Convergence ring construction method and device, electronic equipment and storage medium

Abstract

The invention provides a convergence ring construction method and device, electronic equipment and a storage medium, and relates to the technical field of metro optical transport network planning. The method comprises the following steps: acquiring a path length matrix corresponding to all core machine rooms and all convergence machine rooms in the metro optical transport network; constructing a full-connection network topological structure corresponding to all the core machine rooms according to the path length matrix; performing clustering processing on all the convergence machine rooms according to the path length matrix and predetermined administrative region information to generate a plurality of corresponding target clusters; and constructing a corresponding target convergence ring according to the path length matrix and all the target clusters, and uploading the target convergence ring to a corresponding core machine room based on the full-connection network topology structure and the path length matrix. According to the method, the difference between a planning result and actual deployment is reduced, and meanwhile, the convergence ring construction effect is also improved.

Description

Technical Field

[0001] This application belongs to the field of metropolitan area optical transport network planning technology, specifically relating to a convergence ring construction method, device, electronic equipment and storage medium. Background Technology

[0002] In the context of the rapid development of today's information society, the Metropolitan Area Optical Transport Network (MAN) serves as an important bridge connecting the core network and the access network, carrying a large number of data transmission and service scheduling tasks.

[0003] The topology design of the aggregation layer network directly affects the transmission efficiency, reliability, and operation and maintenance costs of the entire network. In traditional optical transport network planning, the aggregation layer often adopts a ring topology, connecting several aggregation nodes (equipment rooms) into a ring via optical cables, and then connecting them to one or more core nodes. A well-designed aggregation ring can effectively improve the network's fault tolerance and link redundancy.

[0004] Currently, the mainstream method for constructing convergence rings mainly relies on manual planning and configuration. The specific process often depends on the experience of network engineers and existing deployment examples, which leads to a significant difference between the planning results and the actual deployment, requiring further optimization. Summary of the Invention

[0005] The technical problem to be solved by this application is to address the above-mentioned shortcomings of the existing technology by providing a convergence ring construction method, apparatus, electronic device and storage medium. Using the convergence ring construction method, the difference between the planning results and the actual deployment can be reduced, and the convergence ring construction effect can be improved.

[0006] In a first aspect, embodiments of this application provide a method for constructing a convergence ring, including: Obtain a path length matrix corresponding to all core equipment rooms and all aggregation equipment rooms in the metropolitan optical transport network; the path length matrix is ​​used to represent the actual point-to-point path distance between each core equipment room, between each core equipment room and each aggregation equipment room, and between each aggregation equipment room; Construct a fully connected network topology corresponding to all core data centers based on the path length matrix; Based on the path length matrix and predetermined administrative region information, all aggregation computer rooms are clustered to generate multiple target clusters; the target clusters correspond to the administrative region information. Construct corresponding target aggregation rings based on the path length matrix and all target clusters, and connect the target aggregation rings to the corresponding core data centers based on the fully connected network topology and path length matrix; wherein, the target aggregation rings correspond one-to-one with the target clusters.

[0007] In some implementations of the first aspect, obtaining a path length matrix corresponding to all core equipment rooms and all aggregation equipment rooms in the metropolitan optical transport network includes: Obtain the first latitude and longitude coordinates of all core equipment rooms and the second latitude and longitude coordinates of all aggregation equipment rooms in the metropolitan optical transport network; Determine the path length matrix based on all first latitude and longitude coordinates and all second latitude and longitude coordinates.

[0008] In some implementations of the first aspect, obtaining the first latitude and longitude coordinates of all core equipment rooms and the second latitude and longitude coordinates of all aggregation equipment rooms in the metropolitan area optical transport network includes: Obtain the first address information of all core computer rooms and the second address information of all aggregation computer rooms in the metropolitan optical transport network; The first address information is converted into first latitude and longitude coordinates using the geocoding service of the preset map software; The second address information is converted into second latitude and longitude coordinates using the geocoding service of the preset map software.

[0009] In some embodiments of the first aspect, determining the path length matrix based on all first latitude and longitude coordinates and all second latitude and longitude coordinates includes: The path planning interface of the preset map software is called, and the first point-to-point actual path distance is calculated based on all first latitude and longitude coordinates and all second latitude and longitude coordinates. The first point-to-point actual path distance includes: the point-to-point actual path distance between each core computer room, the point-to-point actual path distance between each core computer room and each aggregation computer room, and the point-to-point actual path distance between each aggregation computer room. Generate a path length matrix based on the actual path distance between the first point and the second point.

[0010] In some implementations of the first aspect, all aggregation data centers are clustered based on the path length matrix and predetermined administrative region information to generate multiple target clusters, including: Based on administrative region information, all aggregation data centers are initially clustered to form corresponding primary clusters; each primary cluster corresponds to one administrative region. Based on the K-means clustering algorithm and the path length matrix, all aggregation data centers in all primary clusters are further clustered to generate multiple target clusters.

[0011] In some implementations of the first aspect, a corresponding target convergence ring is constructed based on the path length matrix and all target clusters, including: For each target cluster, the following processing is performed: Extract the corresponding target path distance from the path length matrix based on the current target cluster; the target path distance is the actual point-to-point path distance between each aggregation room in the current target cluster; Based on the distance between the aggregation room and the target path in the current target cluster, the Traveling Salesman Problem (TSP) is modeled, and a TSP model is generated. The TSP model is solved using heuristic or metaheuristic algorithms to generate the target convergence ring corresponding to the current target cluster.

[0012] In some implementations of the first aspect, the target aggregation ring is connected uplinked to the corresponding core data center based on the fully connected network topology and path length matrix, including: The second point-to-point actual path distance between the target aggregation room and all core data centers in the target aggregation ring is determined from the path length matrix; the target aggregation room is either the aggregation room located at the center or the aggregation room located at the edge of the target aggregation ring. Select the two core computer rooms with the smallest actual point-to-point path distance as the primary and backup uplink exits; Based on the fully connected network topology, the target aggregation ring is connected to the two core data centers with the smallest actual point-to-point path distance.

[0013] Based on the same inventive concept, in a second aspect, embodiments of this application also provide a convergence ring construction apparatus, comprising: The acquisition module is used to acquire a path length matrix corresponding to all core equipment rooms and all aggregation equipment rooms in the metropolitan optical transport network. The path length matrix is ​​used to represent the actual point-to-point path distance between each core equipment room, between each core equipment room and each aggregation equipment room, and between each aggregation equipment room. The first construction module is used to construct the full-connectivity network topology corresponding to all core data centers based on the path length matrix. The clustering module is used to cluster all aggregation computer rooms based on the path length matrix and pre-determined administrative region information, generating multiple target clusters; the target clusters correspond to the administrative region information. The second construction module is used to construct the corresponding target aggregation ring based on the path length matrix and all target clusters, and connect the target aggregation ring to the corresponding core data center based on the fully connected network topology and the path length matrix; wherein, the target aggregation ring corresponds one-to-one with the target cluster.

[0014] In some embodiments of the second aspect, the acquisition module is specifically used for: Obtain the first latitude and longitude coordinates of all core equipment rooms and the second latitude and longitude coordinates of all aggregation equipment rooms in the metropolitan optical transport network; determine the path length matrix based on all the first latitude and longitude coordinates and all the second latitude and longitude coordinates.

[0015] In some implementations of the second aspect, when the acquisition module acquires the first latitude and longitude coordinates of all core equipment rooms and the second latitude and longitude coordinates of all aggregation equipment rooms in the metropolitan area optical transport network, it is specifically used for: Obtain the first address information of all core equipment rooms and the second address information of all aggregation equipment rooms in the metropolitan optical transport network; convert the first address information into first latitude and longitude coordinates through the geocoding service of the preset map software; convert the second address information into second latitude and longitude coordinates through the geocoding service of the preset map software.

[0016] In some embodiments of the second aspect, when determining the path length matrix based on all first latitude and longitude coordinates and all second latitude and longitude coordinates, the acquisition module is specifically used for: The path planning interface of the preset map software is called, and the first point-to-point actual path distance is calculated based on all first latitude and longitude coordinates and all second latitude and longitude coordinates. The first point-to-point actual path distance includes: the point-to-point actual path distance between each core computer room, the point-to-point actual path distance between each core computer room and each aggregation computer room, and the point-to-point actual path distance between each aggregation computer room. A path length matrix is ​​generated based on the first point-to-point actual path distance.

[0017] In some implementations of the second aspect, the clustering module is specifically used for: Based on administrative region information, all aggregation data centers are initially clustered to form corresponding primary clusters; each primary cluster corresponds to an administrative region; based on the K-means clustering algorithm and path length matrix, all aggregation data centers in all primary clusters are further clustered to generate multiple target clusters.

[0018] In some implementations of the second aspect, when constructing the corresponding target convergence ring based on the path length matrix and all target clusters, the second construction module is specifically used for: For each target cluster, the following processing is performed: Extract the corresponding target path distance from the path length matrix based on the current target cluster; the target path distance is the actual point-to-point path distance between each aggregation room in the current target cluster; perform Traveling Salesman Problem (TSP) modeling based on the aggregation rooms and target path distances in the current target cluster to generate a TSP model; solve the TSP model using a heuristic algorithm or metaheuristic algorithm to generate the target aggregation ring corresponding to the current target cluster.

[0019] In some implementations of the second aspect, when the second building module connects the target aggregation ring to the corresponding core data center based on the fully connected network topology and path length matrix, it is specifically used for: The second point-to-point actual path distance between the target aggregation room and all core rooms in the target aggregation ring is determined from the path length matrix; the target aggregation room is either the aggregation room located at the center or the aggregation room located at the edge of the target aggregation ring; the two core rooms with the smallest second point-to-point actual path distance are selected as the primary uplink exit and the backup uplink exit; based on the fully connected network topology, the target aggregation ring is connected to the two core rooms with the smallest second point-to-point actual path distance.

[0020] Based on the same inventive concept, in a third aspect, embodiments of this application also provide an electronic device, including: a memory and a processor; The memory stores instructions that the computer executes; The processor executes computer-executable instructions stored in memory to implement a convergence ring construction method as described in any of the first aspects.

[0021] Based on the same inventive concept, in a fourth aspect, embodiments of this application also provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the convergence ring construction method as described in any of the first aspects.

[0022] According to the aggregation ring construction method, apparatus, electronic device, and storage medium provided in this application, a path length matrix corresponding to all core equipment rooms and all aggregation equipment rooms in a metropolitan optical transport network is obtained. A fully connected network topology corresponding to all core equipment rooms is constructed based on the path length matrix. Simultaneously, all aggregation equipment rooms are clustered based on the path length matrix and pre-determined administrative region information, generating multiple corresponding target clusters. A corresponding target aggregation ring is constructed based on the path length matrix and all target clusters, and the target aggregation ring is connected to the corresponding core equipment room based on the fully connected network topology and the path length matrix. Therefore, the target aggregation ring can be constructed based on the actual point-to-point path distances and corresponding administrative region information of all core equipment rooms and all aggregation equipment rooms, reducing the difference between the planning results and the actual deployment, and improving the aggregation ring construction effect. Attached Figure Description

[0023] Figure 1 This illustration shows a flowchart of a convergence ring construction method provided in an embodiment of this application; Figure 2 This illustration shows another flowchart of the convergence ring construction method provided in an embodiment of this application; Figure 3 This illustration shows another flowchart of the convergence ring construction method provided in an embodiment of this application; Figure 4 This illustration shows a schematic diagram of a system functional module provided in an embodiment of this application; Figure 5This is a schematic diagram of the structure of the convergence ring construction device provided in an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the technical solutions of this application, the application will be further described in detail below with reference to the accompanying drawings and embodiments.

[0025] The features and exemplary embodiments of various aspects of this application will now be described in detail. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only configured to explain this application and are not configured to limit this application. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples of this application.

[0026] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes the element.

[0027] As described in the background section, the current mainstream method for constructing convergence rings is mainly based on manual planning and configuration. The specific process often relies on the experience of network engineers and existing deployment examples, which leads to a significant difference between the planning results and the actual deployment, requiring further optimization.

[0028] Example 1

[0029] The convergence ring construction method provided in this application is applied to an electronic device. This electronic device can be a computer, or a device within a computer used to implement the convergence ring construction method; this application does not specifically limit this. The following description uses the example of the convergence ring construction method being executed by an electronic device.

[0030] like Figure 1 As shown, the convergence ring construction method provided in this application embodiment may include steps S101 to S104.

[0031] S101. Obtain a path length matrix corresponding to all core equipment rooms and all aggregation equipment rooms in the metropolitan optical transport network. The path length matrix is ​​used to represent the actual point-to-point path distance between core equipment rooms, between core equipment rooms and aggregation equipment rooms, and between aggregation equipment rooms.

[0032] For example, a core data center can also be called a core node, which is the core hub node in a communication network. An aggregation data center can also be called an aggregation node, which is an intermediate layer node in the layered architecture of a communication network.

[0033] Point-to-point actual path distance is used to characterize the actual path distance between nodes, rather than the straight-line distance or Euclidean distance. Point-to-point actual path distance can be used in network planning to calculate fiber optic cable laying lengths.

[0034] By determining the path length matrix, we can obtain the actual point-to-point path distances between core data centers, between core data centers and aggregation data centers, and between aggregation data centers, thus providing a foundation for building an aggregation ring that better matches the actual deployment.

[0035] S102. Construct a fully connected network topology corresponding to all core computer rooms based on the path length matrix.

[0036] For example, in a full-mesh topology, each core data center has at least a direct connection path to all other core data centers, building an absolutely reliable, ultra-low latency backbone switching plane for the core layer, thus providing a foundation for subsequent aggregation rings to directly connect to core data centers.

[0037] During construction, the actual point-to-point path distance between core data centers can be extracted from the path length matrix, and then the full-connectivity network topology can be constructed based on the actual point-to-point path distance between core data centers.

[0038] S103. Based on the path length matrix and the predetermined administrative region information, cluster all aggregation computer rooms to generate multiple corresponding target clusters. The target clusters correspond to the administrative region information.

[0039] For example, administrative region information can be determined based on actual application, and the corresponding administrative region information may differ in different regions.

[0040] The aggregation data center may correspond to administrative region a and administrative region b. Therefore, clustering can be performed according to administrative regions a and b to obtain multiple primary clusters. At the same time, each primary cluster can be further clustered to obtain the target cluster.

[0041] S104. Construct corresponding target aggregation rings based on the path length matrix and all target clusters, and connect the target aggregation rings to the corresponding core data centers based on the fully connected network topology and path length matrix. Each target aggregation ring corresponds one-to-one with a target cluster.

[0042] For example, a target aggregation ring can be constructed based on the distance between the aggregation data centers within a target cluster. For instance, the three or four closest aggregation data centers can be constructed as a single target aggregation ring. When the target aggregation ring connects to the corresponding core data center, a core data center with short distances and low likelihood of simultaneous failures can be selected based on the fully connected network topology and path length matrix, thereby improving disaster recovery capabilities.

[0043] According to the aggregation ring construction method provided in this application, a path length matrix corresponding to all core equipment rooms and all aggregation equipment rooms in the metropolitan optical transport network is obtained. A fully connected network topology corresponding to all core equipment rooms is constructed based on the path length matrix. Simultaneously, all aggregation equipment rooms are clustered based on the path length matrix and pre-determined administrative region information, generating multiple corresponding target clusters. A corresponding target aggregation ring is constructed based on the path length matrix and all target clusters, and the target aggregation ring is connected uplinked to the corresponding core equipment room based on the fully connected network topology and the path length matrix. This allows the target aggregation ring to be constructed based on the actual point-to-point path distances and corresponding administrative region information of all core equipment rooms and all aggregation equipment rooms, reducing the discrepancy between the planning results and the actual deployment, and improving the aggregation ring construction effect.

[0044] Example 2

[0045] like Figure 2 As shown, the convergence ring construction method provided in this application embodiment is based on the convergence ring construction method provided in embodiment 1 of this application, and further describes the method, which may include steps S201 to S206.

[0046] S201. Obtain the first latitude and longitude coordinates of all core equipment rooms and the second latitude and longitude coordinates of all aggregation equipment rooms in the metropolitan optical transport network.

[0047] For example, the first and second latitude and longitude coordinates can be obtained using map software.

[0048] In some implementations, S201 may be specifically as follows: Obtain the first address information of all core computer rooms and the second address information of all aggregation computer rooms in the metropolitan optical transport network.

[0049] The first address information is converted into first latitude and longitude coordinates using the geocoding service of the preset map software.

[0050] The second address information is converted into second latitude and longitude coordinates using the geocoding service of the preset map software.

[0051] For example, address information may include administrative region, street, and other information.

[0052] For example, the preset map software can be a commonly used map software that can convert the address information of the computer room into corresponding latitude and longitude coordinates. By calling the geocoding service of the preset map software to convert the first address information into first latitude and longitude coordinates and the second address information into second latitude and longitude coordinates, more accurate latitude and longitude coordinates can be obtained, providing a foundation for generating a more accurate path length matrix in the future.

[0053] S202. Determine the path length matrix based on all first latitude and longitude coordinates and all second latitude and longitude coordinates.

[0054] For example, the actual point-to-point path distances between core data centers, between core data centers and aggregation data centers, and between aggregation data centers can be calculated based on the first and second latitude and longitude coordinates. This can be achieved, for instance, through the path planning capabilities of map software.

[0055] In some implementations, S202 may be specifically as follows: The system calls the path planning interface of the preset map software and calculates the first point-to-point actual path distance based on all first latitude and longitude coordinates and all second latitude and longitude coordinates. The first point-to-point actual path distance includes: the point-to-point actual path distance between each core computer room, the point-to-point actual path distance between each core computer room and each aggregation computer room, and the point-to-point actual path distance between each aggregation computer room.

[0056] Generate a path length matrix based on the actual path distance between the first point and the second point.

[0057] For example, through the path planning interface, a path can be generated based on the starting point (such as the first latitude and longitude coordinates) to the ending point (such as the second latitude and longitude coordinates), and the actual point-to-point path distance can be calculated based on the path, thereby improving the accuracy of the actual point-to-point path distance.

[0058] S203. Construct a fully connected network topology corresponding to all core computer rooms based on the path length matrix.

[0059] S204. Based on the administrative region information, all aggregation computer rooms are initially clustered to form corresponding primary clusters. Each primary cluster corresponds to one administrative region.

[0060] For example, the aggregation data center may correspond to administrative region a, administrative region b, and administrative region c. Then, clustering can be performed according to administrative regions a, b, and c to obtain the primary cluster corresponding to administrative region a, the primary cluster corresponding to administrative region b, and the primary cluster corresponding to administrative region c.

[0061] S205. Based on the K-means clustering algorithm and the path length matrix, all aggregation rooms in all primary clusters are further clustered to generate multiple target clusters.

[0062] For example, the K value (target cluster number) of the K-means clustering algorithm can be set according to the number of nodes (data centers) or a path length threshold. The actual point-to-point path distance between each aggregation data center can be extracted from the path length matrix first, and then the K-means clustering algorithm can be used to further cluster based on the actual point-to-point path distance between each aggregation data center, thereby generating multiple target clusters.

[0063] S206. Construct the corresponding target aggregation ring based on the path length matrix and all target clusters, and connect the target aggregation ring to the corresponding core computer room based on the fully connected network topology and path length matrix.

[0064] In some implementations, the process of constructing the corresponding target convergence ring based on the path length matrix and all target clusters in step S206 can be specifically as follows: For each target cluster, the following processing is performed: Extract the corresponding target path distance from the path length matrix based on the current target cluster. The target path distance is the actual point-to-point path distance between each aggregation room in the current target cluster.

[0065] The Traveling Salesman Problem (TSP) is modeled based on the distance between the aggregation data center and the target path in the current target cluster, generating a TSP model.

[0066] The TSP model is solved using heuristic or metaheuristic algorithms to generate the target convergence ring corresponding to the current target cluster.

[0067] For example, the current target cluster refers to the cluster in which TSP modeling, solving, and generating the corresponding target convergence ring are currently performed. After the above steps have been performed on all target clusters, the subsequent uplink process can be executed.

[0068] For example, the aggregation room (node) of each target cluster can be considered as a city point in the Traveling Salesman Problem (TSP), with the path length matrix representing the path weights. The goal is to find a closed loop that traverses all aggregation nodes with the shortest path. Constraints may include: the loop length does not exceed a set maximum value; the number of nodes cannot exceed the ring capacity limit.

[0069] Heuristic or metaheuristic algorithms can be employed, such as Genetic Algorithm (GA), Ant Colony Optimization (ACO), and 2-opt optimization. After solving the problem using heuristic or metaheuristic algorithms, the loop path planning (closed-loop sequence + actual line length) for each cluster's aggregation room can be obtained, thereby constructing the target aggregation loop corresponding to the current target cluster.

[0070] In some implementations, the process of connecting the target aggregation ring to the corresponding core data center based on the fully connected network topology and path length matrix in S206 can be specifically as follows: The second point-to-point actual path distance between the target aggregation room and all core data centers in the target aggregation ring is determined from the path length matrix. The target aggregation room is either the aggregation room located at the center or the edge of the target aggregation ring.

[0071] The two core data centers with the smallest actual point-to-point path distance were selected as the primary and backup uplink exits.

[0072] Based on the fully connected network topology, the target aggregation ring is connected to the two core data centers with the smallest actual point-to-point path distance.

[0073] For example, multiple aggregation data centers located at the edge can be selected, such as two. The second point-to-point actual path distance of the core data center for the primary uplink exit can be the smallest, and the second point-to-point actual path distance of the core data center for the backup uplink exit can be the second smallest.

[0074] By implementing dual uplinks for physical lines or logical links, link redundancy can be ensured and disaster recovery capabilities can be improved.

[0075] When connecting the target aggregation ring to the two core data centers with the smallest actual point-to-point path distance based on the fully connected network topology, two core data centers that will not fail simultaneously can be selected to further improve disaster recovery capabilities.

[0076] The convergence ring construction method in this embodiment is based on a convergence node partitioning mechanism using geographic coordinates and administrative region information. By combining geographic information with administrative region information, it guides the initial partitioning of convergence nodes. Using administrative regions as the basic unit for partitioning avoids the management complexity and construction obstacles caused by cross-regional ring formation, improving the operability and regional independence of network deployment. This mechanism differs from existing partitioning methods based solely on latitude and longitude coordinates or distance, possessing clear engineering adaptability and management convenience.

[0077] Simultaneously, the K-means clustering algorithm is introduced to divide the convergence nodes within each administrative region into multiple clusters. By further clustering multiple convergence nodes within the same region using K-means clustering, the number of nodes in each cluster is reasonable and the spatial distribution is compact, which is conducive to forming well-structured small convergence loops. This clustering process uses node coordinates as input and combines intra-cluster path constraints, significantly improving the feasibility of loop formation and the optimization space of loop paths.

[0078] Secondly, the intra-cluster cycle formation problem is modeled as the Traveling Salesman Problem (TSP), and a combinatorial optimization algorithm is used to solve it. This embodiment innovatively models intra-cluster convergence node cycle formation as a TSP problem, aiming to find the cycle formation sequence with the shortest closed path length while covering all nodes. Furthermore, combined with specific network requirements, combinatorial optimization strategies such as genetic algorithms, ant colony algorithms, or simulated annealing are introduced to significantly improve the quality and efficiency of cycle formation paths.

[0079] Furthermore, the automated design of the entire process supports rapid planning or reconstruction of large-scale converged networks. This embodiment of the method, while achieving path optimization, emphasizes the automated processing of the entire process, including coordinate acquisition, distance calculation, node clustering, path optimization, and uplink planning. It possesses good scalability and adaptability and can be applied to planning or reconstruction projects of large-scale metropolitan area networks.

[0080] To better understand the convergence ring construction method provided in this application embodiment, an exemplary description is given below in conjunction with a specific application implementation.

[0081] like Figure 3 As shown, the steps of the convergence ring construction method in this embodiment include: S301: Obtain the geographical coordinates of the data center. Objective: To provide foundational data for subsequent path calculation and topology construction. Operation: Collect address information of core and aggregation data centers in the metropolitan area optical transport network. Convert the addresses to latitude and longitude coordinates using geocoding services (Geocoding Application Programming Interface, Geocoding API), such as various maps.

[0082] S302: Calculate point-to-point trunk route distances. Objective: To obtain real-world route distances (not Euclidean straight-line distances) to improve the practical feasibility of network deployment. Operation: Using the Route API (Application Programming Interface), calculate the point-to-point trunk route distances between the following: core data centers, between core data centers and aggregation data centers, and between aggregation data centers. The results are stored as a path length matrix, providing input for subsequent algorithms.

[0083] S303: Construct a Full-Mesh Topology for the Core Data Center. Objective: The core layer should possess high reliability and multi-path backup capabilities. Operation: Based on the distance matrix obtained in the previous step, construct a fully connected network (Full-Mesh) topology in the core data center. Each core node must have at least one direct path to all other core nodes. A graph structure can be used for storage, with path weights (distances) labeled.

[0084] S304: Divide the aggregation equipment rooms into administrative regions. Objective: Reduce cross-regional communication and improve the geographical consistency and management convenience of the network. Operation: Use administrative region information to perform preliminary clustering of the aggregation equipment rooms. Each administrative region serves as a partitioning unit, forming a primary cluster.

[0085] S305: Use the K-Means algorithm to further cluster the aggregation rooms within each administrative region. Objective: To distribute a large number of aggregation rooms rationally across multiple physical ring-forming units. Operation: For the aggregation room set in each administrative region, perform a secondary partitioning using the K-means clustering algorithm. Input is the latitude and longitude of the aggregation rooms within that region; the K value (target number of clusters) can be set based on the number of nodes or a path length threshold. Multiple clusters are obtained, each cluster serving as a subsequent ring-forming unit.

[0086] S306: Model the intra-cluster sink node loop problem as a Traveling Salesman Problem (TSP). Objective: To form a closed loop within each cluster, optimizing fiber optic deployment paths. Operation: Treat the sink nodes of each cluster as city points in the TSP. The distance matrix represents the path weights. The objective is to find a closed loop that traverses all sink nodes with the shortest path. Constraints may include: the loop length does not exceed a set maximum value; the number of nodes cannot exceed the ring capacity limit.

[0087] S307: Solving the TSP using a combinatorial optimization algorithm. Objective: To efficiently find the near-optimal closed-loop path. Operation: Use heuristic or metaheuristic algorithms, such as genetic algorithms, ant colony optimization, and 2-opt optimization. Obtain the loop path plan (closed-loop order + actual path length) for each cluster's sink node.

[0088] S308: The aggregation ring connects to the two nearest core data centers. Objective: Ensure the aggregation ring has redundant uplink paths to improve disaster recovery capabilities. Operation: For each ring cluster's central node or any two edge nodes, calculate its distance to all core data centers. Select the two nearest core data centers as primary / backup uplink exits. Implement dual uplinks (physical or logical) to ensure link redundancy.

[0089] The steps at the methodological level described above can be further encapsulated into an automated and digital system, such as... Figure 4 As shown, the system comprises five functional modules, which are further divided into three parts: computing, storage, and interface. The arrows in each part indicate the collaborative relationships between the different functional modules: Module 1: Geographic Data Processing Module. This module is primarily responsible for the system's basic data acquisition and geographic information preprocessing, including the following functionalities: Geographic Coordinate Acquisition: Supports importing latitude and longitude information of the aggregation and core data centers from GIS (Geographic Information System) systems, map APIs, or user input. Path Distance Calculation: Calls map service interfaces to obtain point-to-point road path distances between data centers, rather than simple straight-line distances, to improve the practical feasibility of deployment paths. Data Validation and Coordinate Cleaning: Automatically corrects missing coordinates or offsets and standardizes formats to ensure the accuracy of subsequent algorithm processing. This module is the data entry point for the entire system, and its accuracy directly affects the reliability of subsequent clustering and path planning.

[0090] Module Two: Clustering Module. The clustering module is responsible for initial partitioning and fine-grained clustering of the aggregation nodes based on geographical and administrative information. Its main functions include: Administrative Region Division: Assigning aggregation nodes to different administrative regions based on administrative boundary data to avoid cross-regional loops, which is beneficial for management and maintenance. K-means Clustering: Within each administrative region, the K-means algorithm is further used to cluster the aggregation nodes, ensuring that the nodes within each cluster are spatially concentrated, suitable for loop construction. The number of clusters can be set by the user or dynamically determined by the system based on node density. Cluster Quality Evaluation: Evaluating the clustering effect, such as the average distance within clusters and the maximum radius, provides a reference for subsequent optimization. This module realizes the transformation from the original distribution to structured clustering, which is a prerequisite for loop planning.

[0091] Module 3: Loop Formation Module. The loop formation module is the core optimization engine of this system, responsible for constructing the optimal closed-loop path within each cluster and completing the redundant uplink planning for the convergence ring. It mainly includes: TSP Modeling: Modeling the loop formation problem within each cluster as a Traveling Salesman Problem, defining the objective function as minimizing the total path distance or optimizing hop count control. Combinatorial Optimization Solution: Employing optimization strategies such as genetic algorithms, ant colony algorithms, and simulated annealing to solve for the optimal node access order, achieving efficient closed-loop path generation. Dual Uplink Calculation: Selecting a central node for each cluster, calculating the path distance between it and all core data centers, and selecting the two closest nodes as the primary and backup uplink paths to ensure the reliability and fault recovery capability of the convergence ring. Ring Path Output: Outputting the path sequence, total distance, and connection relationships of each convergence ring in a structured format for subsequent system use. This module introduces intelligent algorithms in path optimization and redundancy design, significantly outperforming traditional manual methods.

[0092] Module Four: Database Module. This module is used for unified storage and management of system data, supporting continuous system use, batch operations, and historical record tracing. It includes: Node and Path Information Database: Stores the geographical attributes, clustering results, and path planning data of aggregation nodes and core nodes. Planning Result Version Control: Supports archiving and comparing planning versions from different times or scenarios, enabling historical tracing and difference analysis. Data Interface Service: Provides a unified API interface, supporting other systems or platforms to call planning results, facilitating integration into upper-layer network management systems. The database module ensures data consistency, scalability, and cross-task reusability during system operation.

[0093] Module Five: Visualization Module. The visualization module provides a graphical representation and interactive control of the entire planning process and results. It is a key interface for users to understand and adjust the design, including: Map Visualization Interface: Dynamically displays the geographical distribution, clustering, and loop structure of convergence nodes and core nodes based on an electronic map. Path Display and Evaluation: Intuitively presents loop paths, connection order, and upstream connections within each cluster. Interactive Adjustment and Recalculation: Allows users to manually adjust parameters such as cluster number and path preferences, with real-time feedback on the adjustment results, supporting planning version comparison and optimization iteration. This module enhances the system's usability and controllability, providing decision-makers with intuitive decision-making basis.

[0094] The following describes the method and system proposed in this embodiment, demonstrating how to plan a 400G (gigabit) optical transmission core and aggregation network based on existing core and aggregation data centers. First, the network is divided according to the geographical coordinates and administrative regions of the core and aggregation data centers, and the distance between any two data centers based on the city's main roads is calculated. Then, in this embodiment, a certain administrative region has 16 aggregation data centers. Based on the aggregation ring networking of the 400G optical transmission network and the service characteristics of a certain administrative region, each aggregation ring connects to 2 core data centers upstream and 2 to 4 aggregation data centers downstream. Therefore, the K value in the K-means algorithm is selected as 5, resulting in 5 clusters.

[0095] Meanwhile, based on the distance and layout of the data centers in the previous step, which is a Transmission Service Provider (TSP) problem, a convergence ring is constructed through combinatorial optimization. Finally, based on the distance between the data centers, two pairs of the closest "core data center - convergence data center" connections are selected for uplink, ultimately presenting the convergence ring network topology of the reconstructed metropolitan area optical transport network.

[0096] The method in this embodiment introduces a clustering partitioning approach oriented towards geographic coordinates and administrative regions, combined with an intra-cluster path optimization mechanism, to achieve automatic clustering and ring planning for large-scale aggregation nodes. Simultaneously, by guiding each aggregation ring to connect to the two shortest-distance core nodes, it effectively improves the network's disaster recovery capabilities and operational stability.

[0097] It is understood that the various method embodiments mentioned above in this application can be combined with each other to form combined embodiments without violating the principle and logic. Due to space limitations, this disclosure will not elaborate further. Those skilled in the art will understand that in the above methods of specific implementation, the specific execution order of each step should be determined by its function and possible internal logic.

[0098] Example 3

[0099] like Figure 5 As shown, the convergence ring construction device 400 provided in this application embodiment is located in an electronic device, and the convergence ring construction device 400 may include: The acquisition module 401 is used to acquire a path length matrix corresponding to all core equipment rooms and all aggregation equipment rooms in the metropolitan optical transport network. The path length matrix is ​​used to represent the actual point-to-point path distance between each core equipment room, between each core equipment room and each aggregation equipment room, and between each aggregation equipment room.

[0100] The first construction module 402 is used to construct a fully connected network topology corresponding to all core computer rooms based on the path length matrix.

[0101] Clustering module 403 is used to cluster all aggregation computer rooms based on the path length matrix and pre-determined administrative region information, generating multiple corresponding target clusters. The target clusters correspond to the administrative region information.

[0102] The second construction module 404 is used to construct the corresponding target aggregation ring based on the path length matrix and all target clusters, and to connect the target aggregation ring to the corresponding core data center based on the fully connected network topology and the path length matrix. Each target aggregation ring corresponds one-to-one with a target cluster.

[0103] In some implementations, the acquisition module 401 is specifically used for: Obtain the first latitude and longitude coordinates of all core equipment rooms and the second latitude and longitude coordinates of all aggregation equipment rooms in the metropolitan optical transport network. Determine the path length matrix based on all the first latitude and longitude coordinates and all the second latitude and longitude coordinates.

[0104] In some implementations, when acquiring the first latitude and longitude coordinates of all core equipment rooms and the second latitude and longitude coordinates of all aggregation equipment rooms in the metropolitan optical transport network, the acquisition module 401 is specifically used for: Obtain the first address information of all core equipment rooms and the second address information of all aggregation equipment rooms in the metropolitan area optical transport network. Convert the first address information into first latitude and longitude coordinates using the geocoding service of the preset map software. Convert the second address information into second latitude and longitude coordinates using the geocoding service of the preset map software.

[0105] In some implementations, when determining the path length matrix based on all first latitude and longitude coordinates and all second latitude and longitude coordinates, the acquisition module 401 is specifically used for: The system calls the path planning interface of a pre-defined map software and calculates the first point-to-point actual path distance based on all first and second latitude and longitude coordinates. The first point-to-point actual path distance includes: the point-to-point actual path distance between core data centers, the point-to-point actual path distance between each core data center and each aggregation data center, and the point-to-point actual path distance between each aggregation data center. A path length matrix is ​​then generated based on the first point-to-point actual path distance.

[0106] In some implementations, clustering module 403 is specifically used for: Based on administrative region information, all aggregation data centers are initially clustered to form corresponding primary clusters. Each primary cluster corresponds to one administrative region. Then, using the K-means clustering algorithm and path length matrix, all aggregation data centers in all primary clusters are further clustered to generate multiple corresponding target clusters.

[0107] In some implementations, when constructing the corresponding target convergence ring based on the path length matrix and all target clusters, the second construction module 404 is specifically used for: For each target cluster, the following processing is performed: The target path distance is extracted from the path length matrix based on the current target cluster. The target path distance is the actual point-to-point path distance between each aggregation room in the current target cluster. A Traveling Salesman Problem (TSP) model is generated based on the aggregation rooms and target path distances in the current target cluster. A heuristic or metaheuristic algorithm is used to solve the TSP model, generating the target aggregation loop corresponding to the current target cluster.

[0108] In some implementations, when the second construction module 404 connects the target aggregation ring to the corresponding core data center based on the fully connected network topology and path length matrix, it is specifically used for: The second point-to-point actual path distance between the target aggregation room and all core rooms in the target aggregation ring is determined from the path length matrix. The target aggregation room is either the aggregation room located at the center or the edge of the target aggregation ring. The two core rooms with the smallest second point-to-point actual path distance are selected as the primary uplink exit and the backup uplink exit. Based on the fully connected network topology, the target aggregation ring is connected uplinked to the two core rooms with the smallest second point-to-point actual path distance.

[0109] The convergence ring construction apparatus provided in this application has the beneficial effects and implementation methods of the convergence ring construction methods provided in Embodiments 1 and 2 of this application. For details, please refer to the specific descriptions of the convergence ring construction methods in Embodiments 1 and 2 above. This embodiment will not repeat them here.

[0110] Example 4

[0111] This application also provides an electronic device, which is intended to be various forms of devices with data processing capabilities, such as servers, convergence ring construction devices, and other suitable devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0112] This electronic device includes a processor and memory. The various components are interconnected via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processor processes instructions that execute within the electronic device.

[0113] The memory is the non-transitory computer-readable storage medium provided in this application. The memory stores instructions executable by at least one processor to cause at least one processor to perform the convergence ring construction method provided in this application. The non-transitory computer-readable storage medium of this application stores computer instructions for causing a computer to perform the convergence ring construction method provided in this application.

[0114] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs, non-transitory computer-executable programs, and modules, such as the program instructions / modules corresponding to the convergence ring construction method in the embodiments of this application. The processor executes various functional applications and data processing of the electronic device by running the non-transitory software programs, instructions, and modules stored in the memory, thereby implementing the convergence ring construction method in the above method embodiments.

[0115] The electronic device provided in this application has the beneficial effects and implementation methods of the convergence ring construction method provided in Embodiments 1 and 2 of this application. For details, please refer to the specific description of the convergence ring construction method in Embodiments 1 and 2 above. This embodiment will not repeat the description here.

[0116] Example 5

[0117] This embodiment also provides a computer-readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it implements the convergence ring construction method in Embodiment 1 or Embodiment 2 above.

[0118] The computer-readable storage medium provided in this application embodiment has the beneficial effects and implementation methods of the convergence ring construction method of embodiment 1 and embodiment 2 of this application. For details, please refer to the specific description of the convergence ring construction method in embodiment 1 and embodiment 2 above. This embodiment will not repeat the description here.

[0119] As is known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information, such as computer-readable program instructions, data structures, program modules, or other data. Computer storage media includes, but is not limited to, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), static random access memory (SRAM), flash memory or other memory technologies, portable compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, it is known to those skilled in the art that communication media typically contain computer-readable program instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0120] The computer-readable program instructions described herein can be downloaded from computer-readable storage media to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network may include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. A network adapter card or network interface in each computing / processing device receives the computer-readable program instructions from the network and forwards them to the computer-readable storage media in the respective computing / processing device.

[0121] It is understood that the above embodiments are merely exemplary implementations used to illustrate the principles of this application, and this application is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and substance of this application, and these modifications and improvements are also considered to be within the scope of protection of this application.

Claims

1. A method for constructing a convergence ring, characterized by, The method comprises the following steps: obtaining a path length matrix corresponding to all core machine rooms and all aggregation machine rooms in a metropolitan optical transport network; the path length matrix is used to represent the point-to-point actual path distance between each core machine room, between each core machine room and each aggregation machine room, and between each aggregation machine room; constructing a full connection network topology corresponding to all core machine rooms according to the path length matrix; performing clustering processing on all aggregation machine rooms according to the path length matrix and predetermined administrative region information to generate a plurality of target clustering clusters corresponding to the target clustering clusters; the target clustering clusters correspond to the administrative region information; constructing a target aggregation ring corresponding to the target clustering clusters according to the path length matrix and all target clustering clusters, and connecting the target aggregation ring to a corresponding core machine room based on the full connection network topology and the path length matrix; the target aggregation ring corresponds to the target clustering cluster one by one.

2. The method of claim 1, wherein, The method for obtaining a path length matrix corresponding to all core machine rooms and all aggregation machine rooms in a metropolitan optical transport network comprises the following steps: obtaining first latitude and longitude coordinates of all core machine rooms and second latitude and longitude coordinates of all aggregation machine rooms in the metropolitan optical transport network; determining a path length matrix according to all first latitude and longitude coordinates and all second latitude and longitude coordinates.

3. The method of claim 2, wherein, The method for obtaining first latitude and longitude coordinates of all core machine rooms and second latitude and longitude coordinates of all aggregation machine rooms in the metropolitan optical transport network comprises the following steps: obtaining first address information of all core machine rooms and second address information of all aggregation machine rooms in the metropolitan optical transport network; converting the first address information into the first latitude and longitude coordinates through a geographic coding service of a preset map software; converting the second address information into the second latitude and longitude coordinates through a geographic coding service of a preset map software.

4. The method of claim 3, wherein, The method for determining a path length matrix according to all first latitude and longitude coordinates and all second latitude and longitude coordinates comprises the following steps: calling a path planning interface of the preset map software, and calculating first point-to-point actual path distances according to all first latitude and longitude coordinates and all second latitude and longitude coordinates; the first point-to-point actual path distances comprise point-to-point actual path distances between each core machine room, between each core machine room and each aggregation machine room, and between each aggregation machine room; generating the path length matrix based on the first point-to-point actual path distances.

5. The method of claim 1, wherein, The method for performing clustering processing on all aggregation machine rooms according to the path length matrix and predetermined administrative region information to generate a plurality of target clustering clusters comprises the following steps: preliminarily clustering and dividing all aggregation machine rooms according to the administrative region information to form corresponding primary clusters; each primary cluster corresponds to an administrative region; performing re-clustering and division on all aggregation machine rooms in all primary clusters according to a K-means clustering algorithm and the path length matrix to generate a plurality of target clustering clusters corresponding to the target clustering clusters.

6. The method of claim 1, wherein, The method for constructing a target aggregation ring corresponding to the target clustering clusters according to the path length matrix and all target clustering clusters comprises the following steps: Processing the following for each target clustering cluster: According to the current target clustering cluster, the corresponding target path distance is extracted from the path length matrix; the target path distance is the point-to-point actual path distance between each convergence machine room in the current target clustering cluster; According to the convergence machine room in the current target clustering cluster and the target path distance, the traveling salesman problem TSP is modeled, and the TSP model is generated; The heuristic algorithm or meta-heuristic algorithm is used to solve the TSP model, and the target convergence ring corresponding to the current target clustering cluster is generated.

7. The method of claim 1, wherein, The target convergence ring is connected to the corresponding core machine room based on the full connection network topology and the path length matrix, including: From the path length matrix, the second point-to-point actual path distance between the target convergence machine room in the target convergence ring and all the core machine rooms is determined; the target convergence machine room is the convergence machine room located at the center or the convergence machine room located at the edge in the target convergence ring; Select the two core machine rooms with the smallest second point-to-point actual path distance as the primary uplink outlet and the standby uplink outlet; Based on the full connection network topology, the target convergence ring is connected to the two core machine rooms with the smallest second point-to-point actual path distance.

8. An aggregation ring building apparatus, comprising: It includes: An acquisition module is configured to acquire a path length matrix corresponding to all core machine rooms and all convergence machine rooms in a metropolitan optical transport network; The path length matrix is used to represent the point-to-point actual path distance between each core machine room, between each core machine room and each convergence machine room, and between each convergence machine room; A first construction module is configured to construct a full connection network topology corresponding to all core machine rooms according to the path length matrix; A clustering module is configured to perform clustering processing on all convergence machine rooms according to the path length matrix and predetermined administrative region information, and generate a plurality of target clustering clusters; the target clustering cluster corresponds to the administrative region information; A second construction module is configured to construct a target convergence ring corresponding to the path length matrix and all target clustering clusters, and connect the target convergence ring to the corresponding core machine room based on the full connection network topology and the path length matrix; wherein the target convergence ring corresponds to the target clustering cluster one by one.

9. An electronic device, comprising: It includes: A memory and a processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the convergence ring construction method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to implement the convergence ring construction method according to any one of claims 1 to 7.

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