Optimization method and system for optical cable network structure, computer device and storage medium

Abstract

The application provides an optical cable network structure optimization method and system, computer equipment and a storage medium, and relates to the technical field of communication. The method comprises the following steps: constructing an optical cable network knowledge graph; determining an optimization range according to the attribute characteristics of nodes and edges in the optical cable network knowledge graph; and executing an optimization strategy on the optimization range based on the scene requirements of the optical cable network. The optimization range comprises redundant optical cable sections and / or non-loop nodes and optical cable sections in the optical cable network. The optimization strategy comprises simplifying the redundant optical cable sections that are repeatedly laid, and / or constructing a predicted optical cable loop for the non-loop nodes and optical cable sections in the optical cable network. The technical scheme provided by the application simplifies the redundant optical cable sections that are repeatedly laid, and constructs multiple predicted optical cable loops for the non-loop nodes and optical cable sections in the optical cable network, thereby realizing the structure optimization of the optical cable network.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a method for optimizing optical fiber network structure, a system for optimizing optical fiber network structure, a computer device, and a computer-readable storage medium. Background Technology

[0002] Optical fiber networks are the foundational layer of network construction, providing transmission channels for various service networks and strongly supporting the development of network intelligence and service differentiation. In terms of coverage, optical fiber networks include different levels such as international long-distance trunk lines, inter-provincial long-distance trunk lines, intra-provincial long-distance trunk lines, and local transmission networks. Local transmission networks can be further divided into different levels based on scale, such as local backbone, local relay, and local access.

[0003] With the vigorous construction of 5G networks, multiple networks such as 3G, 4G, and 5G coexist, leading to a shortage of existing optical cable channel resources. Simultaneously, the local transmission network has a large number of nodes, a wide distribution range, and carries diverse services. Furthermore, with the development of full-service offerings and continuous updates to network technology, there are currently issues such as insufficient construction planning, unreasonable topology structures, inconsistent fiber core utilization, and a shortage of optical cable channel resources. During the construction of the optical cable network, business development continues. As the network scale continues to grow, ensuring broad coverage and efficient utilization of optical cable lines has become a key focus. The diverse topologies and numerous construction planning schemes of optical cable networks present a challenge in comprehensively considering multiple factors and selecting the optimal solution. Currently, frontline operators often make decisions based on local needs and resources, lacking a comprehensive understanding of the overall optical cable network structure and usage. Moreover, there is a lack of effective communication among operators, hindering the solidification and sharing of construction ideas and solutions. Therefore, based on the optical cable network map, it is necessary to streamline redundant optical cable segments to save on construction investment. Summary of the Invention

[0004] This invention was completed to at least partially solve the technical problems existing in the prior art, such as unreasonable optical cable network topology, inconsistent fiber core utilization, and tight optical cable channel resources.

[0005] According to one aspect of the present invention, a method for optimizing the structure of an optical cable network is provided, the method comprising:

[0006] Step S1: Construct a knowledge graph for the optical fiber network, wherein the knowledge graph uses optical junction boxes, optical fiber distribution boxes, optical fiber joints, equipment rooms, racks, and outdoor placement points as nodes, and optical fiber segments as edges.

[0007] Step S2: Determine the optimization range based on the attribute characteristics of nodes and edges in the optical fiber network knowledge graph, and execute optimization strategies on the optimization range based on the scenario requirements of the optical fiber network.

[0008] The scope to be optimized includes non-loop nodes and optical cable segments in the optical cable network.

[0009] The optimization strategy includes constructing predicted optical cable loops for non-loop nodes and optical cable segments in the optical cable network.

[0010] Optionally, step S2, which determines the optimization range based on the attribute characteristics of nodes and edges in the optical fiber network knowledge graph and executes an optimization strategy on the optimization range based on the scenario requirements of the optical fiber network, includes: step S21, based on the constructed optical fiber network knowledge graph, performing loop detection using a depth-first search algorithm to obtain the nodes and edges that form loops and the nodes and edges that do not form loops in the optical fiber network; step S22, calculating the node criticality for the non-loop nodes in the optical fiber network, where the node criticality K(i) of node i is...

[0011]

[0012] Where x(i) represents the number of edges associated with node i, g st n represents the number of shortest paths between node s and node t. st (i) represents the number of shortest paths between node s and node t passing through node i, N represents the number of nodes in the optical cable network, α and β represent coefficients with a set value range of [0,1], and α+β=1; Step S23: Filter the nodes with the top m% of node criticality among the non-loop nodes as nodes to be optimized; Step S24: Perform n-order neighbor node query on the filtered nodes to be optimized to obtain the n-order neighbor node domain of the node to be optimized; Step S25: Record the cluster of nodes to be optimized formed by multiple nodes to be optimized that have intersection in each n-order neighbor node domain, and the associated intersection nodes and associated optical cable segments formed by the intersection of the n-order neighbor node domains of the nodes to be optimized, wherein the cluster of nodes to be optimized and the associated intersection nodes are recorded as nodes to be formed, and the associated optical cable segments are recorded as edges to be formed; and Step S26: Construct a predicted optical cable loop based on the nodes to be formed and the edges to be formed.

[0013] Optionally, step S26 of constructing a predicted optical cable loop based on the nodes to be formed and the edges to be formed includes: step S261, for each node cluster to be optimized, assuming that there are virtual edges between the nodes in the node cluster to be optimized, the length attribute of the virtual edge is calculated and assigned by the latitude and longitude attributes between it and the associated nodes to obtain a virtual mesh topology; step S262, for each virtual mesh topology, taking the node with the highest node criticality as the starting point, the minimum spanning tree path is obtained by the Prim algorithm, which is the predicted optical cable segment to be constructed; and step S263, constructing multiple predicted optical cable loops based on the nodes to be formed, the edges to be formed, and the predicted optical cable segments to be constructed.

[0014] Optionally, in step S262, for each virtual mesh topology, the minimum spanning tree path is obtained by taking the node with the highest node criticality as the starting point and using the Prim algorithm. The minimum spanning tree path is among the predicted optical cable segments to be constructed. If the node with the highest node criticality is not unique, one of the nodes is randomly selected as the starting point.

[0015] Optionally, in step S263, multiple predicted optical cable loops are constructed based on the points to be formed, the edges to be formed, and the predicted optical cable segments to be constructed. The fiber core capacity of the predicted optical cable segment to be constructed is set to the highest value of the fiber core capacity in the predicted optical cable loop where the optical cable segment to be constructed is located.

[0016] Optionally, step S26, which involves constructing a predicted optical cable loop based on nodes to be formed and edges to be formed, includes: selecting node pairs in the node cluster to be optimized with a custom probability to build edges, thereby achieving prediction of the mesh topology.

[0017] Optionally, the attributes of the optical distribution box and optical fiber splitter box as nodes include ID, name, code, management area, longitude, latitude, nominal capacity, installation location type, and installation location; the attributes of the optical cable connector as nodes include ID, name, code, management area, support facility type, and support facility; the attributes of the equipment room and outdoor placement point as nodes include ID, name, code, management area, longitude, and latitude; and the attributes of the rack as nodes include ID, name, code, management area, installation location type, and installation location.

[0018] Optionally, the attributes of the optical cable segment as an edge include ID, name, code, management area, length, optical cable to which it belongs, optical cable level to which it belongs, nominal capacity, number of damaged fiber cores, number of reserved fiber cores, number of occupied fiber cores, starting facility type, starting facility code, ending facility type, ending facility code, and laying method; and wherein, the node and the edge are associated through the correspondence between the starting facility code and ending facility code attributes of the edge and the ID attribute of the node.

[0019] According to another aspect of the present invention, a method for optimizing the structure of an optical cable network is provided. The method includes: step S1, constructing an optical cable network knowledge graph, wherein the optical cable network knowledge graph uses optical junction boxes, optical fiber distribution boxes, optical cable joints, equipment rooms, racks, and outdoor placement points as nodes, and optical cable segments as edges; step S2, determining the scope to be optimized based on the attribute characteristics of the nodes and edges in the optical cable network knowledge graph, and executing an optimization strategy on the scope to be optimized based on the scenario requirements of the optical cable network, wherein the scope to be optimized includes redundant optical cable segments, and the optimization strategy includes simplifying redundant optical cable segments that are repeatedly deployed.

[0020] Optionally, step S2, which determines the optimization range based on the attribute characteristics of nodes and edges in the optical fiber network knowledge graph and executes an optimization strategy on the optimization range based on the scenario requirements of the optical fiber network, includes: step ST21, detecting optical fiber segments between nodes in the optical fiber network knowledge graph based on the constructed optical fiber network knowledge graph, wherein when multiple optical fiber segments are detected between node pairs formed by two neighboring nodes, the multiple optical fiber segments are recorded as multiple optical fiber segments; step ST22, determining the multiple optical fiber segments between each node pair as the group of optical fiber segments to be optimized between the node pairs; step ST23, optimizing the groups of optical fiber segments to be optimized between each node pair.

[0021] Optionally, step ST22, which determines the multiple optical cable segments between each node pair as a group of optical cable segments to be optimized between the node pair, includes: retaining the necessary multiple optical cable segments and determining the remaining multiple optical cable segments as optical cable segments to be optimized, wherein the necessary multiple optical cable segments are backup optical cable segments or dedicated optical cable segments.

[0022] Optionally, step ST23 of optimizing the optical cable segment group between each node pair includes: if the lengths of the optical cable segments in an optical cable segment group to be optimized are not equal, then the longer optical cable segment in the optical cable segment group to be optimized is removed, and the fiber core capacity of the shorter optical cable segment in the optical cable segment group to be optimized is increased as needed.

[0023] Optionally, step ST23 of optimizing the optical cable segment group between each node pair includes: if the lengths of each optical cable segment in an optical cable segment group to be optimized are equal, then the optical cable segment with low fiber core capacity utilization in the optical cable segment group to be optimized is removed, and the fiber core capacity of the remaining optical cable segments in the optical cable segment group to be optimized is increased as needed.

[0024] Optionally, step ST23 of optimizing the optical cable segment group to be optimized between each node pair includes: adjusting the optical cable segment connection device according to the optimized optical cable segment and the number of fiber cores.

[0025] Optionally, the scope to be optimized also includes non-loop nodes and optical cable segments in the optical cable network, and the optimization strategy further includes constructing predicted optical cable loops for non-loop nodes and optical cable segments in the optical cable network. Step S2, which determines the scope to be optimized based on the attribute characteristics of nodes and edges in the optical cable network knowledge graph and executes the optimization strategy for the scope to be optimized based on the scenario requirements of the optical cable network, further includes: before or after executing the optimization strategy of simplifying redundant optical cable segments that are repeatedly deployed, performing the optimization strategy of constructing predicted optical cable loops for non-loop nodes and optical cable segments in the optical cable network.

[0026] According to another aspect of the present invention, an optical fiber network structure optimization system is provided. The system includes: a construction module configured to construct an optical fiber network knowledge graph, wherein the optical fiber network knowledge graph uses optical junction boxes, optical fiber distribution boxes, optical fiber joints, equipment rooms, racks, and outdoor placement points as nodes, and optical fiber segments as edges; and an optimization module configured to determine the scope to be optimized based on the attribute characteristics of the nodes and edges in the optical fiber network knowledge graph, and to execute an optimization strategy on the scope to be optimized based on the scenario requirements of the optical fiber network. The scope to be optimized includes redundant optical fiber segments, and / or non-loop nodes and optical fiber segments in the optical fiber network. The optimization strategy includes simplifying redundant optical fiber segments that are repeatedly deployed, and / or constructing predicted optical fiber loops for non-loop nodes and optical fiber segments in the optical fiber network.

[0027] According to another aspect of the present invention, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor executes the aforementioned optical fiber network structure optimization method.

[0028] According to another aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor performs the aforementioned optical fiber network structure optimization method.

[0029] The technical solution provided by this invention may include the following beneficial effects:

[0030] The optical fiber network structure optimization method provided by this invention uses a knowledge graph to represent the optical fiber network structure, which is intuitive and clear, helping to grasp the overall situation of the optical fiber network. Simultaneously, by simplifying redundant optical fiber segments and constructing multiple predicted optical fiber loops for non-loop nodes and segments in the optical fiber network, structural optimization of the optical fiber network can be achieved. Furthermore, combining the structural characteristics of the optical fiber network in the knowledge graph, this invention provides optimization processes for both redundant optical fiber segment simplification and optical fiber loop prediction, helping to provide decision-making references for the structural optimization of optical fiber networks.

[0031] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0032] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0033] Figure 1 A flowchart illustrating a method for optimizing an optical cable network structure provided by the present invention;

[0034] Figure 2 A schematic diagram illustrating the specific process of step S2 in the optical cable network structure optimization method provided by the present invention;

[0035] Figure 3 for Figure 2 A detailed flowchart of step S26 in step S2 is shown below.

[0036] Figure 4 (a) to Figure 4 (c) is Figure 3 A schematic diagram illustrating a specific example of step S26;

[0037] Figure 5 A detailed flowchart of step S2 of another optical fiber network structure optimization method provided by the present invention;

[0038] Figure 6 A schematic diagram of the structure of the computer device provided by the present invention. Detailed Implementation

[0039] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the specific implementation methods of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific implementation methods described herein are for illustration and explanation only and are not intended to limit the present invention.

[0040] This invention provides a method for optimizing the structure of optical fiber networks.

[0041] Figure 1 This is a flowchart illustrating a method for optimizing an optical fiber network structure according to an embodiment of the present invention. The method includes the following steps:

[0042] Step S1: Construct a knowledge graph for the optical fiber network.

[0043] When constructing the knowledge graph of the optical fiber network, the knowledge graph uses optical junction boxes, optical fiber distribution boxes, optical fiber joints, equipment rooms, racks, and outdoor placement points as nodes, and optical fiber segments as edges.

[0044] In some embodiments, the attributes of node optical distribution boxes and optical fiber distribution boxes may include ID, name, code, management area, longitude, latitude, nominal capacity (total number of terminals), installation location type (equipment room / outdoor placement point), and installation location (matching the ID corresponding to the installation location type). The attributes of node optical cable connectors mainly include ID, name, code, management area, support facility type (manhole / pipe gate / power pole / equipment room / support point / other), and support facility (matching the ID corresponding to the support facility type). The attributes of node equipment rooms and outdoor placement points may include ID, name, code, management area, longitude, and latitude. The attributes of node racks may include ID, name, code, management area, installation location type (equipment room / outdoor placement point), and installation location (matching the ID corresponding to the installation location type).

[0045] In some embodiments, the attributes of the side optical cable segment may include ID, name, code, management area, length, optical cable to which it belongs, optical cable level (international / trunk / trunk / local trunk / local repeater / local access), nominal capacity (total number of fiber cores), number of damaged fiber cores, number of reserved fiber cores, number of occupied fiber cores, starting facility type (equipment room / rack / optical distribution box / optical fiber distribution box / optical cable connector / outdoor placement point), starting facility code (matching the ID corresponding to the starting facility type), ending facility type (equipment room / rack / optical distribution box / optical fiber distribution box / optical cable connector / outdoor placement point), ending facility code (matching the ID corresponding to the ending facility type), laying method (duct / pole overhead / wall suspended / wall nailed / direct burial / underwater), etc.

[0046] In some embodiments, nodes and edges are associated through the correspondence between the edge's start facility code and end facility code attributes and the node's ID attribute.

[0047] In some embodiments, the specific construction process of the optical fiber network knowledge graph may include designing a graph schema, mapping the fields of the existing relational data in the system to the graph schema and importing the data to complete the construction of the optical fiber network knowledge graph.

[0048] Step S2: Determine the scope to be optimized based on the attribute characteristics of nodes and edges in the optical fiber network knowledge graph, and execute optimization strategies for the scope to be optimized based on the scenario requirements of the optical fiber network.

[0049] This step involves analyzing and calculating the optical fiber network map, determining the scope to be optimized based on the attribute characteristics of nodes and edges, and then selecting different optimization strategies based on different optimization objectives.

[0050] In some embodiments, the scope to be optimized includes non-loop nodes and optical cable segments in the optical cable network, and the optimization strategy includes constructing predicted optical cable loops for non-loop nodes and optical cable segments in the optical cable network.

[0051] In some embodiments, the scope to be optimized includes redundant optical cable segments, and the optimization strategy includes streamlining redundant optical cable segments that are repeatedly deployed.

[0052] In some embodiments, the scope to be optimized includes redundant optical cable segments, and / or non-loop nodes and optical cable segments in the optical cable network; the optimization strategy includes simplifying repeatedly deployed redundant optical cable segments, and / or constructing predicted optical cable loops for non-loop nodes and optical cable segments in the optical cable network. In other words, step S2 provides two optimization strategies. In some embodiments, these two optimization strategies can be used sequentially. For example, the optimization strategy of constructing predicted optical cable loops for non-loop nodes and optical cable segments in the optical cable network can be performed before or after the optimization strategy of simplifying repeatedly deployed redundant optical cable segments.

[0053] The basic topologies of optical fiber networks mainly include point-to-point, chain, star, tree, ring, and mesh structures, each with its own advantages and disadvantages. For example, a star topology is simple, but it requires high reliability from the central node, resulting in poor overall security. It also requires more pipeline resources. In a ring topology, there are two routes with opposite transmission directions between nodes, leading to high fiber utilization and security, but an excessive number of nodes can negatively impact transmission efficiency. Mesh topologies offer high security and fiber utilization, but are more complex to manage, and the number of nodes should not be excessive. Therefore, the optimization described in step S2 can be effectively applied to these basic topologies.

[0054] The following sections will describe two optimization processes for step S2: A. Constructing a predicted optical cable loop and B. Simplifying redundant optical cable segments.

[0055] A. Constructing a predictive optical cable loop

[0056] Figure 2 A schematic diagram illustrating the specific process of step S2 in the optical cable network structure optimization method provided by the present invention.

[0057] Specifically, in this optimization process, step S2 includes:

[0058] Step S21: Based on the constructed optical fiber network knowledge graph, a loop detection algorithm based on a depth-first search algorithm is used to detect loops in the optical fiber network and obtain the nodes and edges that have formed loops as well as the nodes and edges that have not formed loops.

[0059] Step S22: Calculate the node criticality for loopable nodes in the optical fiber network, where the node criticality K(i) of node i is...

[0060]

[0061] Where x(i) represents the number of edges associated with node i, g st n represents the number of shortest paths between node s and node t. st (i) represents the number of shortest paths between node s and node t that pass through node i, N represents the number of nodes in the optical fiber network, and α and β represent coefficients with a set value range of [0,1], and α+β=1. For example, α and β can be customized to take values ​​of 0.5 and 0.5 respectively.

[0062] Step S23: Select the nodes that are in the top m percent of terms in terms of node criticality from the nodes that can form a cycle as nodes to be optimized. For example, m can be customized to a value of 20.

[0063] Step S24: Perform an n-order neighbor node query on the selected node to be optimized to obtain the n-order neighbor node domain of the node to be optimized. For example, n can be customized to a value of 2.

[0064] Step S25: Record the clusters of nodes to be optimized formed by multiple nodes that intersect in the n-order neighbor node domains, as well as the associated intersection nodes and associated optical cable segments formed by the intersection of the n-order neighbor node domains of the nodes to be optimized. The clusters of nodes to be optimized and the associated intersection nodes are recorded as nodes to be formed. The associated optical cable segments are recorded as edges to be formed.

[0065] Step S26: Construct a predicted optical cable loop based on the points to be formed and the edges to be formed.

[0066] In some embodiments, such as Figure 3 As shown, step S26, which involves constructing a predicted optical cable loop based on the points to be formed and the edges to be formed, may include:

[0067] Step S261: For each cluster of nodes to be optimized, it is assumed that there are virtual edges between the nodes in the cluster. The length attribute of the virtual edge is calculated and assigned by the latitude and longitude attributes between it and the associated nodes to obtain a virtual mesh topology.

[0068] Step S262: For each virtual mesh topology, starting from the node with the highest criticality, obtain the minimum spanning tree path using the Prim algorithm, which is the predicted optical cable segment to be constructed.

[0069] In some embodiments, in step S262, if the node with the highest criticality is not unique, one of the nodes can be randomly selected as the starting point.

[0070] Step S263: Construct multiple predicted optical cable loops based on the points to be formed, the edges to be formed, and the predicted optical cable segments to be constructed.

[0071] In some embodiments, in step S263, the predicted fiber core capacity of the optical cable segment to be constructed can be set to the highest value of the fiber core capacity in the predicted optical cable loop where the optical cable segment to be constructed is located.

[0072] In some embodiments, step S26 may include selecting node pairs in the cluster of nodes to be optimized with a certain probability to build edges, thereby realizing the prediction of the mesh topology.

[0073] Figure 4 (a) to Figure 4 (c) is a schematic diagram illustrating a specific example of step S26. Specifically, Figure 4 (a) is an example diagram after step S25 of the optical fiber network structure optimization method. Figure 4 In (a), nodes 1-5 (larger circles in the figure) form a cluster of nodes to be optimized, nodes 6-9 (smaller circles in the figure) form associated intersection nodes, and edges r1-r8 (solid lines in the figure) form associated optical cable segments. These nodes and edges are the nodes to be formed and the edges to be formed recorded in step S25. Figure 4 (b) is an example diagram following step S261 of the optical fiber network structure optimization method. For example... Figure 4 As shown in (b), edge x1-x10 (shown as dashed lines in the figure) is a virtual edge obtained through step S261. Figure 4 (c) is an example diagram following step S262 of the optical fiber network structure optimization method. For example... Figure 4 As shown in (c), edges x1, x7, x9, and x10 are the optical cable segments to be constructed obtained after step S262. Figure 4 Based on (c), that is, after step S263, four predicted optical cable loops were constructed based on the nodes to be formed and the edges of the nodes to be formed, as well as the optical cable segments to be constructed (e.g., loops formed by nodes 1, 2, 6, edge r1, edge r2, and edge x1).

[0074] In some embodiments, the prediction of optical cable loops is mainly applied to local access layer optical cable networks. Local network nodes are numerous and widely distributed, with node density varying depending on the service area and traffic volume. Considering factors such as network security, flexibility, and cost, local backbone optical cable networks and local trunk optical cable networks are preferably mesh-structured, while local access optical cable networks are preferably ring-structured. However, in actual construction, due to a lack of overall consideration of the optical cable network structure and a lack of prior assessment of the ever-increasing service demand, star and tree structures are still prevalent in local access optical cable networks. Therefore, based on the optical cable network map, non-loop nodes and optical cable segments in the local access layer optical cable network can be analyzed and optical cable loops predicted.

[0075] Furthermore, constructing predicted optical cable loops can also be applied to the prediction of optical cable mesh topology. The difference lies in step S26, where node pairs can be selected with a certain probability to build edges in the node cluster to be optimized, thereby achieving the prediction of the mesh topology.

[0076] B. Reduction of redundant optical cable segments

[0077] Figure 5 A schematic diagram illustrating the specific process of step S2 in another optical cable network structure optimization method provided by the present invention.

[0078] Specifically, in this optimization process, step S2 includes:

[0079] Step ST21: Based on the constructed optical fiber network knowledge graph, detect the optical fiber segments between nodes in the optical fiber network knowledge graph. When multiple optical fiber segments are detected between node pairs formed by two neighboring nodes, record these multiple optical fiber segments as multiple optical fiber segments.

[0080] Step ST22: Determine the multiple optical cable segments between each node pair as the group of optical cable segments to be optimized between that node pair.

[0081] In some embodiments, step ST22 may include: retaining necessary multiple optical cable segments and identifying the remaining multiple optical cable segments as optical cable segments to be optimized. Necessary multiple optical cable segments are backup optical cable segments or dedicated optical cable segments. For example, necessary optical cable segments may be backup optical cable segments set up to ensure security or dedicated lines specially set up according to the needs of government and enterprise customers.

[0082] Step ST23: Optimize the optical cable segment groups to be optimized between each node pair.

[0083] In some embodiments, step ST23 may include: if the lengths of the optical cable segments in a group of optical cable segments to be optimized are not equal, then remove the longer optical cable segments in the group of optical cable segments to be optimized, and increase the fiber core capacity of the shorter optical cable segments in the group of optical cable segments to be optimized as needed.

[0084] In some embodiments, step ST23 may include: if the lengths of the optical cable segments in a group of optical cable segments to be optimized are equal, then remove the optical cable segments in the group of optical cable segments to be optimized with low core capacity utilization, and increase the core capacity of the remaining optical cable segments in the group of optical cable segments to be optimized as needed.

[0085] In some embodiments, step ST23 may include: adjusting the optical cable segment connection device according to the optimized optical cable segment and the number of fiber cores. In some embodiments, the adjustment means may be to increase the nominal capacity of the optimized optical cable segment.

[0086] Based on the same technical concept, this invention also provides a structural optimization system for optical fiber networks, including a construction module and an optimization module. The construction module is configured to construct an optical fiber network knowledge graph. The optical fiber network knowledge graph uses optical junction boxes, optical fiber distribution boxes, optical cable joints, equipment rooms, racks, and outdoor placement points as nodes, and optical cable segments as edges. The optimization module determines the scope to be optimized based on the attribute characteristics of the nodes and edges in the optical fiber network knowledge graph, and executes optimization strategies based on the scenario requirements of the optical fiber network. In some embodiments, the scope to be optimized includes non-loop nodes and optical cable segments in the optical fiber network, and the optimization strategy includes constructing predicted optical fiber loops for the non-loop nodes and optical cable segments in the optical fiber network. In some embodiments, the scope to be optimized includes redundant optical cable segments, and the optimization strategy includes simplifying repeatedly deployed redundant optical cable segments. In some embodiments, the scope to be optimized includes redundant optical cable segments, and / or non-loop nodes and optical cable segments in the optical cable network; the optimization strategy includes streamlining redundant optical cable segments that are repeatedly deployed, and / or constructing predictive optical cable loops for non-loop nodes and optical cable segments in the optical cable network.

[0087] Based on the same technical concept, embodiments of the present invention also provide a computer device, such as... Figure 6 As shown, the computer device 10 includes a memory 11 and a processor 12. The memory 11 stores a computer program. When the processor 12 runs the computer program stored in the memory 11, the processor 12 executes the aforementioned optical fiber network structure optimization method.

[0088] Based on the same technical concept, the present invention also provides a computer-readable storage medium storing a computer program thereon, wherein when the computer program is executed by a processor, the processor executes the aforementioned optical fiber network structure optimization method.

[0089] In summary, the optical fiber network structure optimization method, system, computer equipment, and storage medium provided in this invention utilize a knowledge graph to represent the optical fiber network structure, providing a clear and intuitive understanding of the network's overall situation. Furthermore, by simplifying redundant optical fiber segments and constructing multiple predicted optical fiber loops for non-loop nodes and segments within the network, structural optimization of the optical fiber network can be achieved. Additionally, by incorporating the structural features of the optical fiber network within the knowledge graph, this invention provides optimization processes for both redundant optical fiber segment simplification and optical fiber loop prediction, offering valuable decision-making references for optical fiber network structure optimization.

[0090] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, 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 can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable 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.

[0091] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for optimizing the structure of an optical fiber network, characterized in that, include: Construct a knowledge graph for the optical fiber network, wherein the knowledge graph uses optical junction boxes, optical fiber distribution boxes, optical fiber joints, equipment rooms, racks, and outdoor placement points as nodes, and optical fiber segments as edges; The scope to be optimized is determined based on the attribute characteristics of nodes and edges in the optical fiber network knowledge graph, and an optimization strategy is executed on the scope to be optimized based on the scenario requirements of the optical fiber network. The scope to be optimized includes redundant optical cable segments. The optimization strategy includes streamlining redundant optical cable segments that are repeatedly deployed. The step of determining the optimization range based on the attribute characteristics of nodes and edges in the optical fiber network knowledge graph, and executing an optimization strategy on the optimization range based on the scenario requirements of the optical fiber network, includes: Based on the constructed optical fiber network knowledge graph, optical fiber segments between nodes of the optical fiber network knowledge graph are detected. When multiple optical fiber segments are detected between node pairs formed by two neighboring nodes, these multiple optical fiber segments are recorded as multiple optical fiber segments. The multiple optical cable segments between each node pair are identified as the group of optical cable segments to be optimized between that node pair; Optimize the optical cable segment groups to be optimized between each node pair; The step of optimizing the optical cable segment groups to be optimized between each node pair includes: If the lengths of the optical cable segments in a group of optical cable segments to be optimized are not equal, then the longer optical cable segments in the group of optical cable segments to be optimized are removed, and the fiber core capacity of the shorter optical cable segments in the group of optical cable segments to be optimized is increased as needed. If all optical cable segments in a group of optical cable segments to be optimized are of equal length, then remove the optical cable segments with low core capacity utilization in the group of optical cable segments to be optimized, and increase the core capacity of the remaining optical cable segments in the group of optical cable segments to be optimized as needed.

2. The method according to claim 1, characterized in that, The step of determining the multiple optical cable segments between each node pair as a group of optical cable segments to be optimized between that node pair includes: Necessary multiple optical cable segments are retained, while the remaining multiple optical cable segments are identified as optical cable segments to be optimized. The necessary multiple optical cable segments are backup optical cable segments or dedicated optical cable segments.

3. The method according to claim 1, characterized in that, The steps for optimizing the optical cable segment groups to be optimized between each node pair include: Adjust the optical cable segment connection equipment according to the optimized optical cable segment and fiber core number.

4. The method according to claim 1, characterized in that, The attributes of optical distribution boxes and optical fiber splitters, which serve as nodes, include ID, name, code, management area, longitude, latitude, nominal capacity, type of installation location, and installation location; The attributes of the optical cable connector as a node include ID, name, code, management area, support facility type, and support facility; The attributes of the data center and outdoor placement points used as nodes include ID, name, code, management area, longitude, and latitude; The attributes of a rack that serves as a node include ID, name, code, management region, location type, and location. The attributes of an optical cable segment as an edge include ID, name, code, management area, length, optical cable, optical cable class, nominal capacity, number of damaged fiber cores, number of reserved fiber cores, number of occupied fiber cores, type of starting facility, code of starting facility, type of ending facility, code of ending facility, and laying method; and Nodes and edges are associated through the correspondence between the edge's start facility code and end facility code attributes and the node's ID attribute.

5. The method according to claim 1, characterized in that, The scope to be optimized also includes non-loop nodes and fiber optic cable segments in the fiber optic network, and the optimization strategy further includes constructing predicted fiber optic loops for non-loop nodes and fiber optic cable segments in the fiber optic network. The step of determining the optimization range based on the attribute characteristics of nodes and edges in the optical fiber network knowledge graph, and executing an optimization strategy on the optimization range based on the scenario requirements of the optical fiber network, further includes: Before or after implementing the optimization strategy to streamline redundant optical cable segments that are repeatedly deployed, an optimization strategy is implemented to predict optical cable loops for non-loop nodes and optical cable segments in the optical cable network.

6. A system for optimizing the structure of an optical fiber network, characterized in that, include: The construction module is set to build a knowledge graph of the optical fiber network, wherein the knowledge graph of the optical fiber network uses optical junction boxes, optical fiber distribution boxes, optical fiber joints, equipment rooms, racks and outdoor placement points as nodes and optical fiber segments as edges. The optimization module determines the scope to be optimized based on the attribute characteristics of nodes and edges in the optical fiber network knowledge graph, and executes an optimization strategy on the scope to be optimized based on the scenario requirements of the optical fiber network. The scope to be optimized includes redundant optical fiber segments, and the optimization strategy includes simplifying redundant optical fiber segments that are repeatedly deployed. The system employs the method for structural optimization of the optical fiber network as described in any one of claims 1 to 5.

7. A computer device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor performs a method for optimizing the structure of the optical fiber network according to any one of claims 1 to 5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, the processor performs a method for optimizing the structure of the optical fiber network according to any one of claims 1 to 5.

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