A 5G private network networking method suitable for industrial Internet

Abstract

The present invention provides a 5G private network networking method suitable for the industrial Internet, which relates to the technical field of industrial Internet. The method collects node communication data in the private network; determines the node association relationship of each data node through the node communication data, and then divides all the data nodes into multiple network slices, and determines the communication isolation of each network slice in the private network; determines the load distribution domain according to the data communication information between each network slice, and determines the load balancing degree according to the load distribution domain and each communication isolation; when the load balancing degree is lower than a preset balancing threshold, screens out congested nodes in each network slice according to the communication traffic of each data node, and balances all congested nodes in the private network based on the traffic engineering algorithm. The present application can realize the balanced distribution of network slices in the private network, thereby improving the load balancing degree of data nodes in the private network.

Description

Technical Field

[0001] The present application relates to the field of industrial Internet technology. More specifically, the present application relates to a 5G private network networking method suitable for the industrial Internet. Background Art

[0002] Industrial Internet is one of the important development directions of modern industrial production. It closely integrates traditional industrial systems with information technology and network communication technology, realizing the interconnection of equipment, production lines, factories and the entire industrial chain. The emergence of 5G technology, especially the application of 5G private networks, provides reliable wireless communication support for the further development of Industrial Internet. 5G private networks have the characteristics of high bandwidth, low latency, and large connections, which can meet the communication needs with extremely high requirements for real-time, stability and security in industrial production.

[0003] In practical applications, since the load of each slice is different, how to maintain load balance among slices is also an important issue. If the communication traffic in a slice is too large, it may cause node congestion and affect the performance of the entire 5G private network. The load balancing mechanism can dynamically adjust the communication traffic according to the load status and communication isolation of the network slice to ensure the overall performance of the network. In the process of 5G private network networking, the balanced distribution of network slices in the private network is achieved, thereby improving the load balance of data nodes in the private network. Summary of the invention

[0004] The present application provides a 5G private network networking method suitable for the Industrial Internet, which can achieve balanced distribution of network slices in the private network, thereby improving the load balancing of data nodes in the private network.

[0005] The present application provides a 5G private network networking method applicable to the industrial Internet, and the networking method comprises the following steps:

[0006] Collect the node communication records of each data node in the private network from the industrial Internet, and then obtain the node communication data;

[0007] Determine the node association relationship of each data node in the private network through the node communication data, divide all data nodes into multiple network slices according to all node association relationships, and then determine the communication isolation of each network slice in the private network;

[0008] Monitor the data communication information between each network slice in real time, determine the load distribution domain of the communication traffic in the private network according to each data communication information, and then determine the load balancing degree of the private network according to the load distribution domain and the communication isolation of each network slice;

[0009] When the load balancing degree is lower than the preset balancing threshold, the congested nodes are screened out in each network slice according to the communication traffic of each data node collected in real time, and then all the congested nodes in the private network are evenly distributed based on the traffic engineering algorithm.

[0010] In this embodiment, determining the node association relationship of each data node in the private network through the node communication data specifically includes:

[0011] For each data node, extract the node communication record of the data node from the node communication data;

[0012] Determine the communication frequency between the data node and other data nodes in the private network through the node communication record;

[0013] The node association relationship of the data nodes is determined according to all communication frequencies, and then the node association relationship of each data node in the private network is obtained.

[0014] In this embodiment, determining the communication isolation of each network slice in the private network specifically includes:

[0015] For each network slice, obtain the node association relationship of each data node in the network slice;

[0016] Obtain node inline information and node outline information of the network slice in all node association relationships;

[0017] Determine the node inlineness of the network slice according to the node inline information;

[0018] Determine the node externality of the network slice according to the node externality information;

[0019] The communication isolation of the network slice in the private network is determined by the node internal connectivity and the node external connectivity, and then the communication isolation of each network slice in the private network is obtained.

[0020] In this embodiment, determining the load distribution domain of the communication traffic in the private network according to each data communication information specifically includes:

[0021] For each network slice, obtain the real-time inbound and outbound traffic of the network slice in the private network during communication from the data communication information of the network slice;

[0022] Determine the load of the network slice according to the real-time inbound flow and the real-time outbound flow, and then obtain the load of each network slice;

[0023] Determine the load distribution domain of communication traffic in the private network based on all load amounts.

[0024] In this embodiment, the load balancing degree of the private network is determined by the communication isolation between the load distribution domain and each network slice, specifically including:

[0025] For each network slice in the private network, determine the load deviation of the network slice in the load distribution domain;

[0026] Determine the load balancing value of the network slice according to the load deviation and the communication isolation of the network slice, and then obtain the load balancing value of each network slice in the private network;

[0027] The load balancing degree of the private network is determined by all load balancing values.

[0028] In this embodiment, screening out congested nodes in each network slice according to the communication traffic of each data node collected in real time specifically includes:

[0029] For each network slice, the communication traffic of each data node in the network slice is collected in real time;

[0030] Filter out all abnormal data nodes in the network slice based on all communication traffic;

[0031] Determine the traffic utilization of each abnormal data node, and then screen out the congested nodes in the network slice based on all traffic utilizations, and then obtain the congested nodes in each network slice.

[0032] In this embodiment, the private network is a 5G network based on network slicing.

[0033] In this embodiment, the balanced distribution of all congested nodes in the private network based on the traffic engineering algorithm is to use the traffic engineering algorithm to redistribute traffic to the congested nodes. In the specific implementation, a suitable traffic engineering algorithm is selected.

[0034] In this embodiment, all data nodes are divided into multiple network slices according to all node association relationships, specifically including:

[0035] All data nodes are constructed into a node undirected graph based on all node association relationships;

[0036] All data nodes in the node undirected graph are divided into multiple network slices based on the community discovery algorithm.

[0037] In this embodiment, the data communication information includes real-time inbound flow and real-time outbound flow.

[0038] The technical solution provided by the embodiments disclosed in this application has the following beneficial effects:

[0039] The node communication records of each data node in the private network are collected from the industrial Internet, and the node communication data is obtained; the node association relationship of each data node in the private network is determined through the node communication data, and all data nodes are divided into multiple network slices according to all the node association relationships, and the communication isolation of each network slice in the private network is determined; the data communication information between each network slice is monitored in real time, and the load distribution domain of the communication traffic in the private network is determined according to each data communication information, and the load balancing degree of the private network is determined according to the load distribution domain and the communication isolation of each network slice; when the load balancing degree is lower than the preset balancing threshold, the congested nodes are screened out in each network slice according to the communication traffic of each data node collected in real time, and all the congested nodes in the private network are evenly distributed based on the traffic engineering algorithm.

[0040] It can be seen that in this application, when the load balancing degree is lower than the preset balancing threshold, the congested nodes are screened out in each network slice according to the communication traffic of each data node collected in real time, and then all the congested nodes of the private network are evenly distributed based on the traffic engineering algorithm; first, the association between nodes is determined, and the key nodes and dependencies are identified, which can provide a basis for the reasonable division of network slices, ensure that the nodes in the slices are highly correlated, and improve the efficiency of the slices. At the same time, the clear node association relationship can reduce the interference between slices, optimize the overall operation efficiency of the network, and improve the networking of the private network; then, the load distribution domain is determined according to the actual communication flow, which is helpful to optimize traffic management. Clear traffic distribution can identify network slices with insufficient or excessive resources, provide a basis for load balancing decisions, reasonably allocate network resources, improve overall operation efficiency, and ensure that the private network maintains stable and efficient performance under high load conditions. Evaluation of load balancing can continuously monitor the health of the private network and identify potential problems. When the load balancing degree is lower than the preset value, the traffic adjustment measures are quickly triggered, which can ensure self-optimization under dynamic load conditions of the network, reduce congestion, and improve the reliability and efficiency of the private network.

[0041] To sum up, the technical solution adopted in this application can achieve balanced distribution of network slices in private network, thereby improving the load balancing of data nodes in private network. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0043] Figure 1This is an exemplary flow chart of a 5G private network networking method applicable to the Industrial Internet provided in this application;

[0044] Figure 2 is an exemplary flow chart for determining node association relationships provided by the present application;

[0045] Figure 3 is an exemplary flow chart for determining a load distribution domain provided in the present application. DETAILED DESCRIPTION

[0046] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0047] The embodiment of the present application provides a 5G private network networking method suitable for the industrial Internet, the core of which is to collect the node communication records of each data node in the private network from the industrial Internet, and then obtain the node communication data; determine the node association relationship of each data node in the private network through the node communication data, divide all the data nodes into multiple network slices according to all the node association relationships, and then determine the communication isolation of each network slice in the private network; monitor the data communication information between each network slice in real time, determine the load distribution domain of the communication traffic in the private network according to each data communication information, and then determine the load balancing degree of the private network according to the load distribution domain and the communication isolation of each network slice; when the load balancing degree is lower than the preset balancing threshold, select the congested nodes in each network slice according to the communication traffic of each data node collected in real time, and then balance all the congested nodes in the private network based on the traffic engineering algorithm. The above scheme can achieve balanced distribution of network slices in the private network, thereby improving the load balancing degree of data nodes in the private network.

[0048] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1 As shown in the figure, this figure is an exemplary flow chart of a 5G private network networking method suitable for industrial Internet according to this embodiment of the present application, and the networking method includes the following steps:

[0049] In step S1, the node communication records of each data node in the private network are collected from the industrial Internet to obtain the node communication data.

[0050] In specific implementation, a network traffic monitoring tool can be used to collect records of each data node in the private network within the preset time period (the default is three days) as node communication records from the industrial Internet. The node communication records of each data node can be obtained, and the collection of all node communication records can be used as historical communication data.

[0051] It should be noted that each node communication record represents the complete process of a communication. Each node communication record is stored in both the sending node and the receiving node. The node communication record of the sending node and the node communication record of the receiving node are associated with the communication number. Each node communication record contains the record number, communication traffic, communication time and communication target node location.

[0052] In step S2, the node association relationship of each data node in the private network is determined through the node communication data, and all data nodes are divided into multiple network slices according to all node association relationships, and then the communication isolation of each network slice in the private network is determined.

[0053] Preferably, in this embodiment, reference Figure 2 As shown, this figure is an exemplary flow chart of determining the node association relationship in an embodiment of the present application. In this embodiment, the node association relationship of each data node in the private network can be determined by the node communication data, which can be implemented by the following steps:

[0054] First, in step S21, for each data node, the node communication record of the data node is extracted from the node communication data;

[0055] Then, in step S22, the communication frequency between the data node and other data nodes in the private network is determined through the node communication record;

[0056] Finally, in step S23, the node association relationship of the data nodes is determined according to all the communication frequencies, and then the node association relationship of each data node in the private network is obtained.

[0057] It should be noted that the node association relationship refers to the strength of the relationship between two data nodes, which is usually represented by the communication frequency and data interaction between the data nodes; nodes with high communication frequency have strong associations, and vice versa; communication frequency refers to the frequency of communication transmission between two data nodes in a specific time period.

[0058] In the specific implementation, first, for each data node, the node communication record of the data node is extracted from the node communication data; secondly, one of the other data nodes in the private network is selected as the comparison data node, and the total number of communications between the data node and the comparison data node can be counted in the node communication record, and the duration of the preset time period can be converted into seconds. The ratio of the total number of communications to the converted preset time period is used as the communication frequency between the data node and the comparison data node, and the above steps are repeated to obtain the communication frequency between the data node and other data nodes in the private network; finally, the set of all communication frequencies can be used as the node association relationship of the data node, and the node association relationship of the data node can be obtained in the above manner.

[0059] In this embodiment, dividing all data nodes into multiple network slices according to all node association relationships can be implemented by the following steps:

[0060] All data nodes are constructed into a node undirected graph based on all node association relationships;

[0061] All data nodes in the node undirected graph are divided into multiple network slices based on the community discovery algorithm.

[0062] It should be noted that in this application, network slicing is a key technology in 5G and future communication networks, which virtualizes multiple independent logical networks (i.e. slices) on a single physical network; a node undirected graph is a graph composed of a set of vertices (nodes) and edges. The edges have no direction, indicating that there is a two-way interactive relationship between nodes.

[0063] In the specific implementation, first, each data node is mapped to a vertex in a graph. For each pair of related nodes, an undirected edge is drawn. The weight of the edge is the correlation between the nodes (such as communication frequency or data volume). The edge weight can be normalized according to the correlation to ensure that the weight has an appropriate impact during the execution of the algorithm. The communication relationship between nodes in the node undirected graph can be visualized through the graph structure. The node undirected graph simplifies the calculation of the correlation relationship and can be used as the input of complex algorithms such as community partitioning to improve computing efficiency. Then, the undirected graph is divided into multiple closely connected subsets through the community discovery algorithm. Each subset is called a community. The nodes in each community have a high correlation, corresponding to one network slice, and multiple network slices can be obtained.

[0064] In this embodiment, the communication isolation of each network slice in the private network can be determined by the following steps:

[0065] For each network slice, obtain the node association relationship of each data node in the network slice;

[0066] Obtain node inline information and node outline information of the network slice in all node association relationships;

[0067] Determine the node inlineness of the network slice according to the node inline information;

[0068] Determine the node externality of the network slice according to the node externality information;

[0069] The communication isolation of the network slice in the private network is determined by the node internal connectivity and the node external connectivity, and then the communication isolation of each network slice in the private network is obtained.

[0070] It should be noted that, in the present application, communication isolation refers to the degree of isolation of a network slice from other slices in communication, reflecting the independence and security of the slice in the private network; node external connectivity refers to the communication between internal nodes of a slice and external nodes, reflecting the degree of interaction between slices; node internal connectivity refers to the communication density between internal nodes of a slice, reflecting the degree of interconnection between nodes within a slice; node internal connectivity information refers to the communication relationship between nodes within a slice, focusing on data exchange within the slice; node external connectivity information refers to the communication relationship between nodes within a slice and nodes of other slices.

[0071] In the specific implementation, first, for each network slice, the node association relationship of each data node in the network slice is obtained; secondly, the set of communication frequencies between data nodes in the network slice in all node association relationships can be used as node intranet information, and the communication frequency between data nodes in the network slice and data nodes in other network slices can be used as node extranet information; then, the standard deviation of all communication frequencies in the node intranet information can be used as the node intranet property of the network slice; further, the standard deviation of all communication frequencies in the node extranet information can be used as the node extranet property of the network slice; finally, the calculation result of node intranet property / (node ​​intranet property + node extranet property) can be used as the communication isolation property of the network slice in the private network. The communication isolation property of each network slice in the private network can be obtained in the above manner.

[0072] In step S3, the data communication information between each network slice is monitored in real time, and the load distribution domain of the communication traffic in the private network is determined according to each data communication information, and then the load balancing degree of the private network is determined by the load distribution domain and the communication isolation of each network slice.

[0073] It should be noted that, in the present application, data communication information refers to the traffic change process between network slices, and the data communication information includes real-time incoming traffic and real-time outgoing traffic. The incoming traffic indicates that the external traffic enters the network slice, and the outgoing traffic indicates that the internal data of the network slice flows to the outside. In specific implementation, the data communication information between network slices can be extracted from the traffic monitoring system of the private network.

[0074] Preferably, in this embodiment, reference Figure 3 As shown, this figure is an exemplary flow chart of determining the load distribution domain in an embodiment of the present application. In this embodiment, the load distribution domain of the communication traffic in the private network can be determined according to each data communication information, which can be implemented by the following steps:

[0075] First, in step S31, for each network slice, the real-time inbound flow and real-time outbound flow of the network slice in the private network during communication are obtained from the data communication information of the network slice;

[0076] Then, in step S32, the load of the network slice is determined according to the real-time inbound flow and the real-time outbound flow, thereby obtaining the load of each network slice;

[0077] Finally, in step S33, the load distribution domain of the communication traffic in the private network is determined according to all the load amounts.

[0078] It should be noted that in this application, the load distribution domain represents the load distribution of each network slice in the private network; the load volume is an important indicator to measure the current operating pressure of the slice. The higher the load volume, the greater the communication demand of the slice; real-time inbound traffic refers to the real-time traffic of external traffic entering the network slice; real-time outbound traffic refers to the real-time traffic of internal data flowing to the outside of the network slice.

[0079] In the specific implementation, first, for each network slice, the real-time inbound traffic and real-time outbound traffic of the network slice in the private network during communication is obtained from the data communication information of the network slice. By obtaining the real-time inbound traffic and outbound traffic, the communication status of each network slice can be timely grasped to ensure that the network resources can be quickly adjusted when the load changes dynamically; then, the sum of the real-time inbound traffic and the real-time outbound traffic can be used as the load of the network slice, and the load of each network slice can be obtained in the above manner; finally, the sum of all loads can be used as the total load of the communication traffic in the private network, and the ratio of each load to the total load can be used as the load distribution value of the corresponding network slice, and the set of all load distribution values ​​can be used as the load distribution domain of the communication traffic in the private network. By calculating the load distribution domain, network slices with higher loads and network slices with lower loads can be identified, thereby optimizing the allocation of network resources, balancing the load of each network slice, and avoiding overload or waste of resources.

[0080] In this embodiment, the load balancing degree of the private network is determined by the communication isolation of the load distribution domain and each network slice, which can be implemented by the following steps:

[0081] For each network slice in the private network, determine the load deviation of the network slice in the load distribution domain;

[0082] Determine the load balancing value of the network slice according to the load deviation and the communication isolation of the network slice, and then obtain the load balancing value of each network slice in the private network;

[0083] The load balancing degree of the private network is determined by all load balancing values.

[0084] It should be noted that in this application, load balancing refers to the load balancing level of each network slice in the entire private network. The closer the value is to 1, the more uniform the load distribution of the entire system and the more efficient the resource utilization. The load balancing value refers to the balanced state of the network slice under the current network load. The closer the value is to 1, the better the load balancing of the slice. The lower the value, the more unbalanced the load. The load deviation indicates the difference between the load of a network slice and the overall average load. A negative deviation indicates that the load of the slice is lower, and a positive deviation indicates that the load is higher.

[0085] In specific implementation, first, for each network slice in the private network, the average of all loads in the load distribution domain is calculated as the load average, and the absolute value of the difference between the load of the network slice and the load average can be used as the load deviation of the network slice in the load distribution domain. The load deviation can be used to identify network slices with too high or too low load, which is convenient for adjusting resources for network slices and optimizing network performance; then, the result of multiplying the reciprocal of the sum of 1 and the load deviation by the communication isolation of the network slice can be used as the load balancing value of each network slice in the private network. The load balancing value is jointly determined by the load deviation and the communication isolation to ensure that slices with larger loads can tolerate larger fluctuations in a high isolation environment, while slices with small loads or poor isolation maintain better load balancing; finally, the standard deviation of all load balancing values ​​can be used as the load balancing degree of the private network. By calculating the overall load balancing degree, it can be determined whether the resource allocation of the current private network is reasonable, and slices that may need to be optimized can be identified to improve the overall performance of the network.

[0086] In step S4, when the load balancing degree is lower than the preset balancing threshold, the congested nodes are screened out in each network slice according to the communication traffic of each data node collected in real time, and then all the congested nodes in the private network are evenly distributed based on the traffic engineering algorithm.

[0087] It should be noted that the balancing threshold represents the load distribution standard of network resources under ideal conditions, and the balancing threshold can be preset based on historical experience and the load balancing requirements of the private network.

[0088] In this embodiment, the following steps may be used to select congested nodes in each network slice according to the communication traffic of each data node collected in real time:

[0089] For each network slice, the communication traffic of each data node in the network slice is collected in real time;

[0090] Filter out all abnormal data nodes in the network slice based on all communication traffic;

[0091] Determine the traffic utilization of each abnormal data node, and then screen out the congested nodes in the network slice based on all traffic utilizations, and then obtain the congested nodes in each network slice.

[0092] It should be noted that in the present application, a congested node is a data node with the highest traffic utilization in a specific time period, which usually indicates that the node is overloaded and may affect communication performance; traffic utilization refers to the ratio of the traffic actually used by a data node to its maximum carrying capacity, usually expressed as a percentage; an abnormal data node is a data node whose communication traffic significantly deviates from the normal range.

[0093] In the specific implementation, first, for each network slice, use a network traffic monitoring tool to perform real-time traffic monitoring on each data node, and collect the inbound and outbound traffic of each data node as the communication traffic of the corresponding data node; then, the data nodes in the network slice whose communication traffic is higher than the abnormal traffic threshold can be regarded as abnormal data nodes, and all abnormal data nodes can be obtained; finally, for each abnormal data node, the maximum processing traffic of the abnormal data node is obtained, and the ratio of the communication traffic of the abnormal data node to the maximum processing traffic can be used as the traffic utilization of the abnormal data node. The traffic utilization of each abnormal data node can be obtained in the above manner, and the abnormal data node with the highest traffic utilization can be used as the congested node of the network slice. The congested nodes in each network slice can be obtained in the above manner.

[0094] In this embodiment, all congested nodes in the private network are balanced based on the traffic engineering algorithm. The traffic engineering algorithm is used to redistribute traffic to the congested nodes. When it is implemented specifically, a suitable traffic engineering algorithm (such as the optimal path algorithm, the load balancing algorithm, etc.) is selected for traffic redistribution. The following algorithms can be used: the shortest path algorithm (such as the Dijkstra algorithm): calculate the path with the least traffic and transfer part of the traffic from the congested node to the non-congested node; considering the bandwidth, delay and other factors of the network, a weighted load balancing algorithm can also be used to balance the load between the congested nodes and the non-congested nodes, which is not limited here.

[0095] It can be seen that in this application, when the load balancing degree is lower than the preset balancing threshold, the congested nodes are screened out in each network slice according to the communication traffic of each data node collected in real time, and then all the congested nodes of the private network are evenly distributed based on the traffic engineering algorithm; first, the association between nodes is determined, and the key nodes and dependencies are identified, which can provide a basis for the reasonable division of network slices, ensure that the nodes in the slices are highly correlated, and improve the efficiency of the slices. At the same time, the clear node association relationship can reduce the interference between slices, optimize the overall operation efficiency of the network, and improve the networking of the private network; then, the load distribution domain is determined according to the actual communication flow, which is helpful to optimize traffic management. Clear traffic distribution can identify network slices with insufficient or excessive resources, provide a basis for load balancing decisions, reasonably allocate network resources, improve overall operation efficiency, and ensure that the private network maintains stable and efficient performance under high load conditions. Evaluation of load balancing can continuously monitor the health of the private network and identify potential problems. When the load balancing degree is lower than the preset value, the traffic adjustment measures are quickly triggered, which can ensure self-optimization under dynamic load conditions of the network, reduce congestion, and improve the reliability and efficiency of the private network.

[0096] To sum up, the technical solution adopted in this application can achieve balanced distribution of network slices in private network, thereby improving the load balancing of data nodes in private network.

[0097] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0098] A person skilled in the art may understand that all or part of the steps in the various methods of the above embodiments may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, the storage medium including a read-only memory (ROM), a random access memory (RAM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), a one-time programmable read-only memory (OTPROM), an electronically-erasable programmable read-only memory (EEPROM), a compact disc (CD-ROM) or other optical disc storage, magnetic disk storage, magnetic tape storage, or any other computer-readable medium that can be used to carry or store data.

[0099] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

Claims

1. A 5G private network networking method suitable for industrial Internet, characterized in that: The networking method comprises the following steps: Collect the node communication records of each data node in the private network from the industrial Internet, and then obtain the node communication data; Determine the node association relationship of each data node in the private network through the node communication data, divide all the data nodes into multiple network slices according to all the node association relationships, and then determine the communication isolation of each network slice in the private network, wherein the communication isolation indicates the degree of isolation of the network slice from other network slices in communication; Monitor the data communication information between each network slice in real time, and determine the load distribution domain of the communication traffic in the private network according to each data communication information, wherein the load distribution domain represents the load distribution of each network slice in the private network, and then determine the load balancing degree of the private network by the load distribution domain and the communication isolation of each network slice; When the load balancing degree is lower than the preset balancing threshold, congested nodes are screened out in each network slice according to the communication traffic of each data node collected in real time, and then all congested nodes of the private network are evenly distributed based on the traffic engineering algorithm; Wherein, determining the node association relationship of each data node in the private network through the node communication data specifically includes: For each data node, extract the node communication record of the data node from the node communication data; Determine the communication frequency between the data node and other data nodes in the private network through the node communication record; The node association relationship of the data nodes is determined according to all the communication frequencies, and then the node association relationship of each data node in the private network is obtained, wherein the set of all communication frequencies is used as the node association relationship of the data nodes.

2. A 5G private network networking method suitable for industrial Internet as claimed in claim 1, characterized in that: Determining the communication isolation of each network slice in the private network specifically includes: For each network slice, obtain the node association relationship of each data node in the network slice; Obtain node inline information and node outline information of the network slice in all node association relationships; Determine the node inlineness of the network slice according to the node inline information; Determine the node externality of the network slice according to the node externality information, wherein the node externality represents the communication status between the internal nodes of the network slice and the external nodes; the node internality represents the communication density between the internal nodes of the network slice; the node internality information represents the communication relationship between the nodes in the network slice; the node externality information represents the communication relationship between the nodes in the network slice and other network slice nodes; The communication isolation of the network slice in the private network is determined by the node internal connectivity and the node external connectivity, and then the communication isolation of each network slice in the private network is obtained.

3. A 5G private network networking method suitable for industrial Internet as claimed in claim 1, characterized in that: Determine the load distribution domain of communication traffic in the private network based on various data communication information, including: For each network slice, obtain the real-time inbound and outbound traffic of the network slice in the private network during communication from the data communication information of the network slice; Determine the load of the network slice according to the real-time inbound flow and the real-time outbound flow, and then obtain the load of each network slice; Determine the load distribution domain of communication traffic in the private network based on all load amounts.

4. A 5G private network networking method suitable for industrial Internet as claimed in claim 1, characterized in that: Determining the load balancing degree of the private network by the communication isolation of the load distribution domain and each network slice specifically includes: For each network slice in the private network, determine the load deviation of the network slice in the load distribution domain; Determine the load balancing value of the network slice according to the load deviation and the communication isolation of the network slice, and then obtain the load balancing value of each network slice in the private network; The load balancing degree of the private network is determined by all load balancing values.

5. A 5G private network networking method suitable for industrial Internet as claimed in claim 1, characterized in that: According to the real-time collected communication traffic of each data node, the congested nodes are screened out in each network slice, including: For each network slice, the communication traffic of each data node in the network slice is collected in real time; Filter out all abnormal data nodes in the network slice based on all communication traffic; Determine the traffic utilization of each abnormal data node, and then screen out the congested nodes in the network slice based on all traffic utilizations, and then obtain the congested nodes in each network slice.

6. A 5G private network networking method suitable for industrial Internet as claimed in claim 1, characterized in that: The private network is a 5G network based on network slicing.

7. A 5G private network networking method suitable for industrial Internet as claimed in claim 1, characterized in that: Balanced distribution of all congested nodes in the private network based on the traffic engineering algorithm is to use the traffic engineering algorithm to redistribute traffic to the congested nodes. When implementing it specifically, select a suitable traffic engineering algorithm.

8. A 5G private network networking method suitable for industrial Internet as claimed in claim 1, characterized in that: Divide all data nodes into multiple network slices according to the node association relationships, including: All data nodes are constructed into a node undirected graph based on all node association relationships; All data nodes in the node undirected graph are divided into multiple network slices based on the community discovery algorithm.

9. A 5G private network networking method suitable for industrial Internet as claimed in claim 1, characterized in that: The data communication information includes real-time inbound flow and real-time outbound flow.

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