Intelligent network address terminal management method and system

Abstract

The present application provides an intelligent network address terminal management method and system, which comprehensively analyzes multiple network segment attribute parameters such as network activity, device connection performance, data transmission efficiency and security performance, and combines the specific capacity requirements of the target network session service to accurately calculate the network resource occupancy expectation and service potential index of each potential network segment. It not only effectively evaluates the availability and stability of the network segment, but also further quantifies the call confidence through the network segment call index, thereby realizing efficient screening and accurate calling of the target network segment sequence. This solution significantly improves the intelligent level of service management of network address terminals, optimizes network resource allocation, enhances the response speed and reliability of network services, and ensures the high-quality operation of network session services.

Description

Technical Field

[0001] The present application relates to the technical field of network communication services, and in particular to an intelligent network address terminal management method and system. Background Art

[0002] In the current era of rapid development of informatization, network address terminals serve as the key bridge between users and network services. Their management efficiency and service quality directly affect user experience and the effective use of network resources. Traditional network address terminal management methods are often based on static configuration or simple polling mechanisms, which are difficult to adapt to complex and changing network environments and service requirements. Especially in the face of large-scale networks, high-concurrency sessions, and diversified service label characteristics, traditional methods are even more powerless, which can easily lead to problems such as uneven allocation of network resources, service response delays, and security risks.

[0003] In order to overcome the above defects, relevant technologies have begun to explore intelligent network address terminal management solutions. Among them, how to accurately evaluate and efficiently schedule potential network segment resources has become the key to improving management efficiency. As the basic unit of network services, the attribute parameters of potential network segments (such as network activity, device connection performance, data transmission efficiency and security performance, etc.) directly determine the service capabilities and stability of the network segments. However, the existing technology lacks an effective method that comprehensively considers multiple network segment attribute parameters and dynamically schedules them in combination with the specific needs of the target network session service. Summary of the invention

[0004] In view of the above-mentioned problems, in combination with the first aspect of the present application, an embodiment of the present application provides an intelligent network address terminal management method, the method comprising:

[0005] Obtaining a network segment attribute parameter sequence associated with each potential network segment of X potential network segments for a target network session service initiated by a network address terminal, wherein the X potential network segments are generated according to a predetermined network partitioning strategy, and the network segment attribute parameter sequence includes each network segment attribute parameter formed by one or more combinations of a network activity parameter sequence, a device connection performance parameter sequence, a data transmission efficiency parameter sequence, and a security performance parameter sequence, and X is a positive integer;

[0006] Acquire a capacity information sequence of each potential network segment facing the target network session service, wherein the capacity information sequence includes one or more combined capacity information determined according to a service label feature of the target network session service;

[0007] Based on the network segment attribute parameter sequence associated with each potential network segment, the network resource occupancy expectation associated with each potential network segment is determined, and based on the capacity information sequence of each potential network segment for the target network session service and the network resource occupancy expectation, the service potential index associated with each potential network segment is determined, wherein the network resource occupancy expectation represents a scheduling probability value of the potential network segment; and the service potential index represents the availability and stability of the potential network segment;

[0008] Based on the relationship between the network resource occupancy expectation and the service potential index associated with each potential network segment, determining a network segment call index associated with each potential network segment, wherein the network segment call index reflects the call confidence of the potential network segment;

[0009] Based on the network segment call index associated with each potential network segment, a target network segment sequence to be called is determined from the X potential network segments, and service management is performed on the network address terminal based on the target network segment sequence to be called, wherein the target network segment sequence includes one or more potential network segments.

[0010] On the other hand, an embodiment of the present application also provides an intelligent network address terminal management system, including a processor and a machine-readable storage medium, wherein the machine-readable storage medium is connected to the processor, the machine-readable storage medium is used to store programs, instructions or codes, and the processor is used to execute the programs, instructions or codes in the machine-readable storage medium to implement the above method.

[0011] Based on the above aspects, the embodiment of the present application comprehensively analyzes multiple network segment attribute parameters such as network activity, device connection performance, data transmission efficiency and security performance, and combines the specific capacity requirements of the target network session service to accurately calculate the network resource occupancy expectation and service potential index of each potential network segment, which not only effectively evaluates the availability and stability of the network segment, but also further quantifies the call confidence through the network segment call index, thereby realizing efficient screening and accurate calling of the target network segment sequence. This solution significantly improves the intelligent level of service management of network address terminals, optimizes network resource allocation, enhances the response speed and reliability of network services, and ensures the high-quality operation of network session services. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Figure 1 It is a schematic diagram of the execution flow of the intelligent network address terminal management method provided in the embodiment of the present application.

[0013] Figure 2 It is a schematic diagram of the hardware architecture of the intelligent network address terminal management system provided in the embodiment of the present application. DETAILED DESCRIPTION

[0014] The present application will be described in detail below with reference to the accompanying drawings. Figure 1 It is a flow chart of an intelligent network address terminal management method provided by an embodiment of the present application. The intelligent network address terminal management method is introduced in detail below.

[0015] Step S110, obtaining a network segment attribute parameter sequence associated with each potential network segment of X potential network segments for a target network session service initiated by a network address terminal, wherein the X potential network segments are generated based on a predetermined network division strategy, and the network segment attribute parameter sequence includes each network segment attribute parameter formed by one or more combinations of a network activity parameter sequence, a device connection performance parameter sequence, a data transmission efficiency parameter sequence, and a security performance parameter sequence, and X is a positive integer.

[0016] In detail, the potential network segment refers to a network area or subnet that may be used to provide network services under a specific network division strategy. It can be divided according to factors such as geographical location, departmental functions, network performance requirements, etc., to carry different network services.

[0017] The predetermined network segmentation strategy refers to the rules or methods formulated during the network planning phase for dividing a large network into multiple smaller, easier-to-manage potential network segments. These strategies may be based on a variety of factors, such as business requirements, security, performance, etc.

[0018] The network segment attribute parameter sequence refers to a series of parameters that describe the performance characteristics of a potential network segment. These parameters may include network activity, device connection performance, data transmission efficiency, security performance, etc., which are used to evaluate the availability, stability and reliability of the network segment.

[0019] The network activity parameter sequence reflects the activity level of network nodes in the network segment, such as the number of visits, online time, interaction frequency, etc. The device connection performance parameter sequence describes the connection capability of devices in the network segment, such as device interface speed, connection stability, etc. The data transmission efficiency parameter sequence evaluates the speed and quality of data transmission in the network segment, such as bandwidth, delay, packet loss rate, etc. The security performance parameter sequence measures the security protection capability and risk level of the network segment, such as security level, effectiveness of protection strategy, risk event records, etc.

[0020] For example, in this embodiment, the server may be a data center server of a large enterprise with a complex network architecture, and the network address terminal may be an office computer or server cluster of each department within the enterprise. The target network session service is, for example, a video conferencing service within the enterprise. The predetermined network partitioning strategy may be formulated based on factors such as department functions, physical location, and network security level.

[0021] First, the server obtains the network activity parameter sequence. For the network activity parameter sequence, taking different departments within the enterprise as an example, the network node access volume of the R&D department may be higher, because R&D personnel need to frequently access resources such as code bases and test servers, and their online time is also longer. In addition, the interaction frequency between R&D personnel is high, and code sharing and collaboration are often carried out. The network node access volume of the administrative department is relatively small, mainly concentrated in the access of office documents and the sending and receiving of emails. The online time is normal office hours, and the interaction frequency is much lower than that of the R&D department.

[0022] Then obtain the security performance parameter sequence. For example, the finance department handles the sensitive financial data of the enterprise, and its network nodes have a high security level, strong protection strategy effectiveness, and few risk event records. It may use advanced encryption technology, strict firewall rules, and conduct regular security audits. The marketing department has a relatively lower security level, and its protection strategy mainly focuses on preventing interference from external malicious marketing information. It may have more risk event records, such as occasional phishing emails.

[0023] For the equipment connection performance parameter sequence, the network segment where the core server cluster is located in the server room contains clear network node identification, and the node location information string shows that they are located in a dedicated room area, with high-speed network interfaces and powerful processing capabilities, and the node connection characteristics are characterized by high-bandwidth, low-latency connections. However, the network segments located in remote office areas of enterprises may have network nodes connected through ordinary network devices, with relatively low bandwidth and slightly poor connection stability.

[0024] Looking at the data transmission efficiency parameter sequence, the backbone network paths within the enterprise are clearly identified, and the path node sequence contains high-performance routers and switches, and the transmission quality rating is high. However, some network paths connected to old office areas may have transmission bottlenecks, and the transmission quality rating is medium.

[0025] Based on the topological relationship between each network node and each potential network segment, the above different parameter sequences are logically linked to each potential network segment. For example, for the potential network segment where the R&D department is located, the network activity parameters, device connection performance parameters, etc. of the R&D department are associated with the network segment to generate the first network data, second network data or third network data (according to the parameter type) associated with each potential network segment. These data are then analyzed to generate a network segment attribute parameter sequence associated with each potential network segment. For example, for the R&D department network segment, its network segment attribute parameter sequence may include parameters such as high network activity, high device connection performance, high data transmission efficiency and high security performance.

[0026] Step S120: Acquire a capacity information sequence of each potential network segment facing the target network session service, wherein the capacity information sequence includes one or more combined capacity information determined according to a service label feature of the target network session service.

[0027] Specifically, the capacity information sequence refers to the resource capacity information that can be provided by a potential network segment for a specific network service. This information is determined based on the service label characteristics of the target network session service (such as the number of concurrent users, data transmission rate, etc.) and is used to evaluate the network segment's ability to carry the service.

[0028] For example, in this embodiment, continuing to take the above enterprise as an example, it is assumed that the service tag features of the target network session service (video conferencing service) include high-definition video transmission, multi-user concurrent support, real-time data interaction, etc.

[0029] If a potential network segment is the core office area network segment of the corporate headquarters, the server obtains its capacity information sequence for the target network session service. For the service tag feature of high-definition video transmission, the corresponding capacity information may be the maximum number of high-definition video streams supported by the network segment, assuming 100 high-definition video streams. For multi-user concurrent support, its capacity information may be the ability to accommodate 1,000 users for video conferencing connections at the same time. For real-time data interaction, its capacity information may be the ability to process 10MB of real-time data interaction per second.

[0030] For example, a branch network segment of an enterprise may only support 50 high-definition video streams, can accommodate 500 users at the same time, and process 5MB of real-time data interaction per second, because the network equipment is older than that of the headquarters. These capacity information constitutes the capacity information sequence of each potential network segment for the target network session service.

[0031] If the target network session service belongs to the collaborative service category, such as the collaborative office platform service within the enterprise, in addition to the basic document sharing and instant messaging functions, the service also integrates project management, workflow approval and other functions. For a potential network segment, the server obtains multiple capacity information for the collaborative service. For example, for the document sharing function, its capacity information may be the ability to store 100GB of shared documents; for the instant messaging function, its capacity information may be the support of 10,000 concurrent messages; for the project management function, its capacity information may be the ability to process relevant data of 50 projects at the same time; for the workflow approval function, its capacity information may be the ability to process 100 approval processes per hour. The capacity information corresponding to these different functions together constitutes the capacity information sequence of the target network session service of the potential network segment for the collaborative service category.

[0032] Step S130, based on the network segment attribute parameter sequence associated with each potential network segment, determine the network resource occupancy expectation associated with each potential network segment, and based on the capacity information sequence of each potential network segment for the target network session service and the network resource occupancy expectation, determine the service potential index associated with each potential network segment, wherein the network resource occupancy expectation represents the scheduling probability value of the potential network segment. The service potential index represents the availability and stability of the potential network segment.

[0033] In detail, the network resource occupancy expectation is a probability value for evaluating a potential network segment being scheduled to provide network services, which is calculated based on a sequence of network segment attribute parameters and reflects the priority and availability of the network segment in resource allocation.

[0034] The service potential index is an indicator for evaluating the availability and stability of a potential network segment in providing network services. It is specifically calculated based on the capacity information sequence of the network segment and the expected network resource occupancy, and is used to guide the rational allocation of network resources.

[0035] For example, continuing with the potential network segments in the enterprise network mentioned earlier, for the R&D department network segment, its network segment attribute parameter sequence includes parameters such as high network activity, higher device connection performance, higher data transmission efficiency, and high security performance.

[0036] First, determine the expected network resource occupancy. Optimize the network segment attribute parameter sequence, assuming that the network segment attribute parameter sequence has four categories of network segment attribute parameters (Y= 4): network activity, device connection performance, data transmission efficiency, and security performance. Arrange the network segment attribute parameters of the same category for each potential network segment. For example, for the network activity parameter, sort the network activity parameters of each potential network segment in the enterprise to generate four network segment attribute parameter clusters (one cluster for each category), each cluster containing X network segment attribute parameters (X is the number of potential network segments in the enterprise). Then divide each network segment attribute parameter cluster equally, assuming that it is divided into two equal subclusters, each of which corresponds to a set value. For the R&D department network segment, determine the equal subclusters corresponding to each network segment attribute parameter in the network segment attribute parameter sequence based on multiple equal subclusters associated with the same category, and then use the set values ​​associated with each corresponding equal subclusters as the target network segment attribute parameter sequence.

[0037] Then, the target network segment attribute parameter sequence is globally calculated, assuming that the importance coefficient corresponding to the network activity is 0.3, the device connection performance is 0.2, the data transmission efficiency is 0.3, and the security performance is 0.2 (these importance coefficients are determined based on the previous steps of standardization conversion, calculation of chaos, and discrimination coefficient). The target network segment attribute parameters of the R&D department network segment are weighted according to the importance coefficient to generate the expected network resource occupancy associated with the R&D department network segment. For example, if the target network segment attribute parameter of network activity is 0.8, the device connection performance is 0.7, the data transmission efficiency is 0.8, and the security performance is 0.9, then the expected network resource occupancy = 0.8×0.3+0.7×0.2 + 0.8×0.3+0.9×0.2 =0.8.

[0038] Then determine the service potential index. Assume that in the capacity information sequence of the R&D department network segment for video conferencing services, the number of high-definition video streams is 100, the number of multi-user concurrent support is 1,000 users, and the real-time data interaction volume is 10MB / second. First, accumulate the network resource occupancy expectations associated with each potential network segment. Assume that the total network resource occupancy expectations of all potential network segments in the enterprise is 5 (global network resource occupancy expectations). Based on the capacity information of the R&D department network segment, determine its contribution to the video conferencing service. Assume that its contribution to the global service capacity index is 0.2 calculated by a certain algorithm (the global service capacity index is assumed to be 1). Based on the global network resource occupancy expectation (5) and the global service capacity index (1), determine the network resource configuration expectation as 0.2×5 = 1. Then, based on the capacity information sequence of the R&D department network segment and the network resource configuration expectation, determine the service potential index associated with the R&D department network segment. For example, if a certain calculation formula is used (the specific formula is determined based on the business needs of the enterprise and the network characteristics), the service potential index = (100 / 100 + 1000 / 1000+10 / 10) / 3×1 = 1 (a simple average calculation method is assumed here; the actual situation may be more complicated).

[0039] Step S140, based on the relationship between the network resource occupancy expectation and the service potential index associated with each potential network segment, determine the network segment call index associated with each potential network segment, wherein the network segment call index reflects the call confidence of the potential network segment.

[0040] In this embodiment, for the R&D department network segment, it is assumed that its expected network resource occupancy is 0.8 and its service potential index is 1.

[0041] If the network resource occupancy expectation and service potential index associated with each potential network segment are used to generate the network segment call index, then the network segment call index of the R&D department network segment = 1 - 0.8 = 0.2. This network segment call index is positively correlated with the call confidence of the potential network segment, that is, the higher the network segment call index, the higher the confidence of calling the network segment for the target network session service.

[0042] For example, the network resource usage expectation of the marketing department network segment is 0.6, and the service potential index is 0.8. Then its network segment call index = 0.8 - 0.6 = 0.2.

[0043] If the network segment call index is generated by calculating the difference between the service potential index and the expected network resource occupancy associated with each potential network segment, and the network segment call index and the call confidence of the potential network segment are negatively correlated, for example, for the network segment of the finance department, its service potential index is 0.9, and the expected network resource occupancy is 0.7, then the network segment call index = 0.9 - 0.7 = 0.2, where the higher the value, the lower the confidence of calling the network segment.

[0044] Step S150, based on the network segment call index associated with each potential network segment, determine the target network segment sequence to be called from the X potential network segments, and perform service management on the network address terminal based on the target network segment sequence to be called, wherein the target network segment sequence includes one or more potential network segments.

[0045] In this embodiment, it is assumed that there are 10 potential network segments (X = 10) in the enterprise, and the network segment call index of each potential network segment is calculated.

[0046] If the target network segment sequence is determined by adopting a method that the network segment call index and the call confidence of the potential network segment are positively correlated. Assuming that the threshold is set to 0.1, if there are one or more network segment call indexes less than the set threshold, for example, there are 3 potential network segments with a network segment call index less than 0.1, then remove these 3 potential network segments from the 10 potential network segments, leaving 7 potential network segments (W = 7). Then arrange these 7 potential network segments in descending order based on the network segment call index, assuming that the arranged order is the R&D department network segment, the headquarters office area network segment, the marketing department network segment, etc. If 3 potential network segments are to be selected as the target network segment sequence to be called (R = 3), then select the first 3 potential network segments in the arranged sequence, namely the R&D department network segment, the headquarters office area network segment, and the marketing department network segment. Then the server performs service management on the network address terminals (office computers, servers, etc. within the enterprise) based on this target network segment sequence, for example, preferentially assigning video conferencing services to these network segments, and reasonably allocating the number of video streams and the number of user connections according to the capacity information of the network segments.

[0047] If the target network segment sequence is determined by adopting a method that the network segment call index and the call confidence of the potential network segment are negatively correlated. Assuming that the threshold is set to 0.3, there are 2 potential network segments whose network segment call index is greater than the set threshold. These 2 potential network segments are removed from the 10 potential network segments, and 8 potential network segments (W = 8) remain. Arrange these 8 potential network segments in ascending order based on the network segment call index. Assume that the order after arrangement is the financial department network segment, the branch network segment, etc. If 4 potential network segments are to be selected as the target network segment sequence to be called (R = 4), the first 4 potential network segments in the arrangement sequence are selected, and then the server performs service management on the network address terminal based on this target network segment sequence, for example, reasonably allocating resources of the collaborative office platform service on these network segments, such as the storage space for document sharing and the concurrent message processing capability of instant messaging.

[0048] Based on the above steps, the embodiment of the present application comprehensively analyzes multiple network segment attribute parameters such as network activity, device connection performance, data transmission efficiency and security performance, and combines the specific capacity requirements of the target network session service to accurately calculate the network resource occupancy expectation and service potential index of each potential network segment, which not only effectively evaluates the availability and stability of the network segment, but also further quantifies the call confidence through the network segment call index, thereby achieving efficient screening and accurate calling of the target network segment sequence. This solution significantly improves the intelligent level of service management of network address terminals, optimizes network resource allocation, enhances the response speed and reliability of network services, and ensures the high-quality operation of network session services.

[0049] In a possible implementation manner, obtaining a sequence of network segment attribute parameters associated with each potential network segment of X potential network segments serving a target network session initiated by a network address terminal includes:

[0050] Obtain one or more combinations of the network activity parameter sequence and the security performance parameter sequence for the predetermined network partitioning strategy, wherein the network activity parameter sequence includes one or more combinations of the number of visits, online time, and interaction frequency of each network node, and the security performance parameter sequence includes one or more combinations of the security level of each network node, the effectiveness of the protection strategy, and the risk event record.

[0051] Based on the topological relationship between each network node and each potential network segment, one or more combinations of the network activity parameter sequence and the safety performance parameter sequence are logically linked to each potential network segment to generate first network data associated with each potential network segment.

[0052] The first network data associated with each potential network segment is analyzed to generate a network segment attribute parameter sequence associated with each potential network segment.

[0053] In this embodiment, taking the enterprise network as an example, the server starts to collect the network activity parameter sequence. In the R&D department of the enterprise, many R&D personnel frequently access resources such as the code hosting platform and the test environment server. For example, for the code hosting platform, the number of visits per day may be as high as thousands of times, because the R&D personnel need to constantly obtain the latest code, submit their own code modifications and other operations. The online time of R&D personnel is also long, from 9 to 18 o'clock during normal working hours, and even during overtime, the average daily online time can reach 9-10 hours. Moreover, the frequency of interaction between R&D personnel is very high. They communicate through code sharing tools, instant messaging tools, etc., and the average frequency of interaction per person per day may reach dozens of times.

[0054] In the sales department, their main online activities are concentrated on accessing the customer relationship management system (CRM) and communicating with customers via email. The CRM system is accessed several hundred times a day because sales staff need to query customer information, update sales opportunities, etc. The online time is slightly shorter than that of R&D staff, basically during normal working hours, about 8 hours a day. The frequency of interaction is mainly email exchanges with customers and communication with the internal sales team, and the frequency of interaction per person is about 10-20 times a day.

[0055] Among them, the company's financial department handles core financial data, and the security level of its network nodes is very high. For example, multi-layer encryption technology is used, and data is highly encrypted during transmission and storage. In terms of the effectiveness of the protection strategy, the firewall rules are set very strictly, only allowing specific internal IP addresses to access financial-related systems, and regular vulnerability scans and security updates are performed to ensure the effectiveness of the protection strategy. In terms of risk event records, due to strict security measures, there are very few risk event records, and there have been almost no data leaks or successful malicious attacks.

[0056] In contrast, the security level of the company's marketing department is relatively low. The main protection strategy is to prevent interference from external malicious marketing information, such as setting up email filtering rules to block spam. Although the security level is not as high as that of the finance department, it also meets the basic security requirements of the company. Occasionally, there are cases of receiving phishing emails in the risk event records, but due to the security awareness training of employees, no actual data security problems have been caused.

[0057] Assume that the enterprise network adopts a layered architecture, with core layer, aggregation layer and access layer. The network nodes of the R&D department are distributed under multiple access layer switches, which are connected to the aggregation layer switches and finally to the core layer switches. The network nodes of the finance department also have their own access layer and aggregation layer connection paths to the core layer.

[0058] Based on this topological relationship, the server logically links the network activity parameters (high access volume, long online time, high interaction frequency) and security performance parameters (relatively high security level, effective protection strategy, few risk event records) of the R&D department with the potential network segment where the R&D department is located. For example, if the potential network segment where the R&D department is located is the network range covered from access layer switch 1 to aggregation layer switch A and then to core layer switch X, then the network activity and security performance related parameters of the R&D department are associated with this potential network segment to generate the first network data associated with this potential network segment. This first network data may include information such as the proportion of node access volume of the R&D department in the network segment, the occupation of network segment resources by online time, and the impact of the security level on the security situation of the entire network segment.

[0059] For the finance department, the security performance parameters of its network nodes (high security level, etc.) and relatively low network activity (compared with the R&D department) are logically linked according to the potential network segments corresponding to its network topology connection path. For example, the potential network segment where the finance department is located is from access layer switch 3 to aggregation layer switch B and then to core layer switch Y. The relevant parameters of the finance department are associated with this potential network segment to generate its first network data, which includes information such as the improvement of the security performance of this potential network segment by the security-related parameters of the finance department nodes, and the utilization of network segment resources by its limited network activity.

[0060] Next, the server analyzes the first network data associated with the potential network segment where the R&D department is located. In terms of network activity, due to the high number of visits, long online time, and high interaction frequency, the analysis shows that the network activity attribute parameter of this network segment is "high". From the perspective of security performance, although the security level is not as high as that of the finance department, considering the effectiveness of the protection strategy and the risk event record, the analysis shows that its security performance attribute parameter is "medium-high". Combining these analysis results, a sequence of network segment attribute parameters associated with the potential network segment where the R&D department is located is generated, such as [network activity: high, security performance: medium-high].

[0061] For example, for the first network data of the potential network segment where the finance department is located, in terms of network activity, due to its relatively low access volume, normal online time and limited interaction frequency, the network activity attribute parameter is analyzed to be "low". In terms of security performance, due to the high security level, strict protection strategy and very few risk event records, the security performance attribute parameter is analyzed to be "high". Thus, a network segment attribute parameter sequence associated with the potential network segment where the finance department is located is generated, such as [network activity: low, security performance: high].

[0062] In a possible implementation manner, obtaining a sequence of network segment attribute parameters associated with each potential network segment of X potential network segments serving a target network session initiated by a network address terminal includes:

[0063] The data transmission efficiency parameter sequence for the predetermined network partitioning strategy is obtained, wherein the data transmission efficiency parameter sequence includes one or more combinations of identifiers of each network path, a path node sequence, and a transmission quality rating.

[0064] Based on the topological relationship between each network path and each potential network segment, the data transmission efficiency parameter sequence is logically linked to each potential network segment of the X potential network segments to generate second network data associated with each potential network segment.

[0065] The second network data associated with each potential network segment is analyzed to generate a network segment attribute parameter sequence associated with each potential network segment.

[0066] In this embodiment, in the enterprise network, the server first identifies the identifiers of each network path. For example, there is a main network path identified as "Path - 1", which starts from the data center of the enterprise headquarters, passes through the core switch "Core- Switch1", then connects to the aggregation switch "Aggregation - Switch2", and then reaches the network node of the R&D department through the access switch "Access - Switch5". This path node sequence (data center - Core - Switch1 - Aggregation - Switch2 - Access - Switch5 - R&D department node) constitutes the key information of this network path.

[0067] Another network path is identified as "Path - 2". It starts from the data center, passes through different core switches "Core - Switch2", connects to other aggregation switches "Aggregation - Switch3", and then to the access switch "Access - Switch8", serving the network nodes of the sales department. The path node sequence is (Data Center - Core - Switch2 - Aggregation - Switch3 - Access - Switch8 - Sales Department Node).

[0068] For "Path - 1", since it uses high-speed fiber connections, and the core switches, aggregation switches, and access switches are all newer devices with high bandwidth and low latency, its transmission quality rating is "high". On this path, the packet loss rate of data transmission is very low, usually below 0.1%, the bandwidth can be stably maintained at more than 1Gbps, and the latency is between 1 and 2 milliseconds.

[0069] Although "Path - 2" is also an internal network path, some links use old twisted-pair cables, and the aggregation switch "Aggregation - Switch 3" has been in service for many years and its performance has declined. The transmission quality of this path is rated "medium", with a packet loss rate of about 0.5%, a bandwidth of about 500Mbps, and a delay of 5-10 milliseconds.

[0070] Consider the potential network segment where the R&D department is located, which has a close topological relationship with "Path - 1". Some nodes in "Path - 1" are key transmission paths of the potential network segment of the R&D department. The server logically associates the identifier of "Path - 1", the path node sequence, and the transmission quality rating with the potential network segment where the R&D department is located. For example, due to the high transmission quality rating of "Path - 1", it has an important positive impact on the overall data transmission efficiency of the potential network segment of the R&D department. The server will record the proportion of "Path - 1" in the potential network segment of the R&D department. For example, if 80% of the transmission capacity of the entire potential network segment of the R&D department depends on "Path - 1", this information will be recorded in the second network data associated with the potential network segment.

[0071] For the potential network segment where the sales department is located, it mainly relies on "Path - 2" for data transmission. The server logically links the relevant data transmission efficiency parameters of "Path - 2" with the potential network segment of the sales department. Since the transmission quality rating of "Path - 2" is "Medium" and it accounts for 70% of the transmission in the potential network segment of the sales department, this situation is also recorded in the second network data associated with the potential network segment of the sales department. This second network data may also include the interactive relationship between "Path - 2" and other secondary network paths in the potential network segment of the sales department. For example, in some cases, when "Path - 2" fails, 10% of the traffic can be switched to the backup path "Path - 3", but the transmission quality rating of "Path - 3" is "Low".

[0072] The server analyzes the second network data associated with the potential network segment of the R&D department. From the 80% share of "Path - 1" in the potential network segment of the R&D department and its high transmission quality rating, the main data transmission path of the potential network segment of the R&D department has the characteristics of high bandwidth, low latency and low packet loss rate. Taking all factors into consideration, the analysis shows that the data transmission efficiency attribute parameter of the potential network segment of the R&D department is "high". This network segment attribute parameter sequence reflects the data transmission capability of the potential network segment of the R&D department. For example, the generated network segment attribute parameter sequence is [Data transmission efficiency: high].

[0073] For the second network data associated with the potential network segment of the sales department, since "Path - 2" accounts for 70% of its transmission and the transmission quality rating is "medium", although there is an alternative path, the quality of the alternative path is low. Comprehensive analysis shows that the data transmission efficiency attribute parameter of the potential network segment of the sales department is "medium". Thus, a network segment attribute parameter sequence associated with the potential network segment of the sales department is generated, such as [Data transmission efficiency: medium].

[0074] In a possible implementation manner, obtaining a sequence of network segment attribute parameters associated with each potential network segment of X potential network segments serving a target network session initiated by a network address terminal includes:

[0075] The device connection performance parameter sequence for the predetermined network partitioning strategy is obtained, wherein the device connection performance parameter sequence includes one or more combinations of identifiers of each network node, node location information strings, and node connection characteristics.

[0076] Based on the inclusion relationship between each network node and each potential network segment, the device connection performance parameter sequence is logically linked to each potential network segment in the X potential network segments to generate third network data associated with each potential network segment.

[0077] For each potential network segment, the structured parameters associated with each network node having an inclusion relationship with the potential network segment are obtained from the third network data associated with the potential network segment. For each potential network segment, the node excitation parameters of each network node facing the potential network segment are determined based on the connection relationship parameters between the potential network segment and the each network node, and the structured parameters associated with the each network node. For each potential network segment, the first network segment attribute parameter associated with the potential network segment is determined based on the node excitation parameters of each network node facing the potential network segment, and the first network segment attribute parameter belongs to a network segment attribute parameter sequence associated with the potential network segment.

[0078] And / or, for each potential network segment, obtain the unstructured parameters associated with each network node having an inclusion relationship with the potential network segment from the third network data associated with the potential network segment. For each potential network segment, determine the influence coefficient of each network node facing the potential network segment based on the connection relationship parameters between the potential network segment and the each network node. For each potential network segment, determine the second network segment attribute parameter associated with the potential network segment based on the influence coefficient of each network node facing the potential network segment and the unstructured parameters associated with each network node, the second network segment attribute parameter belonging to the network segment attribute parameter sequence associated with the potential network segment.

[0079] In this embodiment, in the enterprise network environment, the server begins to obtain the device connection performance parameter sequence. Taking the R&D department as an example, the network node identification of one of the core servers is "Server - R1", and its node location information string indicates that it is located on the 5th floor of the No. 3 cabinet in the data center computer room on the third floor of the enterprise headquarters building. The node connection characteristics of this server are that it has dual 10 Gigabit Ethernet interfaces connected to the high-performance core switch "Core - Switch1", and adopts a redundant link connection method to ensure high availability.

[0080] In the sales department, there is a network printer with a network node identified as "Printer - S1". The node location information string shows that it is located in a corner of the sales department's office area. Its node connection feature is that it is connected to the nearby access switch "Access - Switch3" via a 100M Ethernet interface, and it is a single-link connection.

[0081] For the potential network segment where the R&D department is located, the server logically links the device connection performance parameter sequence with this potential network segment based on the inclusion relationship between each network node and the potential network segment. For example, the potential network segment where "Server - R1" is located may cover the network range covered by the core switch "Core - Switch1" to which it is connected to the downstream aggregation switch and access switch. The server associates the identification, location information string and connection characteristics of "Server - R1" with this potential network segment. Since "Server - R1" is an important device in the R&D department, its high-performance connection characteristics have an important impact on the device connection performance of this potential network segment. The server will record information such as the connection weight of important devices such as "Server - R1" in the potential network segment in the third network data.

[0082] For the potential network segment where the sales department is located, the potential network segment where "Printer - S1" is located extends from the access switch "Access - Switch3" to which it is connected to the range covered by the aggregation switch and the core switch. The server logically links the device connection performance parameters of "Printer - S1" with this potential network segment to generate third-party network data. This data may include the degree of influence of the connection of "Printer - S1" on the connection performance of the potential network segment device. Since it is a low-performance 100M connection device, it has a relatively small effect on improving the device connection performance of the entire potential network segment. This situation will be recorded in the third-party network data.

[0083] Next, from the third network data associated with the potential network segment of the R&D department, the structured parameters associated with each network node having an inclusion relationship with the potential network segment are obtained. For example, for "Server - R1", the structured parameters may include its processor performance, memory capacity, disk I / O speed, etc. Assume that the processor performance of "Server - R1" is a high-performance multi-core processor, the memory capacity is 64GB, and the disk I / O speed is 1000MB / s.

[0084] Based on the connection relationship parameters between the potential network segment and "Server - R1" (such as connection bandwidth, link stability, etc.) and these structural parameters, the node incentive parameters of "Server - R1" for the potential network segment are determined. Due to the high-performance connection (dual 10 Gigabit Ethernet interfaces) and its own powerful hardware performance (high-performance processor, large memory, high disk I / O speed) of "Server- R1", its node incentive parameters may be determined as "high". This means that "Server - R1" has a strong positive role in promoting the device connection performance of the potential network segment of the R&D department.

[0085] For other network nodes in the potential network segment of the R&D department, such as some developers' office computers, their processor performance may be relatively low, with a memory capacity of 8GB, a disk I / O speed of 100MB / s, and connected to the access switch through a 100M Ethernet interface. Based on their connection relationship with the potential network segment and their own structural parameters, their node incentive parameters are determined to be "low".

[0086] Based on the node incentive parameters of each network node for the potential network segment, the first network segment attribute parameter associated with the potential network segment is determined. In the potential network segment of the R&D department, since the node incentive parameters of key devices such as "Server - R1" are "high", and the node incentive parameters of other devices such as office computers are "low", comprehensive consideration is taken to determine that the first network segment attribute parameter associated with the potential network segment of the R&D department is "medium-high". This first network segment attribute parameter reflects the overall incentive situation of the potential network segment in terms of device connection performance by the network node, and reflects the comprehensive level of device connection performance in the network segment.

[0087] In addition, unstructured parameters associated with each network node having an inclusion relationship with the potential network segment can be obtained from the third network data associated with the potential network segment of the sales department. For example, for "Printer - S1", the unstructured parameters may include the frequency of use of the device, the failure rate of the device, etc. Assume that the frequency of use of "Printer - S1" is low, only a few dozen pages of documents are printed every day, and the failure rate is 2 times per year.

[0088] Based on the connection relationship parameters between the sales department's potential network segment and "Printer - S1" (such as connection reliability, bandwidth usage, etc.), determine the impact coefficient of "Printer - S1" on the potential network segment. Since "Printer - S1" is a single-link 100M connection with low usage frequency and low failure rate, its impact coefficient on the device connection performance of the potential network segment is determined to be "low". This means that its impact on the device connection performance of the entire potential network segment is relatively small.

[0089] For other devices in the potential network segment of the sales department, such as the office computers of sales staff, unstructured parameters may include the complexity of software installation, user operation habits, etc. If an office computer is installed with a lot of complex sales management software, and the user often runs multiple software at the same time, this may affect the network connection performance of the device. Based on its connection relationship with the potential network segment and these unstructured parameters, its impact coefficient is determined to be "medium".

[0090] Based on the influence coefficient of each network node on the potential network segment and the unstructured parameters associated with each network node, the second network segment attribute parameter associated with the potential network segment is determined. In the potential network segment of the sales department, considering the low influence coefficient of "Printer - S1" and the medium influence coefficient of office computers, the second network segment attribute parameter associated with the potential network segment of the sales department is determined to be "medium". This second network segment attribute parameter reflects the comprehensive influence of the network nodes on the device connection performance of the potential network segment from another perspective.

[0091] In a possible implementation, step S130 includes:

[0092] Step S131 : optimizing the network segment attribute parameter sequence associated with each potential network segment to generate a target network segment attribute parameter sequence associated with each potential network segment.

[0093] Step S132, globally calculate the target network segment attribute parameter sequence associated with each potential network segment to generate the network resource occupancy expectation associated with each potential network segment, each target network segment attribute parameter in the target network segment attribute parameter sequence corresponds to an importance coefficient, and the importance coefficient is not less than a set threshold.

[0094] In a possible implementation manner, the network segment attribute parameter sequence includes Y categories of network segment attribute parameters, where Y is an integer not less than 1.

[0095] Step S131 includes:

[0096] Step S1311 , arranging the network segment attribute parameters of the same category for each potential network segment to generate Y network segment attribute parameter clusters, each network segment attribute parameter cluster including X network segment attribute parameters.

[0097] Step S1312, equally divide each of the network segment attribute parameter clusters to generate a plurality of equally divided subclusters associated with each category, each equally divided subcluster corresponds to a set value, and each equally divided subcluster includes at least one network segment attribute parameter.

[0098] Step S1313: for the network segment attribute parameter sequence associated with each potential network segment, based on a plurality of average subclusters associated with the same category, determine an average subcluster corresponding to each network segment attribute parameter in the network segment attribute parameter sequence.

[0099] Step S1314: for the network segment attribute parameter sequence associated with each potential network segment, based on the average subclusters corresponding to each network segment attribute parameter in the network segment attribute parameter sequence, set values ​​associated with each corresponding average subclusters as the target network segment attribute parameter sequence.

[0100] The network segment attribute parameter sequence includes Y categories of network segment attribute parameters, and Y is an integer not less than 1.

[0101] In this embodiment, it is assumed that there are three categories of network segment attribute parameters (Y = 3) in the enterprise network, namely network activity, security performance and device connection performance. For the potential network segments where the R&D department, sales department and finance department are located (X = 3 potential network segments), the network segment attribute parameters of the same category are first arranged for each potential network segment.

[0102] Regarding network activity, the R&D department has a high network activity, the sales department has a moderate network activity, and the finance department has a low network activity. The network activity parameters of these three potential network segments are arranged to form a network segment attribute parameter cluster.

[0103] In terms of security performance, the financial department has the highest security performance, followed by the R&D department, and the sales department has a relatively low security performance. The security performance parameters of these three potential network segments are arranged to form a security performance parameter cluster.

[0104] In terms of device connection performance, the R&D department has core servers and other equipment, so the connection performance is good. The sales department has ordinary office equipment, so the performance is average. The financial department's equipment connection performance mainly meets its own security needs, so it is relatively medium. The device connection performance parameters of these three potential network segments are arranged into a device connection performance parameter cluster.

[0105] Taking the network activity parameter cluster as an example, we divide it equally. Assume that it is divided into two equal subclusters. If divided according to the network activity value range, high network activity (R&D department) is one equal subcluster, and medium and low network activity (sales department and finance department) is another equal subcluster. Each equal subcluster corresponds to a set value, for example, the set value corresponding to high network activity is 0.8, and the set value corresponding to medium and low network activity is 0.4.

[0106] Similar equalization operations are performed for the security performance parameter cluster and the device connection performance parameter cluster. For example, the set value corresponding to high security performance (finance department) is 0.9, and the medium-low (R&D department and sales department) is 0.6; the device connection performance is good (R&D department) is 0.7, and the medium-low (sales department and finance department) is 0.5.

[0107] For the potential network segment of the R&D department, the average sub-cluster setting value for its network activity is 0.8 (because it is a high network activity), the setting value for security performance is 0.6 (relative value of medium-low security performance), and the setting value for device connection performance is 0.7 (good device connection performance). Therefore, the target network segment attribute parameter sequence for the potential network segment of the R&D department is [0.8, 0.6, 0.7].

[0108] For the potential network segment of the sales department, the target network segment attribute parameter sequence may be [0.4, 0.6, 0.5], and for the potential network segment of the finance department, it may be [0.4, 0.9, 0.5].

[0109] The method further comprises:

[0110] Step A110 , performing a standardized conversion on the network segment attribute parameter sequence associated with each potential network segment to generate a standardized array, wherein the standardized array is represented as a Y×X array.

[0111] Step A120, based on the standardized array, calculate the proportion of each network segment attribute parameter associated with each potential network segment under each category, generate Y×X proportion values, determine the degree of chaos corresponding to each category based on the Y×X proportion values, determine the discrimination coefficient corresponding to each category based on the degree of chaos corresponding to each category, and determine the importance coefficient associated with each category based on the discrimination coefficient corresponding to each category.

[0112] In this embodiment, the server performs a standardized conversion on the network segment attribute parameter sequence associated with each potential network segment to generate a standardized array. For example, for the network segment attribute parameters of the above three potential network segments (R&D department, sales department, and finance department) and three categories (network activity, security performance, and device connection performance), a 3×3 standardized array is generated.

[0113] Assume that the original network segment attribute parameter sequence of the R&D department is [high network activity, medium-low security performance, good device connection performance]. After standardization, it may be converted into a numerical form, such as [0.8, 0.4, 0.7] (this is just an assumed standardized value, and the actual conversion may be based on a more complex algorithm). The sales department may be converted to [0.4, 0.4,0.5], and the finance department to [0.4, 0.8, 0.5], forming the following standardized array:

[0114] | Potential network segment| Network activity| Security performance| Device connection performance|

[0115] | ---- | ---- | ---- | ---- |

[0116] | R&D Department| 0.8 | 0.4 | 0.7 |

[0117] | Sales Department | 0.4 | 0.4 | 0.5 |

[0118] | Finance Department | 0.4 | 0.8 | 0.5 |

[0119] For each potential network segment under the network activity category, calculate the proportion of the network segment attribute parameters. The network activity parameter proportion of the R&D department is 0.8 / (0.8 + 0.4 + 0.4) = 0.5, the sales department is 0.4 / (0.8 + 0.4 + 0.4) = 0.25, and the finance department is 0.4 / (0.8 + 0.4 + 0.4) = 0.25. In this way, the three proportion values ​​under the network activity category are obtained.

[0120] The proportion values ​​under the security performance and device connection performance categories are calculated in a similar way to generate a total of 3×3 proportion values.

[0121] The degree of chaos for each category can be determined based on these percentages. Chaos can be calculated using some statistical methods, such as calculating the variance of the percentages. Assume that the variance of the percentage of network activity is 0.1 (here is an assumption), the security performance is 0.2, and the device connection performance is 0.15.

[0122] The discrimination coefficient is determined based on the degree of chaos corresponding to each category. The discrimination coefficient can be the inverse of the degree of chaos or a certain mapping relationship based on the degree of chaos. Assume that the discrimination coefficient of network activity is 10 (1 / 0.1), security performance is 5 (1 / 0.2), and device connection performance is 6.67 (1 / 0.15).

[0123] Then, the importance coefficient associated with each category is determined based on the discrimination coefficient. The importance coefficient can be obtained by normalizing the discrimination coefficient. The importance coefficient of network activity is 10 / (10 + 5 + 6.67) ≈ 0.43, the security performance is 5 / (10 + 5 + 6.67) ≈ 0.22, and the device connection performance is 6.67 / (10 + 5 + 6.67) ≈ 0.35.

[0124] Therefore, the target network segment attribute parameter sequence of the potential network segment of the R&D department is [0.8, 0.6, 0.7], and the corresponding importance coefficients are 0.43, 0.22, and 0.35, respectively. Performing global calculation, the expected network resource occupancy = 0.8×0.43 + 0.6×0.22+ 0.7×0.35 = 0.721.

[0125] The target segment attribute parameter sequence of the potential segment of the sales department is [0.4, 0.6, 0.5], calculated according to the same importance coefficient.

[0126] Expected network resource usage = 0.4×0.43 + 0.6×0.22 + 0.5×0.35 = 0.479.

[0127] The target network segment attribute parameter sequence of the potential network segment of the finance department is [0.4, 0.9, 0.5].

[0128] Expected network resource usage = 0.4×0.43 + 0.9×0.22+ 0.5×0.35 = 0.533.

[0129] In a possible implementation manner, determining the service potential index associated with each potential network segment based on the capacity information sequence of each potential network segment for the target network session service and the network resource occupancy expectation includes:

[0130] The network resource occupancy expectations associated with each potential network segment are accumulated to generate a global network resource occupancy expectation; a global service capacity index is determined based on the capacity information sequence of each potential network segment for the target network session service; a network resource configuration expectation is determined based on the global network resource occupancy expectation and the global service capacity index; and a service potential index associated with each potential network segment is determined based on the capacity information sequence of each potential network segment for the target network session service and the network resource configuration expectation.

[0131] In a possible implementation manner, obtaining the capacity information sequence of each potential network segment for the target network session service includes:

[0132] If the target network session service belongs to the collaborative service category, then Z capacity information of each potential network segment facing the target network session service is obtained, and the Z capacity information belongs to the capacity information sequence. The collaborative service category indicates that the network service object has multiple service label features, and Z is a positive integer.

[0133] Determining the global service capacity index based on the capacity information sequence of each potential network segment facing the target network session service includes: determining Z global service capacity indexes based on each capacity information of each potential network segment facing the target network session service.

[0134] The determining of network resource configuration expectations based on the global network resource occupancy expectation and the global service capacity index includes: determining Z network resource configuration expectations based on the global network resource occupancy expectation and the Z global service capacity indices.

[0135] Determining the service potential index associated with each potential network segment based on the capacity information sequence of each potential network segment facing the target network session service and the network resource configuration expectation includes: determining Z service potential sub-indices associated with each potential network segment based on Z capacity information of each potential network segment facing the target network session service and the Z network resource configuration expectations. Performing fusion calculation on the Z service potential sub-indices associated with each potential network segment to generate the service potential index associated with each potential network segment.

[0136] Alternatively, the obtaining of the capacity information sequence of each potential network segment for the target network session service includes: obtaining Q capacity information of each potential network segment for the target network session service, the Q capacity information belonging to the capacity information sequence, and Q is a positive integer.

[0137] Determining the global service capacity index based on the capacity information sequence of each potential network segment facing the target network session service includes: determining Q global service capacity indexes based on each capacity information of each potential network segment facing the target network session service.

[0138] The determining of network resource configuration expectations based on the global network resource occupancy expectation and the global service capacity index includes: determining Q network resource configuration expectations based on the global network resource occupancy expectation and the Q global service capacity indices.

[0139] The determining of the service potential index associated with each potential network segment based on the capacity information sequence of each potential network segment for the target network session service and the network resource configuration expectations includes: determining Q service potential sub-indices associated with each potential network segment based on Q capacity information of each potential network segment for the target network session service and the Q network resource configuration expectations, performing fusion calculation on the Q service potential sub-indices associated with each potential network segment, and generating a service potential index associated with each potential network segment.

[0140] In this embodiment, in the previous enterprise network example, there are potential network segments where the R&D department, sales department, and finance department are located. The expected network resource occupancy of the potential network segment of the R&D department is 0.721, the expected network resource occupancy of the potential network segment of the sales department is 0.479, and the expected network resource occupancy of the potential network segment of the finance department is 0.533.

[0141] The server accumulates the expected network resource usage associated with each potential network segment to generate the expected global network resource usage. The expected global network resource usage = 0.721 + 0.479 + 0.533 = 1.733.

[0142] Assume that the target network conversation service is an internal video conferencing service of an enterprise, which is not a collaborative service category (here, the calculation of the non-collaborative service category is demonstrated first).

[0143] For the potential network segment of the R&D department, the server obtains its capacity information sequence for video conferencing services. For example, the number of HD video streams it supports is 100 (assuming Q = 1 capacity information). For the potential network segment of the sales department, the number of HD video streams it supports is 50, and the number of HD video streams supported by the potential network segment of the finance department is 60.

[0144] Based on each capacity information of each potential network segment for the target network session service, determine Q global service capacity indices. Assume that the total demand for video conferencing services within the enterprise is 200 high-definition video streams (this assumption is made here for the purpose of calculating the global service capacity index).

[0145] The global service capacity index of the potential network segment of the R&D department = 100 / 200 = 0.5. The global service capacity index of the potential network segment of the sales department = 50 / 200 = 0.25, and the global service capacity index of the potential network segment of the finance department = 60 / 200 = 0.3.

[0146] Next, based on the global network resource occupancy expectation and the Q global service capacity indexes, Q network resource configuration expectations are determined.

[0147] For the potential network segment of the R&D department, the expected network resource allocation = 1.733×0.5 = 0.8665.

[0148] For the potential network segment of the sales department, the expected network resource configuration = 1.733×0.25 = 0.43325.

[0149] For the potential network segment of the finance department, the expected network resource configuration = 1.733×0.3 = 0.5199.

[0150] Then, based on the Q capacity information of each potential network segment for the target network session service and the Q network resource configuration expectations, Q service potential sub-indexes associated with each potential network segment are determined.

[0151] For the potential network segment of the R&D department, the service potential sub-index = 100 / 0.8665 (here it is simply calculated based on the proportional relationship between capacity information and expected network resource configuration, which may be more complicated in practice) ≈ 115.41.

[0152] For the sales department potential segment, the service potential sub-index = 50 / 0.43325 ≈ 115.41 (coincidentally the same, but may actually be different depending on different data).

[0153] For the potential network segment of the finance department, the service potential sub-index = 60 / 0.5199 ≈ 115.31.

[0154] The Q service potential sub-indexes associated with each potential network segment are integrated and calculated to generate the service potential index associated with each potential network segment. Since there is only one service potential sub-index (Q = 1), the service potential index is equal to this service potential sub-index. Therefore, the service potential index of the R&D department's potential network segment is approximately 115.41, the service potential index of the sales department's potential network segment is approximately 115.41, and the service potential index of the finance department's potential network segment is approximately 115.31.

[0155] Further assume that the target network conversation service is a collaborative office platform service within the enterprise, which belongs to the collaborative service category. This collaborative office platform service has functions such as document sharing, instant messaging, and project management (assuming Z = 3 capacity information).

[0156] For the potential network segment of the R&D department, the server obtains the capacity information sequence for the collaborative office platform service. For the document sharing function, its capacity information is that it can store 100GB of shared documents; for the instant messaging function, its capacity information is that it supports 10,000 concurrent messages; for the project management function, its capacity information is that it can process the relevant data of 50 projects at the same time.

[0157] For the potential network segment of the sales department, the document sharing capacity is 50GB, the instant messaging supports 5,000 concurrent messages, and can process 20 project-related data at the same time. For the potential network segment of the finance department, the document sharing capacity is 80GB, the instant messaging supports 8,000 concurrent messages, and can process 30 project-related data at the same time.

[0158] Based on each capacity information of each potential network segment for the target network session service, determine Z global service capacity indexes. Assume that the total demand for document sharing within the enterprise is 200GB, the total demand for instant messaging is 20,000 concurrent messages, and the total demand for project management is 100 project-related data.

[0159] Potential network segments for the R&D department:

[0160] The global service capacity index for document sharing = 100 / 200 = 0.5.

[0161] The global service capacity index of instant messaging = 10000 / 20000 = 0.5.

[0162] The global service capacity index for project management = 50 / 100 = 0.5.

[0163] For potential network segments of the sales department:

[0164] The global service capacity index for document sharing = 50 / 200 = 0.25.

[0165] The global service capacity index of instant messaging = 5000 / 20000 = 0.25.

[0166] The global service capacity index for project management = 20 / 100 = 0.2.

[0167] For the potential network segments of the finance department:

[0168] The global service capacity index for document sharing = 80 / 200 = 0.4.

[0169] The global service capacity index of instant messaging = 8000 / 20000 = 0.4.

[0170] The global service capacity index for project management = 30 / 100 = 0.3.

[0171] Next, based on the global network resource occupancy expectation and the Z global service capacity indexes, Z network resource configuration expectations are determined.

[0172] Potential network segments for the R&D department:

[0173] The expected network resource configuration for document sharing = 1.733×0.5 = 0.8665.

[0174] The expected allocation of network resources for instant messaging = 1.733×0.5 = 0.8665.

[0175] The expected allocation of network resources for project management = 1.733×0.5 = 0.8665.

[0176] For potential network segments of the sales department:

[0177] The expected network resource configuration for document sharing = 1.733×0.25 = 0.43325.

[0178] The expected allocation of network resources for instant messaging = 1.733×0.25 = 0.43325.

[0179] The expected allocation of network resources for project management = 1.733 × 0.2 = 0.3466.

[0180] For the potential network segments of the finance department:

[0181] The expected network resource configuration for document sharing = 1.733×0.4 = 0.6932.

[0182] The expected allocation of network resources for instant messaging = 1.733×0.4 = 0.6932.

[0183] The expected allocation of network resources for project management = 1.733×0.3 = 0.5199.

[0184] Then, based on the Z capacity information of each potential network segment for the target network session service and the Z network resource configuration expectations, Z service potential sub-indexes associated with each potential network segment are determined.

[0185] Potential network segments for the R&D department:

[0186] The service potential sub-index of document sharing = 100 / 0.8665 ≈ 115.41.

[0187] The service potential sub-index of instant messaging = 10000 / 0.8665 ≈ 11541.03.

[0188] The service potential sub-index of project management = 50 / 0.8665 ≈ 57.71.

[0189] For potential network segments of the sales department:

[0190] The service potential sub-index of document sharing = 50 / 0.43325 ≈ 115.41.

[0191] The service potential sub-index of instant messaging = 5000 / 0.43325 ≈ 11541.03.

[0192] The service potential sub-index of project management = 20 / 0.3466 ≈ 57.71.

[0193] For the potential network segments of the finance department:

[0194] The service potential sub-index of document sharing = 80 / 0.6932≈115.41.

[0195] The service potential sub-index of instant messaging = 8000 / 0.6932 ≈ 11541.03.

[0196] The service potential sub-index of project management = 30 / 0.5199 ≈ 57.71.

[0197] The Z service potential sub-indices associated with each potential network segment are fused and calculated to generate a service potential index associated with each potential network segment. Fusion methods such as weighted average can be used here. Assume that the weights of document sharing, instant messaging, and project management are 0.3, 0.4, and 0.3 respectively.

[0198] Potential network segments for the R&D department:

[0199] Service potential index = (115.41×0.3 + 11541.03×0.4+ 57.71×0.3)≈4639.74.

[0200] For potential network segments of the sales department:

[0201] Service potential index = (115.41×0.3 + 11541.03×0.4+ 57.71×0.3)≈4639.74.

[0202] For the potential network segments of the finance department:

[0203] Service potential index = (115.41×0.3 + 11541.03×0.4+ 57.71×0.3)≈4639.74.

[0204] Thus, the service potential index associated with each potential network segment can be determined, which helps to further evaluate the availability and stability of each potential network segment in the target network session service, thereby providing an important basis for subsequent network resource management and service allocation.

[0205] In a possible implementation, determining the network segment call index associated with each potential network segment based on the relationship between the network resource occupancy expectation associated with each potential network segment and the service potential index includes:

[0206] The network resource occupancy expectation and service potential index associated with each potential network segment are calculated differentially to generate a network segment calling index associated with each potential network segment, wherein the network segment calling index is positively correlated with the calling confidence of the potential network segment.

[0207] The determining of the target network segment sequence to be called from the X potential network segments based on the network segment call index associated with each potential network segment includes: if there are one or more network segment call indexes less than a set threshold, removing the potential network segments whose network segment call indexes are less than the set threshold from the X potential network segments to generate W potential network segments, where W is an integer not greater than X. Arranging the W potential network segments in descending order of the network segment call index to generate an arrangement sequence. The first R potential network segments in the arrangement sequence are used as the target network segment sequence to be called, where R is an integer not less than 1.

[0208] Alternatively, determining the network segment call index associated with each potential network segment based on the relationship between the network resource occupancy expectation associated with each potential network segment and the service potential index includes:

[0209] The difference between the service potential index associated with each potential network segment and the expected network resource occupancy is calculated to generate a network segment call index associated with each potential network segment, wherein the network segment call index is negatively correlated with the call confidence of the potential network segment.

[0210] The determining of the target network segment sequence to be called from the X potential network segments based on the network segment call index associated with each potential network segment includes: if there is one or more network segment call indexes greater than a set threshold, removing the potential network segments whose network segment call indexes are greater than the set threshold from the X potential network segments to generate W potential network segments, where W is an integer not greater than X. Arranging the W potential network segments in ascending order of the network segment call indexes to generate an arranged sequence. The first R potential network segments in the arranged sequence are used as the target network segment sequence to be called, where R is an integer not less than 1.

[0211] In this embodiment, in the previous enterprise network example, there are potential network segments where the R&D department, sales department, and finance department are located. The expected network resource occupancy of the potential network segment of the R&D department is 0.721, and the service potential index is approximately 115.41 (taking the non-collaborative service category as an example). The expected network resource occupancy of the potential network segment of the sales department is 0.479, and the service potential index is approximately 115.41. The expected network resource occupancy of the potential network segment of the finance department is 0.533, and the service potential index is approximately 115.31.

[0212] The server calculates the difference between the expected network resource occupancy and the service potential index associated with each potential network segment, and generates a network segment call index associated with each potential network segment.

[0213] For the potential network segment of the R&D department, the network segment call index = 115.41 - 0.721 = 114.689.

[0214] For the sales department potential segment, the segment call index = 115.41 - 0.479 = 114.931.

[0215] For the potential network segment of the finance department, the network segment call index = 115.31 - 0.533 = 114.777.

[0216] In the positive correlation example, assume that the threshold is set to 100. Since the call indexes of all network segments (114.689 for the R&D department, 114.931 for the sales department, and 114.777 for the finance department) are greater than the set threshold, there is no need to remove any potential network segments, that is, W = X = 3.

[0217] Based on the descending order of the network segment call index, the three potential network segments are arranged in the following order: sales department potential network segment (114.931), finance department potential network segment (114.777), and R&D department potential network segment (114.689).

[0218] Assuming R = 2, the first two potential network segments in the sequence (the potential network segment of the sales department and the potential network segment of the finance department) are used as the target network segment sequence to be called. This means that when providing target network session services (such as video conferencing services), the server will give priority to allocating resources to the potential network segments where the sales department and the finance department are located, because their network segment call index is higher and is positively correlated with the call confidence, indicating that the reliability and efficiency of services on these network segments may be higher.

[0219] In the negative correlation example, the network segment call index is now generated by performing a difference calculation based on the service potential index and the expected network resource occupancy (assuming a different calculation scenario from the previous one, reviewing the data here, assuming that the expected network resource occupancy of the potential network segment of the R&D department is 0.8 and the service potential index is 50; the expected network resource occupancy of the potential network segment of the sales department is 0.6 and the service potential index is 40; the expected network resource occupancy of the potential network segment of the finance department is 0.7 and the service potential index is 45).

[0220] For the potential network segment of the R&D department, the network segment call index = 50 - 0.8 = 49.2.

[0221] For the potential network segment of the sales department, the network segment call index = 40 - 0.6 = 39.4.

[0222] For the potential network segment of the finance department, the network segment call index = 45 - 0.7 = 44.3.

[0223] Assume that the threshold is set to 45. Since the segment call index of the R&D department's potential segment is 49.2, which is greater than the set threshold, the R&D department's potential segment is removed from the 3 potential segments (X = 3), generating W = 2 potential segments (sales department and finance department potential segments).

[0224] Based on the ascending order of the network segment call index, the two potential network segments are arranged in the order of sales department potential network segment (39.4) and finance department potential network segment (44.3).

[0225] Assuming R = 1, the first potential network segment in the sequence (the potential network segment of the sales department) is used as the target network segment sequence to be called. This shows that in this case, since the network segment call index is negatively correlated with the call confidence, the network segment call index of the potential network segment of the sales department is the lowest, so the server will give priority to allocating resources to the potential network segment where the sales department is located to meet the needs of the target network session service while ensuring the stability and reliability of the service.

[0226] For more potential network segments, assume that in addition to R&D, sales, and finance departments, there are potential network segments for production, human resources, and other departments. For example, the expected network resource occupancy of the potential network segment of the production department is 0.65, and the service potential index is 60; the expected network resource occupancy of the potential network segment of the human resources department is 0.55, and the service potential index is 55.

[0227] In the positive correlation example, for the potential network segment of the production department, the network segment call index = 60 - 0.65 = 59.35. For the potential network segment of the human resources department, the network segment call index = 55 - 0.55 = 54.45.

[0228] Assume that the threshold is set to 50, and R = 3 potential network segments are to be selected. Since the call index of all network segments is greater than the set threshold, W = X (here X = 5, including the network segments where the R&D, sales, finance, production, and human resources departments are located).

[0229] The network segment call index is arranged in descending order as follows: potential network segment of production department (59.35), potential network segment of human resources department (54.45), potential network segment of sales department (114.931), potential network segment of finance department (114.777), and potential network segment of R&D department (114.689).

[0230] Then the target network segment sequence is the potential network segments where the production department, human resources department, and sales department are located.

[0231] In the negative correlation example, assume that the difference is recalculated based on the service potential index and the expected network resource occupancy (assuming data adjustments in different scenarios, the expected network resource occupancy of the potential network segment of the production department is 0.7, and the service potential index is 30; the expected network resource occupancy of the potential network segment of the human resources department is 0.6, and the service potential index is 25).

[0232] For the potential network segment of the production department, the network segment call index = 30 - 0.7 = 29.3.

[0233] For the potential network segment of the human resources department, the network segment calling index = 25 - 0.6 = 24.4.

[0234] Assume that the threshold is set to 25.5. Since the network segment call index of the potential network segment of the production department is 29.3, which is greater than the set threshold, the potential network segment of the production department is removed. At this time, W = 4 (the network segments of the sales, finance, R&D, and human resources departments are left).

[0235] The network segment call index is arranged in ascending order as follows: potential network segment of human resources department (24.4), potential network segment of sales department (39.4), potential network segment of finance department (44.3), and potential network segment of R&D department (49.2).

[0236] Assuming R = 2, the target network segment sequence is the potential network segments where the human resources department and the sales department are located.

[0237] Therefore, according to different association relationships (positive or negative association), the network segment call index associated with each potential network segment can be determined, and a suitable target network segment sequence can be screened out from a large number of potential network segments, thereby effectively managing the service of the network address terminal, ensuring the reasonable allocation of network resources and the efficient operation of the target network session service.

[0238] In a possible implementation, before obtaining a sequence of network segment attribute parameters associated with each potential network segment of the X potential network segments for the target network session service initiated by the network address terminal, the method further includes: generating a network topology map, obtaining the predetermined network partitioning strategy based on a network segment selection action for the network topology map, and segmenting the predetermined network partitioning strategy based on a network segment segmentation instruction corresponding to a segmentation action for the predetermined network partitioning strategy to generate the X potential network segments.

[0239] In this embodiment, in the enterprise network, the server first generates a network topology diagram. The server detects devices in the network through a network discovery protocol (such as SNMP - Simple Network Management Protocol). For example, the server discovers that the data center of the enterprise headquarters has several core switches, such as Core - Switch1, Core - Switch2, etc. These core switches are connected to multiple aggregation switches, such as Aggregation - Switch1, Aggregation - Switch2, etc., and each aggregation switch is connected to multiple access switches, such as Access - Switch1 to Access - Switch10, etc.

[0240] At the same time, the server identifies various terminal devices connected to these access switches, including the R&D department's server cluster (Server - R1, Server - R2, etc.), office computers (PC - R1, PC - R2, etc.), the sales department's office computers (PC - S1, PC - S2, etc.), the finance department's server (Server - F1) and office computers (PC - F1, etc.), as well as related equipment from other departments.

[0241] The server constructs a network topology diagram based on the connection relationship between devices. In this topology diagram, the core switch is located at the top layer, the aggregation switch is in the middle layer, the access switch is in the bottom layer, and the terminal devices are connected to the access switch. The connection line is marked with the connection type, such as optical fiber (marked as Fiber) or twisted pair (marked as Twisted - Pair), and the bandwidth of the connection is marked, such as 1Gbps or 100Mbps.

[0242] In addition to the basic device connection relationship, the server also records other information in the network topology diagram. For example, for the geographical location information of each device, the core switch of the data center is located in a specific computer room area, and the office computers of the sales department are distributed in various offices on the office floor. The server also records the functional information of the device, such as the server of the R&D department is used for code compilation and testing, and the server of the finance department is used for financial data processing, etc.

[0243] Therefore, the server performs network segment selection based on the information such as the department and function of the device in the network topology diagram. For example, considering the convenience of security and management, the server decides to divide all the devices in the R&D department into one or more network segments. Because the R&D department often develops and tests codes, it may require high-bandwidth internal communication, and its data may have high confidentiality. Therefore, for the R&D department, the server chooses to connect all R&D devices under specific access switches (such as Access - Switch1 to Access - Switch3) as an independent network area, which forms part of the predetermined network division strategy based on department functions.

[0244] For the finance department, since it handles sensitive financial data of the enterprise, the server selection divides the server (Server - F1) and office computers (PC - F1, etc.) of the finance department into a network segment with a higher security level and strict access control. This network segment may be connected to the core switch (Core - Switch1) through a specific aggregation switch (such as Aggregation - Switch1), and strict firewall rules are set to only allow specific internal IP addresses to access.

[0245] The sales department's equipment, since its main needs are to communicate with external customers and access the company's sales management system, the server may divide the sales department's office computers (PC-S1, PC-S2, etc.) into a network segment with certain external access rights, while restricting access to sensitive internal corporate resources (such as R&D code libraries and financial data).

[0246] In addition to departmental functions, the server also considers the performance requirements of the equipment. For example, the server cluster of the R&D department (Server - R1, Server - R2, etc.) has high requirements for network bandwidth and transmission speed because it needs to handle a large number of code compilation and data transmission tasks. The server will divide these high-performance devices into a network segment with a high-bandwidth link (such as 1Gbps or higher). For some ordinary office equipment, such as office computers in the sales department and the finance department, their performance requirements are relatively low and they may be divided into a network segment with relatively low bandwidth (such as 100Mbps).

[0247] Therefore, the server segments the predetermined network partitioning strategy according to the segmentation instructions corresponding to the segmentation actions of the predetermined network partitioning strategy, and generates X potential network segments. For example, for the network partitioning strategy of the R&D department, the server may further subdivide the network segments according to the physical location or function of the equipment. If the server clusters of the R&D department are distributed in different cabinets, the server may divide the servers in different cabinets into different potential network segments to improve the flexibility of network management and fault isolation capabilities. Assume that the server cluster of the R&D department is divided into two potential network segments, one containing devices such as Server- R1, and the other containing devices such as Server- R2.

[0248] For the finance department, although the overall network segment has a higher security level, for the purpose of backup and redundancy, the server may divide the finance server (Server - F1) and some office computers (PC - F1, etc.) into one potential network segment, and divide the finance department's backup server and other office computers into another potential network segment.

[0249] In the sales department, the server divides the office computers of the sales department into multiple potential network segments according to different floors of the office area or different sales teams. For example, the office computers of the sales team on the first floor (PC - S1, etc.) are one potential network segment, and the office computers of the sales team on the second floor (PC - S2, etc.) are another potential network segment.

[0250] Based on the above steps, the process from generating a network topology map to obtaining a predetermined network partitioning strategy and then generating X potential network segments is completed, laying the foundation for subsequently obtaining a sequence of network segment attribute parameters associated with each potential network segment.

[0251] Figure 2 The hardware structure of the intelligent network address terminal management system 100 provided in the embodiment of the present application for implementing the above-mentioned intelligent network address terminal management method is shown as follows: Figure 2 As shown, the intelligent network address terminal management system 100 may include a processor 110 , a machine-readable storage medium 120 , a bus 130 , and a communication unit 140 .

[0252] In one possible design, the intelligent network address terminal management system 100 can be a single server or a server group. The server group can be centralized or distributed (for example, the intelligent network address terminal management system 100 can be a distributed system). In some embodiments, the intelligent network address terminal management system 100 can be local or remote. For example, the intelligent network address terminal management system 100 can access information and / or data stored in a machine-readable storage medium 120 via a network. For another example, the intelligent network address terminal management system 100 can be directly connected to the machine-readable storage medium 120 to access the stored information and / or data. In some embodiments, the intelligent network address terminal management system 100 can be implemented on an intelligent network address terminal management system. By way of example only, the intelligent network address terminal management system can include a private cloud, a public cloud, a hybrid cloud, a community cloud, a distributed cloud, an internal cloud, a multi-layer cloud, etc. or any combination thereof.

[0253] The machine-readable storage medium 120 can store data and / or instructions. In some embodiments, the machine-readable storage medium 120 can store data obtained from an external terminal. In some embodiments, the machine-readable storage medium 120 can store data and / or instructions that the intelligent network address terminal management system 100 uses to execute or use to complete the exemplary methods described in this application.

[0254] During the specific implementation process, one or more processors 110 execute computer executable instructions stored in the machine-readable storage medium 120, so that the processor 110 can execute the intelligent network address terminal management method of the above method embodiment. The processor 110, the machine-readable storage medium 120 and the communication unit 140 are connected through the bus 130, and the processor 110 can be used to control the sending and receiving actions of the communication unit 140.

[0255] The specific implementation process of the processor 110 can refer to the various method embodiments executed by the above-mentioned intelligent network address terminal management system 100. The implementation principles and technical effects are similar, and this embodiment will not be repeated here.

[0256] In addition, an embodiment of the present application further provides a readable storage medium, in which computer executable instructions are preset. When a processor executes the computer executable instructions, the above intelligent network address terminal management method is implemented.

[0257] It should be noted that in order to simplify the description disclosed in this application and thus help understand one or more embodiments of the invention, in the foregoing description of the embodiments of the present application, multiple features are sometimes combined into one embodiment, drawings, or descriptions thereof. Similarly, it should be noted that in order to simplify the description disclosed in this application and thus help understand one or more embodiments of the invention, in the foregoing description of the embodiments of the present application, multiple features are sometimes combined into one embodiment, drawings, or descriptions thereof.

Claims

1. An intelligent network address terminal management method, characterized in that: The method comprises: Obtaining a network segment attribute parameter sequence associated with each potential network segment of X potential network segments for a target network session service initiated by a network address terminal, wherein the X potential network segments are generated according to a predetermined network partitioning strategy, and the network segment attribute parameter sequence includes each network segment attribute parameter formed by one or more combinations of a network activity parameter sequence, a device connection performance parameter sequence, a data transmission efficiency parameter sequence, and a security performance parameter sequence, and X is a positive integer; Acquire a capacity information sequence of each potential network segment facing the target network session service, wherein the capacity information sequence includes one or more combined capacity information determined according to a service label feature of the target network session service, and the capacity information sequence refers to resource capacity information that can be provided when describing a potential network segment facing a specific network service; Based on the network segment attribute parameter sequence associated with each potential network segment, the network resource occupancy expectation associated with each potential network segment is determined, and based on the capacity information sequence of each potential network segment for the target network session service and the network resource occupancy expectation, the service potential index associated with each potential network segment is determined, wherein the network resource occupancy expectation represents a scheduling probability value of the potential network segment; and the service potential index represents the availability and stability of the potential network segment; Based on the relationship between the network resource occupancy expectation and the service potential index associated with each potential network segment, determining a network segment call index associated with each potential network segment, wherein the network segment call index reflects the call confidence of the potential network segment; Based on the network segment call index associated with each potential network segment, a target network segment sequence to be called is determined from the X potential network segments, and service management is performed on the network address terminal based on the target network segment sequence to be called, wherein the target network segment sequence includes one or more potential network segments.

2. The intelligent network address terminal management method according to claim 1, characterized in that: The step of obtaining a sequence of network segment attribute parameters associated with each potential network segment of X potential network segments for the target network session service initiated by the network address terminal includes: Obtaining one or more combinations of the network activity parameter sequence and the security performance parameter sequence for the predetermined network partitioning strategy, wherein the network activity parameter sequence includes one or more combinations of the number of visits, online time, and interaction frequency of each network node, and the security performance parameter sequence includes one or more combinations of the security level of each network node, the effectiveness of the protection strategy, and the risk event record; Based on the topological relationship between each network node and each potential network segment, one or more combinations of the network activity parameter sequence and the safety performance parameter sequence are logically associated with each potential network segment to generate first network data associated with each potential network segment; The first network data associated with each potential network segment is analyzed to generate a network segment attribute parameter sequence associated with each potential network segment.

3. The intelligent network address terminal management method according to claim 1, characterized in that: The step of obtaining a sequence of network segment attribute parameters associated with each potential network segment of X potential network segments for the target network session service initiated by the network address terminal includes: Acquire the data transmission efficiency parameter sequence for the predetermined network partitioning strategy, the data transmission efficiency parameter sequence comprising one or more combinations of identifiers of each network path, a path node sequence, and a transmission quality rating; Based on the topological relationship between each network path and each potential network segment, logically link the data transmission efficiency parameter sequence with each potential network segment in the X potential network segments to generate second network data associated with each potential network segment; The second network data associated with each potential network segment is analyzed to generate a network segment attribute parameter sequence associated with each potential network segment.

4. The intelligent network address terminal management method according to claim 1, characterized in that: The step of obtaining a sequence of network segment attribute parameters associated with each potential network segment of X potential network segments for the target network session service initiated by the network address terminal includes: Acquire the device connection performance parameter sequence for the predetermined network partitioning strategy, the device connection performance parameter sequence comprising one or more combinations of identifiers of each network node, node location information strings, and node connection characteristics; Based on the inclusion relationship between each network node and each potential network segment, logically link the device connection performance parameter sequence with each potential network segment in the X potential network segments to generate third network data associated with each potential network segment; For each potential network segment, obtain structured parameters associated with each network node having an inclusion relationship with the potential network segment from the third network data associated with the potential network segment; for each potential network segment, determine node incentive parameters of each network node facing the potential network segment based on connection relationship parameters between the potential network segment and each network node, and structured parameters associated with each network node; for each potential network segment, determine a first network segment attribute parameter associated with the potential network segment based on the node incentive parameters of each network node facing the potential network segment, wherein the first network segment attribute parameter belongs to a network segment attribute parameter sequence associated with the potential network segment; And / or, for each potential network segment, obtain the unstructured parameters associated with each network node having an inclusion relationship with the potential network segment from the third network data associated with the potential network segment; for each potential network segment, determine the influence coefficient of each network node facing the potential network segment based on the connection relationship parameters between the potential network segment and the each network node; for each potential network segment, determine the second network segment attribute parameter associated with the potential network segment based on the influence coefficient of each network node facing the potential network segment and the unstructured parameters associated with each network node, the second network segment attribute parameter belonging to the network segment attribute parameter sequence associated with the potential network segment.

5. The intelligent network address terminal management method according to any one of claims 1 to 4, characterized in that: The determining, based on the network segment attribute parameter sequence associated with each potential network segment, the network resource occupancy expectation associated with each potential network segment includes: Optimizing the network segment attribute parameter sequence associated with each potential network segment to generate a target network segment attribute parameter sequence associated with each potential network segment; A global calculation is performed on a target network segment attribute parameter sequence associated with each potential network segment to generate a network resource occupancy expectation associated with each potential network segment, wherein each target network segment attribute parameter in the target network segment attribute parameter sequence corresponds to an importance coefficient, and the importance coefficient is not less than a set threshold.

6. The intelligent network address terminal management method according to claim 5, characterized in that: The network segment attribute parameter sequence includes Y categories of network segment attribute parameters, where Y is an integer not less than 1; The step of optimizing the network segment attribute parameter sequence associated with each potential network segment to generate a target network segment attribute parameter sequence associated with each potential network segment includes: Arranging the network segment attribute parameters of the same category for each potential network segment to generate Y network segment attribute parameter clusters, each network segment attribute parameter cluster including X network segment attribute parameters; Equally divide each of the network segment attribute parameter clusters to generate a plurality of equal subclusters associated with each category, each equal subcluster corresponds to a set value, and each equal subcluster includes at least one network segment attribute parameter; For the network segment attribute parameter sequence associated with each potential network segment, based on a plurality of average subclusters associated with the same category, determine an average subcluster corresponding to each network segment attribute parameter in the network segment attribute parameter sequence; For the network segment attribute parameter sequence associated with each potential network segment, based on the average subclusters corresponding to each network segment attribute parameter in the network segment attribute parameter sequence, the set values ​​associated with each corresponding average subclusters are used as the target network segment attribute parameter sequence; The network segment attribute parameter sequence includes Y categories of network segment attribute parameters, where Y is an integer not less than 1; The method further comprises: Performing a standardized conversion on the network segment attribute parameter sequence associated with each potential network segment to generate a standardized array, wherein the standardized array is represented as an array of Y×X; Based on the standardized array, the proportion of each network segment attribute parameter associated with each potential network segment under each category is calculated to generate Y×X proportion values; based on the Y×X proportion values, the degree of chaos corresponding to each category is determined; based on the degree of chaos corresponding to each category, the discrimination coefficient corresponding to each category is determined; based on the discrimination coefficient corresponding to each category, the importance coefficient associated with each category is determined.

7. The intelligent network address terminal management method according to claim 1, characterized in that: The determining, based on the capacity information sequence of each potential network segment for the target network session service and the network resource occupancy expectation, of a service potential index associated with each potential network segment comprises: Accumulating the network resource occupancy expectations associated with each potential network segment to generate a global network resource occupancy expectation, determining a global service capacity index based on the capacity information sequence of each potential network segment for the target network session service, determining a network resource configuration expectation based on the global network resource occupancy expectation and the global service capacity index, and determining a service potential index associated with each potential network segment based on the capacity information sequence of each potential network segment for the target network session service and the network resource configuration expectation; The step of obtaining the capacity information sequence of each potential network segment for the target network session service includes: If the target network session service belongs to the collaborative service category, then obtaining Z capacity information of each potential network segment facing the target network session service, the Z capacity information belongs to the capacity information sequence, the collaborative service category indicates that the network service object has multiple service label features, and Z is a positive integer; The determining of the global service capacity index based on the capacity information sequence of each potential network segment facing the target network session service comprises: determining Z global service capacity indexes based on each capacity information of each potential network segment facing the target network session service; The determining of network resource configuration expectations based on the global network resource occupancy expectation and the global service capacity index comprises: determining Z network resource configuration expectations based on the global network resource occupancy expectation and the Z global service capacity indexes; The determining of the service potential index associated with each potential network segment based on the capacity information sequence of each potential network segment facing the target network session service and the network resource configuration expectation comprises: determining Z service potential sub-indices associated with each potential network segment based on Z capacity information of each potential network segment facing the target network session service and the Z network resource configuration expectations; performing fusion calculation on the Z service potential sub-indices associated with each potential network segment to generate the service potential index associated with each potential network segment; Alternatively, the obtaining of the capacity information sequence of each potential network segment facing the target network session service comprises: obtaining Q pieces of capacity information of each potential network segment facing the target network session service, the Q pieces of capacity information belonging to the capacity information sequence, and Q being a positive integer; The determining of the global service capacity index based on the capacity information sequence of each potential network segment facing the target network session service comprises: determining Q global service capacity indexes based on each capacity information of each potential network segment facing the target network session service; The determining of network resource configuration expectations based on the global network resource occupancy expectation and the global service capacity index comprises: determining Q network resource configuration expectations based on the global network resource occupancy expectation and the Q global service capacity indexes; The determining of the service potential index associated with each potential network segment based on the capacity information sequence of each potential network segment for the target network session service and the network resource configuration expectations includes: determining Q service potential sub-indices associated with each potential network segment based on Q capacity information of each potential network segment for the target network session service and the Q network resource configuration expectations, performing fusion calculation on the Q service potential sub-indices associated with each potential network segment, and generating a service potential index associated with each potential network segment.

8. The intelligent network address terminal management method according to claim 1, characterized in that: The determining of the network segment call index associated with each potential network segment based on the relationship between the network resource occupancy expectation associated with each potential network segment and the service potential index includes: Performing a difference calculation on the network resource occupancy expectation and the service potential index associated with each potential network segment to generate a network segment call index associated with each potential network segment, wherein the network segment call index is positively correlated with the call confidence of the potential network segment; The determining of the target network segment sequence to be called from the X potential network segments based on the network segment call index associated with each potential network segment comprises: if there are one or more network segment call indexes less than a set threshold, removing the potential network segments whose network segment call indexes are less than the set threshold from the X potential network segments to generate W potential network segments, where W is an integer not greater than X; arranging the W potential network segments in descending order of the network segment call indexes to generate an arrangement sequence; using the first R potential network segments in the arrangement sequence as the target network segment sequence to be called, where R is an integer not less than 1; Alternatively, determining the network segment call index associated with each potential network segment based on the relationship between the network resource occupancy expectation associated with each potential network segment and the service potential index includes: Performing a difference calculation between the service potential index associated with each potential network segment and the expected network resource occupancy, generating a network segment call index associated with each potential network segment, wherein the network segment call index is negatively correlated with the call confidence of the potential network segment; The determining of a target network segment sequence to be called from the X potential network segments based on the network segment call index associated with each potential network segment includes: if there are one or more network segment call indexes greater than a set threshold, removing the potential network segments whose network segment call indexes are greater than the set threshold from the X potential network segments to generate W potential network segments, where W is an integer not greater than X; arranging the W potential network segments in ascending order of the network segment call indexes to generate an arrangement sequence; and using the first R potential network segments in the arrangement sequence as the target network segment sequence to be called, where R is an integer not less than 1.

9. The intelligent network address terminal management method according to claim 1, characterized in that: Before acquiring a network segment attribute parameter sequence associated with each potential network segment of X potential network segments for a target network session service initiated by a network address terminal, the method further includes: Generate a network topology map, obtain the predetermined network partitioning strategy according to the network segment selection action for the network topology map, and segment the predetermined network partitioning strategy according to the network segment segmentation instruction corresponding to the segmentation action for the predetermined network partitioning strategy to generate the X potential network segments.

10. An intelligent network address terminal management system, characterized in that: The intelligent network address terminal management system includes a processor and a memory, the memory is connected to the processor, the memory is used to store programs, instructions or codes, and the processor is used to execute the programs, instructions or codes in the memory to implement the intelligent network address terminal management method described in any one of claims 1 to 9 above.

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