribution Points) within the end-mesh grid. By calculating the Thiessen polygons of each FAP enclosure, its potential coverage area is determined and compared with the coverage areas of other FAP enclosures to evaluate coverage density. 2. Application of Three-Point Estimation Algorithm: FAPs are automatically selected, and a three-point estimation algorithm (most optimistic, most likely, and most pessimistic values) is used to predict FAP demand and coverage area, providing decision support for FAP site selection and resource allocation. 3. Application of Graph Traversal Algorithm: Intelligent end-to-end resource analysis is achieved, optimizing dynamic routing schemes for service access. Breadth-First Search (BFS) is used to search for paths from potential FAP enclosures to the aggregation room, evaluating optical path resource conditions. 4. End-to-End Resource Evaluation: Access optical path length, hop count, and fiber core resource rules are set. Algorithms are used to evaluate the resource utilization and compliance of each optical path, assessing the optical path resource conditions from potential FAP enclosures to the aggregation room, ensuring the accessibility of the unified bearer point. 5. Dynamic Routing Decision: Based on service requirements, automatically output optimal and suboptimal access optical path routing schemes. Combining the FAP optical path information database and service access point location information, automatically select FAP access points within the terminal mesh and generate the routing scheme with the shortest optical path reachability.

[0158] This disclosure integrates the aforementioned algorithms into the modeled sand table support system, forming a complete solution to achieve scientific planning of FAPs and intelligent end-to-end resource analysis in optical fiber networks. Specifically, it highlights the application of the Voronoi diagram algorithm in FAP coverage assessment, and the use of three-point estimation and traversal algorithms in resource assessment and routing decisions.

[0159] The specific implementation and technical effects of each step in this embodiment are similar to those of the above method embodiments, and will not be repeated here.

[0160] Based on the same inventive concept, embodiments of this disclosure also provide a network service management device. For example... Figure 5 As shown, the network service management device 500 includes:

[0161] The region division module 510 is used to divide the terminal grid into different region types based on the latitude and longitude layer divided by the terminal grid and in combination with the terminal grid data; wherein, the terminal grid data includes at least one of the following: terminal grid information, optical distribution box information, ODB box information, relationship between terminal network and optical distribution box, and relationship between terminal network and ODB box; each region type corresponds to a FAP box coverage radius range;

[0162] The polygon partitioning module 520 is used to perform Thiessen polygon algorithm partitioning on the potential FAP boxes in the end grid to obtain the potential coverage area of ​​each potential FAP box.

[0163] The enclosure setting module 530 is used to set FAP enclosures within the end grid according to the potential coverage range corresponding to each potential FAP enclosure and the set coverage range of each potential FAP enclosure; wherein, the set coverage range is determined based on the FAP enclosure coverage radius range corresponding to each area type;

[0164] The optical path module 540 is used to determine the optical path information from each FAP enclosure to the aggregation room according to the preset optical path rules through a graph traversal algorithm, and to obtain the optical path information set from the FAP enclosure to the aggregation room.

[0165] The optical path selection module 550 is used to select target optical path information from the optical path information set from the FAP cabinet to the aggregation room according to the service requirements of the access service.

[0166] In one possible implementation, the polygon division module 520 includes:

[0167] The selection unit is used to select the cabinets with uplink optical path resources within the terminal grid as potential FAP cabinets;

[0168] Abstraction unit, used to abstract each potential FAP box as an object point on a plane;

[0169] A polygon partitioning unit is used to partition each potential FAP box into a Thiessen polygon based on the object point corresponding to each potential FAP box using the Thiessen polygon algorithm; wherein, the Thiessen polygon corresponding to each potential FAP box is used to indicate the potential coverage area of ​​each potential FAP box.

[0170] In one possible implementation, the housing mounting module 530 is used for:

[0171] Determine the designated FAP enclosure coverage radius range corresponding to the area type where each potential FAP enclosure is located;

[0172] Based on the set FAP cabinet coverage radius range corresponding to each potential FAP cabinet, calculate the set coverage range of each potential FAP cabinet;

[0173] Based on the potential coverage area corresponding to each potential FAP box and the set coverage area of ​​each potential FAP box, the FAP coverage situation within the terminal grid is determined;

[0174] Based on the FAP coverage within the terminal grid, FAP enclosures are installed within the terminal grid.

[0175] In one possible implementation, the optical path module 540 is used for:

[0176] According to the region type of the end grid where the FAP cabinet is located, the optical path length range from the FAP cabinet to the aggregation room is set; each region type corresponds to one optical path length range;

[0177] Set the maximum allowed number of hops in the optical path and fiber core resource rules; wherein, the fiber core resource rules include the number of idle fiber core resources in the entire optical path being greater than or equal to a preset number;

[0178] The optical path length range corresponding to each region type, the maximum allowable number of hops in the optical path, and the fiber core resource rules are determined as preset optical path rules;

[0179] For relay segments between facility IDs and between facility IDs and aggregation site IDs, if the number of relay segments is less than 3, the average distance of the relay segments shall be taken as the relay segment length.

[0180] If the number of relay segments is greater than or equal to 3, the relay segment length is calculated using a three-point estimation algorithm.

[0181] Based on the relay segment length, a node that satisfies the preset optical path rules is selected as the aggregation site node using a graph traversal algorithm.

[0182] Based on the aggregation site node, optical path information from each FAP box in each terminal grid to the aggregation room is generated, resulting in a set of optical path information from the FAP box to the aggregation room.

[0183] In one possible implementation, the network service management device 500 further includes at least one of the following:

[0184] The sorting module is used to normalize and weight the data based on the optical path distance from each FAP box to the aggregation room, fiber core resources, and hop count data, and obtain the optical path priority sorting table corresponding to the end grid.

[0185] The optical path information database module is used to obtain a potential FAP optical path information database and an optical path early warning information database to be optimized based on whether the optical path distance from each FAP enclosure to the aggregation room, fiber core resources, and hop count data meet the preset optical path rules.

[0186] In one possible implementation, the optical path selection module 550 is used for:

[0187] Based on the location information of the access service, calculate the end grid to which the service point of the access service belongs;

[0188] Based on the regional attributes of the terminal grid, select the FAP enclosure access point and aggregation room within the terminal grid;

[0189] Based on the FAP enclosure access point and the aggregation room, the target optical path information is selected from the optical path information set from the FAP enclosure to the aggregation room.

[0190] The specific implementation and technical effects of the device provided in this disclosure are similar to those of the method embodiments described above, and will not be repeated here.

[0191] According to embodiments of the present disclosure, the present disclosure also discloses an electronic device, a computer-readable storage medium, and a computer program product.

[0192] Figure 6 A schematic block diagram of an example electronic device 600 that can be used to implement embodiments of the present disclosure is shown. The electronic device 600 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device may also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0193] like Figure 6 As shown, the electronic device 600 includes a computing unit 601, which can perform various appropriate actions and processes based on a computer program stored in a read-only memory (ROM) 602 or a computer program loaded from a storage unit 608 into a random access memory (RAM) 603. The RAM 603 may also store various programs and data required for the operation of the device 600. The computing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0194] Multiple components in electronic device 600 are connected to I / O interface 605, including: input unit 606, such as keyboard, mouse, etc.; output unit 607, such as various types of displays, speakers, etc.; storage unit 608, such as disk, optical disk, etc.; and communication unit 609, such as network card, modem, wireless transceiver, etc. Communication unit 609 allows electronic device 600 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0195] The computing unit 601 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 601 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the various methods and processes described above, such as network service management methods. For example, in some embodiments, the network service management method may be implemented as a computer software program tangibly contained in a machine-readable medium, such as storage unit 608. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 600 via ROM 602 and / or communication unit 609. When the computer program is loaded into RAM 603 and executed by the computing unit 601, one or more steps of the network service management method described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform network service management methods by any other suitable means (e.g., by means of firmware).

[0196] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0197] The program code of a computer program product used to implement the methods of this disclosure may be written in any combination of one or more programming languages. This program code may be provided to a processor or controller of a general-purpose computer, special-purpose computer, or other programmable data processing apparatus, such that when executed by the processor or controller, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0198] In the context of this disclosure, a computer-readable storage medium can be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium can be a machine-readable signal medium or a machine-readable storage medium. A computer-readable storage medium can be, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of computer-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0199] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor); and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0200] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or middleware components (e.g., application servers), or frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), the Internet, and blockchain networks.

[0201] Computer systems can include clients and servers. Clients and servers are generally geographically separated and typically interact via communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. A server can be a cloud server, also known as a cloud computing server or cloud host, a hosting product within the cloud computing service ecosystem, addressing the shortcomings of traditional physical hosts and VPS (Virtual Private Server, or simply "VPS") services, such as high management difficulty and weak business scalability. Servers can also be servers for distributed systems or servers incorporating blockchain technology.

[0202] It should be understood that the various forms of processes shown above can be used to rearrange, add, or delete steps. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution disclosed in this disclosure can be achieved, and this is not limited herein.

[0203] The specific embodiments described above do not constitute a limitation on the scope of protection of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this disclosure should be included within the scope of protection of this disclosure.

Claims

1. A network service management method, characterized in that, include: Based on the latitude and longitude layers divided by the terminal grid, and combined with the terminal grid data, the terminal grid is divided into different region types; wherein, the terminal grid data includes at least one of the following: terminal grid information, optical distribution box information, ODB box information, relationship between terminal network and optical distribution box, and relationship between terminal network and ODB box; each region type corresponds to a FAP box coverage radius range; The potential FAP boxes within the end grid are divided using the Thiessen polygon algorithm to obtain the potential coverage area of ​​each potential FAP box. Based on the potential coverage area corresponding to each potential FAP box and the set coverage area of ​​each potential FAP box, FAP boxes are set within the terminal grid; wherein, the set coverage area is determined based on the coverage radius range of the FAP box corresponding to each area type; The optical path information from each FAP enclosure to the aggregation room is determined by a graph traversal algorithm according to a preset optical path rule, thus obtaining a set of optical path information from the FAP enclosure to the aggregation room. Based on the service requirements of the access service, select the target optical path information from the optical path information set from the FAP cabinet to the aggregation room.

2. The network service management method according to claim 1, characterized in that, The step of performing Thiessen polygon mapping on the potential FAP boxes within the end grid to obtain the potential coverage area of ​​each potential FAP box includes: The cabinets with uplink optical path resources within the terminal grid are selected as potential FAP cabinets; Each potential FAP box is abstracted as an object point on a plane; The Thiessen polygon algorithm is used to divide the potential FAP box into Thiessen polygons based on the object points corresponding to each potential FAP box; wherein, the Thiessen polygons corresponding to each potential FAP box are used to indicate the potential coverage area of ​​each potential FAP box.

3. The network service management method according to claim 2, characterized in that, The step of setting up FAP cabinets within the end grid according to the potential coverage area corresponding to each potential FAP cabinet and the set coverage area of ​​each potential FAP cabinet includes: Determine the designated FAP enclosure coverage radius range corresponding to the area type where each potential FAP enclosure is located; Based on the set FAP cabinet coverage radius range corresponding to each potential FAP cabinet, calculate the set coverage range of each potential FAP cabinet; Based on the potential coverage area corresponding to each potential FAP box and the set coverage area of ​​each potential FAP box, the FAP coverage situation within the terminal grid is determined; Based on the FAP coverage within the terminal grid, FAP enclosures are installed within the terminal grid.

4. The network service management method according to claim 1, characterized in that, The graph traversal algorithm determines the optical path information from each FAP enclosure to the aggregation room according to preset optical path rules, resulting in a set of optical path information from the FAP enclosure to the aggregation room, including: According to the region type of the end grid where the FAP cabinet is located, the optical path length range from the FAP cabinet to the aggregation room is set; each region type corresponds to one optical path length range; Set the maximum allowed number of hops in the optical path and fiber core resource rules; wherein, the fiber core resource rules include the number of idle fiber core resources in the entire optical path being greater than or equal to a preset number; The optical path length range corresponding to each region type, the maximum allowable number of hops in the optical path, and the fiber core resource rules are determined as preset optical path rules; For relay segments between facility IDs and between facility IDs and aggregation site IDs, if the number of relay segments is less than 3, the average distance of the relay segments shall be taken as the relay segment length. If the number of relay segments is greater than or equal to 3, the relay segment length is calculated using a three-point estimation algorithm. Based on the relay segment length, a node that satisfies the preset optical path rules is selected as the aggregation site node using a graph traversal algorithm. Based on the aggregation site node, optical path information from each FAP box in each terminal grid to the aggregation room is generated, resulting in a set of optical path information from the FAP box to the aggregation room.

5. The network service management method according to claim 4, characterized in that, After determining the optical path information from each FAP enclosure to the aggregation room using the graph traversal algorithm according to preset optical path rules, and obtaining the set of optical path information from the FAP enclosure to the aggregation room, the algorithm further includes at least one of the following: Based on the optical path distance from each FAP enclosure to the aggregation room, fiber core resources, and hop count, the data is normalized and weighted to obtain the optical path priority sorting table corresponding to the end grid. Based on whether the optical path distance from each FAP enclosure to the aggregation room, fiber core resources, and hop count data meet the preset optical path rules, a potential FAP optical path information database and an optical path early warning information database to be optimized are obtained.

6. The network service management method according to claim 1, characterized in that, The step of selecting target optical path information from the optical path information set from the FAP cabinet to the aggregation room according to the service requirements of the access service includes: Based on the location information of the access service, calculate the end grid to which the service point of the access service belongs; Based on the regional attributes of the terminal grid, select the FAP enclosure access point and aggregation room within the terminal grid; Based on the FAP enclosure access point and the aggregation room, the target optical path information is selected from the optical path information set from the FAP enclosure to the aggregation room.

7. A network service management device, characterized in that, include: The region division module is used to divide the terminal grid into different region types based on the latitude and longitude layer of the terminal grid and in combination with the terminal grid data; wherein, the terminal grid data includes at least one of the following: terminal grid information, optical distribution box information, ODB box information, relationship between terminal network and optical distribution box, and relationship between terminal network and ODB box; each region type corresponds to a FAP box coverage radius range; The polygon partitioning module is used to perform Thiessen polygon algorithm partitioning on the potential FAP boxes within the end grid to obtain the potential coverage area of ​​each potential FAP box. The enclosure setting module is used to set FAP enclosures within the end grid according to the potential coverage range corresponding to each potential FAP enclosure and the set coverage range of each potential FAP enclosure; wherein, the set coverage range is determined based on the FAP enclosure coverage radius range corresponding to each area type; The optical path module is used to determine the optical path information from each FAP enclosure to the aggregation room according to a preset optical path rule through a graph traversal algorithm, thereby obtaining a set of optical path information from the FAP enclosure to the aggregation room. The optical path selection module is used to select the target optical path information from the optical path information set from the FAP cabinet to the aggregation room according to the service requirements of the access service.

8. An electronic device, characterized in that, include: processor; Memory used to store the processor's executable instructions; The processor is configured to execute the instructions to implement the network service management method as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the network service management method according to any one of claims 1-6.

10. A computer program product comprising a computer program / instructions, characterized in that, When the computer program / instructions are executed by the processor, they implement the network service management method according to any one of claims 1-6.

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