Dynamic Reconfiguration and Optimization Methods and Systems for Communication Network Topology

Abstract

This application provides a method and system for dynamic reconfiguration and optimization of communication network topology, relating to the field of communication network technology. First, it acquires dynamic information on node operation, real-time information on link transmission, and dynamic data on network service requirements of the communication network. Based on the former two, it generates a network topology elastic association body containing various association rules and logic. It then inputs the service requirement data into the network topology elastic association body to generate a network topology dynamic requirement adaptation factor. Based on the network topology dynamic requirement adaptation factor and the network topology elastic association body, it generates a network topology reconfiguration path self-adaptation sequence containing specific operation instructions and timing. Finally, it adjusts node connection modes and link transmission configurations in a coordinated manner according to the network topology reconfiguration path self-adaptation sequence, synchronously updating association rules to complete dynamic reconfiguration and optimization. This invention improves network stability, reliability, and resource utilization.

Description

Technical Field

[0001] This application relates to the field of communication network technology, and more specifically, to a dynamic reconfiguration and optimization method and system for communication information network topology. Background Technology

[0002] In today's digital age, communication and information networks, as key infrastructure for information transmission and interaction, are of paramount importance in terms of stability and efficiency. With the increasing diversification and complexity of network services, such as high-definition video streaming, large-scale data transmission, and real-time online interaction, higher demands are being placed on the performance of communication and information networks.

[0003] Most existing communication network topologies are statically designed, constructed during the initial planning stage based on anticipated business needs and network scale. However, in actual operation, the working status and resource usage of network nodes change continuously over time. For example, some nodes may experience performance degradation due to hardware failures, software upgrades, or high load operation; link transmission rates and loads also change dynamically due to fluctuations in business traffic. Differences in business traffic at different times may cause some links to become congested, while other links remain idle.

[0004] Meanwhile, network service demands are not static. Service transmission requirements change with factors such as the number of users, service types, and usage time, and service priorities may also be adjusted based on importance and urgency. However, the existing network topology cannot detect these dynamic changes in a timely manner and is difficult to adjust flexibly according to actual needs. This leads to unreasonable allocation of network resources, with some areas experiencing resource shortages while others are idle, reducing the overall network performance and resource utilization, and failing to meet the ever-growing and changing service demands. Summary of the Invention

[0005] In view of this, the purpose of this application is to provide a method and system for dynamic reconfiguration and optimization of communication information network topology.

[0006] According to a first aspect of this application, a dynamic reconfiguration optimization method for communication information network topology is provided, the method comprising:

[0007] The system acquires dynamic information on node operation, real-time information on link transmission, and dynamic data on network service requirements of the communication information network. The dynamic information on node operation includes node working status data and node resource usage data. The real-time information on link transmission includes link transmission rate data and link load data. The dynamic data on network service requirements includes data on changes in service transmission requirements and data on adjustments to service priorities.

[0008] Based on the node's dynamic operating information and the link's real-time transmission information, a network topology elastic association body is generated. The network topology elastic association body includes node dynamic association rules, link dynamic association rules, and the linkage association logic between nodes and links.

[0009] The network service requirement dynamic data is input into the network topology elastic association body. Through the node dynamic association rules, link dynamic association rules and linkage association logic, a network topology dynamic requirement adaptation factor is generated. The network topology dynamic requirement adaptation factor includes node adaptation requirement data and link adaptation requirement data.

[0010] Based on the network topology dynamic demand adaptation factor and the network topology elastic association, a network topology reconstruction path self-adaptation sequence is generated. The network topology reconstruction path self-adaptation sequence includes a node connection reconstruction sub-sequence and a link transmission reconstruction sub-sequence. Each sub-sequence contains specific reconstruction operation instructions and operation timing.

[0011] According to the self-adaptive sequence of the network topology reconstruction path, the connection mode of network nodes and the transmission configuration of network links are adjusted in a coordinated manner, and the dynamic association rules of nodes and links in the network topology elastic association body are updated synchronously to complete the dynamic reconstruction and optimization of the communication information network topology.

[0012] According to a second aspect of this application, a dynamic reconfiguration optimization system for communication information network topology is provided. The dynamic reconfiguration optimization system for communication information network topology includes a machine-readable storage medium and a processor. The machine-readable storage medium stores machine-executable instructions. When the processor executes the machine-executable instructions, the dynamic reconfiguration optimization system for communication information network topology implements the aforementioned dynamic reconfiguration optimization method for communication information network topology.

[0013] According to a third aspect of this application, a computer-readable storage medium is provided, wherein computer-executable instructions are stored therein, and when the computer-executable instructions are executed, the aforementioned dynamic reconfiguration optimization method for communication information network topology is implemented.

[0014] Based on any of the above aspects, the technical effect of this application is as follows:

[0015] By acquiring dynamic information on node operation, real-time information on link transmission, and dynamic data on network service requirements of the communication and information network, a network topology elastic association body is generated based on the above information. This body includes dynamic node association rules, dynamic link association rules, and linkage association logic between nodes and links. It can dynamically reflect the complex relationships between nodes and links. The dynamic network service requirement data is input into the network topology dynamic requirement adaptation factor generated by the network topology elastic association body, which reflects the adaptation of nodes and links to service requirements. The network topology reconstruction path self-adaptation sequence generated based on the network topology dynamic requirement adaptation factor and the elastic association body contains specific reconstruction operation instructions and operation timing. The connection mode of network nodes and the transmission configuration of network links are adjusted in linkage according to the self-adaptation sequence, and the association rules in the elastic association body are updated synchronously. This completes the dynamic reconstruction and optimization of the communication and information network topology, enabling the network to adapt to the dynamic changes of nodes, links, and service requirements in real time. This improves the stability, reliability, and resource utilization of the network, and effectively enhances the overall performance of the communication and information network. Attached Figure Description

[0016] Figure 1 A flowchart illustrating the dynamic reconfiguration and optimization method for communication information network topology provided in an embodiment of this application is shown.

[0017] Figure 2 This illustration shows a schematic diagram of the component structure of a dynamic reconfiguration optimization system for communication information network topology, provided in an embodiment of this application, for implementing the above-described dynamic reconfiguration optimization method for communication information network topology. Detailed Implementation

[0018] Figure 1 This paper illustrates a flowchart of a dynamic reconfiguration and optimization method and system for communication information network topology provided in an embodiment of this application. The detailed steps include:

[0019] Step S110: Obtain dynamic information on node operation, real-time information on link transmission, and dynamic data on network service requirements of the communication information network. The dynamic information on node operation includes node working status data and node resource usage data. The real-time information on link transmission includes link transmission rate data and link load data. The dynamic data on network service requirements includes data on changes in service transmission requirements and data on adjustments to service priorities.

[0020] This embodiment uses an enterprise data center communication network as an application scenario. This network consists of multiple core switches, access switches, server nodes, and transmission links, carrying various services such as internal office work, data storage, and application services. During the data acquisition phase, a distributed, multi-dimensional acquisition architecture is adopted. An in-band acquisition agent is deployed at each network node, periodically collecting node operating status data via network management protocols. This includes parameters such as device CPU load, memory usage, port data packet transmission and reception statistics, and power module voltage. The sampling interval is dynamically adjusted based on parameter importance, with shorter sampling intervals for key parameters at core nodes compared to edge nodes. Node resource usage data covers virtual LAN partitioning configuration, port binding status, and link aggregation group member information, and is updated in real-time through a device configuration database. In real-time link transmission information, transmission rate data is collected using a port counter to measure the physical layer transmission bit rate, and load data is analyzed using deep packet inspection technology to determine the application layer traffic share and differentiate bandwidth usage for different service types. Dynamic data on network service requirements is pushed by the service management platform, which includes records of changes in the service quality level protocol parameters of each service, such as adjustments to the minimum bandwidth guarantee value for video conferencing services and changes to the transmission delay tolerance for database backup services. At the same time, it receives priority ranking updates based on the importance of the services.

[0021] During data transmission, all collected data is transmitted to the data processing center through an encrypted tunnel. Fields containing sensitive information such as device serial numbers and IP addresses are hash-desensitized to ensure that data collection complies with data security standards.

[0022] Step S120: Based on the node's dynamic operating information and the link's real-time transmission information, generate a network topology elastic association body. The network topology elastic association body includes node dynamic association rules, link dynamic association rules, and the linkage association logic between nodes and links.

[0023] After acquiring dynamic information on node operation and real-time information on link transmission, the data is first preprocessed. Time-series data in the node operating status data is smoothed to eliminate noise, and the average load and fluctuation coefficient of the link transmission data are calculated using a sliding window statistical method. An association rule mining algorithm is used to analyze the dynamic information on node operation, identifying state transition relationships and resource consumption patterns between nodes. Reasonable support and confidence thresholds are set to filter out statistically significant node association rules. Cluster analysis is used to classify load levels in the real-time information on link transmission, establishing a mathematical model between link load and transmission rate, and determining the characteristic parameters of transmission rate under different load levels. A directed graph model is used to associate the dynamic association rules of nodes and links, defining the conditions that trigger link adjustments due to node state changes and the impact logic of link state changes on node configuration, forming a linkage logic between nodes and links. The dynamic association rules of nodes, links, and linkage logic are integrated to construct the basic framework of a resilient network topology.

[0024] Step S121: Extract the node working status data and node resource usage data from the node running dynamic information, and divide the node running dynamic information into related dimensions, which include the node's own status dimension and the interaction dimension between nodes.

[0025] The node operational dynamics data is separated into two subsets: node operational status data and node resource usage data. The node's own status dimension comprises multiple levels: the physical layer dimension includes hardware status parameters such as device temperature, power consumption, and fan speed; the data link layer dimension includes port link status, frame check error count, and MAC address table aging time; and the network layer dimension includes routing table update frequency, IP address conflict alarms, and ICMP round-trip time. The parameters of each dimension are weighted using a feature selection algorithm to select parameters that significantly impact node stability, forming a feature set. The inter-node interaction dimension is represented by a traffic matrix, with the horizontal dimension representing the source node identifier and the vertical dimension representing the destination node identifier. Matrix elements represent the number of bidirectional traffic bytes per unit time, while also recording interaction quality indicators such as session establishment success rate and connection hold time. A dimensionality reduction algorithm is used to process the high-dimensional interaction data, retaining the principal components that explain most of the variance as interaction features. During the partitioning process, a mapping table between dimensions is established, recording the dimension and data type of each parameter.

[0026] Step S122: Extract the link transmission rate data and link load data from the real-time link transmission information, and divide the link transmission real-time information into related dimensions. The related dimensions include the link's own transmission dimension and the link and node adaptation dimension.

[0027] Real-time link transmission information is separated into time series data for transmission rate and load distribution datasets. The link's own transmission dimension includes transmission performance metrics and physical characteristic metrics. Transmission performance metrics include throughput, packet loss rate, and latency jitter, collected through a combination of active probing and passive monitoring. Physical characteristic metrics include optical signal attenuation, link distance, and cable type, read through the device management interface. The link and node adaptation dimension focuses on analyzing the interface matching of nodes at both ends of the link, including port rate negotiation results, duplex mode consistency, and link aggregation protocol compatibility. It also records the node port's traffic control policies for the link, such as the status of pause frame mechanisms and priority traffic scheduling configurations. A multi-dimensional scaling analysis method is used to map the link data to a low-dimensional space, and link adaptation anomalies are identified through cluster density. After dimensional division, a binding table between link identifiers and node interfaces is established to ensure the traceability of the association between link data and node data.

[0028] Step S123: Based on the data analysis results of the node's own state dimension, generate node state association sub-rules in the node dynamic association rules. The node state association sub-rules are used to define the association relationship between different node working state data and node resource usage data.

[0029] A correlation analysis is performed on the node's own state dimension data. A sliding window technique is used to discretize continuous data into state intervals, with each parameter divided into three state levels: normal, warning, and alarm. Sequence pattern mining algorithms are used to identify causal relationships between state parameters, analyzing the response patterns of node resource usage data when different node operating state parameters change. Based on these correlations, node state correlation sub-rules are generated, clarifying the potential changes in node resource usage data, as well as the magnitude and trend of these changes, when a node's operating state data changes. The condition part of the rule includes the threshold range of the node's operating state parameters, and the conclusion part includes adjustment suggestions and expected change ranges for node resource usage data. Each sub-rule includes attributes such as a unique identifier, conditional expression, execution action, and confidence level, described and stored using a rule representation language.

[0030] Step S124: Based on the data analysis results of the inter-node interaction dimension, generate node interaction association sub-rules in the node dynamic association rules. The node interaction association sub-rules are used to define the connection response relationship between different nodes.

[0031] Time-series correlation analysis is performed on the traffic matrix data of inter-node interaction dimensions. A causal testing algorithm is used to identify traffic dependencies between nodes, determining the degree of influence and time delay between different nodes. A node interaction network is constructed based on a directed graph model, where nodes represent network devices and directed edge weights are interaction influence coefficients. The importance of a node in the interaction network is calculated using a centrality algorithm. Node interaction patterns are categorized into active request-passive response, bidirectional collaboration, and broadcast diffusion types. Response rules, such as connection establishment timeout thresholds, retry limit, and connection hold-up timer parameters, are defined for different types. The rules include a connection priority handling mechanism; when multiple nodes simultaneously request the same target node resource, the connection establishment order is determined based on the importance and business level of the requesting nodes. Node interaction correlation sub-rules adopt a production rule representation, and dynamic loading and matching execution are achieved through a rule engine.

[0032] Step S125: Based on the data analysis results of the link's own transmission dimension, generate link transmission association sub-rules in the link dynamic association rules. The link transmission association sub-rules are used to define the association relationship between different link transmission rate data and link load data.

[0033] Correlation analysis is performed on the transmission dimension data of the links themselves. A sliding window covariance calculation is used to compare the transmission rate time series with the load data to identify the rate variation patterns corresponding to different load intervals. An adaptive threshold algorithm is used to classify the link load levels, with each level corresponding to a set of transmission rate characteristic parameters, such as the rate fluctuation coefficient in the low load interval, the rate stability index in the medium load interval, and the rate attenuation curve in the high load interval. Based on these characteristics, a rate-load correlation model is established to generate rules that trigger rate adjustments when the load exceeds a certain level, including parameters such as adjustment direction, adjustment step size, and stabilization time. The rules include constraints on rate adjustments, such as optical module operating temperature limits and adjacent link rate matching requirements. A rule conflict detection algorithm ensures parameter consistency during multi-link adjustments. The link transmission correlation sub-rules are stored in a rule base, and version control mechanisms manage rule updates and iterations.

[0034] Step S126: Based on the data analysis results of the link and node adaptation dimension, generate link adaptation association sub-rules in the link dynamic association rules. The link adaptation association sub-rules are used to define the transmission adaptation relationship between the link and the node.

[0035] Pattern recognition is performed on link and node adaptation dimension data to extract matching features between node interface configurations and link performance parameters, analyzing link performance under different interface configurations. A classification algorithm is used to construct an adaptation status evaluation model, with input parameters including port rate configuration, duplex mode, and flow control policies, outputting adaptation status categories and optimization suggestions. Adaptation rules are generated based on the model output, including automatic adjustment logic for interface parameters. For example, when inconsistent rate negotiation is detected between the two ends of the link, the end with the higher configuration is automatically adjusted to auto-negotiation mode; when the link packet loss rate exceeds a threshold and abnormal flow control frame interaction is detected, the receiver buffer size is adjusted. The priority order of adaptation parameters is defined in the rules, such as security configuration taking precedence over performance configuration, and service assurance configuration taking precedence over default configuration, ensuring the correct execution order when multiple rules are triggered. Simultaneously, an adaptation rule exception list is established to mark link-node pairs with special configurations, preventing service interruptions caused by automatic adjustments.

[0036] Step S127: Merge the node state association sub-rules and the node interaction association sub-rules to form a node dynamic association rule.

[0037] A rule fusion method is employed to integrate two sub-rule sets. First, a rule conflict detection matrix is ​​established to analyze the overlap of rule conditions and the degree of contradiction in conclusions. Conflicting rules are prioritized based on their business impact, which is calculated by weighting factors such as the importance of the nodes involved, the number of affected users, and the level of associated business. For non-conflicting rules, combination rules are generated through conjunction operations on rule conditions to expand the applicable scenarios of the rules. The fused rule set is stored using a production rule representation. Each rule includes attributes such as a unique identifier, a set of preconditions, a sequence of execution actions, and rule weights, and is dynamically loaded and executed through a rule interpreter. A conflict resolution log is generated during the rule fusion process, recording the identifier and reason for the overwritten rule, facilitating subsequent rule optimization and auditing.

[0038] Step S128: Merge the link transmission association sub-rule and the link adaptation association sub-rule to form a link dynamic association rule.

[0039] Link transmission-related sub-rules and link adaptation-related sub-rules are fused, and fuzzy logic theory is used to handle the uncertainty of rule conditions. The rate threshold in the transmission rules and the parameter configuration in the adaptation rules are converted into fuzzy sets, and fuzzy membership functions are defined to describe the degree of condition satisfaction. A fuzzy inference engine is used to combine rules and generate comprehensive decisions, such as "when the link load is high and the node interface buffer is insufficient, simultaneously perform link speed reduction and buffer expansion operations." The hierarchical relationship of links is considered during rule fusion, with core link rules having higher priority than access link rules, and primary link rules taking precedence over backup link rules. The fused rules are grouped and stored according to link identifiers. Each group contains basic rules and exception rules. Basic rules apply to normal scenarios, while exception rules are for links with special configurations. The rule set includes version control information, supporting incremental updates and rollback operations. Rule validation tools ensure that the updated rule set is syntactically correct and free of infinite loops.

[0040] Step S129: Based on the node dynamic association rules and the link dynamic association rules, generate the linkage association logic between nodes and links. The linkage association logic is used to define the response relationship between node state changes and link transmission configuration adjustments.

[0041] A linkage and association model based on a directed hypergraph is constructed, where nodes represent network device states and hyperedges represent linkage rules involving multiple nodes and links. Vertex attributes of the hypergraph include device type, current state, and associated services, while hyperedge attributes include trigger conditions, execution actions, and recovery strategies. Causal relationship mining algorithms are used to identify the propagation paths between node state changes and link performance degradation, such as core switch CPU overload leading to increased routing computation latency, which in turn causes unbalanced traffic forwarding in downstream links. Linkage rules are generated based on the propagation paths, defining trigger thresholds and adjustment ranges. For example, when the memory utilization of a core node reaches a warning threshold, the transmission priority of non-critical service links passing through that node is automatically reduced. The linkage logic includes time constraints, such as the duration of continuous abnormal node states and the minimum interval for link adjustments, to avoid frequent triggering of adjustment operations. A state machine model is used to describe the linkage process, with each state corresponding to a set of rules. State transitions are event-driven, such as the "node returns to normal" event triggering link configuration rollback.

[0042] Step S1210: Integrate the node dynamic association rules, the link dynamic association rules, and the linkage association logic, supplement the dynamic association threshold parameters of nodes and links, and generate a network topology elastic association body.

[0043] The dynamic association rules for nodes, links, and linkage logic are integrated into a unified network topology elastic association body. An ontology model is used to represent the knowledge structure, defining classes, attributes, and relationships. Node rule classes include subclasses of state rules and interaction rules; link rule classes include subclasses of transmission rules and adaptation rules; and linkage logic classes include attributes such as trigger conditions and action sequences. An ontology inference engine enables automatic rule expansion and conflict detection. Dynamic association threshold parameters are determined using statistical process control methods. Historical normal operation data is collected to calculate control limits as initial threshold values, which are then dynamically adjusted based on seasonal factors and business growth trends. Threshold parameters are grouped and managed according to device type and business importance, with core devices using stricter threshold standards. The topology elastic association body is stored using a distributed graph database, supporting efficient rule querying and association analysis. Rule matching and action execution services are provided externally through an application programming interface (API). API calls utilize an asynchronous message queue mechanism to ensure system stability under high concurrency scenarios.

[0044] For example, step S12101: extract the node state association sub-rules and node interaction association sub-rules from the node dynamic association rules, analyze the logical association relationship between the two sub-rules and record the associated nodes, and record the sub-rule call priority.

[0045] From the dynamic node association rule base, state-related sub-rule sets and interaction-related sub-rule sets are separated through rule type tags. Each sub-rule contains attributes such as rule identifier, conditional expression, action instruction, and applicable node scope. Logical implication analysis is used to identify the relationships between sub-rules. When the action result of a state rule is the conditional input of an interaction rule, a pre-sequence relationship is established between the rules; when the conditions of two sub-rules contain the same node attributes, a co-occurrence relationship is established. Relationships are recorded in a rule dependency graph, where nodes are rule identifiers and directed edges represent triggering relationships between rules. Associated nodes are determined by parsing the node identifier in the rule conditions; for example, if a rule condition contains "the port 1 status of node A," then node A is recorded as an associated node. Sub-rule invocation priority is determined using analytic hierarchy process (AHP), with evaluation indicators including rule impact scope, response time requirements, and business assurance level. The priority weight of each rule is calculated as the basis for decision-making in case of rule conflicts.

[0046] Step S12102: Extract the link transmission association sub-rule and the link adaptation association sub-rule from the link dynamic association rule, analyze the logical association relationship between the two sub-rules and record the association nodes, and record the sub-rule call priority.

[0047] Transmission and adaptation sub-rules are extracted from the dynamic association rule base of the links, and analysis methods similar to those used for node rules are employed. Link identifiers in the rule conditions are linked to the nodes at both ends, establishing a mapping relationship between link rules and nodes. Logical association analysis focuses on identifying the causal relationship between transmission and adaptation rules; for example, a port rate configuration error in an adaptation rule can trigger a rate threshold in a transmission rule. A Bayesian network model is used to calculate the conditional probability between rules, quantifying the strength of rule associations. Sub-rule invocation priority considers the link's Quality of Service (QoS) protocol parameters; links carrying high-priority services have higher rule priority than ordinary links. The execution cost of rules is also considered, with rules with lower adjustment costs being executed first. Priority calculation results are stored in rule metadata, supporting dynamic adjustments; the priority is automatically updated when the type of service carried by the link changes.

[0048] Step S12103: Bind the node dynamic association rules and the link dynamic association rules according to the association mapping relationship in the linkage association logic to generate an association rule matrix. The association rule matrix records the linkage triggering conditions of node rules and link rules.

[0049] Based on the node-link influence relationships defined in the linkage logic, a two-dimensional association rule matrix is ​​constructed. Rows represent dynamic association rule identifiers for nodes, and columns represent dynamic association rule identifiers for links. Matrix cells store linkage trigger conditions and execution order. Trigger conditions are described using predicate logic expressions, such as "when node rule R1 is executed and the load on link L3 exceeds threshold T, trigger link rule R2." Execution order is described using timing constraints, such as "execute link rule R4 within 5 seconds after node rule R3 is completed." During matrix construction, the descriptions in the linkage logic are parsed by a rule interpreter, automatically generating matrix element content. The association rule matrix supports dynamic expansion; when a new node or link rule is added, the association relationship with other rules is automatically calculated and the matrix is ​​updated. The matrix storage uses a sparse matrix format, recording only cells with association relationships, saving storage space and improving query efficiency.

[0050] Step S12104: Collect historical status data of network node operation and historical status data of network link transmission. Based on the normal operation interval in the historical status data, determine the node dynamic association threshold parameter, which includes the node working status threshold and the node resource occupancy threshold.

[0051] Time-series datasets are generated by extracting node operation and link transmission data from the historical database of the network management system over a specific period. Each parameter undergoes a normality test; parameters conforming to a normal distribution are assigned a normal range using the three-standard-deviation method, while outlier boundaries are calculated using the quartile method for non-normally distributed parameters. Node operating status thresholds are grouped and set according to parameter type, such as CPU utilization threshold, memory utilization threshold, and port error rate threshold. Each threshold includes two levels: warning threshold and critical threshold, each corresponding to different handling strategies. Node resource usage thresholds include the maximum number of virtual LANs, the limit on the number of port binding groups, and the maximum capacity of routing table entries. Initial values ​​are determined based on device hardware specifications and software licensing information, and then dynamically adjusted according to actual configuration and usage. Threshold parameters are stored in configuration files, categorized by device model and firmware version, and can be manually adjusted via the network management interface. Adjustment records are written to the audit log.

[0052] Step S12105: Based on the normal transmission interval in the historical status data, determine the link dynamic association threshold parameter, which includes the link transmission rate threshold and the link load threshold.

[0053] Historical link transmission data is decomposed into time series components, separating trend, seasonal, and random terms. Normal transmission intervals are predicted based on the trend and seasonal terms. Link transmission rate thresholds differentiate between physical layer and application layer rates. The physical layer rate threshold is determined based on link type and specifications; the application layer rate threshold is dynamically adjusted according to service requirements, such as a higher rate threshold for video service links than for file transfer links. Link load thresholds are expressed as a percentage of link capacity, while also considering link redundancy; links with backup paths have higher load thresholds than those without backups. Historical thresholds are adaptively corrected using exponential smoothing. The threshold range is automatically widened when no threshold trigger occurs for several consecutive periods and the actual operating status is good; the threshold range is tightened when triggers are frequent. Threshold parameters are distributed to network devices via a network management protocol notification mechanism, enabling real-time threshold updates.

[0054] Step S12106: Add the node dynamic association threshold parameter to the node dynamic association rule, associate and bind it with the node state association sub-rule and the node interaction association sub-rule, and record the rule adjustment logic triggered by the node dynamic association threshold.

[0055] Threshold parameters are referenced in the conditional expressions of dynamically associated rules for nodes, using parameterized rule notation to replace specific numerical values ​​with threshold variables. A many-to-many association table between threshold parameters and rules is established, recording the rule identifier and specific condition location affected by each threshold parameter. The rule adjustment logic triggered by the threshold is described using an event-condition-action model. When the threshold parameter is updated, the rule conditions are recompiled, updating the conditional expressions in the rule interpreter. The adjustment logic is recorded in the rule change log, including a comparison of rule conditions before and after the threshold change, supporting rule version rollback. Rule verification tools are used to ensure the correct syntax of the associated rules, avoiding condition conflicts or syntax errors.

[0056] Step S12107: Add the link dynamic association threshold parameter to the link dynamic association rule, associate and bind it with the link transmission association sub-rule and the link adaptation association sub-rule, and record the rule adjustment logic triggered by the node dynamic association threshold.

[0057] A binding method similar to that used for node rules is adopted, referencing dynamic threshold parameters in the conditional expressions of link rules. A mapping table is established between link threshold parameters and rules, recording information such as parameter identifier, rule identifier, and condition type. The threshold-triggered rule adjustment logic considers link dependencies; when the threshold parameter of a link changes, it automatically checks the rules of its associated upstream and downstream links, performing cascading adjustments if necessary. The adjustment process employs a transaction mechanism to ensure the atomicity of all related rule adjustments—either all succeed or all are rolled back. The adjustment logic is exposed through a rule management interface, supporting third-party system monitoring and auditing, facilitating administrators' tracking of rule change history.

[0058] Step S12108: Based on the association rule matrix and the node dynamic association threshold bound to the node dynamic association rule and the link dynamic association rule, generate the core data structure of the network topology elastic association body. The core data structure includes a rule storage unit and a linkage invocation unit.

[0059] The core data structure adopts an object-oriented design. The rule storage unit contains a collection of node rule objects and link rule objects. Each rule object includes member variables such as an attribute dictionary, a condition expression tree, and an action instruction list, as well as member methods such as rule matching and condition evaluation. The linkage invocation unit includes components such as an association rule matrix object, a rule scheduler, and an action executor. The rule scheduler determines the rule execution order based on the association relationships and trigger conditions in the matrix; the action executor is responsible for converting rule actions into network device commands and issuing them for execution. The data structure design supports polymorphism, allowing different types of rule objects to override rule matching methods and implement differentiated matching logic. The core data structure is stored in persistent storage through a serialization mechanism using an extensible markup language, facilitating rule import / export and version control. The data structure provides a thread-safe access interface, supporting multi-threaded concurrent read / write operations, and ensures data consistency through a read-write lock mechanism.

[0060] Step S12109: Add a dynamic update channel to the core data structure. The dynamic update channel is used to receive network status update data and trigger rule adjustments.

[0061] The dynamic update channel adopts a publish-subscribe pattern and comprises three modules: a data receiving interface, a data parser, and a rule evaluator. The data receiving interface supports multiple access methods, receiving status update trap messages and periodic status reports from network devices. The data parser performs format conversion and semantic parsing on the received raw data, extracting key events and parameter values. The rule evaluator matches the parsed data against rule conditions in the core data structure; when trigger conditions are met, it generates a rule adjustment request and calls the rule management interface to update the corresponding rules. The dynamic update channel is configured with a flow control mechanism; when the received data rate exceeds a threshold, rate limiting is initiated to ensure the stable operation of the core system. The update channel's operational status is monitored through a heartbeat mechanism; in case of anomalies, it automatically switches to a backup channel to ensure the continuity of the update service.

[0062] Step S121010: Organize the core data structure in a structured manner, integrate the rule storage unit, linkage call unit and dynamic update channel, and generate a network topology elastic association.

[0063] A layered architecture is adopted to organize the core data structure. The data layer includes rule storage units and threshold parameter libraries, providing data persistence and caching services. The logic layer includes linkage invocation units and a rule evaluation engine, implementing rule matching and execution logic. The interface layer includes dynamic update channels and application programming interfaces, providing external system interaction capabilities. Well-defined interfaces facilitate communication between layers, reducing coupling between modules. The topology elastic association deployment adopts a master-slave cluster architecture. The master node is responsible for real-time rule processing, while the slave node synchronizes data and is in a hot standby state, automatically switching over when the master node fails. During system startup, an initialization script loads historical rules and threshold parameters, performs rule integrity checks, and repairs corrupted rule data. During association generation, a system configuration report is output, including statistics such as the number of rules, the number of associations, and the number of threshold parameter groups, serving as a basis for system health assessment.

[0064] Step S130: Input the network service demand dynamic data into the network topology elastic association body, and generate a network topology dynamic demand adaptation factor through the node dynamic association rules, link dynamic association rules and linkage association logic. The network topology dynamic demand adaptation factor includes node adaptation demand data and link adaptation demand data.

[0065] In this embodiment, dynamic data on network service requirements undergoes syntax validation and semantic analysis to convert unstructured service requirement descriptions into structured parameter configurations. The parsed service data is input into the network topology elastic association body via a dynamic update channel. The rule evaluation engine in the network topology elastic association body traverses the dynamic association rules for nodes and links, performing rule condition matching. The matching process employs a forward reasoning strategy, starting with the service requirement parameters and sequentially matching rule conditions. Rules that meet the conditions are activated and execute corresponding actions, generating preliminary adaptation requirements. Linkage and association logic coordinates the preliminary requirements of nodes and links, resolving resource contention and configuration conflicts. The final generated topology dynamic requirement adaptation factor is stored in an Extensible Markup Language (Extreme Markup Language) format, containing detailed adaptation parameters for nodes and links, and is sent to the topology reconstruction module via a message queue. Multiple rounds of verification are performed during the adaptation factor generation process to ensure the rationality and feasibility of the adaptation parameters, avoiding configuration requirements that are inconsistent with the actual network environment.

[0066] Step S131: Separate the service transmission demand change data and service priority adjustment data from the network service demand dynamic data, and extract the transmission bandwidth change data and transmission delay change data from the service transmission demand change data.

[0067] Network service requirement dynamic data is transmitted in Extensible Markup Language (EXPLAIN) format. The root element contains two sub-elements: service transmission requirement and service priority. The Document Object Model (DOM) parser locates the corresponding sub-elements and extracts bandwidth and latency elements from the service transmission requirement change data. The bandwidth element includes attributes such as current value, change magnitude, and effective time; the latency element includes sub-elements such as one-way latency, two-way latency, and latency jitter. For multi-service aggregated requirement data, it is split by service identifier, with each service generating an independent requirement record. Transmission bandwidth change data is divided by time granularity, distinguishing between changes that take effect immediately and those that take effect on a schedule. Changes that take effect immediately are marked as urgent requirements, while changes that take effect on a schedule are marked as reserved requirements. Transmission latency change data is categorized by service type, with real-time and non-real-time services using different processing strategies. A data quality report is generated during data extraction, recording issues such as missing parameters and format errors, and is sent to the service management platform for correction.

[0068] Step S132: Extract the service type identifier data and priority sorting data from the service priority adjustment data, and associate and bind the service type identifier data with the transmission bandwidth change data and transmission delay change data.

[0069] The business priority adjustment data includes a list of business type codes and a priority matrix. The business type codes use the Network Service Classification Standard encoding, and the priority matrix uses numerical levels, with higher values ​​indicating higher priority. Using the business type codes as keywords, a correlation is established with transmission bandwidth change data and transmission delay change data, forming a business requirement triple (business type, bandwidth requirement, delay requirement). During the correlation binding process, the business type codes are standardized, mapping codes from different systems to an internal unified encoding system. Priority ranking data is converted into weighting coefficients for weighted calculations during subsequent resource allocation. The correlation results are stored in a relational database, indexed by business type identifiers to support efficient querying. A correlation binding report is also generated, listing business types for which no matching requirement data was found, prompting administrators to complete the data.

[0070] Step S133: Input the associated and bound business data into the node dynamic association rules of the network topology elastic association body, match the node working status data and node resource usage data through the node status association sub-rules, and output the preliminary node adaptation data.

[0071] Once associated and bound, the business data is submitted to the network topology elastic association body via an application programming interface (API). Interface parameters include business type identifier, priority weight, bandwidth requirements, and latency requirements. The rule matching engine within the association body loads the dynamic association rule set for each node and sequentially matches the business data against the conditions of each rule. The matching process employs a pattern matching algorithm, comparing the business requirement parameters with the thresholds in the rule conditions. Node status association sub-rules read current working status data and resource usage data from the node's dynamic operating information, calculating the node's available resources, such as remaining CPU processing power, free memory space, and the number of available ports. Based on the matching results, preliminary node adaptation data is generated, including a recommended node list, resource allocation schemes, and expected performance indicators. Each recommended scheme is accompanied by a matching score; a higher score indicates better compatibility between the node and business requirements. The preliminary node adaptation data is organized in tabular form, with rows representing recommended nodes and columns representing evaluation indicators, facilitating subsequent filtering and sorting.

[0072] Step S134: Through the node interaction association sub-rules in the node dynamic association rules, perform interactive adaptation processing on the preliminary node adaptation data, and combine it with the business priority sorting data to generate the core part of the node adaptation requirement data.

[0073] The node interaction association sub-rules extract a recommended node list from the initial node adaptation data, analyzing the connection relationships and traffic interaction patterns between nodes. A graph theory algorithm is used to construct a node interaction graph, where nodes represent network devices, edges represent physical connections between nodes, and edge weights represent current traffic load. Based on business priority ranking data, node resources on critical paths are allocated to high-priority services, such as assigning video conferencing services to paths directly connected to core nodes to avoid multi-level forwarding. Interaction adaptation processing includes node load balancing, path redundancy checks, and fault domain isolation. For example, when the load of a recommended node approaches a threshold, some services are automatically diverted to backup nodes; when a single point of failure risk is detected, path redundancy is increased. During processing, historical interaction data in the node interaction association sub-rules is referenced to predict traffic growth trends between nodes and reserve resources in advance. The core part of the generated node adaptation requirements includes fields such as node identifier, resource allocation details, interaction path planning, and priority markers, which are stored in a relational database using structured query language, supporting transaction rollback and data consistency checks.

[0074] Step S135: Input the associated and bound business data into the link dynamic association rules of the network topology elastic association body, match the link transmission rate data and link load data through the link transmission association sub-rules, and output the preliminary link adaptation data.

[0075] After being formatted and bound, the business data is input into the link dynamic association rule engine. The engine first filters the candidate link set based on business type and bandwidth requirements, and the candidate links must meet basic transmission capacity requirements. The link transmission association sub-rules read the current transmission rate and load data from the real-time link transmission information and calculate the remaining link capacity and transmission quality indicators. A fuzzy comprehensive evaluation method is used to score the adaptability of the candidate links. The evaluation indicators include bandwidth sufficiency, load balancing, transmission latency, jitter, etc., and the weight of each indicator is dynamically adjusted according to the business type. Based on the scoring results, preliminary link adaptation data is generated, including a list of recommended links, expected transmission quality, bandwidth allocation suggestions, etc. Each recommended link is accompanied by an adaptability score and risk assessment. The preliminary link adaptation data is output in Extensible Markup Language (Extreme Markup Language) format, including elements such as link identifier, current status, and recommended configuration, for easy subsequent processing and display.

[0076] Step S136: Through the link adaptation association sub-rules in the link dynamic association rules, perform adaptation optimization processing on the preliminary link adaptation data, and combine the transmission bandwidth change data and transmission delay change data in the service transmission demand change data to generate the core part of the link adaptation demand data.

[0077] The link adaptation sub-rules perform in-depth analysis of the recommended links in the initial adaptation data, checking the match between the interface configurations of the nodes at both ends of the link and the business requirements. Adaptation optimization includes operations such as adjusting interface parameters, optimizing protocol configurations, and setting traffic control policies. For example, the MTU values ​​of the nodes at both ends of the link are uniformly adjusted to the optimal value for the business data packet size; the link's queue scheduling algorithm is adjusted based on transmission latency variation data to prioritize low-latency services. During optimization, historical link adaptation data is referenced to identify common adaptation problems and automatically apply solutions. The core part of the generated link adaptation requirements includes fields such as link identifier, interface configuration details, protocol parameter settings, and traffic control policies, stored in a network configuration description language format, which can be directly converted into network device configuration commands. The core data undergoes syntax and logic validation using configuration verification tools to ensure the correctness and executability of the configuration commands.

[0078] Step S137: Invoke the linkage association logic in the network topology elastic association body to perform linkage processing on the core parts of the node adaptation requirement data and the core parts of the link adaptation requirement data, and generate linkage adaptation adjustment data.

[0079] In this embodiment, an association rule matrix is ​​first loaded to identify the relationship between node adaptation requirements and link adaptation requirements. For example, when the CPU resource allocation of node A increases, it may lead to an increase in the traffic load of link L1 flowing through that node. In this case, it is necessary to adjust the bandwidth allocation of link L1 accordingly. The linkage processing adopts a constraint satisfaction problem-solving algorithm, using node resource allocation and link bandwidth configuration as variables and business requirement parameters as constraints, to construct a mathematical model to solve for the optimal resource allocation scheme. During the processing, the system will detect resource conflicts. For example, when multiple services simultaneously request the memory resources of the same node, resource coordination is performed according to the service priority sorting data to prioritize the resource needs of high-priority services. The linkage adaptation adjustment data includes resource conflict solutions, a linkage relationship table of node and link configurations, and adjustment order suggestions. Among them, the resource conflict solutions specify the allocation method of conflicting resources, the linkage relationship table records the correspondence between node configuration changes and link configuration changes, and the adjustment order suggestions specify the execution order of various configurations to avoid operational conflicts.

[0080] Step S138: Based on the linkage adaptation adjustment data, correct the core part of the node adaptation requirement data, supplement the association parameters of node and link linkage adaptation, and form node adaptation requirement data.

[0081] Based on the resource conflict resolution in the linkage adaptation adjustment data, the resource allocation scheme in the core part of the node adaptation requirements is revised. For example, when the linkage process decides to migrate some CPU resources of service B from node C to node D, the CPU resource allocation details of nodes C and D are revised. Supplementary correlation parameters include the binding relationship between nodes and links, resource reservation ratios, and state synchronization mechanisms, such as "port 2 of node E is bound to link L5, reserving 20% ​​of port bandwidth for traffic switching during link failure recovery." The setting of correlation parameters must refer to the interaction thresholds in the node dynamic association rules to ensure that the parameter values ​​are within a safe operating range. The revised node adaptation requirement data is organized in a hierarchical structure, including a basic information section, a resource allocation section, and a linkage relationship section. The basic information section describes the basic attributes of the service and nodes, the resource allocation section lists the allocation of resources such as CPU, memory, and ports in detail, and the linkage relationship section describes the correlation parameters with the links. Consistency checks are performed during data generation to ensure that node resource allocation matches link bandwidth requirements.

[0082] Step S139: Based on the linkage adaptation adjustment data, correct the core part of the link adaptation requirement data, supplement the correlation parameters of link and node linkage adaptation, and form the link adaptation requirement data.

[0083] Referring to the link configuration linkage relationships in the linkage adaptation adjustment data, the core parts of the link adaptation requirements are revised. For example, when the port rate configuration of node F is increased from 1Gbps to 10Gbps, the transmission rate parameters of link L8 connected to that port are revised. Supplementary correlation parameters include the interface mapping relationship between the link and the node, the state detection mechanism, and the failover strategy, such as "the source node of link L8 is port 3 of node F, bidirectional state detection is enabled, and when a link failure is detected, it automatically switches to link L9." The correlation parameter values ​​are determined according to the adaptation threshold in the link dynamic association rules to ensure that the configuration of the link and the node is compatible. The link adaptation requirement data includes sections such as basic link information, transmission parameter configuration, and linkage adaptation parameters, and is stored in Extensible Markup Language format. It is converted into command line instructions executable by network devices through configuration templates. During the revision process, configuration validity checks are performed, such as checking whether the total link bandwidth allocation exceeds the physical link capacity. When invalid configurations are found, they are automatically adjusted and the reasons for the adjustment are recorded.

[0084] Step S1310: Integrate node adaptation requirement data and link adaptation requirement data to generate a network topology dynamic requirement adaptation factor that includes linkage adaptation correlation parameters.

[0085] The adaptation factor integration module reads node adaptation requirement data and link adaptation requirement data. First, it performs a data consistency check to verify whether the association parameters between nodes and links match, such as whether node resource allocation can meet link bandwidth requirements. After the check passes, it extracts the linkage adaptation association parameters and constructs a node-link association graph. In the graph, nodes represent network devices, edges represent links, and edge attributes are linkage parameters. During the integration process, redundancy removal and information compression are performed on the adaptation requirement data, retaining key configuration parameters and deleting duplicate and derived information. The topology dynamic requirement adaptation factor is stored in binary format, including a file header, node requirement segment, link requirement segment, and linkage relationship segment. The file header records metadata such as version number, generation time, and checksum. The node and link requirement segments store parameters in TLV (Type-Length-Value) format, and the linkage relationship segment stores node-link associations using an adjacency list structure. The adaptation factor file ensures integrity and authenticity through encryption and signing. The encryption algorithm uses an advanced encryption standard, and the signing uses an asymmetric encryption algorithm. The generated adaptation factor file is uploaded to the topology reconstruction control center via a file transfer protocol as input parameters for topology reconstruction.

[0086] Step S140: Based on the network topology dynamic demand adaptation factor and the network topology elastic association, generate a network topology reconstruction path self-adaptation sequence. The network topology reconstruction path self-adaptation sequence includes a node connection reconstruction sub-sequence and a link transmission reconstruction sub-sequence. Each sub-sequence contains specific reconstruction operation instructions and operation timing.

[0087] The topology reconfiguration path planning module loads the network topology dynamic demand adaptation factor and the network topology elastic correlation body, and uses a graph search algorithm to find the optimal reconfiguration path from the current topology to the target topology. Path planning considers factors such as reconfiguration cost, service interruption time, and resource utilization, and adopts a heuristic search algorithm. The heuristic function comprehensively calculates the number of reconfiguration steps and the service impact. During the node connection reconfiguration subsequence generation process, based on the connection adjustment data in the node adaptation demand data, it determines operations such as enabling / disabling node ports, changing the members of link aggregation groups, and adjusting the partitioning of virtual LANs. The link transmission reconfiguration subsequence generates operation instructions such as transmission rate adjustment, load balancing configuration, and service quality policy application based on the link adaptation demand data. The operation timing is determined by a timing constraint solver, considering the dependencies of operations and the possibility of parallel execution. For example, port configuration operations must be executed before link aggregation group adjustments, and independent operations of different nodes can be executed in parallel. The self-adaptation sequence is represented by a directed acyclic graph structure, where nodes represent reconfiguration operations, edges represent dependencies between operations, and each operation node contains attributes such as instruction content, target device, and expected execution time. The generated refactoring path self-adaptation sequence is displayed through a visual interface for administrator review and confirmation. Once approved, it is converted into an executable script.

[0088] Step S141: Extract node adaptation requirement data and link adaptation requirement data from the network topology dynamic requirement adaptation factor, and separate node connection adjustment data and node resource configuration adjustment data from the node adaptation requirement data.

[0089] The topology dynamic requirement adaptation factor parsing module locates the node adaptation requirement segment and the link adaptation requirement segment, extracting the corresponding data through type identifiers. Node adaptation requirement data is parsed using TLV format, with type fields of 0x01 indicating node connection adjustment data and 0x02 indicating node resource configuration adjustment data. Node connection adjustment data includes port operation lists, link aggregation configurations, and VLAN membership relationships, such as "Port 1 / 0 / 1: Enabled, added to aggregation group 3, belonging to VLAN 10". Node resource configuration adjustment data includes parameters such as CPU scheduling policies, memory allocation, and cache size, such as "CPU affinity: Service A is bound to CPU cores 1-2, memory reservation: 512MB". During the separation process, the data is validated to check whether the ports in the connection adjustment data exist in the device configuration and whether the resource configuration data exceeds the device hardware specifications. The two types of data are stored in different sets of the in-memory database, indexed by node ID, supporting efficient querying and updating.

[0090] Step S142: Separate the link transmission parameter adjustment data and the link load distribution adjustment data from the link adaptation requirement data, and associate and map the node connection adjustment data with the link transmission parameter adjustment data.

[0091] During the link adaptation requirement data parsing process, transmission parameter adjustment data is extracted using type identifier 0x10, and load allocation adjustment data is extracted using type identifier 0x11. Transmission parameter adjustment data includes parameters such as rate configuration, duplex mode, and flow control, such as "Link L5: Rate 10Gbps, Full-duplex, IEEE802.3x flow control enabled." Load allocation adjustment data includes configurations such as service traffic allocation ratio, priority mapping, and bandwidth guarantee, such as "Video service: Allocate 30% bandwidth, mapped to priority queue 4." The association mapping uses node ports as keys to associate port operations in node connection adjustment data with link endpoints in link transmission parameter adjustment data, such as "Node A's ports 1 / 0 / 2 connect to link L3, performing rate adjustment." The mapping process constructs an association table, recording the correspondence between node ID, port number, link ID, and transmission parameter adjustment ID. The association mapping results are displayed through visual charts, intuitively showing the correspondence between node connections and link parameters, facilitating administrator verification of mapping correctness.

[0092] Step S143: Invoke the node dynamic association rules in the network topology elastic association body, and generate the operation steps and operation sequence of node connection reconstruction based on node connection adjustment data and node resource configuration adjustment data, forming a preliminary sequence of node connection reconstruction.

[0093] The node reconfiguration planning module calls the rule query interface of the network topology elastic association, inputting the node ID and adjustment data to obtain relevant dynamic node association rules. The rule matching engine matches the corresponding rule conditions based on the operation type (e.g., port activation, aggregation group change) in the node connection adjustment data and the parameter values ​​in the resource configuration data, activating the rule and executing actions to generate operation steps. For example, the "Enable Port" operation matches the "Check Link Status Before Port Enabling" rule, generating a link status check step. Operation sequence generation uses the critical path method to identify dependencies between operations, such as the "Join Aggregation Group" operation must be executed after the "Port Enabling" operation, determining the earliest start time and latest completion time of each operation. Each operation step in the preliminary sequence includes attributes such as operation ID, target node, operation command, preconditions, and expected execution time, organized using a work decomposition structure, layered by node and operation type. The preliminary node connection reconfiguration sequence is output in Extensible Markup Language (EXPLAIN) format, containing sequence metadata and a list of operation steps. The metadata records information such as sequence ID, generation time, and associated services, while the list of operation steps is arranged in execution order.

[0094] Step S1431: Extract node state association sub-rules and node interaction association sub-rules from the node dynamic association rules of the network topology elastic association body, and input node connection adjustment data into the node interaction association sub-rules.

[0095] The rule extraction module uses a rule type filter to extract state-related and interaction-related sub-rules from the node dynamic association rule library. State-related sub-rules are stored in the "node_state_rules" directory of the rule library, and interaction-related sub-rules are stored in the "node_interaction_rules" directory. Each sub-rule contains attributes such as rule ID, conditional expression, action list, and applicable node type, and the rule type is distinguished by XML tags. Node connection adjustment data is organized in key-value pairs, containing fields such as "node_id", "port_id", and "operation_type", and is passed to the node interaction-related sub-rules through the rule engine's input interface. The sub-rule's conditional expression parsing module performs pattern matching between the connection adjustment data and the rule conditions. For example, when the operation type is "port_enable", it matches rules containing the "port_state" condition.

[0096] Step S1432: Analyze the node identifier data and connection relationship change data in the node connection adjustment data through node interaction association sub-rules to determine the set of node pairs that need connection adjustment and the adjustment type.

[0097] The parsing module for node interaction association sub-rules performs syntactic analysis on node connection adjustment data, extracting node identification data (e.g., "node_id=S1", "peer_node_id=S2") and connection relationship change data (e.g., "connection_type=trunk", "vlan_id=10"). Semantic analysis determines the adjustment type, including adding connections, deleting connections, and modifying connection attributes. Adding a connection corresponds to the "add_connection" action, deleting a connection corresponds to the "remove_connection" action, and modifying attributes corresponds to the "modify_attribute" action. The node pair set is determined by the "node_id" and "peer_node_id" fields of the node identification data; for example, (S1, S2) represents a connection adjustment between nodes S1 and S2. During parsing, data validity is verified, checking whether the node identifier exists in the network topology and whether the connection relationship change data conforms to protocol specifications.

[0098] Step S1433: Input the node resource configuration adjustment data into the node status association sub-rule, parse the resource type data and resource allocation change data in the node resource configuration adjustment data, and determine the resource adjustment amount and adjustment method for each node.

[0099] Node resource configuration adjustment data includes fields such as "resource_type", "current_value", and "target_value", and is associated with sub-rules through the rule engine interface by inputting the node status. The resource parsing module of the sub-rules distinguishes resource types such as CPU, memory, and storage based on the "resource_type" field, and calculates the resource adjustment amount (target_value - current_value) based on "current_value" and "target_value". The adjustment method is determined based on the resource type and the positive or negative value of the adjustment amount. For example, a positive adjustment amount for CPU resources indicates "increase allocation", while a negative one indicates "decrease allocation". Memory resource adjustment methods include "dynamic expansion" and "static reservation", selected according to the preset strategy in the node's dynamic association rules. The parsing results are stored in the resource adjustment list, and each record contains information such as node ID, resource type, adjustment amount, and adjustment method.

[0100] Step S1434: Based on the node pair set and adjustment type, combined with the node resource adjustment quota and adjustment method, generate the pre-operation and post-operation of each node pair connection adjustment, and record the dependency relationship between operation steps.

[0101] Based on the node pair set (e.g., (S1, S2) and adjustment type (e.g., "add_connection"), and referring to the node resource adjustment quota (e.g., increasing S1's CPU by 5%) and adjustment method (e.g., "dynamic expansion"), pre-operations and post-operations are generated. Pre-operations include resource reservation checks, port status detection, and protocol compatibility verification, such as "checking if port 1 / 0 / 1 of S1 is down" and "verifying if the VLAN configurations of S1 and S2 are consistent." Post-operations include connection status confirmation, traffic switching, and alarm clearing, such as "confirming successful trunk link negotiation between S1 and S2" and "switching service traffic from the backup link to the new link." Dependencies between operation steps are represented by directed edges; for example, the "port enable" operation depends on the successful execution of the "resource reservation check" operation, and this is recorded in the dependency table.

[0102] Step S1435: Based on the dependencies between operation steps, arrange the operation order of node connection adjustment so that the subsequent operation is executed only after the preceding operation is completed, forming an ordered queue of operation steps.

[0103] A topology sorting algorithm is used to order the operation steps, generating an acyclic queue of operation steps with a dependency table as input. During sorting, operations without prerequisite dependencies (such as resource reservation checks) are placed at the front of the queue, while steps that depend on other operations (such as port activation) are placed after the dependent operations. For example, the queue order might be: resource reservation check—port status check—port activation—link negotiation—traffic switching—status confirmation. The sorting result is stored in an adjacency list, with each operation step containing a list of preceding and succeeding operations to ensure the correctness of the execution order.

[0104] Step S1436: Extract the node performance parameters in the network topology elastic association, and determine the execution time of each operation step based on the node performance parameters and node resource adjustment type.

[0105] Performance parameters, including CPU processing power, memory access speed, and port negotiation rate, are extracted from the node attribute library of the network topology elastic association. Examples include "node_performance={'cpu_mips':2000,'mem_bandwidth':1000,'port_negotiation_time':2}". Based on the node resource adjustment type (e.g., CPU expansion, port activation) and performance parameters, the execution time is calculated using empirical formulas. For example, the execution time for port activation = port negotiation rate + configuration activation delay, where the configuration activation delay is dynamically adjusted based on the node's CPU processing power. The calculated execution time is rounded to the nearest integer in seconds and stored in the "duration" attribute of the operation step.

[0106] Step S1437: Based on the operation step queue and the execution time of each operation step, generate the start time of each operation step so that the execution times of adjacent operation steps do not overlap.

[0107] Based on the operation step queue, starting from the initial time (t=0), a start time is assigned to each operation step sequentially. The start time of the preceding operation is 0, and the start time of the subsequent operation equals the start time of the preceding operation plus its execution duration, ensuring no time overlap between adjacent operations. For example, step 1 has a start time of 0 and an execution duration of 2 seconds; step 2 has a start time of 2 and an execution duration of 3 seconds; step 3 has a start time of 5, and so on. The start times are stored in the "start_time" attribute of the operation step, forming a complete timing plan.

[0108] Step S1438: Add an associated node identifier to each operation step and record the associated nodes corresponding to the operation steps and the interaction relationships between the nodes.

[0109] Add a "related_nodes" field to each operation step to record all node identifiers involved in the operation, such as "related_nodes=[S1,S2]". Also add an "interaction_type" field to describe the interaction relationships between nodes, such as "trunk_connection" or "vlan_membership". The associated node identifiers and interaction relationships are extracted from the node interaction association sub-rules by the rule engine, ensuring consistency between the operation steps and the node interaction logic.

[0110] Step S1439: Based on the priority determination rule in the node dynamic association rule for multiple operation steps requesting the same node resource, adjust the execution order of operation steps in the operation step queue that have the risk of resource conflict.

[0111] When multiple operation steps request the same resource on the same node (such as port 1 / 0 / 1 of S1), a priority determination rule is triggered. The priority determination rule calculates a priority score based on factors such as business priority, operation urgency, and resource consumption; operation steps with higher scores are executed first. For example, if the port enable operation of business A (priority level 1) has a higher priority than the port configuration operation of business B (priority level 3), the queue order is adjusted so that the operation of business A is executed first. The adjustment process is recorded in the conflict resolution log, including the conflicting operation ID, original order, new order, and priority score.

[0112] Step S14310: Integrate the adjusted operation step queue, start time and execution duration to form a preliminary sequence for node connection reconstruction. The input of each operation step comes from the output of the previous operation or the preset association rule data.

[0113] The adjusted operation step queue, start time, execution duration, and related nodes are integrated to generate a preliminary sequence for node connection reconstruction. The sequence is stored in JSON format, and each operation step includes fields such as "step_id", "operation_cmd", "start_time", "duration", "related_nodes", and "input_data". The "input_data" field specifies the input source for this step; for example, "input_data={'prev_step_id':'step1','rule_data':'node_state_rule_5'}" indicates that the input comes from the output of step 1 and the preset data of node state rule 5. The integrated preliminary sequence undergoes syntax validation through a rule engine to ensure the legality of operation instructions and the integrity of parameters.

[0114] Step S144: Invoke the link dynamic association rules in the network topology elastic association body, and generate the operation steps and operation sequence of link transmission reconstruction based on the link transmission parameter adjustment data and link load distribution adjustment data, forming a preliminary sequence of link transmission reconstruction.

[0115] The link reconfiguration planning module calls the link rule interface of the network topology elastic associator, passing in link transmission parameter adjustment data (such as rate, duplex mode) and load distribution adjustment data (such as bandwidth ratio, priority). The transmission association sub-rules and adaptation association sub-rules in the link dynamic association rules match the input data, generating operation steps such as link parameter adjustment, load balancing, and traffic shaping. The operation sequence is planned using a Gantt chart method, considering link dependencies (e.g., primary link adjustment must be executed after backup link activation) and device processing capacity to determine the start time and execution duration of each step. The preliminary link transmission reconfiguration sequence includes an operation step list, timing plan, associated link identifiers, etc., using the same data format as the preliminary node connection reconfiguration sequence for easy subsequent collaborative processing.

[0116] Step S1441: Extract link transmission association sub-rules and link adaptation association sub-rules from the link dynamic association rules of the network topology elastic association body, and input the link transmission parameter adjustment data into the link transmission association sub-rules.

[0117] The link rule extraction module reads transmission-related sub-rules ("transmission_rules.xml") and adaptation-related sub-rules ("adaptation_rules.xml") from the "link_rules" directory of the network topology elastic association. Link transmission parameter adjustment data includes fields such as "link_id", "target_rate", and "duplex_mode", which are converted into a format recognizable by the sub-rules through the rule engine's input adapter. For example, "target_rate=10Gbps" is converted to...<rate_unit> Gbps< / rate_unit><rate_value> 10< / rate_value> The condition matching module for transmitting associated sub-rules performs pattern recognition on the input data and activates rules containing the "rate_adjustment" condition.

[0118] Step S1442: Parse the link identification data and transmission parameter change data in the link transmission parameter adjustment data through the link transmission association sub-rules to determine the set of links that need parameter adjustment and the parameter adjustment type.

[0119] The parser for the link transmission association sub-rule performs lexical analysis on the input data, extracting link identifier data (e.g., "link_id=L10") and transmission parameter change data (e.g., "rate_change=+5Gbps", "duplex_change=full"). The parameter adjustment type is determined based on the change data, including rate adjustment, duplex mode switching, and flow control switching, corresponding to operation types such as "rate_adjust", "duplex_switch", and "flow_ctrl_toggle", respectively. The set of links requiring parameter adjustment is determined by the link identifier data; for example, {L10, L12, L15} indicates that parameter adjustments will be performed on these three links. During the parsing process, the validity of the link identifier is verified to ensure that the link exists in the current network topology.

[0120] Step S1443: Input the link load distribution adjustment data into the link adaptation association sub-rule, parse the load type data and load distribution change data in the link load distribution adjustment data, and determine the load adjustment ratio and adjustment direction for each link.

[0121] Link load allocation adjustment data includes fields such as "load_type", "current_ratio", and "target_ratio". After inputting the link adaptation association sub-rules, the parsing module distinguishes between load types such as video, data, and voice based on "load_type", and calculates the load adjustment ratio (target_ratio - current_ratio) based on "current_ratio" and "target_ratio". The adjustment direction is determined by the positive or negative value of the ratio, with positive indicating "increased allocation" and negative indicating "decreased allocation". For example, an adjustment ratio of +15% for video load type means "the bandwidth share of video services on this link increases by 15%". The parsing results are grouped and stored by link ID to form a load adjustment list.

[0122] Step S1444: Based on the link set and parameter adjustment type, combined with the load adjustment ratio and adjustment direction, generate the pre-preparation operation and post-optimization operation for each link transmission parameter adjustment, and record the logical relationship between the operation steps.

[0123] For each link in the link set (e.g., L10), pre-processing and post-optimization operations are generated based on the parameter adjustment type (e.g., rate adjustment) and load adjustment ratio (e.g., +15%). Pre-processing operations include link traffic mirroring, backing up the current configuration, and notifying relevant nodes, such as "Enable traffic mirroring to the monitoring port for L10" and "Back up the current QoS configuration of L10". Post-optimization operations include load balancing verification, transmission quality detection, and configuration persistence, such as "Verify whether the video traffic ratio of L10 has reached the target value" and "Write the new configuration to the startup configuration file". The logical relationships between operation steps are represented by conditional expressions, such as "Post-optimization operations are only executed when the pre-processing operation returns a 'success' status".

[0124] Step S1445: Arrange the operation sequence of link transmission reconstruction according to the logical relationship between the operation steps, so that the core adjustment operation is executed after the preparatory operation is completed, and the post-optimization operation is executed after the core adjustment operation is completed.

[0125] A process orchestration algorithm is used to sequence the operation steps of link transmission reconstruction, following the execution order of "preparation – core adjustment – ​​optimization". Core adjustment operations, including rate modification and load balancing configuration, which directly change link parameters, must be executed after preparatory operations (such as traffic backup) are completed. Optimization operations (such as quality testing) must be initiated after the core adjustment operations are completed and the link status is stable. The sequencing result is represented by a directed graph, where nodes represent operation steps and edges represent logical dependencies, ensuring the rationality of the operation order.

[0126] Step S1446: Extract the link device performance parameters in the network topology elastic association, and determine the execution time of each transmission parameter adjustment operation based on the link device performance parameters and the transmission parameter adjustment type.

[0127] Device performance parameters, including optical module rate level, port processing latency, and configuration activation time, are extracted from the link attribute library of the network topology elastic association. Examples include "link_performance={'module_rate':10G,'config_delay':3,'negotiation_timeout':10}". The execution time is calculated based on the transmission parameter adjustment type (e.g., rate increase, duplex mode switching) and performance parameters. For example, the execution time of a rate adjustment operation = configuration activation time + negotiation timeout, where the negotiation timeout is dynamically adjusted based on the optical module rate level. The execution time is accurate to the second and stored in the "duration" attribute of the operation step.

[0128] Step S1447: Determine the execution time of each load distribution adjustment operation based on the link device performance parameters and load distribution adjustment type.

[0129] Load balancing adjustments include bandwidth ratio adjustments and priority mapping changes, with execution durations determined by the QoS processing capabilities of the link devices and the complexity of the load adjustment. For example, the execution duration of a bandwidth ratio adjustment equals the policy update time plus the traffic redistribution time. The policy update time is negatively correlated with the device's CPU processing capacity, while the traffic redistribution time is positively correlated with the current link load. The specific execution duration is calculated by looking up the performance parameter table in the network topology elastic relation table to obtain the baseline value for the policy update time (e.g., 5 seconds) and the traffic redistribution coefficient (e.g., 0.1 / Mbps).

[0130] Step S1448: Adjust the execution duration of the operation according to the operation sequence, transmission parameters, and load distribution, and generate the start time of each operation step.

[0131] Based on the operation sequence, starting from the initial time (t=0), the execution time of the preceding operation is accumulated to determine the start time of the current operation. For example, if the execution time of the pre-preparation operation is 3 seconds, the start time of the core adjustment operation is 3 seconds; if the execution time of the core adjustment operation is 5 seconds, the start time of the post-optimization operation is 8 seconds. When multiple link operations are independent, they can be executed in parallel with the same start time. The start time is recorded in the "start_time" attribute of the operation step, forming the timing plan for link transmission reconfiguration.

[0132] Step S1449: Add an associated link identifier and an associated node identifier to each operation step, and record the link corresponding to the operation step and the node connected to the link.

[0133] In the operation steps, add a "link_id" field to record the associated link identifier and a "connected_nodes" field to record the node identifiers at both ends of the link, such as "link_id=L10,connected_nodes=[S3,S4]". The associated identifier is obtained by querying the link topology database to ensure the accurate correspondence between links and nodes. The above identifiers are used for device location and status monitoring during operation execution.

[0134] Step S14410: Integrate the operation sequence, start time and execution duration to form a preliminary sequence for link transmission reconstruction. The input of each operation step comes from the output of the preceding operation or the preset data in the link dynamic association rules.

[0135] Information such as operation sequence, start time, execution duration, and associated identifiers are integrated to generate a preliminary sequence for link transmission reconstruction. The sequence is organized in JSON format, with each operation step containing fields such as "step_id", "operation_cmd", "start_time", "duration", "link_id", "connected_nodes", and "input_data". The "input_data" field specifies the input source, such as "input_data={'prev_step_id':'link_step2','rule_data':'link_transmission_rule_3'}". The integrated sequence is checked using a configuration verification tool to ensure that the operation commands conform to the device configuration syntax.

[0136] Step S145: Through the linkage association logic in the network topology elastic association body, perform time-series collaborative processing on the preliminary sequence of node connection reconstruction and the preliminary sequence of link transmission reconstruction, and adjust the execution order of operation steps to eliminate reconstruction operation conflicts.

[0137] The linkage and correlation logic module loads the preliminary sequence of node connection reconstruction and link transmission reconstruction. It identifies operational conflicts using a conflict detection algorithm, such as when the same node is assigned two port operations simultaneously, or when the same link is assigned load adjustment operations before parameter adjustments are completed. Conflict resolution strategies are based on business priorities and operational dependencies, adjusting the execution order of conflicting operations. For example, lower-priority operations are postponed, or operations with dependencies are executed in the order of dependency. After time-series collaborative processing, a unified operation timing table is generated, ensuring that the reconstruction operations of nodes and links do not overlap in time and are logically consistent.

[0138] Step S146: Based on the results of the time-series collaborative processing, match the corresponding reconstruction operation instruction for each operation step in the preliminary sequence of node connection reconstruction. The reconstruction operation instruction includes the operation object identifier, operation content, and operation triggering conditions.

[0139] Based on the operation step queue after time-series collaborative processing, reconstruction operation instructions are matched from the instruction template library of the network topology elastic association. The operation object is identified by a combination of node ID and port number, such as "node_id=S1,port=1 / 0 / 1"; the operation content is the specific configuration command, such as "interfaceGigabitEthernet1 / 0 / 1;noshutdown;switchportmodetrunk;"; and the operation trigger condition is the successful execution status of the preceding operation, such as "trigger_condition=step3.success==true". Operation instructions are generated through template variable substitution to ensure that the parameters in the instructions match the current network environment.

[0140] Step S147: Match each operation step in the preliminary sequence of link transmission reconstruction with a corresponding reconstruction operation instruction, wherein the reconstruction operation instruction format is consistent with the node connection reconstruction operation instruction format.

[0141] The same instruction format as node connection reconfiguration is used to match operation instructions for link transmission reconfiguration steps. The operation object is identified by the link ID, such as "link_id=L10"; the operation content is the link configuration command, such as "interfacePort-channel10;bandwidth10000;duplexfull;"; and the operation trigger condition is the completion status of the relevant node operation, such as "trigger_condition=node_step5.success==true". The unified instruction format facilitates parsing and processing by the operation execution engine.

[0142] Step S148: Extract the operation timing data after timing co-processing, and add operation timing markers to the preliminary sequence of node connection reconstruction and the preliminary sequence of link transmission reconstruction. The operation timing markers include the start time and execution duration of each operation step.

[0143] The start time and duration of each operation step are extracted from the time-series co-processing results and added to the reconstructed sequence as operation time stamps. The time stamps are represented using timestamp format (e.g., "2024-05-20T10:30:00Z") and seconds (e.g., "duration=5") to ensure accurate scheduling by the operation execution engine. The time stamps are stored together with the operation instructions to form complete executable steps.

[0144] Step S149: Integrate the initial sequence of node connection reconstruction with reconstruction operation instructions and operation timing markers to form a node connection reconstruction subsequence.

[0145] The operation steps, reconstruction instructions, and operation timing markers in the initial sequence of node connection reconstruction are integrated, redundant information is removed, and they are sorted by start time to form a node connection reconstruction subsequence. The subsequence is stored in XML format, with the root element "node_reconstruction_sequence" containing multiple "step" sub-elements. Each sub-element contains attributes such as "id", "object", "command", "start_time", and "duration". Validation is performed during the integration process to ensure that timing markers do not overlap and that the instruction format is correct.

[0146] Step S1410: Integrate the preliminary link transmission reconstruction sequence with reconstruction operation instructions and operation timing marks to form a link transmission reconstruction subsequence. Merge the node connection reconstruction subsequence and the link transmission reconstruction subsequence to generate a network topology reconstruction path self-adaptation sequence.

[0147] The initial link transmission reconstruction sequence is integrated in the same way as the node connection reconstruction subsequence to form a link transmission reconstruction subsequence. Then, according to the start time marked by the operation sequence mark, the operation steps of the two subsequences are merged to generate a self-adaptive sequence for network topology reconstruction path. The self-adaptive sequence contains globally unique step IDs, operation object types (nodes / links), operation instructions, start time, execution duration, and other information, stored in a database table structure, supporting transaction management and concurrent access. The generated self-adaptive sequence is displayed through a network topology visualization tool for final confirmation by the administrator.

[0148] Step S150: According to the self-adaptive sequence of the network topology reconstruction path, adjust the connection mode of network nodes and the transmission configuration of network links in a coordinated manner, and synchronously update the node dynamic association rules and link dynamic association rules in the network topology elastic association body to complete the dynamic reconstruction and optimization of the communication information network topology.

[0149] The topology reconfiguration execution engine loads the network topology reconfiguration path self-adaptation sequence and sends reconfiguration operation commands to network devices sequentially according to the operation timing markers. During execution, the execution status of devices is monitored in real time, and operation result feedback is received. After all operation steps are completed, the latest status data of network nodes and links are collected, and the dynamic association rules of nodes and links in the network topology elastic association body are updated, such as adjusting node resource thresholds and updating link load level classification standards. Finally, a reconfiguration optimization report is generated, including information such as network performance comparison before and after reconfiguration and changes in service quality indicators, completing the dynamic reconfiguration optimization of the communication information network topology.

[0150] Step S151: Extract the node connection reconstruction subsequence and link transmission reconstruction subsequence from the network topology reconstruction path self-adaptation sequence, and parse the reconstruction operation instructions, operation timing markers and associated node identifiers in the node connection reconstruction subsequence.

[0151] The sequence parsing module separates node connection reconstruction subsequences (stored in the "node_sequences" table) and link transmission reconstruction subsequences (stored in the "link_sequences" table) from the network topology reconstruction path self-adaptation sequence. It parses the node connection reconstruction subsequences, extracting the "command" field (reconstruction operation instruction), "start_time" and "duration" fields (operation timing markers), and "related_nodes" field (related node identifiers) for each operation step. During parsing, the module verifies the validity of the instruction syntax and node identifiers to ensure that the operation target exists in the current network.

[0152] Step S152: Parse the reconstruction operation instructions, operation timing marks, and associated link identifiers in the link transmission reconstruction subsequence, and sort the node connection reconstruction subsequence and the link transmission reconstruction subsequence in a unified manner according to the operation timing marks.

[0153] The link transmission reconstruction subsequence is parsed, extracting fields such as "command", "start_time", "duration", and "link_id". Then, the operation steps for nodes and links are merged into the same list, sorted in ascending order by the "start_time" field. When start times are the same, node operations take precedence over link operations (or this can be adjusted based on business priority). The unified sorted operation sequence is stored in the "unified_sequence" table, containing fields such as operation type (node / link), operation command, start time, execution duration, and association identifier.

[0154] Step S153: Following the unified sorted operation order, based on the reconstruction operation instructions in the node connection reconstruction subsequence, send connection mode adjustment instructions to the corresponding network node devices to adjust the connection interface configuration and connection protocol parameters of the network nodes.

[0155] The execution engine iterates through the node connection reconstruction steps according to a uniformly ordered sequence. For each step, it determines the target node device based on the "related_nodes" field and sends a connection mode adjustment command from the "command" field to the device via SSH or NETCONF protocol. The command includes interface configuration (such as port enable / disable, VLAN partitioning) and protocol parameters (such as link aggregation protocol and spanning tree protocol configuration). A timeout retransmission mechanism is enabled during transmission to ensure that the command is delivered to the device.

[0156] Step S1531: Extract the operation steps belonging to node connection reconstruction from the unified sorted operation sequence, and activate each operation step in sequence according to the start time in the operation timing mark.

[0157] Steps with the operation type "node" are selected from the uniformly sorted operation sequence and sorted in ascending order of the "start_time" field value. The execution engine has a built-in timer that activates the step and executes the corresponding operation when the system time reaches the step's start time. The activation process is recorded in the execution log, including information such as step ID, activation time, and execution status.

[0158] Step S1532: For each activated operation step, read the operation object identifier, operation content and operation triggering conditions in the corresponding reconstruction operation instruction, and collect the current operating status of the network node device corresponding to the operation object identifier.

[0159] After activating the operation steps, parse the "object" field (operation object identifier, such as "node_id=S1,port=1 / 0 / 1"), "content" field (operation content, such as "switchportmodetrunk"), and "trigger" field (operation trigger condition, such as "port_state=down") of the reconstruction operation instruction. Collect the current operating status of the node device corresponding to the operation object identifier via the SNMP protocol, such as port status, CPU utilization, and memory usage, to verify whether the trigger condition is met.

[0160] Step S1533: Based on the connection interface configuration requirements in the operation content, generate interface configuration adjustment data, which includes interface type selection data, interface rate configuration data, and interface link binding data.

[0161] Based on the connection interface configuration requirements in the operation content (e.g., “interface GigabitEthernet1 / 0 / 1;switchportmodeaccess;vlan10;”), interface configuration adjustment data is generated. The interface type selection data is “access”, “trunk”, or “hybrid”; the interface rate configuration data is “100Mbps”, “1Gbps”, or “10Gbps”; and the interface link binding data is the link aggregation group ID (e.g., “LAG3”). The configuration data is organized in key-value pair format for easy conversion into device commands.

[0162] Step S1534: Based on the connection protocol parameter requirements in the operation content, generate protocol parameter adjustment data, which includes transmission control protocol parameter data, routing protocol parameter data, and session protocol parameter data.

[0163] The protocol parameter requirements, such as "iptcpwindow-size65535;routerospf1;timerhello5;", are extracted from the operation content to generate protocol parameter adjustment data. Transmission control protocol parameters include window size and timeout; routing protocol parameters include routing process ID, Hello time, and metrics; and session protocol parameters include session timeout and authentication method. Parameter data is stored categorized by protocol type to ensure configuration accuracy.

[0164] Step S1535: Encapsulate the interface configuration adjustment data and protocol parameter adjustment data into a connection mode adjustment instruction, send the connection mode adjustment instruction to the network node device corresponding to the operation object identifier, record the instruction sending time and instruction content, and receive the instruction reception confirmation information returned by the network node device.

[0165] Convert interface configuration adjustment data and protocol parameter adjustment data into device-executable command-line instructions, such as "interface GigabitEthernet1 / 0 / 1;switchportmodetrunk;switchporttrunkallowedvlan10-20;". Encapsulate the instructions into XML-formatted configuration messages using a network management protocol (such as NETCONF) and send them to the node device corresponding to the operation object identifier. Record the instruction sending time (accurate to milliseconds) and instruction content, and wait for the device to return confirmation information (such as "OK" or "Error:Invalidparameter").

[0166] Step S1536: During the adjustment operation performed by the network node device, receive adjustment progress data fed back by the device in real time.

[0167] During the device's adjustment operation, progress data, such as "Configuring interface...50%" and "Applying protocol settings...80%", is fed back to the execution engine via an asynchronous messaging mechanism. The execution engine updates the progress data to the execution log in real time, allowing administrators to monitor the operation's progress. If the progress is not completed within the preset timeout period, the execution engine sends a query command to obtain detailed status information.

[0168] Step S1537: After the network node device completes the adjustment operation, it receives the connection status update data fed back by the device. The connection status update data includes the adjusted interface working status data and protocol running status data. The connection status update data is associated with the corresponding operation steps and stored.

[0169] After the device completes the adjustment operation, it returns connection status update data, including interface working status (e.g., "up" / "down"), protocol running status (e.g., "OSPF:Full"), and traffic statistics (e.g., "packetsreceived:1000"). The execution engine associates the above data with the corresponding operation step ID and stores it in the "node_state_updates" table for easy subsequent analysis and auditing.

[0170] Step S154: After performing the connection mode adjustment operation for each node, collect the connection status update data fed back by the network node devices.

[0171] After each node's connection mode adjustment operation is completed, the execution engine proactively sends a status query command to the device to collect connection status update data. If the device does not return data or returns an error status, the execution engine retryes or triggers an alarm mechanism according to a preset strategy. The collected data is temporarily stored in a memory buffer and will be processed uniformly after the link transmission configuration adjustment operation is completed.

[0172] Step S155: Based on the reconstruction operation instructions in the link transmission reconstruction subsequence and combined with the connection status update data, send the transmission configuration adjustment instructions to the corresponding network link devices to adjust the transmission rate parameters and load distribution ratio of the network link.

[0173] The execution engine iterates through the operation steps in the link transmission reconfiguration subsequence, combines node connection status update data (e.g., node port speed has been adjusted to 10Gbps), and generates a link transmission configuration adjustment command. The command includes transmission rate parameters (e.g., "bandwidth 10000") and load balancing ratios (e.g., "class-mapvideobandwidth 30%)", and is sent to the devices at both ends of the link via the network management protocol. Before sending, it verifies that the port status in the connection status update data is "up" to ensure that the prerequisites for link adjustment are met.

[0174] Step S1551: Extract the operation steps belonging to link transmission reconstruction from the unified sorted operation sequence, and activate each operation step in sequence according to the start time in the operation timing mark.

[0175] Steps with the operation type "link" are selected from the uniformly sorted operation sequence and activated sequentially according to the "start_time" field. The activation logic is the same as the node connection reconstruction step, triggered by a timer to ensure that the operation is executed as planned.

[0176] Step S1552: For each activated operation step, read the operation object identifier, operation content and operation triggering condition in the corresponding reconstruction operation instruction, and retrieve the connection status update data associated with the operation step.

[0177] After activating the link transmission reconfiguration step, the operation object identifier (e.g., "link_id=L10"), operation content (e.g., "rate10Gbps"), and operation trigger condition (e.g., "node_port_state=up") are parsed. The connection status update data in the "node_state_updates" table is retrieved by associating the operation step ID to verify whether the port status of the nodes at both ends of the link meets the trigger condition.

[0178] Step S1553: Extract the transmission rate parameter adjustment requirement from the operation content, combine it with the interface rate configuration data in the associated connection status update data, and generate rate parameter adjustment data, which includes target rate value and rate adjustment gradient data.

[0179] The transmission rate parameter adjustment requirement in the operation content (e.g., "setrate10Gbps") is compared with the interface rate configuration data in the connection status update data (e.g., the current rate of the node port is 1Gbps) to generate rate parameter adjustment data. The target rate value is "10Gbps", and the rate adjustment gradient data is the step size for each adjustment (e.g., "2Gbps / step") to ensure a smooth rate adjustment process and avoid traffic fluctuations.

[0180] Step S1554: Extract the load distribution ratio adjustment requirement from the operation content, and combine it with the node resource usage data in the associated connection status update data to generate load distribution adjustment data. The load distribution adjustment data includes the target distribution ratio and the distribution adjustment step size data.

[0181] The load distribution ratio adjustment requirement in the operation content (e.g., "videotraffic 30%)" is compared with the node resource usage data (e.g., current video traffic share of 20%) to generate load distribution adjustment data. The target distribution ratio is "30%", and the distribution adjustment step size is the percentage of each adjustment (e.g., "5% / step") to prevent sudden load changes from causing service interruption.

[0182] Step S1555: Encapsulate the rate parameter adjustment data and load distribution adjustment data into a transmission configuration adjustment command, send the transmission configuration adjustment command to the network link device corresponding to the operation object identifier, record the command sending time, command content and associated connection status update data, and receive the command reception confirmation information returned by the network link device.

[0183] The rate parameter adjustment data and load distribution adjustment data are converted into link device configuration commands, such as "interfacePort-channel10;speed10000;service-policyoutputQoS_policy;". These are then encapsulated into configuration messages and sent to devices at both ends of the link. The sending time, command content, and associated connection status update data (such as node port rate configuration) are recorded. Confirmation messages are received from the devices to ensure the commands are correctly received.

[0184] Step S1556: During the adjustment operation performed by the network link device, receive adjustment progress data fed back by the device in real time.

[0185] When network link devices perform transmission configuration adjustment operations, they provide real-time feedback on the adjustment progress via SNMPTrap or NetFlow messages, such as "Rate adjustment in progress: 40%" or "QoS policy applied: 70%". The execution engine stores the progress data in association with the operation steps, facilitating monitoring and troubleshooting.

[0186] Step S1557: After the network link device completes the adjustment operation, receive the transmission status update data fed back by the device. The transmission status update data includes the actual value of the adjusted transmission rate and the actual load distribution ratio data. The transmission status update data is associated with the corresponding operation steps and the associated connection status update data and stored together.

[0187] After the link device completes the adjustment, it returns transmission status update data, including the actual transmission rate (e.g., "10000Mbps"), load balancing ratio (e.g., "video:30%)", packet loss rate (e.g., "0.1%), etc. The execution engine associates the above data with the operation step ID and the associated connection status update data (e.g., node port configuration), and stores it in the "link_state_updates" table to form a complete operation record.

[0188] Step S156: After performing each link transmission configuration adjustment operation, collect the transmission status update data fed back by the network link device, and integrate the transmission status update data with the connection status update data.

[0189] After each link transmission configuration adjustment operation is completed, the execution engine collects transmission status update data and integrates it with the previously collected connection status update data to form a network status update dataset. During the integration process, data consistency is checked, such as whether the actual link speed matches the node port configuration speed and whether the load distribution ratio reaches the target value. The integration result is stored in the "network_state" table as the basis for subsequent rule updates.

[0190] Step S157: Based on the associated and integrated status update data, extract the node operation dynamic update information and link transmission real-time update information. The node operation dynamic update information includes the adjusted node working status data and node resource usage data.

[0191] From the integrated status update data, dynamic update information of node operation is extracted, including adjusted CPU utilization, memory usage, port status, and other operational status data, as well as resource usage data such as VLAN configuration and link aggregation groups. Data extraction uses structured query language to filter the latest records from the "node_state_updates" and "network_state" tables to ensure the timeliness of the information.

[0192] Step S158: The real-time update information for link transmission includes adjusted link transmission rate data and link load data, and the dynamic association rules of nodes in the network topology elastic association body are corrected based on the dynamic update information of node operation.

[0193] Real-time updates to link transmission information include adjusted transmission rates, load balancing, packet loss rates, and other data. Based on resource usage data (such as newly added VLAN configurations) in the node's dynamic update information, the dynamic node association rules in the network topology elastic association are corrected, such as updating node resource thresholds and adjusting node interaction response times. This correction process is implemented through a rule management interface to ensure that the rules remain consistent with the current node state.

[0194] Step S159: Correct the link dynamic association rules in the network topology elastic association body based on the real-time update information of link transmission.

[0195] Based on real-time updates to link transmission information (such as actual link speed and load level), parameters such as transmission rate thresholds and load level classification criteria in the dynamic link association rules are revised. For example, if the actual link speed remains stable at 10Gbps for a long period, the speed threshold for that link can be increased to avoid falsely triggering speed reduction rules. The revised rules are stored in the rule base, with version numbers incremented, and rollback operations are supported.

[0196] Step S1510: Integrate the node connection mode adjustment results, link transmission configuration adjustment results, and the updated network topology elastic association to complete the dynamic reconstruction and optimization of the communication information network topology.

[0197] The results of node connection mode adjustments (stored in the "node_state_updates" table), link transmission configuration adjustments (stored in the "link_state_updates" table), and the updated network topology elastic relation are integrated to generate the final network topology structure. Key metrics (such as throughput, latency, and packet loss rate) are collected after reconstruction using network performance monitoring tools and compared with those before reconstruction to evaluate the optimization effect. A reconstruction optimization report is generated, including a summary of operation steps, a comparison of state changes, and performance improvement data, marking the completion of the dynamic reconstruction and optimization process of the communication information network topology.

[0198] Figure 2 This application illustrates a dynamic reconfiguration optimization system 100 for communication information network topology, comprising a processor 1001, a memory 1003, and program code stored in the memory 1003. The processor 1001 executes the program code to implement the steps of the dynamic reconfiguration optimization method for communication information network topology. The processor 1001 and the memory 1003 are connected, for example, via a bus 1002. Optionally, the dynamic reconfiguration optimization system 100 may further include a transceiver 1004, which can be used for data interaction between this dynamic reconfiguration optimization system and other dynamic reconfiguration optimization systems for communication information network topology, such as sending and / or receiving data. It should be noted that in actual scheduling, the transceiver 1004 is not limited to one, and the structure of this dynamic reconfiguration optimization system 100 for communication information network topology does not constitute a limitation on the embodiments of this application.

[0199] The memory 1003 is used to store program code for executing the embodiments of this application, and its execution is controlled by the processor 1001. The processor 1001 is used to execute the program code stored in the memory 1003 to implement the steps shown in the foregoing method embodiments.

[0200] This application provides a computer-readable storage medium storing program code, which, when executed by a processor, can implement the steps and corresponding content of the aforementioned method embodiments.

[0201] The above description is only an optional implementation method for some implementation scenarios of this application. It should be noted that for those skilled in the art, other similar implementation methods based on the technical concept of this application, without departing from the technical concept of this application, also fall within the protection scope of the embodiments of this application.

Claims

1. A dynamic reconfiguration optimization method for communication information network topology, characterized in that, The method includes: The system acquires dynamic information on node operation, real-time information on link transmission, and dynamic data on network service requirements of the communication information network. The dynamic information on node operation includes node working status data and node resource usage data. The real-time information on link transmission includes link transmission rate data and link load data. The dynamic data on network service requirements includes data on changes in service transmission requirements and data on adjustments to service priorities. Based on the node's dynamic operating information and the link's real-time transmission information, a network topology elastic association body is generated. The network topology elastic association body includes node dynamic association rules, link dynamic association rules, and the linkage association logic between nodes and links. The network service requirement dynamic data is input into the network topology elastic association body. Through the node dynamic association rules, link dynamic association rules and linkage association logic, a network topology dynamic requirement adaptation factor is generated. The network topology dynamic requirement adaptation factor includes node adaptation requirement data and link adaptation requirement data. Based on the network topology dynamic demand adaptation factor and the network topology elastic association, a network topology reconstruction path self-adaptation sequence is generated. The network topology reconstruction path self-adaptation sequence includes a node connection reconstruction sub-sequence and a link transmission reconstruction sub-sequence. Each sub-sequence contains specific reconstruction operation instructions and operation timing. According to the self-adaptive sequence of the network topology reconstruction path, the connection mode of network nodes and the transmission configuration of network links are adjusted in a coordinated manner, and the dynamic association rules of nodes and links in the network topology elastic association body are updated synchronously to complete the dynamic reconstruction and optimization of the communication information network topology.

2. The dynamic reconfiguration and optimization method for communication information network topology according to claim 1, characterized in that, Based on the dynamic information of node operation and the real-time information of link transmission, a network topology elastic association body is generated. This network topology elastic association body includes dynamic node association rules, dynamic link association rules, and linkage association logic between nodes and links, including: Extract node working status data and node resource usage data from the node running dynamic information, and divide the node running dynamic information into related dimensions, which include the node's own status dimension and the interaction dimension between nodes. Extract the link transmission rate data and link load data from the real-time link transmission information, and divide the link transmission real-time information into related dimensions, which include the link's own transmission dimension and the link and node adaptation dimension. Based on the data analysis results of the node's own state dimension, node state association sub-rules are generated in the node dynamic association rules. The node state association sub-rules are used to define the association relationship between different node working state data and node resource usage data. Based on the data analysis results of the inter-node interaction dimension, node interaction association sub-rules are generated in the node dynamic association rules. These node interaction association sub-rules are used to define the connection response relationship between different nodes. Based on the data analysis results of the link's own transmission dimension, link transmission association sub-rules are generated in the link dynamic association rules. These link transmission association sub-rules are used to define the association relationship between different link transmission rate data and link load data. Based on the data analysis results of link and node adaptation dimensions, link adaptation association sub-rules are generated in the link dynamic association rules. The link adaptation association sub-rules are used to define the transmission adaptation relationship between links and nodes. By integrating the node state association sub-rules and the node interaction association sub-rules, dynamic node association rules are formed. The link transmission association sub-rule and the link adaptation association sub-rule are combined to form a dynamic link association rule; Based on the node dynamic association rules and the link dynamic association rules, a linkage association logic between nodes and links is generated. The linkage association logic is used to define the response relationship between node state changes and link transmission configuration adjustments. By integrating the node dynamic association rules, the link dynamic association rules, and the linkage association logic, and supplementing the dynamic association threshold parameters of nodes and links, a network topology elastic association body is generated.

3. The dynamic reconfiguration and optimization method for communication information network topology according to claim 1, characterized in that, The process involves inputting the dynamic data of network service requirements into the network topology elastic association body, and generating a network topology dynamic requirement adaptation factor through the node dynamic association rules, link dynamic association rules, and linkage association logic. This network topology dynamic requirement adaptation factor includes node adaptation requirement data and link adaptation requirement data, including: The data on changes in service transmission requirements and the data on adjustments to service priorities are separated from the dynamic data on network service requirements. The data on changes in transmission bandwidth and transmission delay are then extracted from the data on changes in service transmission requirements. Extract the service type identifier data and priority sorting data from the service priority adjustment data, and associate and bind the service type identifier data with the transmission bandwidth change data and transmission delay change data; The associated business data is input into the node dynamic association rules of the network topology elastic association body. The node working status data and node resource usage data are matched through the node status association sub-rules, and the preliminary node adaptation data is output. By using the node interaction association sub-rules in the node dynamic association rules, the initial node adaptation data is processed for interactive adaptation, and combined with the business priority sorting data, the core part of the node adaptation requirement data is generated. The associated and bound business data is input into the link dynamic association rule of the network topology elastic association body. The link transmission rate data and link load data are matched through the link transmission association sub-rule, and the preliminary link adaptation data is output. The link adaptation association sub-rules in the link dynamic association rules are used to perform adaptation optimization processing on the preliminary link adaptation data. Combined with the transmission bandwidth change data and transmission delay change data in the service transmission demand change data, the core part of the link adaptation demand data is generated. The linkage logic in the network topology elastic association body is invoked to perform linkage processing on the core parts of the node adaptation requirement data and the core parts of the link adaptation requirement data, generating linkage adaptation adjustment data. Based on the linkage adaptation adjustment data, the core part of the node adaptation requirement data is corrected, and the correlation parameters of node and link linkage adaptation are supplemented to form node adaptation requirement data. Based on the linkage adaptation adjustment data, the core part of the link adaptation requirement data is corrected, and the correlation parameters of link and node linkage adaptation are supplemented to form the link adaptation requirement data. Integrate node adaptation requirement data and link adaptation requirement data to generate a dynamic network topology requirement adaptation factor that includes linkage adaptation correlation parameters.

4. The dynamic reconfiguration and optimization method for communication information network topology according to claim 1, characterized in that, Based on the network topology dynamic demand adaptation factor and the network topology elastic association, a network topology reconstruction path self-adaptation sequence is generated. This sequence includes node connection reconstruction sub-sequences and link transmission reconstruction sub-sequences, comprising: Extract node adaptation requirement data and link adaptation requirement data from the network topology dynamic requirement adaptation factor, and separate node connection adjustment data and node resource configuration adjustment data from the node adaptation requirement data; Separate the link transmission parameter adjustment data and link load distribution adjustment data from the link adaptation requirement data, and associate and map the node connection adjustment data with the link transmission parameter adjustment data. The node dynamic association rules in the network topology elastic association body are invoked. Based on the node connection adjustment data and node resource configuration adjustment data, the operation steps and operation sequence of node connection reconstruction are generated to form a preliminary sequence of node connection reconstruction. The link dynamic association rules in the network topology elastic association body are invoked, and the operation steps and operation sequence of link transmission reconstruction are generated based on the link transmission parameter adjustment data and the link load distribution adjustment data, forming a preliminary sequence of link transmission reconstruction. Through the linkage association logic in the network topology elastic association, the preliminary sequence of node connection reconstruction and the preliminary sequence of link transmission reconstruction are processed in a time-series coordination manner to adjust the execution order of operation steps in order to eliminate reconstruction operation conflicts. Based on the results of the time-series collaborative processing, a corresponding reconstruction operation instruction is matched for each operation step in the preliminary sequence of node connection reconstruction. The reconstruction operation instruction includes the operation object identifier, operation content and operation triggering conditions. Each operation step in the preliminary sequence of link transmission reconstruction is matched with a corresponding reconstruction operation instruction, and the reconstruction operation instruction format is consistent with the node connection reconstruction operation instruction format. Extract the operation timing data after timing co-processing, and add operation timing markers to the preliminary sequence of node connection reconstruction and the preliminary sequence of link transmission reconstruction. The operation timing markers include the start time and execution duration of each operation step. Integrate the initial sequence of node connection reconstruction with reconstruction operation instructions and operation timing markers to form a node connection reconstruction subsequence; The initial sequence of link transmission reconstruction with reconstruction operation instructions and operation timing marks is integrated to form a link transmission reconstruction subsequence. The node connection reconstruction subsequence and the link transmission reconstruction subsequence are merged to generate a network topology reconstruction path self-adaptive sequence.

5. The dynamic reconfiguration and optimization method for communication information network topology according to claim 4, characterized in that, The step of invoking the node dynamic association rules in the network topology elastic association body, based on node connection adjustment data and node resource configuration adjustment data, to generate the operation steps and operation sequence for node connection reconstruction includes: Extract node state association sub-rules and node interaction association sub-rules from the node dynamic association rules of the network topology elastic association body, and input node connection adjustment data into the node interaction association sub-rules; By parsing the node identification data and connection relationship change data in the node connection adjustment data through node interaction association sub-rules, the set of node pairs that need connection adjustment and the adjustment type are determined. Input the node resource configuration adjustment data into the node status association sub-rule, parse the resource type data and resource allocation change data in the node resource configuration adjustment data, and determine the resource adjustment amount and adjustment method for each node; Based on the node pair set and adjustment type, combined with the node resource adjustment quota and adjustment method, generate the pre-operation and post-operation for each node pair connection adjustment, and record the dependency relationship between operation steps; Based on the dependencies between operation steps, the order of node connection adjustment is arranged so that subsequent operations are executed only after the preceding operations are completed, forming an ordered queue of operation steps. Extract the node performance parameters from the network topology elastic association, and determine the execution time of each operation step based on the node performance parameters and node resource adjustment type; Based on the operation step queue and the execution time of each operation step, the start time of each operation step is generated so that the execution times of adjacent operation steps do not overlap. Add an associated node identifier to each operation step, and record the associated nodes corresponding to the operation steps and the interaction relationships between the nodes; Based on the priority determination rules in the node dynamic association rules when multiple operation steps request the same node resource, the execution order of operation steps with resource conflict risk in the operation step queue is adjusted. The integrated and adjusted operation steps queue, start time, and execution duration form a preliminary sequence for node connection reconstruction. The input of each operation step comes from the output of the preceding operation or preset association rule data.

6. The dynamic reconfiguration and optimization method for communication information network topology according to claim 4, characterized in that, The step of invoking the link dynamic association rules in the network topology elastic association body, and generating the link transmission reconstruction operation steps and operation sequence based on link transmission parameter adjustment data and link load distribution adjustment data, includes: Extract link transmission association sub-rules and link adaptation association sub-rules from the link dynamic association rules of the network topology elastic association body, and input link transmission parameter adjustment data into the link transmission association sub-rules; By parsing the link identification data and transmission parameter change data in the link transmission parameter adjustment data through the link transmission association sub-rules, the set of links that need parameter adjustment and the type of parameter adjustment are determined. Input the link load distribution adjustment data into the link adaptation association sub-rule, parse the load type data and load distribution change data in the link load distribution adjustment data, and determine the load adjustment ratio and adjustment direction for each link; Based on the link set and parameter adjustment type, combined with the load adjustment ratio and adjustment direction, generate the pre-preparation operation and post-optimization operation for each link transmission parameter adjustment, and record the logical relationship between the operation steps; Based on the logical relationship between the operation steps, the operation sequence of link transmission reconstruction is arranged so that the core adjustment operation is performed after the preparatory operation is completed, and the post-optimization operation is performed after the core adjustment operation is completed. Extract the link device performance parameters from the network topology elastic association, and determine the execution time of each transmission parameter adjustment operation based on the link device performance parameters and the transmission parameter adjustment type; Based on the link device performance parameters and load distribution adjustment type, determine the execution time of each load distribution adjustment operation; The execution time of each operation step is adjusted according to the operation sequence, transmission parameters, and load distribution to generate the start time of each operation step. Add associated link identifiers and associated node identifiers to each operation step, and record the links corresponding to the operation steps and the nodes connected to those links. By integrating the operation sequence, start time, and execution duration, a preliminary sequence for link transmission reconstruction is formed. The input for each operation step comes from the output of the preceding operation or the preset data in the link dynamic association rules.

7. The dynamic reconfiguration and optimization method for communication information network topology according to claim 1, characterized in that, The step of adjusting the connection mode of network nodes and the transmission configuration of network links in conjunction with the self-adaptive sequence of the network topology reconstruction path, and synchronously updating the node dynamic association rules and link dynamic association rules in the network topology elastic association body, includes: Extract node connection reconstruction subsequences and link transmission reconstruction subsequences from the network topology reconstruction path self-adaptation sequence, and parse the reconstruction operation instructions, operation timing markers and associated node identifiers in the node connection reconstruction subsequences; Parse the reconstruction operation instructions, operation timing marks, and associated link identifiers in the link transmission reconstruction subsequence, and sort the node connection reconstruction subsequence and link transmission reconstruction subsequence in a unified manner according to the operation timing marks; Following the unified sorted operation order, based on the reconstruction operation instructions in the node connection reconstruction subsequence, a connection mode adjustment instruction is sent to the corresponding network node device to adjust the network node's connection interface configuration and connection protocol parameters. After performing the connection mode adjustment operation for each node, collect the connection status update data fed back by the network node devices; Based on the reconstruction operation instructions in the link transmission reconstruction subsequence, combined with the connection status update data, a transmission configuration adjustment instruction is sent to the corresponding network link device to adjust the transmission rate parameters and load distribution ratio of the network link. After performing each link transmission configuration adjustment operation, the transmission status update data fed back by the network link devices is collected, and the transmission status update data is correlated and integrated with the connection status update data. Based on the associated and integrated status update data, dynamic update information of node operation and real-time update information of link transmission are extracted. The dynamic update information of node operation includes adjusted node working status data and node resource usage data. The real-time link transmission update information includes adjusted link transmission rate data and link load data, and the node dynamic association rules in the network topology elastic association body are corrected based on the node operation dynamic update information. The link dynamic association rules in the network topology elastic association body are corrected based on real-time link transmission update information. By integrating the results of node connection mode adjustment, link transmission configuration adjustment, and the updated network topology elastic association, dynamic reconstruction and optimization of the communication information network topology is completed.

8. The dynamic reconfiguration optimization method for communication information network topology according to claim 7, characterized in that, The step involves sending connection mode adjustment instructions to the corresponding network node devices according to the unified sorted operation order and based on the reconstruction operation instructions in the node connection reconstruction sub-sequence. This adjusts the connection interface configuration and connection protocol parameters of the network nodes, including: Extract the operation steps that belong to node connection reconstruction from the unified sorted operation sequence, and activate each operation step in sequence according to the start time in the operation timing mark; For each activated operation step, read the operation object identifier, operation content and operation triggering conditions from the corresponding reconstruction operation instruction, and collect the current running status of the network node device corresponding to the operation object identifier; Based on the connection interface configuration requirements in the operation content, interface configuration adjustment data is generated, which includes interface type selection data, interface rate configuration data, and interface link binding data. Based on the connection protocol parameter requirements in the operation content, protocol parameter adjustment data is generated, which includes transmission control protocol parameter data, routing protocol parameter data, and session protocol parameter data. The interface configuration adjustment data and protocol parameter adjustment data are encapsulated into a connection mode adjustment command, which is sent to the network node device corresponding to the operation object identifier. The command sending time and command content are recorded, and the command reception confirmation information returned by the network node device is received. During the adjustment operation performed by the network node device, the adjustment progress data fed back by the device is received in real time; After the network node device completes the adjustment operation, it receives the connection status update data fed back by the device. The connection status update data includes the adjusted interface working status data and protocol running status data. The connection status update data is associated with the corresponding operation steps and stored.

9. The dynamic reconfiguration and optimization method for communication information network topology according to claim 7, characterized in that, The reconstruction operation instructions in the link transmission reconstruction sub-sequence, combined with connection state update data, send transmission configuration adjustment instructions to the corresponding network link devices to adjust the transmission rate parameters and load distribution ratio of the network link, including: Extract the operation steps belonging to link transmission reconfiguration from the unified sorted operation sequence, and activate each operation step sequentially according to the start time in the operation timing mark; For each activated operation step, read the operation object identifier, operation content and operation triggering condition from the corresponding reconstruction operation instruction, and retrieve the connection status update data associated with that operation step. The transmission rate parameter adjustment requirements are extracted from the operation content, and combined with the interface rate configuration data in the associated connection status update data to generate rate parameter adjustment data, which includes target rate value and rate adjustment gradient data. The load allocation ratio adjustment requirements are extracted from the operation content, and the node resource usage data in the associated connection status update data are combined to generate load allocation adjustment data, which includes target allocation ratio and allocation adjustment step size data. The rate parameter adjustment data and load distribution adjustment data are encapsulated into a transmission configuration adjustment command. The transmission configuration adjustment command is sent to the network link device corresponding to the operation object identifier. The command sending time, command content and associated connection status update data are recorded. The command reception confirmation information returned by the network link device is received. During the adjustment operation of the network link device, the adjustment progress data fed back by the device is received in real time; After the network link device completes the adjustment operation, it receives transmission status update data from the receiving device. The transmission status update data includes the actual value of the adjusted transmission rate and the actual load distribution ratio data. The transmission status update data is then associated with the corresponding operation steps and the associated connection status update data and stored together.

10. A dynamic reconfiguration optimization system for communication information network topology, characterized in that, The method includes a processor and a computer-readable storage medium storing machine-executable instructions that, when executed by the processor, implement the dynamic reconfiguration optimization method for communication information network topology as described in any one of claims 1-9.

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