Flow control method, apparatus, device, and storage medium

Abstract

This application provides a flow control method, apparatus, device, and storage medium, relating to the field of communication technology. The method includes: acquiring network performance indicators for each network element among multiple network elements corresponding to multiple specialties; determining a target flow control scenario based on the network performance indicators of each network element; determining a target flow control policy set corresponding to the target flow control scenario based on the target flow control scenario and the correspondence between preset flow control scenarios and flow control policy sets; determining multiple bottleneck network elements corresponding to multiple specialties based on the network performance indicators of the multiple network elements; determining at least one target bottleneck network element from the multiple bottleneck network elements based on the target flow control policy set; determining a flow control instruction based on the at least one target bottleneck network element; and sending the flow control instruction to the network management system of the specialty corresponding to each of the at least one target bottleneck network element. This method is applicable during flow control processes to ensure the normal operation of the core network.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a flow control method, apparatus, device and storage medium. Background Technology

[0002] The operator's network may include multiple networks / specialties such as evolved packet core (EPC), Internet protocol multimedia subsystem (IMS), 5th generation mobile communication technology core (5GC), and Internet of Things. These multiple networks / specialties undertake multiple functions such as air interface access, user data management, mobility management, session management, service triggering, and billing, and realize user voice, messaging, data and other value-added services.

[0003] However, in some cases, the number of signaling and service requests may surge, causing a strong impact on network elements in the operator's network and potentially causing some networks / specialties to malfunction. Summary of the Invention

[0004] This application provides a flow control method, apparatus, device, and storage medium, which can ensure the normal operation of various networks / specialties in the operator's network under abnormal or faulty process scenarios.

[0005] In a first aspect, this application provides a flow control method, apparatus, device, and storage medium. The method includes: a flow control system acquiring network performance indicators for each network element among multiple network elements corresponding to multiple specialties; the flow control system determining a target flow control scenario based on the network performance indicators of each network element; the flow control system determining a target flow control policy set corresponding to the target flow control scenario based on the target flow control scenario and the correspondence between preset flow control scenarios and flow control policy sets; the flow control policy set being used to indicate the priority of multiple specialties in executing flow control; the flow control system determining multiple bottleneck network elements corresponding to multiple specialties based on the network performance indicators of multiple network elements; each specialty corresponding to one bottleneck network element; the flow control system determining at least one target bottleneck network element from the multiple bottleneck network elements based on the target flow control policy set; the flow control system determining a flow control instruction based on the at least one target bottleneck network element; and the flow control system sending the flow control instruction to the network management system of the specialty corresponding to each of the at least one target bottleneck network element.

[0006] In one possible implementation, the flow control system determines multiple bottleneck network elements corresponding to multiple specialties based on the network performance indicators of multiple network elements. This includes: the flow control system acquiring the processing capacity of each network element among the multiple network elements; the processing capacity is the number of transactions per second (TPS); the flow control system acquiring the network performance indicators of each network element in the first period; the flow control system determining the estimated service impact data of each network element based on the network performance indicators of each network element in the first period; and the flow control system determining the bottleneck network elements corresponding to each specialty based on the processing capacity of each network element and the estimated service impact data, thus obtaining multiple bottleneck network elements.

[0007] Optionally, the flow control system determines the bottleneck network element for each specialty based on the processing capacity of each network element and the estimated service impact data. This includes: the flow control system determining the flow control activation threshold for each network element based on its processing capacity; and the flow control system designating the network element whose estimated service impact data is greater than the flow control activation threshold among one or more network elements corresponding to each specialty as the bottleneck network element.

[0008] Optionally, the method further includes: if there is a target specialty among multiple specialties where the estimated service impact data of the corresponding network element is less than the flow control activation threshold, then the flow control system will take the network element with the smallest difference between the flow control activation threshold and the estimated service impact data among one or more network elements corresponding to the target specialty as the bottleneck network element.

[0009] Optionally, the flow control system determines at least one target bottleneck network element from multiple bottleneck network elements according to the target flow control policy set, including: the flow control system sorts the multiple bottleneck network elements in descending order of priority indicated by the target flow control policy set to obtain a first sorting result; the flow control system determines the estimated service impact data of the (M+1)th bottleneck network element after flow control is performed on the Mth bottleneck network element in the first sorting result; M is a positive integer; if the estimated service impact data of the (M+1)th bottleneck network element is less than the flow control activation threshold, the flow control system takes the first M bottleneck network elements in the first sorting result as target bottleneck network elements.

[0010] Optionally, before the flow control system obtains the network performance indicators of each network element among multiple network elements corresponding to multiple specialties, the method further includes: the flow control system obtaining a flow control parameter standard library; the flow control parameter standard library includes the specialty name, network element type, flow control measures, flow control instructions, and flow control effect.

[0011] Optionally, the method further includes: the flow control system determining a first network element and a second network element based on a flow control parameter standard library; the first network element being the flow control object of the flow control measures; the second network element being the network element related to the first network element in the flow control effect; the flow control system determining the load change of the second network element after the flow control measures are implemented on the first network element; and the flow control system determining a flow control strategy set based on the load change of the second network element after the flow control measures are implemented on the first network element.

[0012] The flow control method provided in this application can obtain network performance indicators of network elements corresponding to each of multiple specialties, determine the target flow control scenario based on the network performance indicators, determine the target flow control policy set based on the target flow control scenario, determine the bottleneck network element in each specialty based on the network performance indicators, and determine the target bottleneck network element from the bottleneck network elements in each specialty for flow control based on the target flow control policy set, thereby mitigating the impact caused by a sudden increase in the number of signaling and service requests and ensuring the normal operation of the operator's network.

[0013] Secondly, this application provides a flow control device, which is applied to a flow control system connected to multiple professional network management systems; each professional system corresponds to one or more network elements; the device includes: an acquisition unit and a processing unit.

[0014] The acquisition unit is used to acquire the network performance indicators of each network element among multiple network elements corresponding to multiple specialties.

[0015] The processing unit is configured to: determine the target flow control scenario based on the network performance indicators of each network element; determine the target flow control policy set corresponding to the target flow control scenario based on the target flow control scenario and the correspondence between the preset flow control scenario and flow control policy set; determine multiple bottleneck network elements corresponding to multiple specialties based on the network performance indicators of multiple network elements; determine at least one target bottleneck network element from the multiple bottleneck network elements based on the target flow control policy set; determine flow control instructions based on the at least one target bottleneck network element; and send flow control instructions to the network management system of the specialty corresponding to each of the at least one target bottleneck network element.

[0016] Optionally, the processing unit is specifically used to obtain the processing capacity of each of the multiple network elements; obtain the network performance indicators of each network element in the first period; determine the estimated service impact data of each network element based on the network performance indicators of each network element in the first period; and determine the bottleneck network element corresponding to each specialty based on the processing capacity and the estimated service impact data of each network element, thereby obtaining multiple bottleneck network elements.

[0017] Optionally, the processing unit is specifically used to determine the flow control activation threshold for each network element based on the processing capacity of each network element; and to designate the network element whose estimated service impact data is greater than the flow control activation threshold among one or more network elements corresponding to each specialty as the bottleneck network element.

[0018] Optionally, the processing unit is specifically used to, if the estimated service impact data of each of the multiple network elements is less than the flow control activation threshold, select the network element with the smallest difference between the flow control activation threshold and the estimated service impact data among one or more network elements corresponding to each specialty as the bottleneck network element.

[0019] Optionally, the processing unit is specifically used to sort multiple bottleneck network elements in descending order of priority as indicated by the target flow control policy set to obtain a first sorting result; determine the estimated service impact data of the (M+1)th bottleneck network element after flow control is performed on the Mth bottleneck network element in the first sorting result; M is a positive integer; if the estimated service impact data of the (M+1)th bottleneck network element is less than the flow control activation threshold, the first M bottleneck network elements in the first sorting result are taken as target bottleneck network elements.

[0020] Optionally, the acquisition unit is also used to acquire a flow control parameter standard library; the flow control parameter standard library includes professional names, network element types, flow control measures, flow control instructions, and flow control effects.

[0021] Optionally, the processing unit is further configured to determine a first network element and a second network element based on a flow control parameter standard library; the first network element is the flow control object of the flow control measures; the second network element is the network element related to the first network element in the flow control effect; determine the load change of the second network element after the flow control measures are implemented on the first network element; and determine a flow control strategy set based on the load change of the second network element after the flow control measures are implemented on the first network element.

[0022] Thirdly, this application provides a computer program product that, when run on a computer, causes the computer to perform the steps of the related method described in the first aspect, so as to implement the method described in the first aspect.

[0023] Fourthly, this application provides an electronic device comprising: a processor and a memory; the memory storing processor-executable instructions; when the processor is configured to execute the instructions, causing the electronic device to perform the method described in the first aspect above.

[0024] Fifthly, this application provides a computer-readable storage medium comprising: computer software instructions; when the computer software instructions are executed in an electronic device, they cause the electronic device to perform the method described in the first aspect above.

[0025] The beneficial effects of the second to fifth aspects mentioned above can be referred to the first aspect, and will not be repeated here. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0027] Figure 1A schematic diagram illustrating an implementation scenario of the flow control method provided in this application embodiment;

[0028] Figure 2 A flowchart illustrating the flow control method provided in an embodiment of this application;

[0029] Figure 3 A schematic diagram illustrating the correspondence between flow control scenarios and flow control strategy sets provided in the embodiments of this application;

[0030] Figure 4 Another flowchart illustrating the flow control method provided in this application embodiment;

[0031] Figure 5 A schematic diagram illustrating key network performance metrics provided in the embodiments of this application;

[0032] Figure 6 Another flowchart illustrating the flow control method provided in this application embodiment;

[0033] Figure 7 A schematic diagram of the flow control parameter standard library provided in the embodiments of this application;

[0034] Figure 8 Another flowchart illustrating the flow control method provided in this application embodiment;

[0035] Figure 9 A schematic diagram of priority parameters provided in the embodiments of this application;

[0036] Figure 10 Another flowchart illustrating the flow control method provided in this application embodiment;

[0037] Figure 11 This is a schematic diagram of the composition of the flow control device provided in the embodiments of this application;

[0038] Figure 12 This is another schematic diagram of the flow control device provided in the embodiments of this application;

[0039] Figure 13 This is a schematic diagram illustrating the composition of an electronic device provided in an embodiment of this application. Detailed Implementation

[0040] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0041] It should be noted that in the embodiments of this application, the words "exemplarily" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplarily" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplarily" or "for example" is intended to present the relevant concepts in a specific manner.

[0042] To facilitate a clear description of the technical solutions of the embodiments of this application, the terms "first" and "second" are used in the embodiments of this application to distinguish the same or similar items with essentially the same function and effect. Those skilled in the art can understand that the terms "first" and "second" are not intended to limit the quantity or execution order.

[0043] The operator's network may include multiple networks / specialties such as evolved packet core (EPC), Internet protocol multimedia subsystem (IMS), 5th generation mobile communication technology core (5GC), and Internet of Things. These multiple networks / specialties undertake multiple functions such as air interface access, user data management, mobility management, session management, service triggering, and billing, and realize user voice, messaging, data and other value-added services.

[0044] However, in some cases, the number of signaling and service requests may surge, causing a strong impact on network elements in the operator's network and potentially causing some networks / specialties to malfunction.

[0045] Based on this, this application provides a flow control method, apparatus, device, and storage medium, which can collect network performance indicators of various professional network elements, select bottleneck network elements according to priority, and determine flow control instructions, thereby enabling the core network to continue to operate normally even after being subjected to severe impacts in some cases.

[0046] The following description is provided in conjunction with the accompanying drawings.

[0047] Figure 1 This is a schematic diagram illustrating an implementation scenario of the flow control method provided in this application. For example... Figure 1 As shown, the scenario may include: a flow control system 100 and multiple professional network management systems 200 connected to the flow control system. Figure 1The example 200 uses multiple professional network management systems, including EPC professional network management system, 5GC professional network management system, IMS professional network management system, home subscriber server (HSS) / unified data management (UDM) professional network management system, high signal transfer point (HSTP) professional network management system, and diameter routing agent (DRA) professional network management system.

[0048] The flow control system 100 can be deployed on electronic devices with computing and processing capabilities, such as computers or servers.

[0049] The server can be a single server or a server cluster consisting of multiple servers. In some embodiments, the server cluster can also be a distributed cluster. Optionally, the server can also be implemented on a cloud platform, such as a private cloud, public cloud, hybrid cloud, community cloud, distributed cloud, inter-cloud, and multi-cloud, or any combination thereof. This application does not impose any limitations on this.

[0050] The flow control system 100 can be used to control the flow of network elements in multiple disciplines. The specific process can be referred to in the following embodiments, and will not be repeated here.

[0051] The specific form of the network management system 200 can be referred to the flow control system 100, and will not be repeated here.

[0052] The network management system 200 is used to manage network elements in the corresponding specialties.

[0053] For example, each specialty can correspond to one or more network elements, and the network management system 200 can be used to manage one or more network elements corresponding to the specialty.

[0054] For example, taking the network management system of the EPC profession as an example, the EPC profession can correspond to network elements such as network node (mobility management entity, MME), service gateway (SGW), public data network gateway (PGW), and policy and charging rule function (PCRF). The network management system of the EPC profession can manage multiple network elements corresponding to the above EPC profession.

[0055] For example, taking the 5GC professional network management system as an example, the 5GC professional can correspond to the session management function (SMF) network element, the policy control function (PCF) network element, the application function (AF) network element, the network slice selection function (NSSF) network element, etc. The 5GC professional network management system can manage multiple network elements corresponding to the above 5GC professional.

[0056] The execution entity of the flow control method provided in this application embodiment is the flow control system 100. As described above, the flow control system 100 can be an electronic device with computing processing capabilities, such as a computer or server. Optionally, the flow control system 100 can also be an application (APP) with flow control functions installed in the aforementioned electronic device; or, the flow control system 100 can also be a processor (e.g., a central processing unit (CPU)) in the aforementioned electronic device; or, the flow control system 100 can also be a software system or platform deployed in the aforementioned electronic device; or, the flow control system 100 can also be a functional module in the aforementioned electronic device used to execute the flow control method, etc. This application embodiment does not impose any limitations on these aspects.

[0057] The flow control method provided in the embodiments of this application is described below with reference to the accompanying drawings.

[0058] Figure 2 This is a schematic flowchart of the flow control method provided in an embodiment of this application. Figure 2 As shown, the method includes S101 to S107.

[0059] S101. The flow control system obtains the network performance indicators of each network element in multiple network elements corresponding to multiple specialties.

[0060] The flow control system is the aforementioned flow control system 100. As mentioned above, each specialty can correspond to one or more network elements.

[0061] For example, the performance indicators of each network element in multiple network elements corresponding to multiple specialties can be shown in Table 1 below:

[0062] Table 1

[0063]

[0064] As shown in Table 1, this table can include professional items, network element items, and network performance indicator items. Professional items can include: Professional A and Professional B. Network element items can include: Network element a1, Network element a2, and Network element b1. Network performance indicator items can include: Indicator 1, Indicator 2, Indicator 3, Indicator 4, Indicator 5, Indicator 6, Indicator 7, Indicator 8, and Indicator 9. There are corresponding relationships between Professional A, Network element a1, Indicator 1, Indicator 2, and Indicator 3; between Professional A, Network element a2, Indicator 4, Indicator 5, and Indicator 6; and between Professional B, Network element b1, Indicator 7, Indicator 8, and Indicator 9.

[0065] S102. The flow control system determines the target flow control scenario based on the network performance indicators of each network element.

[0066] The target flow control scenarios can include: routine flow control (conservative routine flow control implemented to cope with unknown emergencies when all indicators are normal), high load flow control (flow control deployment is initiated for a certain type of network element or strongly related network elements when the memory or central processing unit (CPU) utilization rate is too high), and signaling storm flow control (emergency implementation in case of an abnormal situation).

[0067] Optionally, the flow control system may have a pre-defined correspondence between flow control scenarios and network performance levels. The flow control system can determine the current network performance level of the operator's network based on the network performance indicators of each network element; and determine the target flow control scenario based on the correspondence between flow control scenarios and network performance levels, as well as the current network performance level of the operator's network.

[0068] For example, the flow control system can use the current network performance level of the operator's network as an index, traverse the correspondence between flow control scenarios and network performance levels, and take the flow control scenario corresponding to the current network performance level of the operator's network as the target flow control scenario.

[0069] S103. The flow control system determines the target flow control strategy set corresponding to the target flow control scenario based on the target flow control scenario and the correspondence between the preset flow control scenario and the flow control strategy set.

[0070] The flow control policy set is used to indicate the priority of multiple professionals in implementing flow control.

[0071] For example, Figure 3 This diagram illustrates the correspondence between flow control scenarios and flow control strategy sets provided in embodiments of this application. Figure 3As shown, this correspondence can include flow control scenario items, flow control policy (set) items, and flow control measure items. The flow control scenario item can include two scenarios: 5G signaling storm and network element high load. The flow control policy (set) item can include two flow control policy sets:

[0072] (1) 5GC AMF flow control and MME flow control confirmation. If necessary, MME flow control should be carried out. The specific flow control measures for the 4G network should be determined by referring to the MME bottleneck, HSS bottleneck, HSTP bottleneck and DRA bottleneck. That is, the priority of multiple professionals to perform flow control as indicated by this flow control strategy set is: 5GC professional > HSS / UDM professional > EPC professional.

[0073] (2) 1. AMF: 5GC AMF flow control and MME flow control confirmation. MME flow control should be carried out when necessary. The specific flow control measures for the 4G network should be determined with reference to the MME bottleneck, HSS bottleneck and HSTP bottleneck. 2. UDM: Regional AMF flow control is wired, and UDM flow control is secondary. That is, the priority of multiple professionals to perform flow control as indicated by this flow control strategy set is: EPC professional > HSS / UDM professional.

[0074] S104. The flow control system determines multiple bottleneck network elements corresponding to multiple specialties based on the network performance indicators of multiple network elements.

[0075] Each specialty can correspond to a bottleneck network element.

[0076] The specific process of S104 can be referred to below. Figure 4 As described in S1041 to S1044, they will not be repeated here.

[0077] S105. The flow control system determines at least one target bottleneck network element from multiple bottleneck network elements based on the target flow control strategy set.

[0078] The specific process of S105 can be referred to below. Figure 6 As described in S1051 to S1053, they will not be repeated here.

[0079] S106. The flow control system determines the flow control command based on at least one target bottleneck network element.

[0080] Among them, the flow control command is used to instruct flow control to be applied to at least one target bottleneck network element.

[0081] S107. The flow control system sends flow control commands to the network management system corresponding to at least one target bottleneck network element.

[0082] For example, if the target bottleneck network elements are SGW network elements and PGW network elements, the flow control system can determine that the professional corresponding to SGW network elements and PGW network elements is EPC professional, and send flow control instructions to the network management system of EPC professional.

[0083] For example, if the target bottleneck network elements are PCF network elements and NSSF network elements, the flow control system can determine that the professional corresponding to PCF network elements and NSSF network elements is 5GC professional, and send flow control instructions to the network management system of 5GC professional.

[0084] In the flow control method provided in this application embodiment, the flow control system can determine the bottleneck network element by obtaining the network performance indicators of the network element, and determine the target bottleneck network element according to the flow control policy set. The obtained target bottleneck network element determines the flow control instruction, and sends the determined flow control instruction to the corresponding professional network management system, thereby achieving the normal operation of the core network when the number of signaling and service requests suddenly increases and causes a strong impact on each network element.

[0085] The following is a description of S104.

[0086] In some possible embodiments, Figure 4 This is another schematic flowchart illustrating the flow control method provided in an embodiment of this application. Figure 4 As shown, the above S104 may specifically include S1041 to S1044.

[0087] S1041, The flow control system obtains the processing capacity of each of the multiple network elements.

[0088] Processing capacity is measured in transactions per second (TPS). TPS can be provided by various manufacturers based on a comprehensive evaluation of their software and hardware capabilities. TPS can be updated as needed to accommodate hardware expansion or software optimization.

[0089] S1042. The flow control system obtains the network performance indicators of each network element in the first cycle.

[0090] For example, the network performance indicators collected by the flow control system in the first cycle include sorting out key indicator templates. The flow control system can obtain real-time key indicators of each profession from the network management systems of each profession and put them into the database. Figure 5 A schematic diagram illustrating key network performance metrics provided in the embodiments of this application, such as... Figure 5As shown, the key network performance indicators collected by the flow control system include start time, period, network element name, number of real-time SMF 5G PDU sessions, number of currently online sessions created by PCW-C via GTP S5 / S8 / S2a / S2b, number of currently online 5G NSA user sessions created by PGW-C via GTP S5 / S8, number of real-time online sessions in SGW-C form, number of real-time online 5G NSA sessions in SGW-C form, number of real-time online sessions in SPGW-C combined form, and number of real-time online 5G NSA sessions in SPGW-C combined form.

[0091] S1043. The flow control system determines the estimated service impact data for each network element based on the network performance indicators of each network element in the first cycle.

[0092] The estimated impact data for each network element refers to the average number of transactions per second (to be processed) for that network element during the second period following the first period. The second period may be the same as or different from the first period. This application does not impose any restrictions on this.

[0093] Optionally, the flow control system can use a traffic model, a user online model, or an impact model to determine the estimated service impact data for each network element based on the network performance indicators of each network element in the first cycle. The traffic model, user online model, and impact model can be found in relevant technical documents and will not be elaborated upon here.

[0094] S1044. The flow control system determines the bottleneck network element corresponding to each specialty based on the processing capacity of each network element and the estimated service impact data, thus obtaining multiple bottleneck network elements.

[0095] Among them, the bottleneck network element refers to the network element whose processing capacity is lower than the estimated business impact data or whose processing capacity is the smallest difference from the estimated business impact data.

[0096] Optionally, S1044 may specifically include the following steps:

[0097] Step 1: The flow control system determines the flow control activation threshold for each network element based on its processing capacity.

[0098] For example, the flow control system obtains the processing capacity (number of transactions per second) of each network element in multiple historical periods by collecting historical network performance indicators, and uses the maximum value of the processing capacity in multiple historical periods as the flow control start threshold of the corresponding network element, or multiplies the maximum value by a calibration coefficient to obtain the flow control start threshold of the corresponding network element.

[0099] The calibration coefficient can be preset in the electronic device by the administrator. For example, the calibration coefficient can be 80% or 85%. This application does not limit the specific value of the calibration coefficient.

[0100] Step 2: The flow control system identifies the network elements whose estimated service impact data exceeds the flow control activation threshold from one or more network elements corresponding to each specialty as bottleneck network elements.

[0101] In some possible embodiments, if there are target specialties among multiple specialties where the estimated service impact data of the corresponding network elements is (all) less than the flow control activation threshold, the flow control system can use the network element with the smallest difference between the flow control activation threshold and the estimated service impact data among one or more network elements corresponding to the target specialty as the bottleneck network element.

[0102] For example, taking profession A in Table 1 above as an example, assuming that the flow control activation thresholds for network elements a1, a2, and a3 corresponding to profession A are T1, T2, and T3 respectively, and the estimated impact data for network elements a1, a2, and a3 are Y1, Y2, and Y3 respectively, if the estimated service impact data for the corresponding network elements in profession A are all less than the corresponding flow control activation thresholds, that is, Y1 is less than T1, Y2 is less than T2, and Y3 is less than T3, then the flow control system can use the network element with the smallest value among T1-Y1, T2-Y2, and T3-Y3 as the bottleneck network element. Assuming that T1-Y1 is the smallest, the flow control system can use network element a1 as the bottleneck network element for profession A.

[0103] The following is a description of S105.

[0104] In some possible embodiments, Figure 6 This is another schematic flowchart illustrating the flow control method provided in an embodiment of this application. For example... Figure 6 As shown, the above S105 may specifically include S1051 to S1053.

[0105] S1051. The flow control system sorts multiple bottleneck network elements in descending order of priority as indicated by the target flow control policy set, and obtains the first sorting result.

[0106] S1052. After the flow control system determines the estimated service impact data of the M+1th bottleneck network element after performing flow control on the Mth bottleneck network element in the first sorting result.

[0107] Where M is a positive integer.

[0108] S1053. If the estimated service impact data of the (M+1)th bottleneck network element is less than the flow control activation threshold, the flow control system will take the first M bottleneck network elements in the first ranking result as the target bottleneck network elements.

[0109] In some possible embodiments, before the flow control system obtains the network performance indicators of each network element among multiple network elements corresponding to multiple specialties, the flow control system may also obtain a flow control parameter standard library. The flow control parameter standard library includes specialty names, network element types, flow control measures, flow control commands, and flow control effects.

[0110] For example, please refer to Figure 7 , Figure 7 This is a schematic diagram of the flow control parameter standard library provided in the embodiments of this application. Figure 7 Taking EPC and 5GC as examples, some flow control parameters are illustrated.

[0111] In some possible embodiments, Figure 8 This is another schematic flowchart illustrating the flow control method provided in an embodiment of this application. For example... Figure 8 As shown, before S101 above, the method may also include S201 to S203.

[0112] S201. The flow control system determines the first network element and the second network element based on the flow control parameter standard library.

[0113] Among them, the first network element is the target of flow control measures; the second network element is the network element related to the first network element in the flow control effect.

[0114] For example, taking the EPC profession as an example, the above Figure 7 One of the flow control measures corresponding to the EPC specialty in the flow control parameter standard library is flow control based on the International Mobile Subscriber Identity (IMSI) segment. The corresponding flow control object is the MME network element. The flow control effect is related to the MME network element, the HSTP network element, the HSS network element, and the DRA network element. Therefore, the MME network element is the first network element, and the HSTP network element is the second network element.

[0115] S202. After the flow control system determines that flow control measures have been implemented on the first network element, the load change of the second network element is as follows.

[0116] S203. The flow control system determines the flow control strategy set based on the load change of the second network element after the flow control measures are implemented on the first network element.

[0117] For example, a flow control system can determine the priority indicated by a set of flow control policies based on the magnitude of a priority parameter. For the target network element implementing flow control, the priority parameter can be determined by the load changes of other reference network elements after flow control is implemented. For example, the priority parameter could be 1, 2, -1, -2, etc.

[0118] For example, Figure 9This is a schematic diagram of priority parameters provided for embodiments of this application. For example... Figure 9 As shown, with the number 1 as the origin, if the target network element implements flow control and has a positive impact on the reference network element (i.e., load decrease), then for the reference network element, this priority parameter is greater than 1 and points to N, where N is a positive integer greater than 1; if the target network element implements flow control and has a negative impact on the reference network element (i.e. load increase), then for the reference network element, this priority parameter is less than 1 and points to -N.

[0119] For example, taking the flow control correlation between AMF network elements in the 5GC specialization and network elements in the EPC and HSTP specializations as an example, Table 2 shows the priority parameters corresponding to the network elements in the EPC and HSTP specializations respectively.

[0120] Table 2

[0121] AMF AMF inter-sr flow control AMF 1 AMF AMF inter-sr flow control SMF 2 AMF AMF inter-sr flow control MME -1 AMF AMF inter-sr flow control HSTP -2

[0122] As shown in Table 2, after the AMF network element implements flow control, the load of the SMF network element decreases, and the priority parameter can be recorded as 2; the load of the MME network element increases, and the priority parameter can be recorded as -1; the load of the HSTP network element increases significantly, and the priority parameter can be recorded as -2.

[0123] Based on the understanding of the above embodiments, Figure 10 This is another schematic flowchart illustrating the flow control method provided in an embodiment of this application. For example... Figure 10 As shown, the flow control system can first determine the flow control scenario, then match the flow control strategy (set) according to different flow control scenarios, associate multiple professional bottleneck network elements, determine the flow control command (for the target bottleneck network element), and send it to the (corresponding) professional network management system. The specific process can be referred to the above embodiments, and will not be repeated here.

[0124] The foregoing primarily describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the aforementioned functions, it includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art may use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0125] In an exemplary embodiment, Figure 11 This is a schematic diagram of the composition of the flow control device provided in the embodiments of this application. This flow control device can be applied to the aforementioned flow control system, such as... Figure 11 As shown, the flow control device may include a flow control parameter analysis and processing module, a network bottleneck assessment module, and a flow control deployment and implementation module.

[0126] The flow control parameter analysis and processing module can specifically include the following functions: surveying and storing flow control parameters by specialty; analyzing the correlation between flow control parameters across specialties; and implementing inter-specialty collaborative flow control scenarios.

[0127] The network bottleneck assessment module can specifically include the following functions: performance data collection and storage by specialty; sudden traffic volume analysis by specialty; impact prediction by specialty; resource threshold survey by specialty; and resource threshold storage by specialty.

[0128] The flow control deployment and implementation module can specifically include the following functions: cross-disciplinary flow control deployment.

[0129] In exemplary embodiments, the above modules may also be integrated or divided into different functional units. Figure 12 This is another schematic diagram of the flow control device provided in the embodiments of this application, such as... Figure 12 As shown, the device may include an acquisition unit 1201 and a processing unit 1202.

[0130] The acquisition unit 1201 is used to acquire the network performance indicators of each network element among multiple network elements corresponding to multiple specialties.

[0131] The processing unit 1202 is configured to: determine a target flow control scenario based on the network performance indicators of each network element; determine a target flow control policy set corresponding to the target flow control scenario based on the target flow control scenario and the correspondence between the preset flow control scenario and flow control policy set; determine multiple bottleneck network elements corresponding to multiple specialties based on the network performance indicators of multiple network elements; determine at least one target bottleneck network element from the multiple bottleneck network elements based on the target flow control policy set; determine a flow control instruction based on the at least one target bottleneck network element; and send the flow control instruction to the network management system of the specialty corresponding to each of the at least one target bottleneck network element.

[0132] In some possible embodiments, the processing unit 1202 is specifically used to obtain the processing capability of each of the multiple network elements; obtain the network performance indicators of each network element in the first period; determine the estimated service impact data of each network element based on the network performance indicators of each network element in the first period; and determine the bottleneck network element corresponding to each specialty based on the processing capability of each network element and the estimated service impact data, thereby obtaining multiple bottleneck network elements.

[0133] In other possible embodiments, the processing unit 1202 is specifically used to determine the flow control activation threshold of each network element based on the processing capacity of each network element; and to designate the network element whose estimated service impact data is greater than the flow control activation threshold among one or more network elements corresponding to each specialty as the bottleneck network element.

[0134] Optionally, the processing unit 1202 is specifically used to select the network element with the smallest difference between the flow control activation threshold and the estimated service impact data among one or more network elements corresponding to each profession if the estimated service impact data of each network element is less than the flow control activation threshold.

[0135] In some other possible embodiments, the processing unit 1202 is specifically used to sort multiple bottleneck network elements in descending order of priority indicated by the target flow control policy set to obtain a first sorting result; determine the estimated service impact data of the (M+1)th bottleneck network element after flow control is performed on the Mth bottleneck network element in the first sorting result; M is a positive integer; if the estimated service impact data of the (M+1)th bottleneck network element is less than the flow control activation threshold, the first M bottleneck network elements in the first sorting result are taken as target bottleneck network elements.

[0136] In some other possible embodiments, the acquisition unit 1201 is also used to acquire a flow control parameter standard library; the flow control parameter standard library includes professional names, network element types, flow control measures, flow control instructions, and flow control effects.

[0137] In some other possible embodiments, the processing unit 1202 is further configured to determine a first network element and a second network element based on a flow control parameter standard library; the first network element is the flow control object of the flow control measures; the second network element is the network element related to the first network element in the flow control effect; determine the load change of the second network element after the flow control measures are implemented on the first network element; and determine a flow control strategy set based on the load change of the second network element after the flow control measures are implemented on the first network element.

[0138] In an exemplary embodiment, this application also provides an electronic device that can be applied to the above-described flow control system. Figure 13 This is a schematic diagram illustrating the composition of an electronic device provided in an embodiment of this application. For example... Figure 13 As shown, the electronic device includes a processor 1301 and a memory 1302; the memory 1302 stores instructions executable by the processor 1301; when the processor 1301 is configured to execute instructions, the electronic device performs the method described in the foregoing embodiments.

[0139] In an exemplary embodiment, this application also provides a computer-readable storage medium storing computer program instructions thereon; when the computer program instructions are executed by an electronic device, the electronic device causes the electronic device to perform the method described in the foregoing embodiments. The computer-readable storage medium may be a non-transitory computer-readable storage medium, such as a ROM, random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device.

[0140] In an exemplary embodiment, this application also provides a computer program product containing computer execution instructions, which, when run on an electronic device, causes the electronic device to perform any of the methods provided in the above embodiments.

[0141] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any combination thereof. When implemented using software programs, implementation can be, in whole or in part, in the form of a computer program product. This computer program product includes one or more computer-executable instructions. When these computer-executable instructions are loaded and executed on a computer, all or part of the flow or function according to the embodiments of this application is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer-executable instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer-executable instructions can be transmitted from one website, computer, server, or data center to another via wired (e.g., coaxial cable, fiber optic, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means.

[0142] Although this application has been described herein in conjunction with various embodiments, those skilled in the art, by reviewing the accompanying drawings, disclosure, and appended claims, will understand and implement other variations of the disclosed embodiments in carrying out the claimed application. In the claims, the word "comprising" does not exclude other components or steps, and "a" or "an" does not exclude multiple components. A single processor or other unit can implement several functions listed in the claims. While different dependent claims may recite certain measures, this does not mean that these measures cannot be combined to produce good results.

[0143] Although this application has been described in conjunction with specific features and embodiments, it is obvious that various modifications and combinations can be made thereto without departing from the spirit and scope of this application. Accordingly, this specification and drawings are merely exemplary illustrations of this application as defined by the appended claims, and are considered to cover any and all modifications, variations, combinations, or equivalents within the scope of this application. Clearly, those skilled in the art can make various alterations and modifications to this application without departing from the spirit and scope of this application. Thus, if such modifications and modifications of this application fall within the scope of the claims of this application and their equivalents, this application is also intended to include such modifications and modifications.

[0144] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A flow control method, characterized in that, The method is applied to a flow control system, which is connected to multiple specialized network management systems. Each specialty corresponds to one or more network elements; the method includes: The flow control system acquires the network performance indicators of each network element among the multiple network elements corresponding to the multiple specialties; The flow control system determines the target flow control scenario based on the network performance indicators of each network element; The flow control system determines the target flow control strategy set corresponding to the target flow control scenario based on the target flow control scenario and the correspondence between the preset flow control scenario and the flow control strategy set; the flow control strategy set is used to indicate the priority of the multiple professionals performing flow control. The flow control system determines multiple bottleneck network elements corresponding to the multiple specialties based on the network performance indicators of the multiple network elements; each specialty corresponds to one bottleneck network element. The flow control system determines at least one target bottleneck network element from the plurality of bottleneck network elements according to the target flow control policy set; The flow control system determines flow control instructions based on the at least one target bottleneck network element; The flow control system sends the flow control command to the professional network management system corresponding to each of the at least one target bottleneck network element.

2. The method according to claim 1, characterized in that, The flow control system determines multiple bottleneck network elements corresponding to the multiple specialties based on the network performance indicators of the multiple network elements, including: The flow control system obtains the processing capacity of each of the multiple network elements; the processing capacity is the number of transactions per second (TPS). The flow control system acquires the network performance indicators of each network element within the first cycle. The flow control system determines the estimated service impact data for each network element based on the network performance indicators of each network element in the first period. The flow control system determines the bottleneck network element corresponding to each specialty based on the processing capacity of each network element and the estimated service impact data, thus obtaining the multiple bottleneck network elements.

3. The method according to claim 2, characterized in that, The flow control system determines the bottleneck network element corresponding to each specialty based on the processing capacity of each network element and the estimated service impact data, including: The flow control system determines the flow control activation threshold for each network element based on the processing capacity of each network element. The flow control system designates one or more network elements corresponding to each specialty as bottleneck network elements whose estimated service impact data exceeds the flow control activation threshold.

4. The method according to claim 3, characterized in that, The method further includes: If there is a target specialty among the multiple specialties whose estimated service impact data for the corresponding network element is less than the flow control activation threshold, then the flow control system will select the network element with the smallest difference between the flow control activation threshold and the estimated service impact data among one or more network elements corresponding to the target specialty as the bottleneck network element.

5. The method according to any one of claims 1-4, characterized in that, The flow control system determines at least one target bottleneck network element from the plurality of bottleneck network elements according to the target flow control policy set, including: The flow control system sorts the multiple bottleneck network elements in descending order of priority as indicated by the target flow control policy set, and obtains a first sorting result; The flow control system determines the estimated service impact data of the (M+1)th bottleneck network element after performing flow control on the Mth bottleneck network element in the first sorting result; M is a positive integer. If the estimated service impact data of the (M+1)th bottleneck network element is less than the flow control activation threshold, the flow control system will take the first M bottleneck network elements in the first sorting result as the target bottleneck network elements.

6. The method according to claim 1, characterized in that, Before the flow control system acquires the network performance indicators of each network element among the multiple network elements corresponding to the multiple specialties, the method further includes: The flow control system acquires a standard library of flow control parameters; the standard library of flow control parameters includes professional names, network element types, flow control measures, flow control commands, and flow control effects.

7. The method according to claim 6, characterized in that, The method further includes: The flow control system determines a first network element and a second network element based on the flow control parameter standard library; the first network element is the flow control object of the flow control measures; the second network element is the network element related to the first network element in the flow control effect. The flow control system determines the load change of the second network element after the flow control measures are implemented on the first network element; The flow control system determines the flow control strategy set based on the load change of the second network element after the flow control measures are implemented on the first network element.

8. A flow control device, characterized in that, The device is applied to a flow control system, which is connected to multiple professional network management systems; each professional system corresponds to one or more network elements; the device includes: an acquisition unit and a processing unit; The acquisition unit is used to acquire the network performance indicators of each network element among the multiple network elements corresponding to the multiple specialties; The processing unit is configured to: determine a target flow control scenario based on the network performance indicators of each network element; determine a target flow control policy set corresponding to the target flow control scenario based on the target flow control scenario and the correspondence between the preset flow control scenario and flow control policy set; the flow control policy set is used to indicate the priority of the multiple specialties in performing flow control; determine multiple bottleneck network elements corresponding to the multiple specialties based on the network performance indicators of the multiple network elements; each specialty corresponds to one bottleneck network element; determine at least one target bottleneck network element from the multiple bottleneck network elements based on the target flow control policy set; determine a flow control instruction based on the at least one target bottleneck network element; and send the flow control instruction to the network management system of the specialty corresponding to each of the at least one target bottleneck network element.

9. An electronic device, characterized in that, The electronic device includes: a processor and a memory; The memory stores instructions that the processor can execute; When the processor is configured to execute the instructions, the electronic device performs the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes: computer software instructions; When the computer software instructions are executed in an electronic device, the electronic device causes the electronic device to perform the method as described in any one of claims 1-7.

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