Enterprise multi-branch networking deployment method and system

Abstract

The invention discloses an enterprise multi-branch networking deployment method and system, and relates to the technical field of network communication. The method comprises the following steps: constructing a service function hierarchical tree structure; performing network service demand matching of each service tree node on the service function level tree structure, and establishing network service demand parameters mapped with the service tree nodes; establishing a multi-dimensional mapping space; selecting available resource nodes for matching for each service tree node; and performing matching optimization by using the connection constraint and the adaptive fitness function, establishing a binding relationship, establishing a network topological graph based on the binding relationship and the service function hierarchical tree structure, and performing networking deployment according to the network topological graph. The technical problems of unreasonable network architecture, low resource utilization rate and low deployment efficiency caused by difficulty in accurately matching service requirements and network resources during enterprise multi-branch networking deployment in the prior art are solved, and the technical effects of improving the resource utilization rate and the deployment efficiency are achieved.

Description

Technical Field

[0001] The present invention relates to the field of network communication technologies, and particularly to a networking deployment method and system for multiple branches of an enterprise. Background Art

[0002] Different branches of an enterprise often carry independent or collaborative business functions. Network deployment not only needs to meet the basic communication needs of each branch, but also needs to accurately match the service types, performance requirements, and resource dependency relationships of each business node. However, common networking methods in the prior art mostly rely on manual configuration or static templates, lacking in-depth analysis and modeling of the internal business dependency relationships within an enterprise, and it is difficult to dynamically match and optimize network resources according to actual business needs, resulting in problems such as unreasonable network architecture, low resource utilization rate, low deployment efficiency, and difficult subsequent maintenance. Summary of the Invention

[0003] This application provides a networking deployment method and system for multiple branches of an enterprise, solving the technical problems in the prior art that it is difficult to accurately match business requirements and network resources during the networking deployment of multiple branches of an enterprise, resulting in unreasonable network architecture, low resource utilization rate, and low deployment efficiency.

[0004] In the first aspect of this application, a networking deployment method for multiple branches of an enterprise is provided. The method includes:

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

[0006] In the second aspect of this application, a networking deployment system for multiple branches of an enterprise is provided. The system includes:

[0007] A relationship recognition module, configured to obtain a business data set of an enterprise, use the business data set to recognize the dependency attribution relationship between multi-branch business nodes of the enterprise, and construct a business function hierarchical tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependency relationships; a requirement matching module, configured to perform network service requirement matching for each business tree node of the business function hierarchical tree structure, and establish network service requirement parameters mapped to the business tree nodes; a mapping space construction module, configured to obtain all available resource nodes of the current network and establish a multi-dimensional mapping space. The multi-dimensional mapping space is constructed with business tree nodes as the first mapping end and all available resource nodes as the second mapping end; a node matching module, configured to traverse from top to bottom according to the business function hierarchical tree structure, and select available resource nodes for matching for each business tree node; a network deployment module, configured to configure the connection constraints between parent and child nodes, perform matching optimization using the connection constraints and an adaptation fitness function, 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, obtain the business data set of the enterprise, use the business data set to recognize the dependency attribution relationship between multi-branch business nodes of the enterprise, and construct a business function hierarchical tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependency relationships. Next, perform network service requirement matching for each business tree node of the business function hierarchical tree structure, and establish network service requirement parameters mapped to the business tree nodes. Then, obtain all available resource nodes of the current network and establish a multi-dimensional mapping space. The multi-dimensional mapping space is constructed with business tree nodes as the first mapping end and all available resource nodes as the second mapping end. Then, traverse from top to bottom according to the business function hierarchical tree structure, and select available resource nodes for matching for each business tree node. Finally, configure the connection constraints between parent and child nodes, perform matching optimization using the connection constraints and an adaptation fitness function, 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. This solves the technical problem in the prior art that it is difficult to accurately match business requirements and network resources during the multi-branch network deployment of enterprises, resulting in an unreasonable network architecture, low resource utilization rate, and low deployment efficiency, and achieves the technical effect of improving resource utilization rate and deployment efficiency. Description of the Drawings

[0010] To more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0011] Figure 1 Schematic diagram of the network deployment method for multiple branches of an enterprise provided by an embodiment of the present application;

[0012] Figure 2 Schematic diagram of the network deployment system structure for multiple branches of an enterprise provided by an embodiment of the present application.

[0013] Explanation of reference numerals: relationship recognition module 11, requirement matching module 12, mapping space construction module 13, node matching module 14, network deployment module 15. Detailed implementation manners

[0014] By providing a network deployment method and system for multiple branches of an enterprise, the present application solves the technical problems in the prior art that it is difficult to accurately match business requirements and network resources during the network deployment of multiple branches of an enterprise, resulting in an unreasonable network architecture, low resource utilization rate, and low deployment efficiency.

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only some embodiments of the present application, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts belong to the scope of protection of the present application.

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

[0017] Embodiment 1, as Figure 1 shown, the present application provides a network deployment method for multiple branches of an enterprise, wherein the method includes:

[0018] Obtain the business data set of the enterprise, use the business data set to identify the dependency attribution relationship between the business nodes of multiple branches of the enterprise, and construct a business function hierarchical tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependency relationships.

[0019] In the embodiments of the present application, by obtaining the business data sets in the enterprise's multi-branch network, including terminal behavior logs, system access paths, and business module dependency relationships, the dependency attribution relationships between each branch business node within the enterprise are 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 collection platform. These logs record information such as the applications accessed, resources accessed, and operations initiated by each terminal during use, thus reflecting the business interaction situations 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 dependency relationships 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 further obtain the dependency relationships between business modules.

[0020] During the process of identifying dependency relationships, a graph theory method is adopted to use each business node as the vertex of the graph and the dependency relationships between business nodes as the edges to construct a business dependency graph. Then, graph analysis techniques (such as the shortest path algorithm, clustering analysis, etc.) are used to identify the direct or indirect dependencies between each node, ensuring that the relationships of all business nodes are comprehensively and accurately described. Based on the dependency graph, a business function hierarchical tree structure is constructed. This structure hierarchically arranges business nodes from top to bottom according to the dependency relationships. Each node represents an independent business module or service, the root node represents the enterprise's core business module or service, and the child nodes represent the sub-modules that have dependency relationships with the root node or other modules.

[0021] Match the network service requirements of each business tree node of the business function hierarchical tree structure, and establish network service requirement parameters mapped to the business tree nodes.

[0022] In the embodiments of the present application, based on the constructed business function hierarchical tree structure, detailed network service requirement matching is performed for each business tree node. Each business tree node represents a specific business module or function, and this 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, they may require higher bandwidth and throughput; while for business modules with high real-time requirements, such as video conferencing or online trading systems, they may have strict requirements for latency. By analyzing the workload, performance requirements, and network resource consumption of the business module, the specific network service requirements of each business node are accurately identified. Based on these requirements, network service requirement parameters mapped to each business tree node are established, defining the key performance indicators such as bandwidth, latency, and throughput required for each node.

[0023] Obtain all available resource nodes of the current network and establish a multi-dimensional mapping space, where the business tree nodes are used as the first mapping end and all available resource nodes are used as the second mapping end to construct the multi-dimensional mapping space.

[0024] In the embodiment of the present application, through the network management system, all available resource nodes in the current network are obtained. These resource nodes can be computing nodes, storage nodes, bandwidth resource nodes, security devices, routers, etc. in the network, and the specific types depend on the enterprise's network architecture and business requirements. After obtaining all available resource nodes, a multi-dimensional mapping space is established, where the business tree nodes are used as the first mapping end and the resource nodes are used as the second mapping end. By constructing the multi-dimensional mapping space, an exact match between the business tree nodes and the resource nodes is achieved, thereby ensuring that the network service requirements (such as bandwidth, latency, throughput, security, etc.) of each business node can be supported by the corresponding resources. The multi-dimensionality of the mapping space includes: the network service requirement dimension of the business tree nodes, the capability dimension of the resource nodes (such as bandwidth, processing capacity, etc.), and the matching constraint dimension (such as geographical location, network topology, etc.).

[0025] Traverse from top to bottom according to the tree-like structure of the business function hierarchy, and select available resource nodes for matching for each business tree node.

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

[0027] Configure the connection constraints between 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 tree-like structure of the business function hierarchy, and perform network deployment according to the network topology diagram.

[0028] In the embodiments of the present application, the connection constraints between the parent and child nodes are configured to ensure that the service nodes at different levels in the hierarchical tree structure of the business functions can be effectively connected and work together. Specifically, by analyzing the data dependency relationship between the parent and child nodes, a data flow constraint is established to ensure that the data meets the bandwidth and latency requirements when transmitted between the parent and child nodes; at the same time, considering the control dependency relationship between the parent and child nodes, such as operations like startup, scheduling, and approval, a control dependency constraint is generated to ensure that the requirements of time delay and link stability are met during the transmission of control signals. Using the configured connection constraints and the adaptation fitness function, a matching optimization process is carried out. The adaptation fitness function evaluates the matching degree of the resource nodes based on the network service requirements (such as bandwidth, latency, etc.) of each business tree node, and performs optimization through an optimization algorithm to select the optimal resource nodes 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 situation of the resource nodes to achieve the optimal binding between 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 hierarchical tree structure of the business functions, a network topology diagram can be further established. This network topology diagram clearly shows the connection relationships, data flow paths, and resource node allocation situations among the internal business modules of the enterprise. Finally, according to the established network topology diagram, a network deployment process is executed, appropriate resource nodes are allocated to each business module, and the network configuration is optimized according to the business requirements to ensure the rationality, stability, and efficiency of the network architecture.

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

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

[0031] Preferably, by analyzing the data flow between parent and child nodes, obtain the transmission path of data from the parent node to the child node, and analyze the connectivity of this path to ensure that data can be transmitted smoothly in the network without interruption or bottleneck. Then, based on the result of path connectivity analysis, conduct bandwidth support analysis to evaluate whether the data flow between parent and child nodes can obtain sufficient bandwidth support to ensure that data transmission does not become congested or delayed. According to these analysis results, establish data dependency constraints, that is, determine the parameter requirements such as bandwidth and delay during the data transmission process between parent and child nodes to ensure the stability and transmission efficiency of the data flow.

[0032] In addition, it is also necessary to conduct constraint analysis on the control signal transmission between parent and child nodes. Specifically, the control, startup, scheduling, approval and other processes between parent and child nodes will affect the network performance, so it is necessary to conduct analysis of time delay and link stability. On this basis, generate the instruction transmission time delay index and link stability index to describe the timeliness and stability requirements when the control signal is transmitted from the parent node to the child node. The instruction transmission time delay index reflects the time required for the control instruction to be transmitted in the network, and the link stability index reflects the reliability and stability of the network link during the instruction transmission process. According to these analysis results, establish control dependency constraints to ensure that the control signal between parent and child nodes is transmitted within a reasonable time delay and meets the stability requirements of the network. Integrate the data dependency constraints and control dependency constraints to form a complete connection constraint between parent and child nodes.

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

[0034] Perform position clustering matching on the service tree nodes of the service function hierarchical tree structure to establish a position clustering matching result; use the position clustering matching result to perform synchronous clustering sorting on all available resource nodes to establish a synchronous clustering sorting result; during the process of performing matching optimization, update and iterate according to the fitness value of each group of solutions and the synchronous clustering sorting result to complete the matching optimization.

[0035] In the embodiment of the present application, use the configured connection constraint and adaptation fitness function to perform matching optimization to ensure that each service tree node can be matched with a suitable resource node and finally establish an effective binding relationship.

[0036] Before performing matching optimization, perform position clustering matching on each service tree node in the service function hierarchical tree structure. Specifically, cluster the service tree nodes according to factors such as their hierarchical relationship and service requirements in the tree structure to form a set of position clustering matching results.

[0037] After obtaining the position clustering matching results, these results are used to synchronously cluster and sort all available resource nodes in the network. Synchronous clustering and sorting sorts the available resource nodes according to their characteristics (such as bandwidth, latency, processing power, etc.), making the allocation of resource nodes more efficient and ensuring that resources can meet the needs of service tree nodes in the best way.

[0038] In the process of matching and optimization, an adaptation fitness function is used to evaluate each set of solutions, and iterative updates are performed according to the fitness value and the synchronous clustering and sorting results. Each set of solutions represents a possible matching scheme between service nodes and resource nodes, and the fitness value reflects the quality of the scheme, specifically including multiple indicators such as bandwidth, latency, cost, and security. Through the continuous update and iteration process, the adaptation fitness function continuously optimizes the matching results, selects the optimal resource nodes for binding, and finally forms a stable and efficient binding relationship between service nodes and resource nodes.

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

[0040] The adaptation fitness function is used to evaluate the matching degree between service tree nodes and available resource nodes to select the optimal resource allocation scheme. The evaluation indicators of the adaptation fitness function mainly include latency indicator, energy consumption indicator, security indicator, and cost indicator. These indicators can comprehensively reflect the advantages and disadvantages of resource allocation, ensuring that while meeting the service requirements, the network architecture optimizes network performance, reduces energy consumption, improves security, and reduces costs.

[0041] The latency indicator is used to evaluate the communication latency between service tree nodes and available resource nodes. The adaptation fitness function calculates and optimizes the communication latency according to factors such as the physical distance, network load, and routing path between each node in the network, ensuring that the latency of service data transmission in the network meets the requirements.

[0042] The energy consumption indicator reflects the energy consumption efficiency of resource nodes in network deployment. The adaptation fitness function selects resource nodes with lower energy consumption and higher resource utilization efficiency by calculating the energy consumption of each resource node, achieving the purpose of energy conservation and consumption reduction, thereby reducing network operation costs and environmental impacts.

[0043] The security indicator is used to evaluate the security between each resource node in the network topology. The adaptation fitness function performs a security assessment according to the security characteristics (such as firewalls, security protocols, etc.) of each resource node, ensuring that nodes with sufficient security protection are selected during matching, thereby enhancing the network's anti-attack ability and data protection ability.

[0044] The cost metric evaluates the cost - effectiveness of each resource node during the matching process. The adaptation fitness function comprehensively considers the costs of each node and preferentially selects those resource nodes that can meet business requirements and have lower operating costs to achieve cost optimization.

[0045] Furthermore, during the process of performing matching optimization, update and iteration are carried out according to the fitness values of each set of solutions and the synchronous clustering sorting results to complete the matching optimization, including:

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

[0047] In each iteration, the system needs to locate the business tree node for the current iterative optimization, that is, select the business node that needs to be matched currently. These nodes are dynamically updated according to factors such as changes in business requirements and service dependencies to ensure that the business nodes that need to be optimized can be selected in each iteration. After determining the business tree node that needs to be optimized currently, the system uses the synchronous clustering sorting result to locate the resource nodes related to this node. Synchronous clustering sorting is sorted according to the resource demand characteristics and resource availability characteristics of the nodes to form a sorted list. According to the requirements of the current business tree node, this sorting result can guide the system to quickly find the resource node that best matches the business tree node, avoiding ineffective matching and resource waste. Then, the system will obtain the fitness value of the current solution. The fitness value is calculated through the adaptation fitness function and reflects the quality of the matching between the current resource node and the business tree node. According to the fitness value of the current solution and the synchronous clustering sorting result, the system will perform a search breakthrough evaluation. This evaluation is used to determine whether the current solution has broken through the current local optimal solution, that is, whether it is possible to find a better matching scheme. If the result of the breakthrough evaluation is a breakthrough pass, it means that the matching result of the current solution has exceeded the local optimum, and the system will perform further matching updates. After the breakthrough pass evaluation, the system will perform cross - clustering search update of the current solution, that is, the system will no longer be limited to the resource nodes within the current clustering cluster, but start to search across clustering clusters to find better resource nodes for matching. Through multiple rounds of iteration, continuously updating and optimizing the matching result, the system can finally find the best matching relationship between the business tree node and the resource node, thereby improving the efficiency of network deployment and resource utilization rate. Each iterative update is based on the fitness value and the synchronous clustering sorting result. Through cross - cluster search and fitness optimization, it is ensured that the final matching result is optimal.

[0048] Furthermore, using the fitness value and the synchronous clustering sorting result for search breakthrough evaluation includes:

[0049] If the search breakthrough evaluation is a breakthrough failure result, then perform in-cluster search update within the synchronized clustering sorting result positioning to determine the search direction and adaptive search step size; use the search direction and adaptive search step size to complete the optimization matching.

[0050] If the search breakthrough evaluation is a breakthrough failure result, that is, the current solution fails to exceed the local optimal solution, then the system will perform in-cluster search update within the synchronized clustering sorting result positioning. The purpose of in-cluster search update is to find a better resource node matching scheme within the current clustering cluster, thereby improving the matching quality and avoiding unnecessary cross-cluster searches. To this end, the system will determine the search direction and adaptive search step size. The search direction refers to the direction of optimization within the current cluster, which may be optimization in dimensions such as bandwidth, latency, and energy consumption, while the adaptive search step size is dynamically adjusted according to the feedback during the search process to achieve more efficient search and matching. After determining the search direction and adaptive search step size, the system will use this information to complete the optimization matching. Through further search and update, the matching result is optimized, ensuring that when the local optimal solution cannot be broken through, fine adjustment and optimization can be carried out within the existing clustering cluster, and finally a suitable resource node matching scheme can be found, thereby further improving the utilization rate of network resources and the accuracy of matching.

[0051] Furthermore, after performing the search breakthrough evaluation using the fitness value and synchronized clustering sorting result positioning, it also includes:

[0052] After matching is completed at any service tree node, add the matched available resource nodes to the taboo list; during the search and matching process, determine whether the result is that there are no adaptable available resource nodes; if the result of no adaptable available resource nodes appears during the search and matching process, generate a fallback instruction and set the matching degradation of the fallback node; complete the optimization matching according to the fallback instruction and the matching degradation.

[0053] After matching is completed at each service tree node, the system will add the matched available resource nodes to the taboo list. The role of the taboo list is to record the already matched resource nodes to avoid reselecting these already used resource nodes during subsequent matching processes, thereby avoiding unnecessary resource reallocation.

[0054] During the matching process, the system will continuously determine whether there are unadapted available resource nodes. If, during the current iteration, the system cannot find a suitable resource node to match the service tree node, that is, it fails to adapt to any available resource nodes, the system will generate a fallback instruction. This fallback instruction instructs the system to readjust the matching strategy and perform matching degradation processing on the fallback node. Matching degradation means adjusting the currently unmatched node to a lower-priority resource node so that it can participate in the optimization process again with a lower matching priority during subsequent matching.

[0055] After executing the fallback instruction and matching degradation, the system will continue to perform optimal matching to ensure that after the fallback node degrades, the most suitable resource node can be found for matching as much as possible. The combination of the generation of the fallback instruction and the implementation of the matching degradation strategy can effectively avoid search interruption caused by the inability to match resource nodes, and ensure that the system can adaptively adjust and continue to optimize resource allocation.

[0056] Furthermore, performing matching optimization using the said connection constraint and adaptation fitness function further includes:

[0057] Perform node stability analysis on the service tree nodes within the service function hierarchical tree structure to establish stability impact factors; use the stability impact factors to establish additional matching constraints, and perform matching optimization based on the additional matching constraints, the connection constraint, and the adaptation fitness function.

[0058] During the process of performing matching optimization using the connection constraint and the adaptation fitness function, in addition to relying on the connection constraint and the adaptation fitness function, it also includes performing node stability analysis on each service tree node in the service function hierarchical tree structure. The purpose of node stability analysis is to evaluate the possible stability impact of each service tree node in the network topology, especially in terms of network load, latency, bandwidth usage, and resource dependencies. By quantifying the various characteristics of the service tree nodes, the stability impact factor of each node is calculated, which reflects the stability degree of the node in the network. The stability factor includes but is not limited to the resource consumption of the node, the frequency of data transmission between nodes, the load condition of the node, and the degree of dependence of the node on other nodes. The system will introduce additional matching constraints for each service tree node according to the stability impact factor. The additional matching constraints are restrictive conditions generated based on the results of node stability analysis, which are used to ensure that during the resource matching process, nodes with poor stability will not be assigned to overly important or resource-demanding nodes, avoiding uneven resource allocation or causing system instability. For example, nodes with poor stability will be restricted from matching with resource nodes with high loads, thereby ensuring the reasonable allocation of resource nodes and guaranteeing the stable operation of the entire network.

[0059] After introducing additional matching constraints, the system will perform matching optimization based on the connection constraints, additional matching constraints and adaptation fitness functions. By introducing stability constraints in the optimization process, the system can ensure efficient use of resources while avoiding problems 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 node and service tree node for binding based on the matching results that comprehensively consider stability, resource adaptability and service dependencies, thereby forming an optimized network topology. This network topology can ensure the efficiency and stability of the network, optimize resource utilization, and improve 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, the fitness dynamic graph, and the resource utilization heat map.

[0062] By monitoring the network deployment process and tracking the progress of the deployment task in real time, we can obtain the deployment progress graph, fitness dynamic graph, and resource utilization heat map; the deployment progress graph shows the completion status and progress of the current network deployment task; the fitness dynamic graph performs real-time monitoring based on the fitness function 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 depth of color indicates the usage intensity of different resource nodes.

[0063] During the deployment progress monitoring process, the system visualizes the above charts, allowing users to intuitively understand the current deployment status through the graphical interface. By intuitively displaying the deployment progress, fitness, and resource utilization, users can quickly obtain important real-time data and feedback, make more accurate decisions, optimize resource allocation, and ensure that the network deployment is successfully completed according to the predetermined goals.

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

[0065] First, obtain the business data set of the enterprise, use the business data set to identify the dependency attribution relationship between the multi-branch business nodes of the enterprise, and construct a business function hierarchical tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependency relationships. Next, perform network service requirement matching for each business tree node in the business function hierarchical tree structure, and establish network service requirement parameters mapped to the business tree nodes. Then, obtain all available resource nodes of the current network and establish a multi-dimensional mapping space. The multi-dimensional mapping space is constructed with business tree nodes as the first mapping end and all available resource nodes as the second mapping end. Then, traverse from top to bottom according to the business function hierarchical tree structure, and select available resource nodes for matching for each business tree node. Finally, configure the connection constraints between 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 network 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 during the multi-branch network deployment of enterprises, resulting in an unreasonable network architecture, low resource utilization rate, and low deployment efficiency, and achieves the technical effect of improving resource utilization rate and deployment efficiency.

[0066] Embodiment 2, based on the same inventive concept as the multi-branch network deployment method of the enterprise in the foregoing embodiment, as Figure 2 shown, the present application provides a multi-branch network deployment system for an enterprise. Among them, the system includes:

[0067] A relationship recognition module 11, configured to obtain the business data set of the enterprise, use the business data set to identify the dependency attribution relationship between the multi-branch business nodes of the enterprise, and construct a business function hierarchical tree structure. The business data set includes terminal behavior logs, system access paths, and business module dependency relationships; a requirement matching module 12, configured to perform network service requirement matching for each business tree node in the business function hierarchical tree structure, and establish network service requirement parameters mapped to the business tree nodes; a mapping space construction module 13, configured to obtain all available resource nodes of the current network and establish a multi-dimensional mapping space. The multi-dimensional mapping space is constructed with business tree nodes as the first mapping end and all available resource nodes as the second mapping end; a node matching module 14, configured to traverse from top to bottom according to the business function hierarchical tree structure, and select available resource nodes for matching for each business tree node; a network deployment module 15, configured to configure the connection constraints between 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 network deployment according to the network topology diagram.

[0068] Further, the network deployment module 15 is configured to execute the following method:

[0069] 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 control, start, scheduling, and approval of parent and child nodes, generate instruction transfer delay metrics and link stability metrics based on the constraint analysis results, and establish control dependency constraints with the instruction transfer delay metrics and link stability metrics; establish the connection constraints with the data dependency constraints and control dependency constraints.

[0070] Furthermore, the network deployment module 15 is used to execute the following method:

[0071] Perform location clustering matching on the service tree nodes of the service function hierarchical tree structure to establish a location clustering matching result; use the location clustering matching result to perform synchronous clustering sorting on all available resource nodes to establish a synchronous clustering sorting result; during the process of performing matching optimization, update and iterate according to the fitness value of each group of solutions and the synchronous clustering sorting result to complete the matching optimization.

[0072] Furthermore, the network deployment module 15 is used to execute the following method:

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

[0074] Furthermore, the network deployment module 15 is used to execute the following method:

[0075] If the search breakthrough evaluation is a non-breakthrough result, perform in-cluster search update within the synchronous clustering sorting result to determine the search direction and adaptive search step size; use the search direction and adaptive search step size to complete the optimization matching.

[0076] Furthermore, the network deployment module 15 is used to execute the following method:

[0077] After any service tree node completes the matching, add the matched available resource node to the taboo list; during the search matching process, determine whether the result is that there is no adapted available resource node; if the result of no adapted available resource node appears during the search matching process, generate a fallback instruction and set the matching degradation of the fallback node; complete the optimization matching according to the fallback instruction and the matching degradation.

[0078] Furthermore, the network deployment module 15 is used to execute the following method:

[0079] Perform node stability analysis on the business tree nodes within the business function hierarchy tree structure, and establish stability impact factors; establish additional matching constraints using the stability impact factors, and perform matching optimization based on the additional matching constraints, the connection constraints, and the adaptation fitness function.

[0080] Further, the network deployment module 15 is used to execute the following method:

[0081] Monitor the progress of the network deployment process, establish a deployment progress diagram, a fitness dynamic diagram, and a resource utilization heat map; visually present the deployment progress diagram, the fitness dynamic diagram, and the resource utilization heat map.

[0082] Further, the network deployment module 15 is used to execute the following method:

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

[0084] It should be noted that the above-mentioned sequence of embodiments of the present application is only for description and does not represent the advantages or disadvantages of the embodiments. And the above describes specific embodiments of this specification. The processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0085] The above are only the preferred embodiments of the present application and are 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 within the protection scope of the present application.

[0086] This specification and the drawings are only exemplary descriptions of the present application and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the present application and its equivalent technologies, the present application is intended to include these changes and modifications.

Claims

1. An enterprise multi-branch networking deployment method, characterized in that: The method comprises: Acquire the business data set of the enterprise, 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, wherein the business data set includes terminal behavior logs, system access paths, and business module dependencies; Matching the network service demand of each service tree node to the service function hierarchical tree structure, and establishing network service demand 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 tree structure of business function hierarchy from top to bottom, and select available resource nodes to match for each business tree node; Configure the connection constraints of the 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 hierarchy tree structure, and perform networking deployment according to the network topology diagram.

2. The enterprise multi-branch networking deployment method according to claim 1, characterized in that: The configuration of the connection constraints between the parent and child nodes includes: 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 parent and child nodes, generate instruction transmission delay indicators and link stability indicators based on the constraint analysis results, and establish control dependency constraints with the instruction transmission delay indicators and link stability indicators; The connection constraint is established based on the data dependency constraint and the control dependency constraint.

3. The enterprise multi-branch networking deployment method according to claim 1, characterized in that: The method of using the connection constraint and the adaptation fitness function to perform matching optimization and establish a binding relationship includes: Performing location cluster matching of the service tree nodes on the service function hierarchical tree structure to establish a location cluster matching result; Using the position cluster matching result, synchronously cluster and sort all the available resource nodes to establish a synchronous cluster sorting result; In the process of performing matching optimization, the fitness value of each set of solutions and the synchronous clustering sorting results are updated and iterated to complete the matching optimization.

4. The enterprise multi-branch networking deployment method as claimed in claim 3, characterized in that: 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 clustering sorting result to complete the matching optimization, including: Locate the service tree node of the current iterative optimization, and locate the synchronous clustering sorting result according to the service 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.

5. The enterprise multi-branch networking deployment method according to claim 4, characterized in that: The method of using the fitness value and the synchronous clustering sorting result positioning to conduct search breakthrough evaluation includes: If the search breakthrough evaluation is a breakthrough failure result, then performing an intra-cluster search update within the synchronous cluster sorting result positioning to determine the search direction and the adaptive search step size; The search direction and the adaptive search step length are used to complete the optimal matching.

6. The enterprise multi-branch networking deployment method according to claim 4, characterized in that: After the fitness value and the synchronous clustering sorting result positioning are used to 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 match process, determining whether there is no result of an adapted available resource node; If there is no result of adapting available resource node in 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.

7. The enterprise multi-branch networking deployment method according to claim 1, characterized in that: The use of the connection constraint and the adaptation fitness function to perform matching optimization also includes: Perform node stability analysis on the business tree nodes in the business function hierarchy tree structure and establish stability influencing 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.

8. The enterprise multi-branch networking deployment method according to claim 1, characterized in that: The performing networking deployment according to the network topology diagram includes: Perform progress monitoring of the network deployment process, and establish 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.

9. The enterprise multi-branch networking deployment method according to claim 1, characterized in that: The evaluation indexes of the adaptation fitness function include a delay index, an energy consumption index, a safety index, and a cost index.

10. The enterprise multi-branch networking deployment system is characterized by: The system for implementing the enterprise multi-branch networking deployment method according to any one of claims 1 to 9 comprises: A relationship identification module is used to obtain the business data set of the enterprise, use the business data set to identify the dependency relationship between the multi-branch business nodes of the enterprise, 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, used to match the network service demand of each business tree node to the business function hierarchical tree structure, and establish network service demand parameters mapped to the business tree nodes; A mapping space construction module, used to obtain all available resource nodes of the current network and establish a multi-dimensional mapping space, wherein 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; A node matching module is used to traverse the tree structure of the business function hierarchy 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 the 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 hierarchy tree structure, and perform network deployment according to the network topology diagram.

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