Communication room distribution management system and method based on remote cross scheduling

Abstract

This invention discloses a communication equipment room wiring control system and method based on remote cross-scheduling, relating to the field of secure communication technology. The system and method include the following steps: S1, acquiring wiring resource status data and constructing a wiring resource map; S2, generating a task constraint expression set and evaluating the feasibility of candidate paths; S3, identifying the preferred cross-scheduling scheme and generating a scheme-level scheduling record; S4, performing consistency verification on the current task and generating scheduling data tags. This invention effectively improves the wiring resource modeling capability and the feasibility proof problem of remote cross-scheduling in communication equipment room scenarios, solving the problem of silent mismatch risk between heterogeneous boards due to the lack of pre-execution feasibility proof.

Description

Technical Field

[0001] This invention relates to the field of secure communication technology, specifically to a communication equipment room wiring control system and method based on remote cross-scheduling. Background Technology

[0002] With the development of intelligent operation and maintenance, remote wiring management and multi-service board collaborative scheduling in communication equipment rooms, existing technologies have the ability to remotely schedule, monitor lines, record resources, loop back ports, test bit errors, detect handsets, protect TPS, monitor environmental conditions and monitor optical cables for E1 links, telephone links, fiber optic links and environmental monitoring objects. However, most existing systems are still mainly based on single command execution and decentralized status display, lacking data graphs, constraint compilation, scheme disambiguation and consistency verification mechanisms for scheduling tasks.

[0003] For example, the invention patent with announcement number CN115114600B discloses a unified management and control method and system for built-in and external devices, including: monitoring the insertion event of a hot-swappable device and obtaining the device's policy change event; based on the insertion event and policy change event, obtaining the corresponding / sys path information and identifying the type information of the external or built-in device; based on the device type information, responding to the device's policy change event, performing device management policy matching; based on different built-in or external device type information, searching for driver information matching the device from the corresponding path, thereby establishing the association relationship between the bus, driver, and device; based on the association relationship, debinding the device and driver from the application layer and kernel layer respectively, realizing unified management and control of built-in and external devices, greatly enhancing the unified and comprehensive management and control capability of system devices.

[0004] For example, the invention patent with announcement number CN119203256B discloses a method and system for the operation, maintenance, and management of third-party tools for independent websites. This includes: determining the thread support requirements of the task execution end of the independent website from task execution thread logs to identify the target thread that needs to be connected to by the third-party tool; determining the connection relationship between the target thread and the virtual nodes based on the operating status of the virtual nodes that the target thread is allowed to access within the independent website, and generating a virtual node connection layout; adjusting the bandwidth configuration of the virtual nodes based on the execution time-domain characteristic information of all target threads, and calling the third-party tool to connect to the triggered virtual node to ensure accurate connection between the third-party tool and the target thread; and judging whether the third-party tool has engaged in abnormal behavior based on its working behavior information, and performing permission and / or connection control on the third-party tool to prevent it from performing unauthorized operations on the independent website and improve the operational security of the independent website.

[0005] In existing technologies, if existing systems in heterogeneous board hybrid scenarios do not perform unified verification of constraints such as interface compatibility, protection occupancy, test occupancy, link continuity, non-switchable intermediate nodes, and power-down pass-through relationships before execution, silent mismatches may occur, such as command execution succeeding but end-to-end unavailability, protection relationships being broken, and test conflicts, which are difficult to detect at the command stage.

[0006] Therefore, in order to address the above problems, there is an urgent need for a communication equipment room wiring control system and method based on remote cross-scheduling. Summary of the Invention

[0007] Technical problems to be solved To address the shortcomings of existing technologies, this invention provides a communication equipment room wiring control system and method based on remote cross-scheduling, which solves the problem of silent mismatch risk between heterogeneous boards due to the lack of feasibility proof before implementation.

[0008] Technical solution To achieve the above objectives, the present invention provides the following technical solution: a communication equipment room wiring control method based on remote cross-scheduling, comprising: S1, collecting data on the heterogeneous wiring objects participating in remote cross-scheduling within the communication equipment room throughout the entire process, acquiring wiring resource status data, and constructing a wiring resource map; S2, parsing the scheduling task based on the wiring resource map, generating a task constraint expression set, evaluating the feasibility of candidate paths, and generating a candidate feasible subgraph set; S3, performing scheme disturbance benefit analysis based on the candidate feasible subgraph set, identifying the preferred cross-scheduling scheme, and generating a scheme-level scheduling record; S4, evaluating the coordination of scheduling consistency based on the preferred cross-scheduling scheme, performing consistency verification on the current task, and generating scheduling data tags.

[0009] Furthermore, the specific process of collecting data on the heterogeneous wiring objects participating in remote cross-connection scheduling within the communication equipment room, obtaining wiring resource status data, and constructing a wiring resource map is as follows: The entire process of collecting data from the communication equipment room is performed to obtain wiring resource status data. This data includes: equipment room number, chassis number, slot number, board type, board number, port number, port direction identifier, interface type, signal type, framing attributes, user-side identifier, equipment-side identifier, current cross-connection relationship identifier, protection occupancy identifier, test occupancy identifier, delay test data, handset status data, AC voltage test data, DC voltage test data, and insulation... Resistance test data, loop resistance test data, and optical cable monitoring data are collected. The wiring resource status data is uniformly correlated using device local time, gateway reception time, and platform entry time. Integrity verification, consistency checks, anomaly marking, and minimum-maximum normalization are performed on the wiring resource status data. A hierarchical object identifier is constructed using room number, chassis number, slot number, board number, and port number. This unifies the correlation between port connections, object occupancy, primary and backup protection relationships, test relationships between test tasks and ports, and observation relationships between monitoring objects and link objects, thus constructing a wiring resource map.

[0010] Furthermore, the specific process of parsing the scheduling task based on the wiring resource graph and generating the task constraint expression set is as follows: Extract local subgraphs related to the current task from the wiring resource graph; these local subgraphs include source nodes, target nodes, intermediate transfer nodes, protection-related nodes, and test-related nodes; using interface type, signal type, framing attribute, port direction, time slot occupancy status, protection group identifier, and test access point identifier as matching criteria, decompose each natural language statement into a list of attribute-value pairs for the role correspondence requirements, service adaptation requirements, protection maintenance requirements, test isolation requirements, path continuity requirements, and power-down path maintenance requirements in the remote cross-scheduling task. Establish a correspondence between these pairs and the attribute fields of nodes or edges in the graph. Generate specific constraint expressions based on the mapping results, converting them into sets of allowed connection pairs, prohibited connection pairs, node sequences or edge sequences, and spatial or electrical continuity conditions, respectively, to form the task constraint expression set.

[0011] Furthermore, the specific process for evaluating the feasibility of candidate paths is as follows: Based on the task constraint expression set, constraint matching is performed on each candidate connection chain in the local subgraph; the number of connection segments in the current candidate path is counted to obtain the number of compatible segments; the number of connection segments in the current candidate path with board mismatch, interface mismatch, or role mismatch is counted to obtain the number of conflict segments; the number of connection segments in the current candidate path that maintain the continuity of the preceding and following connections is counted to obtain the number of continuous valid segments; the total number of connection segments included in the current candidate path is counted to obtain the total number of candidate segments; the number of data relationships in the current candidate path that can maintain the original power-off pass-through association is counted to obtain the number of maintained relationships; the number of data relationships in the current candidate path that would destroy the original power-off pass-through association is counted to obtain the number of destroyed relationships; the number of nodes occupied by protected relationships and the number of nodes occupied by protected relationships in the current candidate path are counted. The number of nodes occupied by the test task and the number of intermediate nodes marked as non-switchable are used to obtain the number of protected nodes, the number of test nodes, and the number of restricted nodes, respectively. The number of compatible nodes is divided by the sum of the number of compatible nodes, the number of conflict nodes, and the zero-prevention items to obtain the compatibility satisfaction items. The number of consecutive valid nodes is divided by the sum of the total number of candidate segments and the zero-prevention items to obtain the path continuity items. The number of relationships maintained is divided by the sum of the number of relationships maintained, the number of relationships broken, and the zero-prevention items to obtain the pass-through maintenance items. The minimum value among the compatibility satisfaction items, path continuity items, and pass-through maintenance items is selected as the path bottleneck item. The number of protected nodes, the number of test nodes, and the number of restricted nodes are added together and then a constant term of 1 is added to perform a logarithmic operation. The logarithmic operation result plus the constant term of 1 gives the constraint item. The path bottleneck item is divided by the constraint item to obtain the pre-screening bottleneck constraint value, which is used to evaluate the feasibility of the candidate path.

[0012] Furthermore, the specific process of generating the candidate feasible subgraph set is as follows: The pre-approval bottleneck constraint value is compared with the pre-approval threshold in real time. When the pre-approval bottleneck constraint value is less than the pre-approval threshold, the current candidate path is determined not to meet the feasibility proof conditions before scheduling. The current candidate path is then removed from the list of candidate paths to be executed. Simultaneously, structured prohibition proof information is output, including the bottleneck constraint item that caused the failure, the unique identifier of the triggered constraint item, and the corresponding graph edge identifier or node identifier. A set of prohibition reasons corresponding to the current candidate path is generated. When the pre-approval bottleneck constraint value is greater than or equal to the pre-approval threshold, the current candidate path is retained, and the pre-approval bottleneck constraint value corresponding to the current candidate path is written into the candidate feasible subgraph set.

[0013] Furthermore, the specific process of performing scheme disturbance benefit analysis based on the candidate feasible subgraph set is as follows: Based on the candidate feasible subgraph set, the port relationships, protection relationships, and test relationships in the current candidate scheme are matched with the existing relationship mappings in the wiring resource graph using the relationship inheritance comparison method. The number of port relationships, protection relationships, and test relationships that can be directly used is counted to obtain the reusable quantity. Using the relationship difference detection method, the target mapping relationship under the current candidate scheme is compared with the existing mapping relationship item by item. The number of port mapping relationships, protection mapping relationships, and test mapping relationships that need to be modified is counted to obtain the number of ports to be adjusted and the number of protection relationships to be adjusted, respectively. The quantity and number of tests to be adjusted are determined. Using an object identifier association retrieval method, associated records corresponding to the objects involved in the current candidate solution are extracted, and counted according to the anomaly marker field and the verification pass marker field to obtain the number of anomaly associations and the number of verification passes. Solution disturbance benefit analysis is performed: the reusable quantity is incremented by 1 and divided by the sum of the number of ports to be adjusted, the number of protections to be adjusted, the number of tests to be adjusted, and the zero-prevention items to obtain the reuse ratio. Then, a hyperbolic tangent transformation is applied to the reuse ratio to obtain the reuse benefit item. The anomaly risk item is obtained by dividing the number of anomaly associations by the sum of the number of anomaly associations, the number of verification passes, and the zero-prevention items. The solution benefit difference is obtained by subtracting the anomaly risk item from the reuse benefit item.

[0014] Furthermore, the specific process of identifying the preferred crossover scheme and generating a scheme-level scheduling record is as follows: The scheme benefit difference value corresponding to each candidate scheme is compared in real time, and the candidate scheme with the largest scheme benefit difference value is selected as the preferred crossover scheme; when multiple candidate schemes have the same scheme benefit difference value or the difference value is less than the difference threshold, the corresponding pre-approval bottleneck constraint value is further compared, and the candidate scheme with the largest pre-approval bottleneck constraint value is selected as the preferred crossover scheme; the preferred crossover scheme is structurally bound with the task number, source object identifier, target object identifier, business type identifier, scheme benefit difference value, pre-approval bottleneck constraint value, and prohibition reason to generate a scheme-level scheduling record.

[0015] Furthermore, the specific process for evaluating the coordination of scheduling consistency based on the preferred crossover scheme is as follows: Based on the preferred crossover scheme, the current task is matched item by item with the target mapping relationship in the preferred crossover scheme through the mapping consistency comparison method. The verification records of consistent and inconsistent matching are counted to obtain the number of consistent verification items and the number of inconsistent verification items. Through the protection relationship backtracking comparison method, the protection relationship after the current task is executed is compared item by item with the protection mapping relationship corresponding to the preferred crossover scheme. The number of consistent and inconsistent protection relationships is counted to obtain the number of consistent protections and the number of inconsistent protections. Through the integrity check method, the monitoring data not returned by the current task during the consistency verification process is counted to obtain the number of missing monitoring items. Finally, all monitoring data participating in the verification are counted. The total number of monitoring items is obtained. Verification items are obtained by dividing the number of consistent verification items by the sum of the number of consistent verification items, inconsistent verification items, and zero-prevention items. Protection items are obtained by dividing the number of consistent protection items by the sum of the number of consistent protection items, inconsistent protection items, and zero-prevention items. The monitoring ratio is obtained by dividing the number of missing monitoring items by the sum of the total number of monitoring items and zero-prevention items. The monitoring item is obtained by subtracting the monitoring ratio from one. The average index is obtained by adding the verification items, protection items, and monitoring items and then dividing by three. The squares of the differences between the verification items and the average index, the protection items and the average index, and the monitoring items and the average index are calculated respectively. The sum of these three squared differences is divided by three, and the square root is taken to obtain the discrete item. The scheduling consistency coordination value is obtained by dividing the average index by 1 and the sum of the discrete items, and the scheduling consistency coordination is evaluated.

[0016] Furthermore, the specific process of performing consistency verification on the current task and generating scheduling data tags is as follows: The scheduling consistency coordination value is compared with the scheduling consistency threshold in real time. When the scheduling consistency coordination value is greater than or equal to the scheduling consistency threshold, the current task is determined to have passed the consistency verification. The nodes, node attributes, and corresponding edge relationships corresponding to the current task are synchronously refreshed to form the current wiring relationship. When the scheduling consistency coordination value is less than the scheduling consistency threshold, the current task is determined to have a consistency anomaly, and an anomaly reason identifier is output. The consistency judgment data, task number, source object identifier, target object identifier, business type identifier, pre-approval bottleneck constraint value, solution benefit difference value, scheduling consistency coordination value, and time information of the current task are structurally bound to generate scheduling data tags.

[0017] Furthermore, a second aspect of the present invention provides a communication equipment room wiring control system based on remote cross-scheduling, applied to a communication equipment room wiring control method based on remote cross-scheduling, comprising: a resource graph construction module, used to collect data on heterogeneous wiring objects participating in remote cross-scheduling within the communication equipment room throughout the entire process, obtain wiring resource status data, and construct a wiring resource graph; a constraint compilation module, used to parse scheduling tasks based on the wiring resource graph, generate a task constraint expression set, evaluate the feasibility of candidate paths, and generate a set of candidate feasible subgraphs; a scheme disambiguation module, used to perform scheme disturbance benefit analysis based on the set of candidate feasible subgraphs, identify preferred cross-scheduling schemes, and generate scheme-level scheduling records; and a consistency verification module, used to evaluate the coordination of scheduling consistency based on preferred cross-scheduling schemes, perform consistency verification on the current task, and generate scheduling data labels.

[0018] Beneficial effects The present invention has the following beneficial effects: (1) This invention constructs a wiring resource map by uniformly collecting, uniformly associating time and uniformly mapping the data of the computer room object, chassis object, slot object, board object, port object, link object, protection object, test object and monitoring object, and converging the status data that were originally scattered in different boards, different test interfaces and different monitoring channels into a unified data base, thereby improving the global visibility and relationship traceability of the wiring resources in the communication computer room.

[0019] (2) This invention introduces the number of compatible nodes, number of conflicting nodes, number of continuous effective nodes, number of nodes maintaining relationships, number of nodes breaking relationships, number of protected nodes, number of tested nodes and number of restricted nodes to construct the pre-screening bottleneck constraint value. It can identify the shortest board in the candidate path from three dimensions: basic compatibility, path continuity and power failure pass-through maintenance. It also superimposes the inhibitory effects of protection occupation, test occupation and structural restriction, thereby improving the pertinence and judgment accuracy of the feasibility proof before scheduling.

[0020] (3) In this invention, by further expanding the preferred cross-scheme into port relationship adjustment mapping, protection relationship adjustment mapping and test relationship adjustment mapping, the output of the scheduling task no longer stays at a single command level, but forms a structured mapping object that can be used for subsequent verification, write-back and review, thereby enhancing the data carrying capacity and subsequent map update capability of the remote cross-scheme process.

[0021] (4) This invention writes port relationship adjustment mapping, protection relationship adjustment mapping, test relationship adjustment mapping and corresponding verification information that have passed the consistency check into the wiring resource map, and generates anomaly cause identifier, review prompt information, candidate recovery relationship mapping and scheduling data label for tasks that have failed the consistency check, and further summarizes them into a remote cross-scheduling consistency analysis report, thereby realizing closed-loop management from resource collection, pre-review simulation, scheme selection, execution verification to map update and anomaly review.

[0022] Of course, any product implementing this invention does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0023] Figure 1 This is a flowchart of the communication equipment room wiring control method based on remote cross-scheduling according to the present invention; Figure 2 This is an architecture diagram of the communication equipment room wiring control system based on remote cross-scheduling according to the present invention; Figure 3 This is a comparison chart of bottleneck constraint values ​​in the preliminary review of candidate paths for this invention. Figure 4 This is a bar chart comparing the reuse benefits and abnormal risk items of this invention. Figure 5 This is a distribution diagram of the abnormal types of remote cross-scheduling in this invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] Please see Figures 1-5 The present invention provides a technical solution: a communication equipment room wiring control method based on remote cross-scheduling, including S1, collecting data on the heterogeneous wiring objects participating in remote cross-scheduling in the communication equipment room throughout the process, obtaining wiring resource status data, and constructing a wiring resource map; S2, based on the wiring resource graph, the scheduling task is parsed to generate a set of task constraint expressions, and the feasibility of candidate paths is evaluated to generate a set of candidate feasible subgraphs; S3, based on the candidate feasible subgraph set, performs scheme disturbance benefit analysis, identifies the preferred cross scheme, and generates scheme-level scheduling records; S4 evaluates the coordination of scheduling consistency based on the preferred crossover scheme, performs consistency verification on the current task, and generates scheduling data labels.

[0026] Specifically, the process of collecting data on the heterogeneous cabling objects participating in remote cross-connection scheduling within the communication equipment room, obtaining cabling resource status data, and constructing a cabling resource map is as follows: The system performs full-process data acquisition on equipment room objects, chassis objects, slot objects, board objects, port objects, link objects, protection objects, test objects, and monitoring objects within the communication equipment room. The acquisition interfaces include a Simple Network Management Protocol (SMMP) interface, a Remote Procedure Call (RPC) interface, and a message queue telemetry transmission interface. The transmission protocol uses Transmission Control Protocol (TCP), with a sampling period of every 30 seconds and support for event-triggered incremental acquisition to obtain wiring resource status data. This data includes: equipment room number, chassis number, slot number, board type, board number, port number, port direction identifier, interface type, signal type, framing attributes, user-side identifier, equipment-side identifier, current cross-connection identifier, protection occupancy identifier, test occupancy identifier, latency test data, telephone status data, AC voltage test data, DC voltage test data, insulation resistance test data, loop resistance test data, and optical cable monitoring data. Board types include E1 boards, automatic telephone boards, magneto interface boards, two-wire audio boards, four-wire audio boards, optical interface boards, environmental monitoring boards, optical cable monitoring boards, and protection boards.

[0027] The wiring resource status data is uniformly correlated using device local time, gateway reception time, and platform entry time. Integrity checks are performed on the numbers in the wiring resource status data, removing data records with missing primary identifiers. Consistency checks are performed between identifiers in the wiring resource status data; if the same port is simultaneously marked as both user-side and device-side, a role conflict is identified; if the same port has both protection and test occupancy identifiers, an occupancy conflict is identified; if the source or target port referenced by a link object does not exist in the port object, a relationship break is identified. Data records with role conflicts, occupancy conflicts, or relationship breaks are marked as anomalies. Minimum-maximum normalization is performed on test data and fiber optic monitoring data, mapping each numerical field to a unified numerical range. A hierarchical object identifier is constructed using room number, chassis number, slot number, board number, and port number. This unifies the correlation between port connection relationships, object occupancy relationships, primary and backup protection relationships, test relationships between test tasks and ports, and observation relationships between monitoring objects and link objects, thus constructing a wiring resource map. Graph nodes are used to represent data center objects, board objects, port objects, and link objects, while graph edges are used to represent reachability relationships, mapping relationships, occupancy relationships, protection relationships, and testing relationships.

[0028] The node attributes and edge attributes of the wiring resource map are respectively written with board compatibility attributes, interface matching attributes, role correspondence attributes, protection retention attributes, test exclusion attributes, non-switchable attributes, and power failure pass-through retention attributes to form a map attribute set, which provides a unified data foundation for the pre-approval simulation and data verification of remote cross-scheduling tasks.

[0029] This implementation plan automates and refines the data acquisition and status management of heterogeneous cabling objects in communication equipment rooms throughout the entire process, significantly improving the real-time performance, completeness, and consistency of cabling resource data. Through a unified association and anomaly detection mechanism across multiple protocols and time dimensions, data conflicts and breaks are effectively eliminated, ensuring the accuracy and reliability of resource status. The constructed cabling resource map and attribute set provide an intuitive and predictable unified data foundation for remote cross-connect scheduling tasks, supporting pre-screening verification and conflict avoidance, greatly improving scheduling efficiency and success rate, reducing the risk of manual intervention and misoperation, and enhancing the intelligence level and resource utilization of network operation and maintenance.

[0030] Specifically, the process of parsing the scheduling task based on the wiring resource graph to generate a task constraint representation set is as follows: Extracting local subgraphs related to the current task from the wiring resource graph; the local subgraphs are extracted from the graph using a breadth-first traversal algorithm based on the source and target identifiers in the task, with an extraction depth limited to five hops; the local subgraphs include source nodes, target nodes, intermediate transfer nodes, protection-related nodes, and test-related nodes; protection-related nodes refer to backup nodes that have a protection group binding relationship with the source or target node, and test-related nodes refer to intermediate nodes with test access point identifiers; using interface type, signal type, framing attributes, port direction, time slot occupancy status, protection group identifier, and test access point identifier as matching criteria, the requirements for role correspondence, service adaptation, protection maintenance, test isolation, path continuity, and power failure path maintenance in the remote cross-scheduling task are assessed. The matching criteria are determined by directly reading each field from the node and edge attributes of the local subgraph. Each natural language statement is decomposed into a list of attribute-value pairs, and a correspondence is established with the attribute fields of nodes or edges in the graph. The correspondence is completed by full attribute name matching or based on a synonym mapping table. Specific constraint expressions are generated based on the mapping results. The constraint expressions adopt first-order predicate logic form and are converted into sets of allowed connection pairs, prohibited connection pairs, node sequences or edge sequences, and spatial or electrical continuity conditions, respectively. Each pair in the allowed connection pair set must satisfy the consistency of interface type and signal type, and each pair in the prohibited connection pair set must violate at least one matching criterion. A task constraint expression set is formed and stored in the form of a key-value pair list. Each constraint is accompanied by a source requirement identifier.

[0031] In this implementation scheme, by performing local subgraph extraction and depth-constrained traversal on the wiring resource graph, precise location and efficient isolation of elements related to scheduling tasks are achieved, significantly reducing the computational complexity of subsequent constraint generation. Based on fields such as interface type, signal type, framing attributes, time slot occupancy, protection group identifier, and test access point in node and edge attributes, a mapping relationship between natural language requirements and graph attributes is established, supporting fuzzy matching of synonyms and improving the flexibility and fault tolerance of task parsing.

[0032] Specifically, the process of evaluating the feasibility of candidate paths is as follows: Based on the task constraint expression set, constraint matching is performed on each candidate connection chain in the local subgraph. The number of connection segments in the current candidate path is counted to obtain the number of compatible segments; the number of connection segments in the current candidate path with board mismatch, interface mismatch, or role mismatch is counted to obtain the number of conflict segments; the number of connection segments in the current candidate path that maintain the continuity of the preceding and following connections is counted to obtain the number of continuous valid segments; the total number of connection segments contained in the current candidate path is counted to obtain the total number of candidate segments; the number of data relationships in the current candidate path that can maintain the original power-off pass-through association is counted to obtain the number of maintained relationships; the number of data relationships in the current candidate path that would destroy the original power-off pass-through association is counted to obtain the number of destroyed relationships; the number of nodes occupied by protected relationships, the number of nodes occupied by test tasks, and the number of intermediate nodes marked as non-switchable in the current candidate path are counted to obtain the number of protected nodes, the number of test nodes, and the number of restricted nodes, respectively.

[0033] The compatibility quantity is divided by the sum of the compatibility quantity, conflict quantity, and zero-prevention item to obtain the compatibility satisfaction item; the continuous valid quantity is divided by the sum of the total number of candidate segments and zero-prevention item to obtain the path continuity item; the maintenance relationship quantity is divided by the sum of the maintenance relationship quantity, disruption relationship quantity, and zero-prevention item to obtain the pass-through maintenance item; the minimum value among the compatibility satisfaction item, path continuity item, and pass-through maintenance item is selected as the path bottleneck item. The reason for using the minimum value strategy instead of the weighted average is that a low satisfaction level in any key dimension of remote cross-connect scheduling will directly lead to the unavailability of the entire path. Taking the minimum value can accurately identify and avoid the risk of silent mismatch and prevent other high indicators from masking the bottleneck. The bottleneck constraint is determined by summing the number of protected nodes, test nodes, and restricted nodes, then adding a constant term of 1 and performing a logarithmic operation. The result of this logarithmic operation, plus the constant term 1, yields the constraint term. The use of logarithmic operations instead of linear or exponential operations aims to slow the growth rate of the constraint term as the number of occupied or restricted nodes increases, avoiding excessive penalties for paths with a large number of nodes. This also maintains the scalability of the constraint term under changes in the number of nodes, making the pre-approval bottleneck constraint value more focused on the path bottleneck rather than the absolute number of nodes. The path bottleneck term is then divided by the constraint term to obtain the pre-approval bottleneck constraint value, which is used to evaluate the feasibility of candidate paths.

[0034] The specific formula for calculating the pre-approval bottleneck constraint value is as follows: ; In the formula, This represents the pre-examination bottleneck constraint value, used to characterize the degree to which the current candidate path meets the pre-execution constraints; This represents the number of compatible connections, used to characterize the effective connection size that meets the basic connectivity requirements in the current candidate path. This represents the number of conflicts, used to characterize the scale of conflicting connections in the current candidate path that do not meet the basic connectivity requirements; This represents the number of consecutive valid paths, used to characterize the degree to which the current candidate path maintains continuity in the topology. This represents the total number of candidate segments, used as a normalization benchmark for a continuous number of valid segments; This represents the number of relationships maintained, used to characterize the degree to which the current candidate path inherits the relationships maintained by the original power-down path; This indicates the number of disruptive relationships, used to characterize the degree to which the current candidate path disrupts the relationship between the original power-down path and the maintenance relationship. This indicates the number of protected nodes, used to characterize the degree to which the current candidate path is constrained by protection relationships; This indicates the number of test nodes, which characterizes the degree to which the current candidate path is subject to test occupancy constraints. This indicates the number of nodes that are limited, and is used to characterize the degree to which there are structural switching constraints in the current candidate path; This indicates the zero-preservation term, which is obtained by setting a very small positive constant and is used to avoid the denominator being zero.

[0035] As shown in Table 1, the preliminary evaluation table for candidate paths is used to statistically analyze the preliminary evaluation indicators for each of the six average indicators: Path Average Indicator P1: Average number of compatible segments is 18, average number of conflicts is 1, average number of consecutive valid segments is 17, average total number of candidate segments is 19, average number of maintained relationships is 9, and the average preliminary bottleneck constraint value is 0.4263; Path Average Indicator P2: Average number of compatible segments is 16, average number of conflicts is 3, average number of consecutive valid segments is 15, average total number of candidate segments is 19, average number of maintained relationships is 8, and the average preliminary bottleneck constraint value is 0.3025; Path Average Indicator P3: Average number of compatible segments is 19, average number of conflicts is 0, average number of consecutive valid segments is 18, average total number of candidate segments is 20, and the average number of maintained relationships is [missing information]. 10. The average bottleneck constraint value for the preliminary review is 0.5316; the average bottleneck constraint value for path P4 is 0.2683, with an average of 14 compatible segments, 4 conflict segments, 14 consecutive valid segments, 18 candidate segments, and 7 maintained relationships. The average bottleneck constraint value for the preliminary review is 0.4236; the average bottleneck constraint value for path P6 is 0.2874, with an average of 15 compatible segments, 2 conflict segments, 13 consecutive valid segments, 17 candidate segments, and 6 maintained relationships. Overall data shows that fewer conflicts, higher compatibility and continuous valid numbers, larger pre-approval bottleneck constraints, and better path feasibility and overall quality. Among them, the path average index P3 has no conflicts and the best in all indicators, with the highest constraint value. The path average index P4 has the most conflicts and the lowest constraint value, with the weakest overall quality.

[0036] Table 1 Candidate Path Preliminary Evaluation Form like Figure 3The chart comparing the pre-approval bottleneck constraint values ​​of candidate paths, with the candidate path number (P1-P6) on the horizontal axis and the pre-approval bottleneck constraint value on the vertical axis, visually presents the comprehensive pre-approval constraint level of each path using blue bars, and uses red dashed lines to mark the pre-approval threshold as the benchmark for path feasibility judgment. The data shows that the average bottleneck constraint value of path P3 is the highest, significantly higher than the pre-approval threshold, indicating its optimal comprehensive feasibility and path quality. The average constraint values ​​of paths P1 and P5 are next, also higher than the threshold, indicating good pre-approval pass rate. The average constraint values ​​of paths P2, P4, and P6 are lower than the pre-approval threshold, with the average constraint value of path P4 being the lowest, indicating the weakest comprehensive feasibility. This chart clearly quantifies the pre-approval performance of each candidate path, intuitively distinguishing between compliant and non-compliant paths, providing a clear visual basis for candidate path selection and prioritization.

[0037] This implementation plan achieves quantitative decision support in the pre-screening stage of remote cross-scheduling tasks by conducting multi-dimensional and refined feasibility assessments of candidate paths. It effectively avoids the masking of key shortcomings by weighted averages and accurately identifies silent mismatch risks. Simultaneously, logarithmic calculations are used for the number of constraint nodes to prevent excessive penalties on long paths, maintaining the scalability of evaluation indicators across different path lengths. The generated pre-screening bottleneck constraint values ​​can intuitively and comprehensively reflect the degree to which each candidate path meets the pre-execution constraints.

[0038] Specifically, the process of generating the set of candidate feasible subgraphs is as follows: The system compares the pre-approval bottleneck constraint value with the pre-approval threshold in real time. When the pre-approval bottleneck constraint value is less than the pre-approval threshold, the current candidate path is determined not to meet the feasibility proof conditions before scheduling. The current candidate path is then removed from the list of candidate paths to be executed. Based on the verification data of the candidate path's corresponding board compatibility, interface matching, role correspondence, protection occupancy, test occupancy, non-switchable relationship, and power-down pass-through retention relationship, the system extracts the constraint conflict items that caused the current candidate path to fail the pre-approval. Simultaneously, it outputs structured prohibition proof information, including the bottleneck constraint item that caused the failure and the unique identifier of the triggered constraint item. The system generates a set of prohibition reasons corresponding to the current candidate path, based on the identifier and its corresponding graph edge or node identifier. This set is obtained by mapping each constraint matching failure item. The specific mapping rules are as follows: board compatibility issues are mapped to board mismatch identifiers; interface matching issues are mapped to interface conflict identifiers; role correspondence issues are mapped to role mismatch identifiers; protection occupancy conflicts are mapped to protection occupancy identifiers; test occupancy conflicts are mapped to test occupancy identifiers; non-switchable relationships are mapped to restricted node identifiers; and power-down pass-through maintenance relationships are mapped to power-down pass-through failure identifiers. When the pre-approval bottleneck constraint value is greater than or equal to the pre-approval threshold, the current candidate path is retained, and the corresponding pre-approval bottleneck constraint value is written into the candidate feasible subgraph set. The prohibition reason set includes board mismatch identifiers, interface conflict identifiers, role mismatch identifiers, protection occupancy identifiers, test occupancy identifiers, restricted node identifiers, and power-down pass-through failure identifiers.

[0039] This implementation plan significantly improves the interpretability and traceability of pre-scheduling review, enabling operations and maintenance personnel to quickly locate the root cause of failures and assist in subsequent path adjustments or manual intervention. For paths that meet the conditions, their pre-scheduling bottleneck constraint values ​​are written into the candidate feasible subgraph set, ensuring that the scheduling process only handles paths that have passed feasibility proofs. This effectively reduces the risk of invalid attempts and resource conflicts, and improves the overall efficiency and success rate of remote cross-scheduling.

[0040] Specifically, the process of conducting perturbation benefit analysis based on the candidate feasible subgraph set is as follows: Based on the candidate feasible subgraph set, a relationship inheritance comparison method is used to match the port relationships, protection relationships, and test relationships in the current candidate scheme with the existing relationship mappings in the wiring resource graph. The number of port relationships, protection relationships, and test relationships that can be directly used is counted to obtain the reusable quantity. A relationship difference detection method is used to compare the target mapping relationship under the current candidate scheme with the existing mapping relationship item by item, and the number of port mapping relationships, protection mapping relationships, and test mapping relationships that need to be modified is counted to obtain the number of ports to be adjusted, the number of protection relationships to be adjusted, and the number of tests to be adjusted, respectively. An object identifier association retrieval method is used to extract the association records corresponding to the objects involved in the current candidate scheme, and the records are traversed and counted according to the anomaly marker field and the verification pass marker field to obtain the number of abnormal associations and the number of verification passes. The anomaly marker field originates from the markings applied to data records of role conflicts, occupancy conflicts, and relationship breaks during the construction of the wiring resource graph. The anomaly association count represents the total number of records with the aforementioned anomaly markers in the nodes or edges involved in the candidate solution; a higher count indicates a greater potential risk of silent mismatch. The verification pass marker field originates from the pass markers generated after manual confirmation or automated backtesting verification following the execution of the scheduling task. The verification pass count represents the total number of records with the verification pass marker in the nodes or edges involved in the candidate solution; a higher count indicates stronger stability and verifiability of the corresponding object. By incorporating the anomaly association count and the verification pass count into the calculation of the solution benefit difference, the risk of silent mismatch caused by the selection of unstable or abnormal objects can be effectively suppressed, in addition to the reuse benefits, thereby improving the long-term reliability of the scheduling solution.

[0041] To analyze the benefits of the scheme's disturbance, add 1 to the number of reusable items and divide it by the sum of the number of ports to be adjusted, the number of protections to be adjusted, the number of tests to be adjusted, and the zero-prevention items to obtain the reuse ratio. Then, perform a hyperbolic tangent transformation on the reuse ratio to obtain the reuse benefit item. Divide the number of abnormal associations by the sum of the number of abnormal associations, the number of verification passes, and the zero-prevention items to obtain the abnormal risk item. Subtract the abnormal risk item from the reuse benefit item to obtain the scheme benefit difference value.

[0042] The specific formula for calculating the difference in returns between the two plans is as follows: ; In the formula, This represents the difference in benefits between the proposed solutions, used to characterize the priority of the current candidate solutions; This represents the number of reusable elements, used to characterize the degree to which the current candidate solution inherits from the existing relational structure; This indicates the number of ports to be adjusted, which characterizes the scale of port relationship adjustments made by the current candidate scheme. This indicates the number of protections to be adjusted, used to characterize the scale of adjustment to protection relationships by the current candidate scheme; This indicates the number of tests to be adjusted, used to characterize the scale of adjustment of the test relationship by the current candidate solution; This indicates the number of abnormal associations, used to characterize the abnormal activity level of the objects involved in the current candidate solution; This indicates the number of successful verifications, used to characterize the stability and verifiability of the objects involved in the current candidate solution; This indicates the zero-preservation term, which is obtained by setting a very small positive constant and is used to avoid the denominator being zero.

[0043] This implementation plan effectively balances the inheritance of existing relationships with the disturbance costs brought about by adjustments, while suppressing the risk of silent mismatch caused by the selection of abnormal or unverified objects. This evaluation method provides a scientific and quantifiable decision-making basis for the selection of optimal solutions for remote cross-scheduling tasks, significantly improving the long-term stability, resource utilization efficiency, and operational reliability of scheduling schemes, and reducing the probability of potential failures caused by frequent adjustments or abnormal reuse.

[0044] Specifically, the process of identifying the preferred crossover scheme and generating a scheme-level scheduling record is as follows: The system compares the difference in revenue between candidate solutions in real time and selects the candidate solution with the largest difference as the preferred cross solution. When multiple candidate solutions have the same difference in revenue or the difference is less than the threshold, the system further compares the corresponding pre-approval bottleneck constraint values ​​and selects the candidate solution with the largest pre-approval bottleneck constraint value as the preferred cross solution. The prohibition reason field records the structured prohibition proof information set output when the candidate solution is determined not to meet the feasibility proof conditions during the pre-approval stage. This set includes the bottleneck constraint item that caused the failure, the unique identifier of the triggered constraint item, and the corresponding graph edge or node identifier. This set is mapped from the constraint conflict items after the candidate path is eliminated, specifically including board mismatch identifier, interface conflict identifier, role mismatch identifier, protection occupation identifier, test occupation identifier, restricted node identifier, and power failure pass-through destruction identifier. For the finally selected preferred cross solution, this field is empty, indicating no prohibition reason. The preferred cross solution is structured and bound with the task number, source object identifier, target object identifier, business type identifier, solution revenue difference value, pre-approval bottleneck constraint value, and prohibition reason to generate a solution-level scheduling record.

[0045] like Figure 4The bar chart comparing reuse benefits and abnormal risks, with candidate solutions on the horizontal axis and index values ​​on the vertical axis, uses blue bars to represent reuse benefits and red bars to represent abnormal risks, visually comparing the overall performance of each solution in terms of benefits and risks. The data shows that Solution D has the highest reuse benefit index value at 0.95, while its abnormal risk index value is the lowest at only 0.02, resulting in the best overall performance. Solution B has a reuse benefit index value of 0.91, second only to Solution D, and an abnormal risk index value of 0.06, showing good overall performance. Solutions A and E have reuse benefit index values ​​of 0.78 and 0.73 respectively, and abnormal risk index values ​​of 0.06 and 0.05 respectively, placing them at a moderate level. Solution C has the lowest reuse benefit index value at 0.62 and an abnormal risk index value of 0.06, resulting in the weakest overall performance. This chart clearly quantifies the benefit-risk balance level of each candidate solution, providing an intuitive visual basis for solution selection and decision-making.

[0046] This implementation scheme achieves automatic optimization and conflict avoidance of candidate schemes by comparing the difference in benefits between schemes and the pre-screening bottleneck constraint value in real time. When the benefit difference values ​​are similar, the pre-screening bottleneck constraint value is introduced as a secondary criterion to ensure the robustness and overall optimality of the optimization result. This significantly improves the efficiency and accuracy of identifying the optimal scheme in remote cross-scheduling tasks, reduces the cost of manual comparison, and enhances the traceability and subsequent auditing capabilities of the task by fully recording scheduling information, effectively ensuring the security and reliability of scheduling execution.

[0047] Specifically, the process of evaluating the coordination of scheduling consistency based on the preferred crossover scheme is as follows: Based on the preferred cross-connect scheme, a mapping consistency comparison method is used, with port number pairs and cross-connection identifiers as matching keys, to match the current task with the target mapping relationship in the preferred cross-connect scheme item by item. The verification records of consistent and inconsistent matches are counted to obtain the number of consistent and inconsistent verification items. A protection relationship backtracking comparison method is used, with protection group identifiers and primary / backup port binding relationships as comparison benchmarks, to compare the protection relationship after the current task execution with the protection mapping relationship corresponding to the preferred cross-connect scheme item by item. The number of consistent and deviating protection relationships is counted, and the response timeout records of each monitoring point are traversed to obtain the number of consistent and inconsistent protections. An integrity check method is used to count the monitoring data that the current task did not return during the consistency verification process to obtain the number of missing monitoring items. All monitoring data involved in the verification are counted, including latency test data, telephone status data, AC / DC voltage test data, insulation resistance test data, loop resistance test data, and optical cable monitoring data, to obtain the total number of monitoring items.

[0048] The verification item is obtained by dividing the number of consistent verification items by the sum of the number of consistent verification items, the number of inconsistent verification items, and the zero-prevention items. The protection item is obtained by dividing the number of consistent protection items by the sum of the number of consistent protection items, the number of inconsistent protection items, and the zero-prevention items. The monitoring ratio is obtained by dividing the number of missing monitoring items by the total number of monitoring items and the sum of the zero-prevention items. The monitoring item is obtained by subtracting the monitoring ratio from one. The average index is obtained by adding the verification items, protection items, and monitoring items and then dividing by three. The squares of the differences between the verification items and the average index, the protection items and the average index, and the monitoring items and the average index are calculated respectively. The square root of the sum of the three squared differences is then used to obtain the discrete item. The scheduling consistency coordination value is obtained by dividing the average index by 1 and the sum of the discrete items. The coordination of scheduling consistency is then evaluated.

[0049] The reason for using a combination of average indicators and discrete terms instead of a single weighted average is that consistent scheduling requires not only high values ​​for the verification, protection, and monitoring items individually, but also balanced coordination among them. Using only the average indicator might result in one item being extremely high while the other two are low. Although the average value may still be acceptable, in actual scheduling, this could lead to hidden faults due to deviations in protection relationships or missing monitoring data. The discrete term quantifies the degree of deviation among the three. Dividing the average indicator by one and adding the discrete term penalizes scheduling results with significant imbalances, thereby more accurately identifying the optimal cross-scheme with good coordination among the verification, protection, and monitoring dimensions. This effectively reduces subsequent operational risks caused by mismatched protection relationships or monitoring blind spots.

[0050] The specific formula for calculating the scheduling consistency coordination value is as follows: ; In the formula, This represents the scheduling consistency coordination value, which characterizes the degree of consistency between the current task execution feedback and the expected scheduling mapping, as well as the degree of balance among the consistency components. This refers to a verification item, used to characterize the degree of consistency between line verification data, voice verification data, electrical test data, or optical cable test data and the expected scheduling mapping. This represents a protection item, used to characterize the degree of consistency between the protection mapping after the current task is executed and the protection mapping during the pre-screening stage; This refers to a monitoring item, which characterizes the completeness of the monitoring evidence returned during the consistency verification process of the current task.

[0051] This implementation plan can more accurately identify well-coordinated scheduling results across the three dimensions, providing a scientific and balanced quantitative basis for post-event verification and quality evaluation of remote cross-scheduling tasks. It significantly improves the reliability, stability, and maintainability of scheduling execution and reduces potential risks caused by deviations in protection relationships or missing monitoring data.

[0052] Specifically, the process of performing consistency checks on the current task and generating scheduling data tags is as follows: The system compares the scheduling consistency coordination value with the scheduling consistency threshold in real time. When the scheduling consistency coordination value is greater than or equal to the scheduling consistency threshold, the current task is determined to have passed the consistency check. The scheduling consistency coordination value is then written into the wiring resource graph, completing the graph update. The nodes, node attributes, and corresponding edge relationships corresponding to the current task are synchronously refreshed to form the current wiring relationships. The scope of synchronous refresh includes: the mapping relationship between ports, the protection relationship between primary and backup, the test relationship between test tasks and ports, and the observation relationship between monitoring objects and links. The refresh strategy adopts a full replacement method, that is, the latest relationship state after the current task is executed overwrites the original relationship in the graph. If any write failure or graph constraint conflict occurs during the refresh process, a transaction rollback is triggered to restore the graph state before the refresh, and the rollback reason is recorded in the abnormal pending set. When the scheduling consistency coordination value is less than the scheduling consistency threshold, the current task is determined to have a consistency anomaly. An anomaly reason identifier is output, and the anomaly type corresponding to the current task is written into the abnormal pending set.

[0053] The consistency judgment data, task number, source object identifier, target object identifier, business type identifier, pre-approval bottleneck constraint value, solution benefit difference value, scheduling consistency coordination value, and time information of the current task are structurally bound to generate scheduling data tags. After the task is completed, all scheduling data tags are summarized to generate a remote cross-scheduling consistency analysis report. The remote cross-scheduling consistency analysis report includes task pass distribution, task anomaly distribution, silent mismatch distribution, protection deviation distribution, test conflict distribution, monitoring missing distribution, and candidate recovery relationship statistics, which are used to characterize the overall consistency status of various scheduling tasks in the pre-approval, execution, and verification stages.

[0054] like Figure 5 The distribution chart of remote cross-scheduling anomaly types, with anomaly type on the vertical axis and occurrence frequency on the horizontal axis, visually presents the frequency distribution of various scheduling anomalies. Among them, board mismatch occurs most frequently, making it the most common anomaly type in remote cross-scheduling; monitoring failure occurs next, belonging to high-frequency anomalies; interface conflict, protection deviation, role mismatch, and test conflict occur in descending order of frequency, belonging to medium-frequency anomalies; power failure and pass-through failure occur least frequently, representing a relatively occasional anomaly type. This chart clearly quantifies the frequency of various anomalies, identifies high-frequency risk points in the scheduling process, and provides data support for targeted optimization of the scheduling process and the development of anomaly prevention strategies.

[0055] In this implementation plan, the port mappings, protection relationships, test relationships, and observation relationships in the wiring resource graph are refreshed synchronously through a full replacement method, ensuring that the current wiring status and execution results are strictly consistent. A transaction rollback mechanism is introduced to automatically restore the state before the refresh and record the cause of the abnormality when a write fails or a graph constraint conflict occurs, effectively ensuring data consistency and system robustness.

[0056] Specifically, the second aspect of this invention provides a communication equipment room wiring control system based on remote cross-scheduling, applied to a communication equipment room wiring control method based on remote cross-scheduling, comprising: a resource graph construction module, used to collect data on heterogeneous wiring objects participating in remote cross-scheduling within the communication equipment room throughout the entire process; the collection interface includes a Simple Network Management Protocol (SMMP) interface and a Message Queue Telemetry Transmission (MQT) interface; the sampling period is thirty seconds; the collection objects cover equipment room objects, chassis objects, slot objects, board objects, port objects, link objects, protection objects, test objects, and monitoring objects; to obtain wiring resource status data and construct a wiring resource graph; and a constraint compilation module, used to parse the scheduling task based on the wiring resource graph, decompose the natural language requirements in the task into a list of attribute-value pairs, map them to the attribute fields of graph nodes or edges, and generate a set of allowed connection pairs and a set of prohibited connection pairs. The system consists of a set of node sequences and a set of continuity conditions to form a task constraint expression set, and evaluates the feasibility of candidate paths to generate a set of candidate feasible subgraphs. A scheme disambiguation module performs scheme perturbation benefit analysis based on the candidate feasible subgraph set. During the analysis, it counts the number of reusable items, the number of ports to be adjusted, the number of protections to be adjusted, the number of tests to be adjusted, the number of anomaly associations, and the number of successful verifications. It calculates the scheme benefit difference by subtracting the anomaly risk from the reuse benefit item, identifies the preferred cross-scheme, and generates a scheme-level scheduling record. A consistency verification module evaluates the coordination of scheduling consistency based on the preferred cross-scheme, performs consistency verification on the current task, compares the scheduling consistency coordination value with the scheduling consistency threshold, and refreshes the mapping relationships, protection relationships, test relationships, and observation relationships in the graph if they pass; otherwise, it outputs an anomaly cause identifier and generates scheduling data labels.

[0057] This implementation plan achieves full automation and intelligence in the management and control of cabling in communication equipment rooms through the collaborative work of four modules: resource graph construction, constraint compilation, scheme disambiguation, and consistency verification. The system can collect the status of heterogeneous cabling objects in real time and build a unified resource graph, providing a precise data foundation for remote scheduling.

[0058] It should be noted that, in this document, relational terms such as "first" and "second" are used only 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 process, method, article, or apparatus.

[0059] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to the specific implementations described. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, thereby enabling those skilled in the art to better understand and utilize the invention. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A communication room distribution management method based on remote cross-scheduling, characterized in that, Includes the following steps: S1 collects data on the heterogeneous wiring objects participating in remote cross-scheduling within the communication equipment room throughout the entire process, obtains wiring resource status data, and constructs a wiring resource map; S2, based on the wiring resource graph, the scheduling task is parsed to generate a set of task constraint expressions, and the feasibility of candidate paths is evaluated to generate a set of candidate feasible subgraphs; S3, based on the candidate feasible subgraph set, performs scheme disturbance benefit analysis, identifies the preferred cross scheme, and generates scheme-level scheduling records; S4 evaluates the coordination of scheduling consistency based on the preferred crossover scheme, performs consistency verification on the current task, and generates scheduling data labels.

2. The method of claim 1, wherein the method further comprises: The specific process of collecting data on the heterogeneous cabling objects participating in remote cross-connection scheduling within the communication equipment room, obtaining cabling resource status data, and constructing a cabling resource map is as follows: The entire process of data collection in the communication equipment room is performed to obtain wiring resource status data. The wiring resource status data includes: equipment room number, chassis number, slot number, board type, board number, port number, port direction identifier, interface type, signal type, framing attribute, user side identifier, equipment side identifier, current cross-connection identifier, protection occupancy identifier, test occupancy identifier, delay test data, telephone status data, AC voltage test data, DC voltage test data, insulation resistance test data, loop resistance test data, and optical cable monitoring data. The wiring resource status data is uniformly correlated with the device local time, gateway reception time, and platform entry time. Integrity verification, consistency check, anomaly marking, and minimum-maximum normalization are performed on the wiring resource status data. Hierarchical object identifiers are constructed using room number, chassis number, slot number, board number, and port number. The connection relationships between ports, the occupancy relationships between objects, the protection relationships between primary and backup, the testing relationships between test tasks and ports, and the observation relationships between monitoring objects and link objects are uniformly correlated to construct a wiring resource map.

3. The method of claim 1, wherein the method further comprises: The specific process of parsing the scheduling task based on the wiring resource graph to generate a task constraint expression set is as follows: Extract local subgraphs related to the current task from the wiring resource graph. The local subgraphs include source nodes, target nodes, intermediate transfer nodes, protection-related nodes, and test-related nodes. Using interface type, signal type, framing attribute, port direction, time slot occupancy status, protection group identifier, and test access point identifier as matching criteria, decompose each natural language statement into a list of attribute and value pairs for the role correspondence requirements, service adaptation requirements, protection maintenance requirements, test isolation requirements, path continuity requirements, and power failure path maintenance requirements in the remote cross-scheduling task. Establish a correspondence between these lists and the attribute fields of nodes or edges in the graph. Generate specific constraint expressions based on the mapping results, and convert them into sets of allowed connection pairs, prohibited connection pairs, node sequences or edge sequences, and spatial or electrical continuity conditions to form a task constraint expression set.

4. The method of claim 1, wherein the method further comprises: The specific process for evaluating the feasibility of candidate paths is as follows: Based on the task constraint expression set, constraint matching is performed on each candidate connection chain in the local subgraph, and the number of connection segments in the current candidate path is counted to obtain the number of compatible links. The number of conflicting connection segments in the current candidate path is calculated by counting the number of connection segments that have board mismatch, interface mismatch, or role mismatch. The number of consecutive valid connection segments in the current candidate path is calculated by counting the number of connection segments that maintain the continuity between the preceding and following connections. The total number of candidate segments is calculated by counting the total number of connection segments in the current candidate path. The number of data relationships that can maintain the original power-down pass-through association in the current candidate path is calculated by counting the number of relationships that would break the original power-down pass-through association in the current candidate path. The number of protected nodes, test nodes, and restricted nodes in the current candidate path are calculated by counting the number of nodes occupied by protected relationships, the number of nodes occupied by test tasks, and the number of intermediate nodes marked as non-switchable. Divide the number of compatible items by the sum of the number of compatible items, the number of conflicting items, and the zero-prevention items to obtain the compatibility satisfaction items; The path continuity term is obtained by dividing the number of consecutive valid segments by the sum of the total number of candidate segments and the zero-prevention term. The path continuity term is obtained by dividing the number of maintenance relationships by the sum of the number of maintenance relationships, the number of destruction relationships, and the zero-prevention term. The path continuity term is obtained by selecting the minimum value from the compatibility satisfaction term, the path continuity term, and the path continuity term. The logarithmic operation is performed by adding the number of protected nodes, the number of tested nodes, and the number of restricted nodes, and then adding the constant term 1 to the logarithmic operation result. The constraint term is obtained by adding the constant term 1 to the logarithmic operation result. The path bottleneck term is divided by the constraint term to obtain the pre-examination bottleneck constraint value, which is used to evaluate the feasibility of the candidate path.

5. The method of claim 1, wherein the method further comprises: The specific process for generating the candidate feasible subgraph set is as follows: The system compares the pre-approval bottleneck constraint value with the pre-approval threshold in real time. When the pre-approval bottleneck constraint value is less than the pre-approval threshold, the current candidate path is determined not to meet the feasibility proof conditions before scheduling. The current candidate path is then removed from the list of candidate paths to be executed, and structured prohibition proof information is output, including the bottleneck constraint item that caused the failure, the unique identifier of the triggered constraint item, and the corresponding graph edge identifier or node identifier. A set of prohibition reasons corresponding to the current candidate path is generated. When the pre-approval bottleneck constraint value is greater than or equal to the pre-approval threshold, the current candidate path is retained, and the pre-approval bottleneck constraint value corresponding to the current candidate path is written into the candidate feasible subgraph set.

6. The method of claim 1, wherein the method further comprises: The specific process of performing the perturbation benefit analysis based on the candidate feasible subgraph set is as follows: Based on the candidate feasible subgraph set, the port relationships, protection relationships, and test relationships in the current candidate scheme are matched with the existing relationship mappings in the wiring resource graph using the relationship inheritance comparison method. The number of port relationships, protection relationships, and test relationships that can be directly used is counted to obtain the reusable quantity. The target mapping relationship under the current candidate scheme is compared with the existing mapping relationship item by item using the relationship difference detection method. The number of port mapping relationships, protection mapping relationships, and test mapping relationships that need to be modified is counted to obtain the number of ports to be adjusted, the number of protection relationships to be adjusted, and the number of tests to be adjusted, respectively. By using the object identifier association retrieval method, the associated records corresponding to the objects involved in the current candidate solution are extracted, and the abnormal association count and the verification pass count are obtained by traversing and counting according to the abnormal flag field and the verification pass flag field respectively. To analyze the benefits of the scheme's disturbance, add 1 to the number of reusable items and divide it by the sum of the number of ports to be adjusted, the number of protections to be adjusted, the number of tests to be adjusted, and the zero-prevention items to obtain the reuse ratio. Then, perform a hyperbolic tangent transformation on the reuse ratio to obtain the reuse benefit item. Divide the number of abnormal associations by the sum of the number of abnormal associations, the number of verification passes, and the zero-prevention items to obtain the abnormal risk item. Subtract the abnormal risk item from the reuse benefit item to obtain the scheme benefit difference value.

7. The method of claim 1, wherein the method further comprises: The specific process of identifying the preferred crossover scheme and generating a scheme-level scheduling record is as follows: The system compares the difference in revenue between each candidate solution in real time and selects the candidate solution with the largest difference in revenue as the preferred cross solution. When multiple candidate solutions have the same difference in revenue or the difference is less than the difference threshold, the system further compares the corresponding pre-approval bottleneck constraint values ​​and selects the candidate solution with the largest pre-approval bottleneck constraint value as the preferred cross solution. The preferred cross solution is then structured and bound to the task number, source object identifier, target object identifier, business type identifier, difference in revenue, pre-approval bottleneck constraint value, and prohibition reason to generate a solution-level scheduling record.

8. The communication equipment room wiring control method based on remote cross-scheduling according to claim 1, characterized in that: The specific process for evaluating the coordination of scheduling consistency based on the preferred crossover scheme is as follows: Based on the preferred cross scheme, the mapping consistency comparison method is used to match the current task with the target mapping relationship in the preferred cross scheme item by item. The verification records with consistent and inconsistent matching are counted to obtain the number of consistent verification items and the number of inconsistent verification items. By using the protection relationship backtracking comparison method, the protection relationships after the current task is executed are compared item by item with the protection mapping relationships corresponding to the preferred cross scheme. The number of protection relationships that are consistent and those that have deviated is counted to obtain the number of consistent protections and the number of inconsistent protections. By using the integrity check method, the monitoring data that was not returned during the consistency verification process of the current task is counted to obtain the number of missing monitoring items. The total number of monitoring items is obtained by statistically analyzing all monitoring data involved in the verification. The verification item is obtained by dividing the number of consistent verification items by the sum of the number of consistent verification items, the number of inconsistent verification items, and the zero-prevention item. The protection item is obtained by dividing the consistent protection quantity by the sum of the consistent protection quantity, the inconsistent protection quantity, and the zero-prevention item; The monitoring ratio is obtained by dividing the number of missing monitoring items by the sum of the total number of monitoring items and the zero-prevention items. The monitoring items are obtained by subtracting the monitoring ratio from one. The average index is obtained by adding the verification items, protection items, and monitoring items and then dividing by three. The squares of the differences between the verification items and the average index, the protection items and the average index, and the monitoring items and the average index are calculated respectively. The squares of the three differences are added together, divided by three, and then the square root is taken to obtain the discrete items. The scheduling consistency coordination value is obtained by dividing the average index by 1 and the sum of the discrete items. The coordination of scheduling consistency is evaluated.

9. The communication equipment room wiring control method based on remote cross-scheduling according to claim 1, characterized in that: The specific process of performing consistency verification on the current task and generating scheduling data tags is as follows: The scheduling consistency coordination value is compared with the scheduling consistency threshold in real time. When the scheduling consistency coordination value is greater than or equal to the scheduling consistency threshold, it is determined that the current task has passed the consistency check. The nodes, node attributes and corresponding edge relationships of the current task are synchronously refreshed to form the current wiring relationship. When the scheduling consistency coordination value is less than the scheduling consistency threshold, it is determined that there is a consistency anomaly in the current task, and the anomaly cause identifier is output. The consistency judgment data, task number, source object identifier, target object identifier, business type identifier, pre-approval bottleneck constraint value, solution benefit difference value, scheduling consistency coordination value and time information of the current task are structured and bound to generate scheduling data tags.

10. A communication room distribution management system based on remote cross-scheduling, applying the communication room distribution management method based on remote cross-scheduling according to any one of claims 1-9, characterized in that, include: The resource map construction module is used to collect data on heterogeneous wiring objects participating in remote cross-scheduling within the communication equipment room throughout the entire process, obtain wiring resource status data, and construct a wiring resource map. The constraint compilation module is used to parse the scheduling task based on the wiring resource graph, generate a set of task constraint expressions, evaluate the feasibility of candidate paths, and generate a set of candidate feasible subgraphs. The scheme disambiguation module is used to perform scheme perturbation benefit analysis based on the candidate feasible subgraph set, identify the preferred cross scheme, and generate scheme-level scheduling records. The consistency verification module is used to evaluate the coordination of scheduling consistency based on the preferred crossover scheme, perform consistency verification on the current task, and generate scheduling data tags.

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