Enterprise multi-branch networking deployment method and system

Abstract

The present invention discloses a method and system for enterprise multi-branch networking deployment, and relates to the field of network communication technology. The method comprises: constructing a business function hierarchical tree structure; matching the network service requirements of each business tree node in the business function hierarchical tree structure, and establishing network service requirement parameters mapped to the business tree nodes; establishing a multi-dimensional mapping space; selecting available resource nodes to match for each business tree node; using connection constraints and adaptation fitness functions to perform matching optimization, establish a binding relationship, establish a network topology diagram based on the binding relationship and the business function hierarchical tree structure, and perform networking deployment according to the network topology diagram. This solves the technical problem in the prior art that it is difficult to accurately match business requirements and network resources when deploying enterprise multi-branch networking, resulting in unreasonable network architecture, low resource utilization, and low deployment efficiency, thereby achieving the technical effect of improving resource utilization and deployment efficiency.

Description

Technical Field

[0001] The present invention relates to the field of network communication technology, and in particular to a method and system for deploying enterprise multi-branch networking. Background Art

[0002] Different enterprise branches often carry independent or collaborative business functions. Network deployment must not only meet the basic communication needs of each branch, but also accurately match the service types, performance requirements, and resource dependencies of each business node. However, common networking methods in existing technologies often rely on manual configuration or static templates, lacking in-depth analysis and modeling of internal business dependencies within the enterprise. This makes it difficult to dynamically match and optimize network resources based on actual business needs, resulting in irrational network architecture, low resource utilization, inefficient deployment, and difficult ongoing maintenance. Summary of the Invention

[0003] This application provides a method and system for enterprise multi-branch networking deployment, which solves the technical problem in the existing technology that it is difficult to accurately match business needs and network resources when deploying enterprise multi-branch networking, resulting in unreasonable network architecture, low resource utilization and low deployment efficiency.

[0004] A first aspect of the present application provides a method for deploying a multi-branch network in an enterprise, the method comprising:

[0005] Obtain the enterprise's business data set, use the business data set to identify the dependency and attribution relationship between the enterprise's multi-branch business nodes, and build a business function hierarchical tree structure, wherein the business data set includes terminal behavior logs, system access paths, and business module dependencies; match the network service requirements of each business tree node in the business function hierarchical tree structure, and establish network service requirement parameters mapped to the business tree nodes; obtain all available resource nodes in the current network, and establish a multidimensional mapping space, wherein the multidimensional mapping space is constructed with the business tree node as the first mapping end and all available resource nodes as the second mapping end; traverse the business function hierarchical tree structure from top to bottom, and select an available resource node to match for each business tree node; configure the connection constraints of parent and child nodes, use the connection constraints and the adaptation fitness function to perform matching optimization, establish a binding relationship, establish a network topology diagram based on the binding relationship and the business function hierarchical tree structure, and perform network deployment according to the network topology diagram.

[0006] A second aspect of the present application provides a system for deploying a multi-branch network in an enterprise, the system comprising:

[0007] A relationship identification module is used to obtain the enterprise's business data set, use the business data set to identify the dependency and attribution relationship between the enterprise's multi-branch business nodes, and construct a business function hierarchical tree structure, wherein the business data set includes terminal behavior logs, system access paths, and business module dependencies; a demand matching module is used to match the network service requirements of each business tree node in the business function hierarchical tree structure, and establish network service demand parameters mapped to the business tree nodes; a mapping space construction module is used to obtain all available resource nodes in the current network and establish a multidimensional mapping space, wherein the multidimensional mapping space is constructed with the business tree node as the first mapping end and all available resource nodes as the second mapping end; a node matching module is used to traverse the business function hierarchical tree structure from top to bottom, and select an available resource node to match for each business tree node; a network deployment module is used to configure the connection constraints of parent and child nodes, use the connection constraints and the adaptation fitness function to perform matching and optimization, establish a binding relationship, establish a network topology diagram based on the binding relationship and the business function hierarchical tree structure, and perform network deployment according to the network topology diagram.

[0008] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0009] First, an enterprise's business data set is obtained. The data set is used to identify the dependencies between the enterprise's multi-branch business nodes and construct a business function hierarchy tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependencies. Next, the business function hierarchy tree structure is matched to the network service requirements of each business tree node, establishing network service requirement parameters mapped to the business tree nodes. Next, all available resource nodes in the current network are obtained, and a multidimensional mapping space is established. The multidimensional mapping space is constructed with the business tree nodes as the first mapping end and all available resource nodes as the second mapping end. Then, the business function hierarchy tree structure is traversed top-down, selecting a matching available resource node for each business tree node. Finally, connectivity constraints are configured for parent and child nodes. A matching optimization is performed using the connectivity constraints and an adaptive fitness function to establish binding relationships. A network topology is then constructed based on the binding relationships and the business function hierarchy tree structure, and network deployment is performed according to the network topology. This solves the technical problem of the difficulty in accurately matching business requirements with network resources in the deployment of multi-branch networks in enterprises in the prior art, resulting in an irrational network architecture, low resource utilization, and low deployment efficiency. This improves resource utilization and deployment efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0010] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0011] Figure 1 A flowchart of a method for deploying a multi-branch enterprise network according to an embodiment of the present application;

[0012] Figure 2 A schematic diagram of the enterprise multi-branch networking deployment system structure provided in an embodiment of the present application.

[0013] Explanation of the accompanying drawings: relationship identification module 11, demand matching module 12, mapping space construction module 13, node matching module 14, network deployment module 15. DETAILED DESCRIPTION

[0014] This application solves the technical problem in the existing technology that it is difficult to accurately match business needs and network resources when deploying multi-branch networks in an enterprise, resulting in unreasonable network architecture, low resource utilization and low deployment efficiency, by providing a method and system for deploying multi-branch networks in an enterprise.

[0015] The following will be combined with the accompanying drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only some of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0016] It should be noted that the terms "including" and "having" are intended to cover non-exclusive inclusions. For example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or modules that are not clearly listed or are inherent to these processes, methods, products or devices.

[0017] Example 1, as Figure 1 As shown, the present application provides a method for deploying a multi-branch network in an enterprise, wherein the method includes:

[0018] Obtain the enterprise's business data set, use the business data set to identify the dependency relationship between the enterprise's multi-branch business nodes, and build a business function hierarchical tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependencies.

[0019] In an embodiment of the present application, by obtaining business data sets in the enterprise's multi-branch network, including terminal behavior logs, system access paths and business module dependencies, the dependency attribution relationship between each branch business node within the enterprise is identified and analyzed, and a business function hierarchical tree structure is constructed accordingly. Specifically, terminal behavior logs are collected from each terminal device (such as computers, mobile devices, etc.) through a log management system or a data acquisition platform. These logs record information such as the applications accessed, resources accessed, and operations initiated by each terminal during use, thereby reflecting the business interaction between different terminals; system access path information is obtained through a network monitoring system. The system access path information records the communication paths, data flows and their dependencies between each business module or service within the enterprise. By analyzing these path data, it is possible to identify which business modules need to rely on other modules to provide services, and then obtain the dependencies between business modules.

[0020] During dependency identification, a graph theory approach is used to construct a business dependency graph, with each business node as a vertex and the dependencies between business nodes as edges. Graph analysis techniques (such as shortest path algorithms and cluster analysis) are then used to identify direct and indirect dependencies between nodes, ensuring a comprehensive and accurate description of the relationships between all business nodes. Based on the dependency graph, a hierarchical tree structure of business functions is constructed. This structure layers business nodes from top to bottom according to their dependencies. Each node represents an independent business module or service. The root node represents the enterprise's core business module or service, while child nodes represent submodules that have dependencies on the root node or other modules.

[0021] The service function hierarchical tree structure is matched with the network service demand of each service tree node, and network service demand parameters mapped to the service tree nodes are established.

[0022] In an embodiment of the present application, based on the constructed business function hierarchical tree structure, detailed network service demand matching is performed for each business tree node. Each business tree node represents a specific business module or function, and the node has different network service requirements according to its business needs. These network service requirements include but are not limited to parameters such as bandwidth, latency, throughput, and security. For example, for business modules that require high data transmission, such as data storage or file transfer systems, higher bandwidth and throughput may be required; while for business modules with higher real-time requirements, such as video conferencing or online trading systems, there may be strict requirements on latency. By analyzing the workload, performance requirements, and network resource consumption of the business modules, the specific network service requirements of each business node are accurately identified. Based on these requirements, network service demand parameters mapped to each business tree node are established to define key performance indicators such as bandwidth, latency, and throughput required for each node.

[0023] All available resource nodes of the current network are acquired, and a multi-dimensional mapping space is established. The multi-dimensional mapping space is constructed with the service tree node as the first mapping end and all available resource nodes as the second mapping end.

[0024] In an embodiment of the present application, all available resource nodes in the current network are obtained through a network management system. These resource nodes can be computing nodes, storage nodes, bandwidth resource nodes, security devices, routers, etc. in the network, and the specific type depends on the network architecture and business needs of the enterprise. After obtaining all available resource nodes, a multidimensional mapping space is established, in which the business tree node serves as the first mapping end and the resource node serves as the second mapping end. By constructing a multidimensional mapping space, an accurate match is made between the business tree node and the resource node, thereby ensuring that the network service requirements (such as bandwidth, delay, throughput, security, etc.) of each business node can be supported by corresponding resources. The multidimensionality of the mapping space includes: the network service requirement dimension of the business tree node, the capability dimension (such as bandwidth, processing power, etc.) of the resource node, and the matching constraint dimension (such as geographical location, network topology, etc.).

[0025] Traverse the business function hierarchy tree structure from top to bottom and select an available resource node to match for each business tree node.

[0026] In an embodiment of the present application, based on the constructed business function hierarchy tree structure, a top-down traversal method is adopted to select the adapted available resource nodes. Specifically, the business function hierarchy tree starts from the root node, which represents the core business module of the enterprise, and traverses all child nodes downward in sequence, each child node corresponding to a business module or function. During the traversal process, for each business tree node, according to the network service requirements of the node (such as bandwidth, delay, throughput, security, etc.), a suitable available resource node is selected for matching. The matching selection of each business tree node will be gradually determined according to its hierarchical relationship in the tree structure to ensure that the network requirements of the parent node and the child node can be effectively supported in the topology structure.

[0027] Configure the connection constraints of the parent and child nodes, use the connection constraints and the adaptation fitness function to perform matching optimization, establish a binding relationship, establish a network topology diagram based on the binding relationship and the business function hierarchical tree structure, and perform networking deployment according to the network topology diagram.

[0028] In an embodiment of the present application, the connection constraints between the parent and child nodes are configured to ensure that the business nodes at different levels in the business function hierarchy tree structure can be effectively connected and work together. Specifically, by analyzing the data dependency between the parent and child nodes, data flow constraints are established to ensure that the data meets the bandwidth and delay requirements when transmitted between the parent and child nodes; at the same time, considering the control dependency between the parent and child nodes, such as startup, scheduling, approval and other operations, control dependency constraints are generated to ensure that the requirements of delay and link stability are met during the control signal transmission process. The configured connection constraints and the adaptation fitness function are used to perform a matching optimization process. The adaptation fitness function evaluates the matching degree of the resource node based on the network service requirements (such as bandwidth, delay, etc.) of each business tree node, and optimizes through the optimization algorithm to select the optimal resource node to meet the service quality requirements of the business module. During the optimization process, the adaptation fitness function is continuously iterated to update the matching of the resource nodes to achieve the optimal binding of the business tree nodes and the resource nodes. After completing the matching optimization, a binding relationship between the parent and child nodes is established to ensure that the service requirements of each node are met and a stable resource allocation structure is formed. Based on these binding relationships and the constructed business function hierarchical tree structure, a network topology diagram can be further constructed. This network topology diagram clearly displays the connections between business modules within the enterprise, data flow paths, and resource node allocation. Finally, based on the established network topology diagram, the network deployment process is executed, allocating appropriate resource nodes to each business module and optimizing the network configuration based on business needs to ensure the rationality, stability, and efficiency of the network architecture.

[0029] Furthermore, configuring the connection constraints between parent and child nodes includes:

[0030] Obtain the data flow direction between the parent and child nodes, perform path connectivity and bandwidth support analysis based on the data flow direction, and establish data dependency constraints; perform process constraint analysis on the control, startup, scheduling, and approval of the parent and child nodes, generate instruction transmission delay indicators and link stability indicators based on the constraint analysis results, and establish control dependency constraints based on the instruction transmission delay indicators and link stability indicators; establish the connection constraints based on the data dependency constraints and control dependency constraints.

[0031] Preferably, by analyzing the data flow between parent and child nodes, the data transmission path from parent to child is obtained, and the connectivity of this path is analyzed to ensure that data can be transmitted smoothly in the network without interruption or bottlenecks. Next, based on the results of the path connectivity analysis, a bandwidth support analysis is performed to assess whether the data flow between parent and child nodes can obtain sufficient bandwidth support to ensure that data transmission is not congested or delayed. Based on these analysis results, data dependency constraints are established, that is, the bandwidth, delay and other parameter requirements between parent and child nodes during the data transmission process are determined to ensure the stability of the data flow and transmission efficiency.

[0032] Furthermore, constraint analysis is required for control signal transmission between parent and child nodes. Specifically, processes such as control, startup, scheduling, and approval between parent and child nodes affect network performance, necessitating an analysis of latency and link stability. Based on this, instruction transmission latency and link stability metrics are generated to describe the timeliness and stability requirements for control signal transmission from parent to child nodes. The instruction transmission latency metric reflects the time required for control instructions to be transmitted across the network, while the link stability metric reflects the reliability and stability of the network link during instruction transmission. Based on these analysis results, control dependency constraints are established to ensure that control signals between parent and child nodes are transmitted within a reasonable latency and meet network stability requirements. By combining data dependency constraints and control dependency constraints, a complete set of parent-child node connection constraints is formed.

[0033] Furthermore, using the connection constraint and the adaptation fitness function to perform matching optimization and establish a binding relationship includes:

[0034] Performing position cluster matching on the business tree nodes of the business function hierarchical tree structure to establish a position cluster matching result; utilizing the position cluster matching result to synchronously cluster and sort all the available resource nodes to establish a synchronous cluster sorting result; in the process of performing matching optimization, updating and iterating are performed according to the fitness value of each group of solutions and the synchronous cluster sorting result to complete the matching optimization.

[0035] In the embodiment of the present application, the configured connection constraints and adaptation fitness function are used to perform matching optimization to ensure that each service tree node can be matched with a suitable resource node, and ultimately establish a valid binding relationship.

[0036] Before performing matching optimization, each business tree node in the business function hierarchy tree structure is subjected to location cluster matching. Specifically, the business tree nodes are clustered according to factors such as their hierarchical relationship in the tree structure and service requirements to form a set of location cluster matching results.

[0037] After obtaining the location cluster matching results, these results are used to perform synchronous cluster sorting on all available resource nodes in the network. Synchronous cluster sorting sorts available resource nodes based on their characteristics (such as bandwidth, latency, and processing power). This makes resource node allocation more efficient and ensures that resources can optimally meet the needs of service tree nodes.

[0038] During the matching and optimization process, each solution set is evaluated using an adaptive fitness function and iteratively updated based on the fitness value and the results of the synchronous clustering ranking. Each solution set represents a possible matching scheme for business nodes and resource nodes, and the fitness value reflects the pros and cons of this scheme, including multiple metrics such as bandwidth, latency, cost, and security. Through continuous updates and iterations, the adaptive fitness function continuously optimizes the matching results, selects the optimal resource nodes for binding, and ultimately forms a stable and efficient binding relationship between business nodes and resource nodes.

[0039] Furthermore, the evaluation indicators of the adaptation fitness function include delay indicator, energy consumption indicator, security indicator, and cost indicator.

[0040] The adaptation fitness function is used to evaluate the degree of match between service tree nodes and available resource nodes to select the optimal resource allocation solution. The evaluation metrics of the adaptation fitness function mainly include latency, energy consumption, security, and cost. These metrics can comprehensively reflect the quality of resource allocation, ensuring that the network architecture meets service needs while optimizing network performance, reducing energy consumption, improving security, and lowering costs.

[0041] The delay indicator is used to evaluate the communication delay between the service tree nodes and the available resource nodes. The adaptive fitness function calculates the communication delay based on factors such as the physical distance between each node in the network, network load, routing path, etc., and optimizes it to ensure that the delay of service data transmission in the network meets the requirements.

[0042] The energy consumption index reflects the energy efficiency of resource nodes in network deployment. The adaptive fitness function calculates the energy consumption of each resource node and selects those resource nodes with low energy consumption and high resource utilization efficiency to achieve the purpose of energy saving and consumption reduction, thereby reducing network operating costs and environmental impact.

[0043] Security indicators are used to evaluate the security between resource nodes in the network topology. The adaptive fitness function will perform security assessments based on the security features of each resource node (such as firewalls, security protocols, etc.) to ensure that nodes with sufficient security guarantees are selected during matching, thereby improving the network's anti-attack capabilities and data protection capabilities.

[0044] The cost indicator evaluates the cost-effectiveness of each resource node in the matching process. The adaptation fitness function will comprehensively consider the cost of each node and give priority to those resource nodes that can meet business needs and have lower operating costs to achieve cost optimization.

[0045] Furthermore, during the matching optimization process, the fitness value of each solution group and the synchronous clustering sorting results are updated and iterated to complete the matching optimization, including:

[0046] Locate the business tree node of the current iterative optimization, and locate the synchronous clustering sorting result based on the business tree node; obtain the fitness value of the current solution, and use the fitness value and the synchronous clustering sorting result to perform search breakthrough evaluation; if the search breakthrough evaluation is a breakthrough pass evaluation, perform a cross-cluster cluster search update of the current solution to complete the optimal matching.

[0047] During each iteration, the system locates the business tree node for optimization in the current iteration, specifically the business node that requires matching. These nodes are dynamically updated based on changes in business requirements, service dependencies, and other factors, ensuring that the business node to be optimized is selected in each iteration. Once the business tree node to be optimized is determined, the system uses the results of synchronized clustering sorting to locate the resource nodes associated with that node. Synchronous clustering sorting sorts nodes based on their resource requirements and availability, forming a ranked list. Based on the requirements of the current business tree node, this ranking guides the system to quickly find the resource node that best matches the business tree node, avoiding ineffective matches and wasted resources. The system then obtains the fitness value of the current solution. This fitness value is calculated using an adapted fitness function and reflects the quality of the match between the current resource node and the business tree node. Based on the current solution's fitness value and the synchronized clustering sorting results, the system performs a search breakthrough evaluation to determine whether the current solution has surpassed the current local optimum, that is, whether a better match is possible. If the result of the breakthrough evaluation is breakthrough passed, it means that the matching result of the current solution has surpassed the local optimum, and the system will perform further matching updates. After the breakthrough pass evaluation, the system will perform a cross-cluster search update for the current solution. That is, the system will no longer be limited to the resource nodes within the current cluster, but will begin searching across clusters to find more optimal resource nodes for matching. Through multiple rounds of iteration, continuous updating and optimization of matching results, the system will eventually find the optimal matching relationship between service tree nodes and resource nodes, thereby improving the efficiency of network deployment and resource utilization. Each iterative update is based on the fitness value and the synchronized cluster sorting results. Through cross-cluster search and fitness optimization, it ensures that the final matching result is optimal.

[0048] Furthermore, the fitness value and the synchronous clustering ranking result positioning are used to perform search breakthrough evaluation, including:

[0049] If the search breakthrough evaluation is a breakthrough failure result, an intra-cluster search update is performed within the synchronous cluster sorting result positioning to determine a search direction and an adaptive search step; and the search direction and the adaptive search step are used to complete the optimal matching.

[0050] If the breakthrough search evaluation fails, meaning the current solution fails to surpass the local optimal solution, the system will perform an intra-cluster search update within the synchronized cluster ranking results. The goal of this intra-cluster search update is to find a more optimal resource node matching solution within the current cluster, thereby improving matching quality and avoiding unnecessary cross-cluster searches. To this end, the system determines a search direction and an adaptive search step size. The search direction refers to the direction of optimization within the current cluster, which may be in areas such as bandwidth, latency, and energy consumption. The adaptive search step size is dynamically adjusted based on feedback during the search process to achieve more efficient search and matching. After determining the search direction and adaptive search step size, the system uses this information to complete the optimal matching. Through further searches and updates, the matching results are optimized. This ensures that if a local optimal solution cannot be surpassed, fine-tuning and optimization can be performed within the existing cluster to ultimately find a suitable resource node matching solution, further improving network resource utilization and matching accuracy.

[0051] Furthermore, after performing search breakthrough evaluation using the fitness value and the synchronous clustering ranking result positioning, the method further includes:

[0052] After any business tree node is matched, the matched available resource node is added to the taboo list; during the search and matching process, it is determined whether there is a result that no adapted available resource node exists; if there is a result that no adapted available resource node exists during the search and matching process, a fallback instruction is generated, and the matching degradation of the fallback node is set; the optimal matching is completed according to the fallback instruction and the matching degradation.

[0053] After each business tree node is matched, the system will add the matched available resource nodes to the taboo list. The function of the taboo list is to record the matched resource nodes to avoid selecting these used resource nodes again in the subsequent matching process, thereby avoiding unnecessary resource duplication.

[0054] During the matching process, the system determines in real time whether there are any unmatched available resource nodes. If, during the current iteration, the system cannot find a suitable resource node to match the service tree node, meaning it fails to match any available resource nodes, the system generates a fallback instruction. This fallback instruction instructs the system to readjust the matching strategy and handle the fallback node through match downgrade. Match downgrade involves reassigning the currently unmatched node to a lower-priority resource node, allowing it to re-enter the optimization process at a lower matching priority in subsequent matches.

[0055] After executing the fallback command and matching downgrade, the system will continue to search for optimal matching, ensuring that the most suitable resource node can be found as much as possible after the fallback node is downgraded. The generation of fallback commands combined with the implementation of the matching downgrade strategy can effectively avoid search interruptions caused by unmatched resource nodes, ensuring that the system can adaptively adjust and continue to optimize resource allocation.

[0056] Furthermore, using the connection constraint and the adaptation fitness function to perform matching optimization also includes:

[0057] Perform node stability analysis on the business tree nodes in the business function hierarchy tree structure and establish a stability impact factor; use the stability impact factor to establish additional matching constraints, and perform matching optimization based on the additional matching constraints, the connection constraints and the adaptation fitness function.

[0058] The matching optimization process using connectivity constraints and adaptive fitness functions not only relies on connectivity constraints and adaptive fitness functions but also includes node stability analysis for each service tree node in the service function hierarchy tree structure. The purpose of node stability analysis is to assess the potential stability impact of each service tree node in the network topology, particularly in terms of network load, latency, bandwidth usage, and resource dependency. By quantifying various characteristics of service tree nodes, a stability impact factor is calculated for each node, reflecting the node's stability within the network. This stability factor includes, but is not limited to, the node's resource consumption, the frequency of inter-node data transmission, the node's load, and the node's dependence on other nodes. Based on the stability impact factor, the system introduces additional matching constraints for each service tree node. These additional matching constraints are generated based on the node stability analysis results. They ensure that during resource matching, nodes with poor stability are not assigned to overly important nodes or nodes with high resource demands, thereby preventing uneven resource allocation and potentially leading to system instability. For example, nodes with poor stability are restricted from matching with resource nodes with high loads, thereby ensuring the proper allocation of resource nodes and ensuring stable operation of the entire network.

[0059] After introducing additional matching constraints, the system performs matching optimization based on the combined effects of these constraints and the adaptive fitness function. By incorporating stability constraints into the optimization process, the system ensures efficient resource utilization while avoiding issues such as network performance degradation, overload, or link instability caused by unstable resource allocation. Through the matching optimization process, the system selects the best resource nodes and binds them to service tree nodes based on a comprehensive consideration of stability, resource adaptability, and service dependencies, thereby forming an optimized network topology. This network topology ensures network efficiency and stability, optimizes resource utilization, and improves the reliability of network deployment.

[0060] Furthermore, performing network deployment according to the network topology diagram includes:

[0061] Perform progress monitoring of the network deployment process, establish a deployment progress graph, a fitness dynamic graph, and a resource utilization heat map; and visualize the deployment progress graph, fitness dynamic graph, and resource utilization heat map.

[0062] By monitoring the network deployment process and tracking the progress of deployment tasks in real time, we can obtain a deployment progress chart, a fitness dynamic chart, and a resource utilization heat map. The deployment progress chart shows the completion status and progress of the current network deployment task. The fitness dynamic chart monitors the fitness function in real time during the deployment process, showing the fitness changes between the current network architecture and the ideal target. The resource utilization heat map is used to display the utilization of each resource node during the deployment process, and the usage intensity of different resource nodes is indicated by the depth of color.

[0063] During deployment progress monitoring, the system visualizes the above charts, allowing users to intuitively understand the current deployment status through a graphical interface. By visually displaying deployment progress, adaptability, and resource utilization, users can quickly obtain important real-time data and feedback, making more accurate decisions, optimizing resource allocation, and ensuring that network deployment is completed smoothly according to planned goals.

[0064] In summary, the embodiments of the present application have at least the following technical effects:

[0065] First, an enterprise's business data set is obtained. The data set is used to identify the dependencies between the enterprise's multi-branch business nodes and construct a business function hierarchy tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependencies. Next, the business function hierarchy tree structure is matched to the network service requirements of each business tree node, establishing network service requirement parameters mapped to the business tree nodes. Next, all available resource nodes in the current network are obtained, and a multidimensional mapping space is established. The multidimensional mapping space is constructed with the business tree nodes as the first mapping end and all available resource nodes as the second mapping end. Then, the business function hierarchy tree structure is traversed top-down, selecting a matching available resource node for each business tree node. Finally, connectivity constraints are configured for parent and child nodes. A matching optimization is performed using the connectivity constraints and an adaptive fitness function to establish binding relationships. A network topology is then constructed based on the binding relationships and the business function hierarchy tree structure, and network deployment is performed according to the network topology. This solves the technical problem of the difficulty in accurately matching business requirements with network resources in the deployment of multi-branch networks in enterprises in the prior art, resulting in an irrational network architecture, low resource utilization, and low deployment efficiency. This improves resource utilization and deployment efficiency.

[0066] Example 2, based on the same inventive concept as the enterprise multi-branch networking deployment method in the above embodiment, Figure 2 As shown, the present application provides a network deployment system for multiple branches of an enterprise, wherein the system includes:

[0067] The relationship identification module 11 is used to obtain the business data set of the enterprise, use the business data set to identify the dependency and attribution relationship between the enterprise's multi-branch business nodes, and construct a business function hierarchical tree structure, wherein the business data set includes terminal behavior logs, system access paths, and business module dependencies; the demand matching module 12 is used to match the network service requirements of each business tree node in the business function hierarchical tree structure, and establish network service requirement parameters mapped to the business tree nodes; the mapping space construction module 13 is used to obtain all available resource nodes in the current network and establish a multidimensional mapping space, wherein the multidimensional mapping space is constructed with the business tree node as the first mapping end and all available resource nodes as the second mapping end; the node matching module 14 is used to traverse the business function hierarchical tree structure from top to bottom, and select an available resource node to match for each business tree node; the network deployment module 15 is used to configure the connection constraints of parent and child nodes, use the connection constraints and the adaptation fitness function to perform matching and optimization, establish a binding relationship, establish a network topology diagram based on the binding relationship and the business function hierarchical tree structure, and perform network deployment according to the network topology diagram.

[0068] Furthermore, the networking deployment module 15 is configured to execute the following method:

[0069] Obtain the data flow direction between the parent and child nodes, perform path connectivity and bandwidth support analysis based on the data flow direction, and establish data dependency constraints; perform process constraint analysis on the control, startup, scheduling, and approval of the parent and child nodes, generate instruction transmission delay indicators and link stability indicators based on the constraint analysis results, and establish control dependency constraints based on the instruction transmission delay indicators and link stability indicators; establish the connection constraints based on the data dependency constraints and control dependency constraints.

[0070] Furthermore, the networking deployment module 15 is configured to execute the following method:

[0071] Performing position cluster matching on the business tree nodes of the business function hierarchical tree structure to establish a position cluster matching result; utilizing the position cluster matching result to synchronously cluster and sort all the available resource nodes to establish a synchronous cluster sorting result; in the process of performing matching optimization, updating and iterating are performed according to the fitness value of each group of solutions and the synchronous cluster sorting result to complete the matching optimization.

[0072] Furthermore, the networking deployment module 15 is configured to execute the following method:

[0073] Locate the business tree node of the current iterative optimization, and locate the synchronous clustering sorting result based on the business tree node; obtain the fitness value of the current solution, and use the fitness value and the synchronous clustering sorting result to perform search breakthrough evaluation; if the search breakthrough evaluation is a breakthrough pass evaluation, perform a cross-cluster cluster search update of the current solution to complete the optimal matching.

[0074] Furthermore, the networking deployment module 15 is configured to execute the following method:

[0075] If the search breakthrough evaluation is a breakthrough failure result, an intra-cluster search update is performed within the synchronous cluster sorting result positioning to determine a search direction and an adaptive search step; and the search direction and the adaptive search step are used to complete the optimal matching.

[0076] Furthermore, the networking deployment module 15 is configured to execute the following method:

[0077] After any business tree node is matched, the matched available resource node is added to the taboo list; during the search and matching process, it is determined whether there is a result that no adapted available resource node exists; if there is a result that no adapted available resource node exists during the search and matching process, a fallback instruction is generated, and the matching degradation of the fallback node is set; the optimal matching is completed according to the fallback instruction and the matching degradation.

[0078] Furthermore, the networking deployment module 15 is configured to execute the following method:

[0079] Perform node stability analysis on the business tree nodes in the business function hierarchy tree structure and establish a stability impact factor; use the stability impact factor to establish additional matching constraints, and perform matching optimization based on the additional matching constraints, the connection constraints and the adaptation fitness function.

[0080] Furthermore, the networking deployment module 15 is configured to execute the following method:

[0081] Perform progress monitoring of the network deployment process, establish a deployment progress graph, a fitness dynamic graph, and a resource utilization heat map; and visualize the deployment progress graph, fitness dynamic graph, and resource utilization heat map.

[0082] Furthermore, the networking deployment module 15 is configured to execute the following method:

[0083] The evaluation indicators of the adaptation fitness function include delay indicator, energy consumption indicator, security indicator and cost indicator.

[0084] It should be noted that the order in which the embodiments of the present application are presented is for illustrative purposes only and does not necessarily represent the superiority or inferiority of the embodiments. Furthermore, the foregoing descriptions of specific embodiments of this specification are provided. The processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0085] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

[0086] This specification and drawings are merely illustrative of the present application and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Obviously, those skilled in the art may make various modifications and variations to this application without departing from the scope of this application. Thus, this application is intended to include such modifications and variations as fall within the scope of this application and its equivalents.

Claims

1. An enterprise multi-branch network deployment method, characterized in that: The method comprises: Obtaining the enterprise's business data set, using the business data set to identify the dependency relationships between the enterprise's multi-branch business nodes, and constructing a business function hierarchical tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependencies; Matching the network service requirements of each service tree node to the service function hierarchical tree structure, and establishing network service requirement parameters mapped to the service tree nodes; Acquire all available resource nodes of the current network and establish a multidimensional mapping space, wherein the multidimensional mapping space is constructed with the service tree node as the first mapping end and all available resource nodes as the second mapping end; Traverse the business function hierarchy tree structure from top to bottom and select an available resource node to match each business tree node; Configuring connection constraints between parent and child nodes, performing matching and optimization using the connection constraints and an adaptation fitness function to establish a binding relationship, establishing a network topology based on the binding relationship and the service function hierarchical tree structure, and performing network deployment according to the network topology; The configuration of the connection constraints between the parent and child nodes includes: Obtain the data flow between parent and child nodes, perform path connectivity and bandwidth support analysis based on the data flow, and establish data dependency constraints; Perform process constraint analysis on the control, startup, scheduling, and approval of parent and child nodes, generate instruction transmission delay indicators and link stability indicators based on the constraint analysis results, and establish control dependency constraints based on the instruction transmission delay indicators and link stability indicators; Establishing the connection constraint based on the data dependency constraint and the control dependency constraint; The method of using the connection constraint and the adaptation fitness function to perform matching optimization and establish a binding relationship includes: Performing position cluster matching on the service tree nodes of the service function hierarchical tree structure to establish a position cluster matching result; Performing synchronous clustering sorting on all available resource nodes using the position cluster matching result to establish a synchronous clustering sorting result; In the process of performing matching optimization, the fitness value of each solution group and the synchronous clustering sorting result are updated and iterated to complete the matching optimization.

2. The enterprise multi-branch networking deployment method according to claim 1, characterized in that: In the process of performing the matching optimization, updating and iterating are performed according to the fitness value of each set of solutions and the synchronous clustering sorting result to complete the matching optimization, including: Locate the business tree node of the current iterative optimization, and locate the synchronous clustering sorting result according to the business tree node; Obtaining the fitness value of the current solution, and using the fitness value and the synchronous clustering sorting result positioning to perform search breakthrough evaluation; If the search breakthrough evaluation is a breakthrough pass evaluation, a cross-cluster search update of the current solution is performed to complete the optimal matching.

3. The enterprise multi-branch networking deployment method according to claim 2, characterized in that: The method of using the fitness value and the synchronous clustering sorting result to locate and conduct search breakthrough evaluation includes: If the breakthrough evaluation result is a breakthrough failure, performing an intra-cluster search update within the synchronous cluster sorting result location to determine the search direction and the adaptive search step size; The search direction and the adaptive search step size are used to complete the optimal matching.

4. The enterprise multi-branch networking deployment method according to claim 2, characterized in that: After the fitness value and the synchronous clustering sorting result are used to locate and perform search breakthrough evaluation, the method further includes: After any business tree node is matched, the matched available resource node is added to the taboo list; During the search and matching process, determining whether there is no matching available resource node; If there is no result of an adaptable available resource node during the search and matching process, a fallback instruction is generated and the matching degradation of the fallback node is set; The optimal matching is completed according to the fallback instruction and the matching degradation.

5. The enterprise multi-branch networking deployment method according to claim 1, characterized in that: The matching optimization using the connection constraint and the adaptation fitness function also includes: Perform node stability analysis on the business tree nodes within the business function hierarchy tree structure and establish stability impact factors; The stability influencing factor is used to establish an additional matching constraint, and matching optimization is performed based on the additional matching constraint, the connection constraint and the adaptation fitness function.

6. The enterprise multi-branch network deployment method according to claim 1, characterized in that: The performing network deployment according to the network topology diagram includes: Monitor the progress of network deployment and create deployment progress charts, fitness dynamic charts, and resource utilization heat maps. The deployment progress graph, fitness dynamic graph, and resource utilization heat map are visualized.

7. The enterprise multi-branch networking deployment method according to claim 1, characterized in that: The evaluation indicators of the adaptation fitness function include delay indicator, energy consumption indicator, security indicator and cost indicator.

8. The enterprise multi-branch network deployment system is characterized by: The system for implementing the enterprise multi-branch networking deployment method according to any one of claims 1 to 7 comprises: A relationship identification module is used to obtain the enterprise's business data set, use the business data set to identify the dependency relationships between the enterprise's multi-branch business nodes, and build a business function hierarchical tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependencies; A demand matching module is used to match the network service demand of each business tree node in the business function hierarchical tree structure and establish network service demand parameters mapped to the business tree nodes; A mapping space construction module is used to obtain all available resource nodes in the current network and establish a multidimensional mapping space, wherein the multidimensional mapping space is constructed with the service tree node as the first mapping end and all available resource nodes as the second mapping end; The node matching module is used to traverse the business function hierarchy tree structure from top to bottom and select an available resource node to match for each business tree node; The network deployment module is used to configure the connection constraints of parent and child nodes, use the connection constraints and the adaptation fitness function to perform matching optimization, establish a binding relationship, establish a network topology diagram based on the binding relationship and the business function hierarchical tree structure, and perform network deployment according to the network topology diagram.

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