Multi-user data traffic management method, electronic equipment and storage medium

Abstract

The invention provides a multi-user data traffic management method, electronic equipment and a storage medium, and relates to the technical field of communication. The method comprises the steps that service content data and service feature data of a plurality of terminals are acquired, the service feature data comprise service types, and the service content data and the service feature data are data extracted from data code streams acquired from a data acquisition control function entity; screening out at least two terminals with the same service type from the plurality of terminals, analyzing the service content data of the at least two terminals, and determining the service relevance of the at least two terminals; and managing the data traffic of the at least two terminals by adopting a preset management strategy matched with the service relevance according to the service relevance of the at least two terminals. The statistical accuracy of the data traffic of each terminal is improved, so that each terminal determines the use cost and the like based on the correct quantity traffic statistical information, and the use experience of a user is improved.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a method for managing multi-user data traffic, an electronic device, and a storage medium. Background Art

[0002] With the increasing popularity of mobile broadband networks and the improvement of mobile terminal hardware performance, mobile terminals can use a variety of different types of Internet applications, which can enrich the user experience based on mobile terminals. At the same time, each mobile operator needs to customize different control strategies for each application service according to the different types of user usage requirements, so as to allocate limited mobile network resources to application services with higher bandwidth requirements, improve user experience without reducing communication costs.

[0003] However, network-side devices can currently only identify and control the service message traffic of a single user, and are unable to identify the associated service message traffic between multiple users, resulting in errors when counting the data traffic of each user, reducing the user experience. Summary of the invention

[0004] The present application provides a method for managing multi-user data traffic, an electronic device, and a storage medium.

[0005] An embodiment of the present application provides a method for managing multi-user data traffic, the method comprising: acquiring service content data and service feature data of multiple terminals, wherein the service feature data comprises a service type, and the service content data and the service feature data are data extracted from a data code stream acquired by a data acquisition control function entity; screening out at least two terminals with the same service type from the multiple terminals, and analyzing the service content data of the at least two terminals to determine the service relevance of the at least two terminals; and managing the data traffic of the at least two terminals using a preset management strategy matching the service relevance based on the service relevance of the at least two terminals.

[0006] An embodiment of the present application provides a method for managing multi-user data traffic, the method comprising: acquiring service content data and service feature data of a target terminal, the service feature data including a service type; sending the service content data and service feature data of the target terminal to a network data analysis function entity; and in response to a preset management policy fed back by the network data analysis function entity, managing the data traffic of the target terminal according to the preset management policy, wherein the preset management policy is a policy that matches the service association of at least two terminals, and the at least two terminals include the target terminal.

[0007] An embodiment of the present application provides an electronic device, comprising: one or more processors; a memory on which one or more programs are stored, and when the one or more programs are executed by the one or more processors, the one or more processors implement any one of the multi-user data traffic management methods in the embodiment of the present application.

[0008] An embodiment of the present application provides a readable storage medium, which stores a computer program. When the computer program is executed by a processor, any method for managing multi-user data traffic in the embodiment of the present application is implemented.

[0009] According to the multi-user data traffic management method, electronic device and storage medium of the embodiment of the present application, by acquiring service content data and service feature data of multiple terminals, wherein the service feature data includes service type, the service content data and service feature data are data extracted from the data code stream acquired by the data acquisition control function entity, and the service content data and service feature data in the service processing process performed by each terminal can be clearly identified, so as to facilitate screening of multiple terminals to screen out at least two terminals with the same service type; then, the service content data of the at least two terminals are analyzed to determine the service relevance of the at least two terminals, accurately identify whether the services performed by the at least two terminals are related, and determine whether the at least two terminals are performing the same service processing, so as to obtain the service status of the terminals; according to the service relevance of the at least two terminals, a preset management strategy matching the service relevance is adopted to manage the data traffic of the at least two terminals, so as to improve the statistical accuracy of the data traffic of each terminal, so that each terminal can determine its usage fee based on the correct quantity traffic statistical information, etc., thereby improving the user experience.

[0010] With regard to the above embodiments and other aspects of the present application and their implementation, further description is provided in the accompanying drawings, detailed description and claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 A schematic diagram of managing user data traffic in the relevant technical solution provided in an embodiment of the present application is shown.

[0012] Figure 2 A flow chart of a method for managing multi-user data traffic provided in an embodiment of the present application is shown.

[0013] Figure 3 A flow chart of a method for managing multi-user data traffic provided in an embodiment of the present application is shown.

[0014] Figure 4 A block diagram showing the composition of a network data analysis functional entity provided in an embodiment of the present application.

[0015] Figure 5 A block diagram showing the composition of a data acquisition control functional entity provided in an embodiment of the present application is shown.

[0016] Figure 6 A block diagram showing the composition of a multi-user data traffic management system provided by an embodiment of the present application.

[0017] Figure 7 A block diagram showing the composition of a multi-user data traffic management system provided by an embodiment of the present application.

[0018] Figure 8 A flowchart illustrating a working method of a multi-user data traffic management system provided by an embodiment of the present application is shown.

[0019] Fig. 9 A structural diagram showing an exemplary hardware architecture of a computing device capable of implementing the method and apparatus for managing multi-user data traffic according to an embodiment of the present invention. DETAILED DESCRIPTION

[0020] In order to make the purpose, technical solution and advantages of the present application more clear, the embodiments of the present application will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments and features in the embodiments of the present application can be combined with each other arbitrarily without conflict.

[0021] In order to meet the operators' refined operational needs based on content billing, bandwidth control, security protection, behavior analysis, statistical reporting, etc., the relevant technical solutions provide a management method for user data traffic. Figure 1 FIG. 1 is a schematic diagram showing the management of user data traffic in the related technical solution provided in the embodiment of the present application. Figure 1 As shown, the session management function (SMF) entity 1100 sends the management rules to the user plane function (UPF) entity 1200 so that the user plane function entity 1200 can manage the data stream sent by the terminal 1300 and forward the corresponding data stream to the communication network 1400, so that the terminal 1300 can interact with other terminals for services.

[0022] The user plane function entity 1200 includes a message parsing module 1210, a rule matching module 1220, a rule base 1230 and a policy execution module 1240. The message parsing module 1210 includes a serial peripheral interface (Serial Peripheral Interface, SPI) submodule 1211, a deep packet inspection (Deep Packet Inspection, DPI) submodule 1212 and a host port interface detection (Host Port Interface, HPI) submodule 1213; the policy execution module 1240 includes a charging policy submodule 1241, a quality of service policy submodule 1242 and a forwarding policy submodule 1243.

[0023] SPI submodule 1211 is used to process the data stream (such as business data message, etc.) sent by terminal 1300 at the transport layer and network layer using SPI technology to obtain the "five-tuple (i.e., source address, source port, destination address, destination port and protocol type)" information in the data message.

[0024] The DPI submodule 1212 is used to parse and match the data stream sent by the terminal 1300 at the application layer using the DPI technology to obtain characteristic information of the application layer data (for example, network protocol information, operation code information, etc.).

[0025] The HPI submodule 1213 is used to analyze and match specific features in the data stream sent by the terminal 1300 based on a complex communication protocol using the HPI technology, but a specific protocol library needs to be updated regularly.

[0026] However, the data flow processing methods of the above-mentioned multiple sub-modules in the UPF entity 1200 can only enable the UPF entity 1200 to identify and control the business message traffic of a single user, but cannot identify the related business message traffic between multiple users, which causes errors when counting the data traffic of each user, thereby reducing the user experience.

[0027] For example, when terminal A and terminal B are using application C for a video call service, the UPF entity 1200 can only identify that the traffic used by terminal A is used to open application C and perform service processing based on application C; and the traffic used by terminal B is used to open application C and perform service processing based on application C. However, the UPF entity 1200 cannot learn that terminals A and B perform associated service processing (i.e., perform video call service) through application C, and cannot associate the data traffic of terminals A and B, resulting in errors in the statistics of the data traffic of terminal A and the statistics of the data traffic of terminal B; further, the UPF entity 1200 cannot provide corresponding communication quality services for terminals A and B during the process of performing video call service through application C, which reduces the user experience of interactive services between multiple terminals.

[0028] The present application provides a multi-user data traffic management method, electronic device and storage medium to solve the above problems.

[0029] Figure 2 The flowchart of a method for managing multi-user data traffic provided by an embodiment of the present application is shown. The method for managing multi-user data traffic can be applied to a network data analysis function (NWDAF) entity. Figure 2 As shown, the method for managing multi-user data traffic in the embodiment of the present application includes but is not limited to the following steps.

[0030] Step S201: Acquire service content data and service feature data of multiple terminals.

[0031] The service characteristic data includes the service type, service content data and service characteristic data, which are data extracted from the data code stream obtained by the data acquisition control function entity.

[0032] Step S202: at least two terminals with the same service type are selected from multiple terminals, and service content data of the at least two terminals are analyzed to determine service relevance of the at least two terminals.

[0033] Step S203: managing data traffic of the at least two terminals using a preset management strategy matching the service relevance according to the service relevance of the at least two terminals.

[0034] In this embodiment, by acquiring service content data and service feature data of multiple terminals, wherein the service feature data includes service type, and the service content data and service feature data are data extracted from the data code stream acquired by the data acquisition control function entity, the service content data and service feature data in the service processing process performed by each terminal can be clearly identified, so as to facilitate screening of multiple terminals to screen out at least two terminals with the same service type; then, the service content data of the at least two terminals are analyzed to determine the service relevance of the at least two terminals, accurately identify whether the services performed by the at least two terminals are related, and determine whether the at least two terminals are performing the same service processing, thereby knowing the service status of the terminals; based on the service relevance of the at least two terminals, a preset management strategy matching the service relevance is adopted to manage the data traffic of the at least two terminals, thereby improving the statistical accuracy of the data traffic of each terminal, so that each terminal can determine its usage fee based on the correct quantity traffic statistical information, etc., thereby improving the user experience.

[0035] In some exemplary embodiments, the step S203 of managing the data traffic of the at least two terminals according to the service relevance of the at least two terminals by using a preset management policy matching the service relevance may be implemented in the following manner:

[0036] When it is determined that the services of at least two terminals are mutually related, a multi-user management strategy is used to uniformly manage the data traffic of the at least two terminals; when it is determined that the services of at least two terminals are unrelated, a single-user management strategy is used to manage the data traffic of each terminal respectively.

[0037] The data traffic of at least two terminals is uniformly managed by adopting a multi-user management strategy, so that when counting the data traffic of at least two terminals, the use of the data traffic can be optimized based on the relevant associated information of the services of the at least two terminals.

[0038] For example, for at least two terminals, based on the data traffic used in service A, only the usage of one terminal is counted, while other terminals share the data traffic used in service A, and the data traffic of other terminals is reduced at a preset ratio. In this way, when at least two terminals are processing service A at the same time, the data traffic therein can be shared, thereby improving the user experience.

[0039] Different strategies (such as multi-user management strategy or single-user management strategy) are used to manage the data flow of the terminal, so as to accurately count the data flow of each terminal and improve the statistical accuracy of the data flow.

[0040] In some exemplary embodiments, the multi-user management strategy includes a multi-user billing statistics strategy and a multi-user communication service quality assurance strategy. The multi-user management strategy is used to uniformly manage the data traffic of at least two terminals, including:

[0041] According to the multi-user billing statistics strategy, the data traffic used by at least two terminals in the process of performing services of the same service type is counted, and the corresponding fees are determined based on the statistically obtained data traffic; according to the multi-user communication service quality assurance strategy, communication quality assurance service is provided for at least two terminals.

[0042] Among them, the multi-user billing statistics strategy is used to determine the communication charges corresponding to at least two terminals based on the data traffic used by at least two terminals in the process of performing services of the same service type obtained by statistics, so that the data traffic of at least two terminals in the process of performing the same service processing of the same service type can be shared, and the communication charges of each terminal are determined based on the shared data traffic, which can reduce the statistical errors of data traffic of each terminal.

[0043] The multi-user communication service quality assurance strategy is to provide the corresponding service quality (QoS) assurance work for at least two terminals that are processing the same service of the same service type. Among them, QoS can include best-effort service (Best-Effort service), integrated service (Int-Serv), and differentiated service (Differentiated service, Diff-Serv) and other different services.

[0044] The use of a multi-user communication service quality assurance strategy can provide better services for communication services between at least two terminals. It is an effective security mechanism that can solve problems such as network delay and congestion and improve the communication efficiency between at least two terminals.

[0045] In some exemplary embodiments, analyzing the business content data of at least two terminals and determining the business relevance of at least two terminals in step S202 can be implemented in the following manner: matching the business content data of at least two terminals based on a string matching method to obtain a matching result; and determining the business relevance of at least two terminals based on the matching result.

[0046] Among them, the string matching method can be to perform complete data matching on the business content data of at least two terminals (that is, to match the business content data of each terminal with the business content data of other terminals one by one), or to use a string matching algorithm (Knuth-Morris-Pratt, KPM) to match the business content data of at least two terminals to obtain a matching result.

[0047] It should be noted that the KPM algorithm uses information after matching failures to minimize the number of matches between the pattern string and the main string to achieve the purpose of fast matching. The KPM algorithm is simple to operate and is convenient for quickly matching the business content data of at least two terminals to determine the business relevance of at least two terminals.

[0048] For example, the service content data of one of the at least two terminals is a string O, and the string length is n; the service content data of the other terminal is a string F, and the string length is m. By determining whether the string F appears in the string O, the service association between the strings O and F is determined.

[0049] Normally, it is necessary to traverse each position in string O to determine whether string F appears at each position in string O, but the complexity is O(n*m); while the KPM algorithm can determine the maximum common length by calculating the maximum length of the common part of the prefix and suffix of the string before each position of string F (excluding the string itself, otherwise the maximum length is always the string itself); and after obtaining the maximum common length of each position of string F, use the maximum common length to quickly compare it with string O.

[0050] Each time when the characters of the two strings are different, the string F can be moved forward by (matched length - maximum common length) positions according to the maximum common length, and then the next position can be compared. In fact, the forward movement of string F is only a conceptual movement. As long as the comparison between string F and string O starts from the maximum common length, the purpose of moving string F forward can be achieved, thereby reducing the string matching complexity to O(n+m), which can speed up data processing and improve data processing efficiency.

[0051] In some exemplary embodiments, the analysis of the business content data of at least two terminals and the determination of the business relevance of the at least two terminals in step S202 can be implemented in the following manner: based on the business processing order of each terminal, the business content data of each terminal is sampled to obtain the sampled data of each terminal; the sampled data of each terminal is hashed to determine the hash value of the sampled data of each terminal; the hash values ​​of the sampled data of at least two terminals are compared, and the business relevance of the at least two terminals is determined based on the comparison result.

[0052] Among them, hashing the sampled data of each terminal separately can be to perform hash operations on the sampled data of each terminal separately, so as to obtain the hash value of the sampled data of each terminal, which can not only ensure the security of the sampled data, but also facilitate the subsequent comparison of each sampled data, thereby improving the data processing efficiency.

[0053] Further, when it is determined that the hash values ​​of the sampled data of at least two terminals are the same (or the hash values ​​are the same), the business relevance of the at least two terminals is determined to be mutually related; otherwise, the business relevance of the at least two terminals is determined to be unrelated. The business relevance of at least two terminals can be accurately determined, which facilitates the subsequent use of different management strategies to manage the data traffic of at least two terminals, thereby improving the management accuracy of the data traffic of the terminals.

[0054] In some exemplary embodiments, analyzing the business content data of at least two terminals and determining the business relevance of at least two terminals in step S202 can be implemented in the following manner: inputting the business content data and / or business feature data of at least two terminals into a target classification model for identification, and determining the business relevance of at least two terminals.

[0055] The target classification model is a model corresponding to the business type selected from a plurality of preset classification models in a preset classification model library.

[0056] For example, different application identifiers (Application IDentity, AppID) can be used to characterize the service type of the service performed by the terminal; and AppID is used as the index of the model, and the model corresponding to the AppID is screened from multiple preset classification models in the preset classification model library as the target classification model. Thus, the obtained target classification model can identify the service content data and / or service feature data of at least two terminals for a specific AppID, and determine the service relevance of at least two terminals.

[0057] It should be noted that each business type corresponds to a preset classification model, and the preset classification model is a model obtained by training an initial classification model based on positive sample data and reverse sample data.

[0058] The positive sample data is sample service data having the same preset service type, and the negative sample data is sample service data having a preset service type different from that of the positive sample data.

[0059] For example, a support vector machine (SVM) algorithm, a reinforcement learning (RL) algorithm, etc. are used as training methods to train the positive sample data and the reverse sample data to obtain a preset classification model, so that the preset classification model can accurately identify the service feature data of the terminal and accurately determine the service relevance of at least two input terminals.

[0060] In some exemplary embodiments, before executing step S202 of filtering out at least two terminals with the same service type from multiple terminals, after executing step S201 of acquiring service content data and service feature data of multiple terminals, the method further includes: using the service feature data as a keyword and the service content data as key information, and storing the service content data and service feature data of the multiple terminals in a database respectively.

[0061] In the database, a data format of key (business feature data)-value (business content data) can be constructed to facilitate data search.

[0062] By storing the business content data and business feature data of multiple terminals in a database, it is possible to simultaneously extract the business content data of multiple terminals, thereby matching the business content data of multiple terminals to determine the business relevance of multiple terminals and improving data processing efficiency.

[0063] In some exemplary embodiments, the service feature data further includes: timestamp information, terminal identification (for example, a terminal permanent identifier (SUbscription Permanent Identifier, SUPI) etc.), and at least one of Policy and Charging Control Rule (PCC Rule) information.

[0064] The PCC Rule information includes: at least one of service data flow inspection information, policy control information, and billing related information; the service data flow is packet data detected using a service data flow template (Service Data Flow Template) in the PCC rule information; wherein the service data flow template includes a preset number (for example, 5, or 10, etc.) of service data flow filters (Service Data Flow Filter).

[0065] PCC rules include dynamic PCC rules and static predefined PCC rules. Among them, dynamic PCC rules are sent to the Policy and Charging Enforcement Function (PCEF) entity through the Policy and Charging Rules Function (PCRF) for execution. PCRF can create, modify, and delete dynamic PCC rules. Static predefined PCC rules are pre-configured by the PCEF entity, and PCRF can only reference static predefined PCC rules.

[0066] The service type includes: at least one of a video service type, a voice service type, a data upload service type, a data download service type, and a live broadcast service type.

[0067] The service characteristic data also includes characteristic information of the data code stream (for example, the size of the transmission code stream of the data code stream, the number of uplink transmissions, the number of downlink transmissions, etc.).

[0068] By reflecting the business characteristic data through the above-mentioned different information, the characteristics of the business data traffic used by the terminal when processing business data can be reflected through business characteristic data of different dimensions, so as to accurately identify the data traffic of the terminal and improve the statistical accuracy of the data traffic of the terminal.

[0069] Figure 3 The flowchart of a method for managing multi-user data traffic provided by an embodiment of the present application is shown. The method for managing multi-user data traffic can be applied to a data collection control function (DCCF) entity. Figure 3 As shown, the method for managing multi-user data traffic in the embodiment of the present application includes but is not limited to the following steps.

[0070] Step S301, obtaining service content data and service feature data of a target terminal.

[0071] Among them, the business characteristic data includes business type.

[0072] Step S302: Send the service content data and service feature data of the target terminal to the network data analysis function entity.

[0073] Step S303, in response to the preset management policy fed back by the network data analysis function entity, the data flow of the target terminal is managed according to the preset management policy.

[0074] The preset management policy is a policy that matches the service association of at least two terminals, and the at least two terminals include the target terminal.

[0075] In this embodiment, by acquiring the service content data and service feature data of the target terminal, the service content data and service feature data of the target terminal in the process of performing service processing with other terminals can be acquired, wherein the service feature data includes the service type, so as to facilitate understanding of the data traffic used by the target terminal; the service content data and service feature data of the target terminal are sent to the network data analysis function entity, so that the network data analysis function entity can screen out at least two terminals with the same service type from the multiple terminals based on the acquired service content data and service feature data of the multiple terminals, and then analyze the service content data of the at least two terminals to determine the service relevance of the at least two terminals, and then send the preset management policy matching the service relevance to the current device (i.e., the data acquisition control function entity) based on the service relevance of the at least two terminals. After receiving the preset management policy fed back by the network data analysis function entity, the data acquisition control function entity manages the data traffic of the target terminal according to the preset management policy, which can improve the statistical accuracy of the data traffic of each terminal, so as to determine the cost of the communication traffic of each terminal based on the correct quantitative traffic statistical information, and improve the user experience.

[0076] In some exemplary embodiments, the target terminal is communicatively connected to a user plane function entity.

[0077] The acquisition of service content data and service feature data of the target terminal in step S301 includes: acquiring the data code stream of the target terminal connected to the communication terminal through the user plane function entity based on the message subscription method; parsing the data code stream of the target terminal to obtain the service content data and service feature data of the target terminal.

[0078] Managing the data traffic of the target terminal according to the preset management policy in step S303 includes: forwarding the preset management policy to the user plane function entity so that the user plane function entity manages the data traffic of the target terminal according to the preset management policy.

[0079] Among them, the data acquisition and control functional entity can send a service data subscription request to the user plane functional entity so as to subscribe to the data code stream of the target terminal connected to the communication interface obtained by the user plane functional entity; when the user functional entity feeds back a service data subscription response to the data acquisition and control functional entity, and the service data subscription response includes a subscription success identifier, it can be determined that the message subscription is successful; at this time, the data acquisition and control functional entity can promptly obtain the data code stream of the target terminal connected to the communication interface obtained by the user plane functional entity.

[0080] When the data acquisition control functional entity receives the data code stream of the target terminal connected to the communication interface from the user plane functional entity, it can perform message parsing on the data code stream to obtain the service content data and service feature data of the target terminal.

[0081] The service feature data includes at least one of timestamp information, service type, SUPI of the terminal, and PCC Rule information. The service content data represents the actual service data payload of the target terminal when performing service processing.

[0082] Through a message subscription-based method, the data code stream of the target terminal that is in communication connection with the user plane function entity is obtained, and the data code stream is parsed, and the service content data and service feature data of the target terminal obtained by the analysis are sent to the network data analysis function entity, so that the network data analysis function entity can screen out at least two terminals with the same service type from multiple terminals based on the service content data and service feature data of the multiple terminals obtained, and then analyze the service content data of the at least two terminals to determine the service relevance of the at least two terminals, and then send the preset management policy matching the service relevance to the data acquisition control function entity based on the service relevance of the at least two terminals; further, after receiving the preset management policy fed back by the network data analysis function entity, the data acquisition control function entity forwards the preset management policy to the user plane function entity, so that the user plane function entity can manage the data traffic of the target terminal according to the preset management policy, so that the user plane function entity can accurately count the data traffic of each terminal, so as to determine the cost of the communication traffic of each terminal based on the correct quantitative traffic statistical information, etc., thereby improving the user experience.

[0083] The following describes the device according to the embodiment of the present invention in detail with reference to the accompanying drawings. Figure 4 FIG. 1 is a block diagram showing a network data analysis functional entity provided in an embodiment of the present application. Figure 4 As shown, the network data analysis functional entity 400 includes but is not limited to the following modules.

[0084] The first acquisition module 401 is configured to acquire service content data and service feature data of multiple terminals.

[0085] The service characteristic data includes the service type, service content data and service characteristic data, which are data extracted from the data code stream obtained by the data acquisition control function entity.

[0086] The analysis module 402 is configured to select at least two terminals with the same service type from multiple terminals, and analyze the service content data of the at least two terminals to determine the service relevance of the at least two terminals.

[0087] The management module 403 is configured to manage the data traffic of the at least two terminals according to the service relevance of the at least two terminals by adopting a preset management policy matching the service relevance.

[0088] It should be noted that the network data analysis functional entity 400 in this embodiment can implement any one of the multi-user data traffic management methods applied to the network data analysis functional entity in the embodiments of the present application.

[0089] According to the network data analysis function entity of the embodiment of the present application, the business content data and business feature data of multiple terminals are obtained through the first acquisition module, wherein the business feature data includes the business type, and the business content data and business feature data are data extracted from the data code stream obtained by the data acquisition control function entity, which can clearly define the business content data and business feature data in the business processing process performed by each terminal, so as to facilitate the screening of multiple terminals to screen out at least two terminals with the same business type; then, the business content data of at least two terminals are analyzed using the analysis and determination module to determine the business relevance of at least two terminals, accurately identify whether the businesses performed by at least two terminals are related, and determine whether at least two terminals are performing the same business processing, so as to know the business situation performed by the terminals; the management module is used to manage the data traffic of at least two terminals based on the business relevance of at least two terminals, using a preset management strategy matching the business relevance, so as to improve the statistical accuracy of the data traffic of each terminal, so that each terminal can determine its usage fee based on the correct quantitative traffic statistical information, etc., thereby improving the user's usage experience.

[0090] Figure 5 FIG. 1 is a block diagram showing a data acquisition control functional entity provided by an embodiment of the present application. Figure 5 As shown, the data acquisition control functional entity 500 includes but is not limited to the following modules.

[0091] The second acquisition module 501 is configured to acquire service content data and service feature data of a target terminal.

[0092] Among them, the business characteristic data includes business type.

[0093] The sending module 502 is configured to send the service content data and service feature data of the target terminal to the network data analysis function entity.

[0094] The processing module 503 is configured to respond to the preset management policy fed back by the network data analysis function entity and manage the data traffic of the target terminal according to the preset management policy.

[0095] The preset management policy is a policy that matches the service association of at least two terminals, and the at least two terminals include the target terminal.

[0096] In some exemplary embodiments, the target terminal is connected to the user plane function entity in communication. The second acquisition module 501 is used to obtain the data code stream of the target terminal connected to the user plane function entity through the user plane function entity based on the message subscription method; parse the data code stream of the target terminal to obtain the service content data and service feature data of the target terminal. The processing module 503 is used to forward the preset management policy to the user plane function entity so that the user plane function entity manages the data flow of the target terminal according to the preset management policy.

[0097] It should be noted that the data acquisition control function entity 500 in this embodiment can implement any method for managing multi-user data traffic applied to the data acquisition control function entity in the embodiments of the present application.

[0098] According to the data acquisition and control functional entity of the embodiment of the present application, the service content data and service feature data of the target terminal are acquired through the second acquisition module, and the service content data and service feature data of the target terminal in the process of performing service processing with other terminals can be acquired, wherein the service feature data includes the service type, which is convenient for understanding the data traffic used by the target terminal; the service content data and service feature data of the target terminal are sent to the network data analysis functional entity by using the sending module, so that the network data analysis functional entity can screen out at least two terminals with the same service type from the multiple terminals based on the acquired service content data and service feature data of the multiple terminals, and then analyze the service content data of the at least two terminals to determine the service relevance of the at least two terminals, and then use the processing module to send the preset management policy matching the service relevance to the current device (i.e., the data acquisition and control functional entity) based on the service relevance of the at least two terminals. After receiving the preset management policy fed back by the network data analysis functional entity, the data acquisition and control functional entity manages the data traffic of the target terminal according to the preset management policy, which can improve the statistical accuracy of the data traffic of each terminal, so as to determine the cost of the communication traffic of each terminal based on the correct quantitative traffic statistical information, and improve the user experience.

[0099] Figure 6 FIG. 1 is a block diagram showing a management system for multi-user data traffic provided by an embodiment of the present application. Figure 6 As shown, the management system of the multi-user data traffic includes but is not limited to the following devices: a user plane functional entity 610 and multiple terminals (e.g., a first terminal 621, a second terminal 622, ..., an Nth terminal 62N, where N represents the number of terminals and N is an integer greater than or equal to 2).

[0100] The user plane functional entity 610 includes a network data analysis functional entity 611 .

[0101] The user plane function entity 610 can manage and control the data traffic of multiple terminals connected to it through the network data analysis function entity 611, so as to achieve the management of the data traffic of multiple terminals.

[0102] Among them, the network data analysis function entity 611 can implement any one of the management methods for multi-user data traffic applied to the network data analysis function entity in the embodiments of the present application.

[0103] Figure 7 FIG. 1 is a block diagram showing a management system for multi-user data traffic provided by an embodiment of the present application. Figure 7 As shown, the management system of the multi-user data traffic includes but is not limited to the following devices.

[0104] The first terminal 711, the first access device 781, the first user plane function entity 721, the first data acquisition control function entity 761; the second terminal 712, the second access device 782, the second user plane function entity 722, the second data acquisition control function entity 762; as well as the session management function entity 730, the policy control function (PCF) entity 740, the network data analysis function entity 750 and the target network (DN) 770.

[0105] Among them, the first data acquisition control function entity 761 is used to obtain the business content data and business characteristic data of the first terminal 711, and the business characteristic data includes the business type; send the business content data and business characteristic data of the first terminal 711 to the network data analysis function entity 750; respond to the preset management policy fed back by the network data analysis function entity 750, and manage the data flow of the first terminal 711 according to the preset management policy.

[0106] The second data acquisition control function entity 762 is used to obtain the business content data and business characteristic data of the second terminal 712, where the business characteristic data includes the business type; send the business content data and business characteristic data of the second terminal 712 to the network data analysis function entity 750; and manage the data flow of the second terminal 712 according to the preset management policy fed back by the network data analysis function entity 750 in response to the preset management policy.

[0107] The preset management policy is a policy that matches the service relevance of the service performed between the first terminal 711 and the second terminal 712 .

[0108] The network data analysis function entity 750 is used to obtain service content data and service feature data of multiple terminals (such as the first terminal 711, the second terminal 712, and the third terminal (not shown in the figure), etc.), wherein the service feature data includes the service type, and the service content data and the service feature data are data extracted from the data code stream obtained by the data acquisition control function entity (such as the first data acquisition control function entity 761 or the second data acquisition control function entity 762); select at least two terminals with the same service type (such as the first terminal 711 and the second terminal 712) from the multiple terminals, and analyze the service content data of the first terminal 711 and the second terminal 712 to determine the service relevance of the first terminal 711 and the second terminal 712; and manage the data traffic of the first terminal 711 and the second terminal 712 using a preset management strategy matching the service relevance based on the service relevance of the first terminal 711 and the second terminal 712.

[0109] In a public land mobile network (PLMN), each user plane function entity is respectively connected to its corresponding data acquisition control function entity, so that the service content data and service feature data of the terminal in each user plane function entity are respectively collected through each data acquisition control function entity. That is, the first user plane function entity 721 is connected to the first data acquisition control function entity 761, and the second user plane function entity 722 is connected to the first data acquisition control function entity 762.

[0110] The first data collection control function entity 761 is used to collect the service content data and service characteristic data of the first terminal 711 which is in communication with the first access device 781; the second data collection control function entity 762 is used to collect the service content data and service characteristic data of the second terminal 712 which is in communication with the first access device 782.

[0111] In some embodiments, the network data analysis function entity 750 can obtain multi-user associated traffic subscription information from the PCF entity 740; then, match the obtained business content data of the first terminal 711 and the business content data of the second terminal 712 to determine the business association between the first terminal 711 and the second terminal 712; and match the multi-user associated traffic subscription information obtained from the PCF entity 740 with the multi-user associated traffic subscription information obtained from the PCF entity 740 to determine whether it is necessary to execute a multi-user management policy on the first terminal 711 and the second terminal 712.

[0112] When it is determined that the business association between the first terminal 711 and the second terminal 712 is mutually associated, a multi-user management strategy can be used to uniformly manage the data traffic of the first terminal 711 and the second terminal 712 based on the data traffic information of multiple users subscribed by the first terminal 711 and the second terminal 712 on the PCF.

[0113] When it is determined that the service association between the first terminal 711 and the second terminal 712 is irrelevant, a single user management strategy is adopted to manage the data traffic of the first terminal 711 and the second terminal 712 respectively.

[0114] Figure 8 A flowchart showing a method for managing a multi-user data flow management system provided by an embodiment of the present application is shown. Figure 8 As shown, the working method of the management system for multi-user data traffic includes but is not limited to the following steps.

[0115] Step S801 , the network data analysis function entity 750 sends a first subscription request message to the PCF entity 740 .

[0116] Among them, the first subscription request message is used to subscribe to multi-user associated traffic subscription information.

[0117] For example, the network data analysis function entity 750 sends a first subscription request message to the PCF entity 740 through the PCF event exposure (Npcf_EventExposure) service to subscribe to the multi-user associated traffic subscription message.

[0118] For another example, the network data analysis function entity 750 sends a message to the PCF entity 740 to subscribe to PCF open events (Npcf_EventExposure_Subscribe), which is used to request to subscribe to multi-user associated traffic contract messages.

[0119] Step S802 , the PCF entity 740 feeds back a first message subscription response to the network data analysis function entity 750 .

[0120] The first subscription message response includes the terminal's identifier SUPI, policy and charging control rule PCC information, and the like.

[0121] For example, the PCF entity 740 feeds back a PCF event open response (Npcf_EventExposure_Notify) message to the network data analysis function entity 750, so that the network data analysis function entity 750 obtains the message that it has successfully subscribed to the multi-user associated traffic contract.

[0122] Step S803: The first terminal 711 successfully establishes a voice service with the first user plane function entity 721 through message interaction.

[0123] In some embodiments, the first terminal 711 may also establish at least one of a video service, a data upload service, a data download service, and a live broadcast service with the first user plane function entity 721 .

[0124] Step S804: the first user plane function entity 721 sends a second subscription request message for analyzing the associated data traffic of the first terminal 711 to the first data acquisition control function entity 761, so that the first data acquisition control function entity 761 transparently transmits the second subscription request message to the network data analysis function entity 750.

[0125] The first user plane function entity 721 and the first data acquisition control function entity 761 are located in the same PLMN.

[0126] For example, the first user plane function entity 721 can subscribe to the first data acquisition control function entity 761 for a task for collecting associated data traffic of the first terminal 711 through the data management (Ndccf_DataManagement) service; when the first data acquisition control function entity 761 receives the second subscription request message, it will pass the second subscription request message to the network data analysis function entity 750 through the analysis subscription (AnalyticsSubscription) service.

[0127] In some embodiments, the first data collection control function entity 761 subscribes to the associated traffic analysis task of the first terminal 711 from the network data analysis function entity 750 through the Nnwdaf_AnalyticsSubscription service.

[0128] The network data analysis function entity 750 subscribes to the data collection task of the first terminal 711 from the first data collection control function entity 761 through the Ndccf_DataManagement service.

[0129] Step S805, after receiving the second subscription request message, the network data analysis function entity 750 will feedback the second subscription message response to the first data acquisition control function entity 761, and the second subscription message response will carry the message for subscribing to the data collection task for the first terminal 711; the first data acquisition control function entity 761 will pass the received second subscription message response to the first user plane function entity 721.

[0130] Among them, the network data analysis function entity 750 sends a second subscription message response to the first data acquisition control function entity 761 through the Ndccf_DataManagement service; after receiving the second subscription request message, the first data acquisition control function entity 761 will pass the second subscription message response to the first user plane function entity 721 through the Nupf_EventExposure service, so that the first user plane function entity 721 can feed back the acquired data code stream of the first terminal 711 to the first data acquisition control function entity 761.

[0131] The data code stream of the first terminal 711 includes service content data and service feature data of the first terminal 711 .

[0132] In some embodiments, the network data analysis function entity 750 can subscribe to the data collection task for the first terminal 711 from the first data collection control function entity 761 through the Ndccf_DataManagement_Subscribe message; the first data collection control function entity 761 then subscribes to the data collection task for the first terminal 711 from the first user plane function entity 721 through the Nupf_EventExposure_Subscribe message.

[0133] In some embodiments, the first data collection control function entity 761 subscribes to the data collection task of the first terminal 711 from the first user plane function entity 721 through the Nupf_EventExposure service.

[0134] The first user plane function entity 721 subscribes to the multi-user associated traffic subscription information from the first data collection control function entity 761 through the Ndccf_DataManagement_Subscribe message.

[0135] The first data collection control function entity 761 then subscribes to the traffic analysis task associated with the first terminal 711 from the network data analysis function entity 750 through the Nnwdaf_AnalyticsSubscription_Subscribe message.

[0136] It should be noted that the data collection process for the second terminal 712 and the subscription to the associated data flow analysis task for the second terminal 712 can be implemented in the manner of the above steps S803 to S804, which will not be described in detail here.

[0137] Step S806: The first terminal 711 initiates a service with associated data traffic to the second terminal 712. The first user plane function entity 721 corresponding to the first terminal 711 obtains the service message sent by the first terminal 711 by identifying the acquired data code stream.

[0138] Step S807 : The first user plane function entity 721 manages the data traffic of the first terminal 711 using a single user management strategy.

[0139] Step S808 : The first user plane function entity 721 sends the received service data code stream of the first terminal 711 to the target network 770 , so as to perform service interaction with the second terminal 712 through the target network 770 .

[0140] The second terminal 712 will also use the single-user management strategy to manage the data traffic of the second terminal 712 through the second user plane function entity 722 .

[0141] It should be noted that, while executing step S808, the first user plane function entity 721 also needs to execute step S809.

[0142] Step S809, the first user plane function entity 721 sends the acquired service feature data and service content data of the first terminal 711 to the first data acquisition control function entity 761, so that the first data acquisition control function entity 761 forwards the service feature data and service content data of the first terminal 711 to the network data analysis function entity 750.

[0143] The service characteristic data includes at least one of: timestamp information, service type, SUPI of the terminal, and PCC Rule information.

[0144] In some embodiments, the service type may be a type represented by an AppID, for example, at least one of a video service type, a voice service type, a data upload service type, a data download service type, and a live broadcast service type.

[0145] For example, the first user plane function entity 721 sends the service characteristic data of the first terminal 711 to the first data acquisition control function entity 761 through the Nupf_EventExposure service; when the first data acquisition control function entity 761 receives the service characteristic data of the first terminal 711, the first data acquisition control function entity 761 forwards the service characteristic data of the first terminal 711 to the network data analysis function entity 750 through the Ndccf_DataManagement service.

[0146] For another example, the first user plane function entity 721 sends the service characteristic data of the first terminal 711 to the first data acquisition control function entity 761 through the Nupf_EventExposure_Notify message; when the first data acquisition control function entity 761 receives the service characteristic data of the first terminal 711, the first data acquisition control function entity 761 forwards the service characteristic data of the first terminal 711 to the network data analysis function entity 750 through the Ndccf_DataManagement_Notify message.

[0147] It should be noted that the second terminal 712 that performs corresponding services with the first terminal 711 has a processing procedure for services with data traffic associated with the first terminal 711 in the same manner as the first terminal 711, that is, the processing flow is the same as steps S806 to S809. Ultimately, the network data analysis function entity 750 will also obtain the service feature data and service content data of the second terminal 712, which will not be repeated here.

[0148] In step S810, the network data analysis function entity 750 analyzes the received business feature data and business content data of the first terminal 711, as well as the business feature data and business content data of the second terminal 712, determines the business association between the first terminal 711 and the second terminal 712, and generates a multi-user management strategy when it is determined that the business association between the first terminal 711 and the second terminal 712 is mutually associated.

[0149] The multi-user management strategy is used to uniformly manage the data traffic of the first terminal 711 and the second terminal 712. For example, the multi-user management strategy includes a multi-user billing statistics strategy and a multi-user communication service quality assurance strategy. For example, according to the multi-user billing statistics strategy, the data traffic used by the first terminal 711 and the second terminal 712 in the process of performing services of the same service type is counted, and the corresponding fees are determined based on the statistically obtained data traffic; according to the multi-user communication service quality assurance strategy, the first terminal 711 and the second terminal 712 are provided with a communication quality assurance service.

[0150] In some embodiments, the network data analysis function entity 750 may analyze the service feature data and service content data of the first terminal 711 and the service feature data and service content data of the second terminal 712 in the following manner to determine the service association between the first terminal 711 and the second terminal 712 .

[0151] First, the network data analysis functional entity 750 extracts the business type from the business feature data of the first terminal 711 and the business type from the business feature data of the second terminal 712. By comparing the business types of the two terminals, it can be determined that the two terminals are performing the same type of business processing; then, based on the string matching method, the business content data of the first terminal 711 and the second terminal 712 are matched to obtain a matching result; based on the matching result, the business association between the first terminal 711 and the second terminal 712 is determined.

[0152] Among them, if the matching result is that the business content data of the first terminal 711 and the business content data of the second terminal 712 are adapted, it can be determined that the services being conducted by the first terminal 711 and the second terminal 712 are interrelated, for example, the first terminal 711 and the second terminal 712 are conducting voice calls, or video calls and other services.

[0153] In some exemplary embodiments, based on the business processing order of each terminal, the business content data of each terminal is sampled to obtain the sampled data of each terminal; the sampled data of each terminal is hashed to determine the hash value of the sampled data of each terminal; the hash values ​​of the sampled data of at least two terminals are compared, and the business relevance of the at least two terminals is determined based on the comparison result.

[0154] Among them, hashing the sampled data of each terminal separately can be to perform hash operations on the sampled data of each terminal separately, so as to obtain the hash value of the sampled data of each terminal, which can not only ensure the security of the sampled data, but also facilitate the subsequent comparison of each sampled data, thereby improving the data processing efficiency.

[0155] Further, when it is determined that the hash values ​​of the sampled data of at least two terminals are the same (or the hash values ​​are the same), the service associations of the at least two terminals are determined to be mutually associated; otherwise, the service associations of the at least two terminals are determined to be unrelated.

[0156] When it is determined that the business association of at least two terminals is mutually associated, a multi-user management strategy can be used to uniformly manage the data traffic of the at least two terminals; when it is determined that the business association of at least two terminals is unrelated, a single-user management strategy can be used to manage the data traffic of each terminal separately, so as to facilitate accurate statistics of the data traffic of each terminal and improve the statistical accuracy of the data traffic.

[0157] In some exemplary embodiments, the multi-user management strategy includes a multi-user billing statistics strategy and a multi-user communication service quality assurance strategy. The network data analysis function entity 750 counts the data traffic used by the first terminal 711 and the second terminal 712 in the process of performing services of the same service type according to the multi-user billing statistics strategy, and determines the corresponding fees based on the statistically obtained data traffic; and provides communication quality assurance services for the first terminal 711 and the second terminal 712 according to the multi-user communication service quality assurance strategy.

[0158] In some exemplary embodiments, service content data and / or service feature data of at least two terminals are input into a target classification model for identification to determine the service relevance of the at least two terminals.

[0159] The target classification model is a model corresponding to the business type selected from a plurality of preset classification models in a preset classification model library.

[0160] For example, different AppIDs can be used to characterize the service types of the services performed by the terminal; and AppID can be used as the index of the model to select the model corresponding to the AppID from multiple preset classification models in the preset classification model library as the target classification model. Thus, the obtained target classification model can identify the service content data and / or service feature data of at least two terminals for a specific AppID and determine the service relevance of at least two terminals.

[0161] In some exemplary embodiments, each business type corresponds to a preset classification model, which is a model obtained by training an initial classification model based on positive sample data and reverse sample data. The positive sample data is sample business data with the same preset business type, and the reverse sample data is sample business data with a different preset business type from the positive sample data.

[0162] For example, the SVM algorithm, RL algorithm, etc. are used as training methods to train the positive sample data and the negative sample data to obtain a preset classification model, so that the preset classification model can accurately identify the service feature data of the terminal and accurately determine the service relevance of at least two input terminals.

[0163] It should be noted that the service data of each terminal can also be stored in the database to facilitate processing of the service data of multiple terminals. For example, the service feature data of the terminal is used as a keyword and the service content data of the terminal is used as key information to store the service content data and service feature data of multiple terminals in the database.

[0164] In step S811, the network data analysis functional entity 750 sends the multi-user management policy and the service association between the first terminal 711 and the second terminal 712 to the first data acquisition control functional entity 761, so that the first data acquisition control functional entity 761 can forward the multi-user association policy and the service association between the first terminal 711 and the second terminal 712 to the first user plane functional entity 721.

[0165] Among them, the network data analysis function entity 750 can send the multi-user management policy and the business correlation between the first terminal 711 and the second terminal 712 to the first data acquisition control function entity 761 through the Nnwdaf_AnalyticsSubscription service; the first data acquisition control function entity 761 then forwards the multi-user management policy and the business correlation between the first terminal 711 and the second terminal 712 to the first user plane function entity 721 through the Ndccf_DataManagemen service.

[0166] In some embodiments, the network data analysis function entity 750 can inform the first data acquisition control function entity 761 of the multi-user management policy and the service association between the first terminal 711 and the second terminal 712 by sending a Nwdaf_AnalyticsSubscription_Notify message to the first data acquisition control function entity 761; when the first data acquisition control function entity 761 receives the above information, the first data acquisition control function entity 761 forwards the above information to the first user plane function entity 721 through the Ndccf_DataManagemen_Notify message.

[0167] Step S812: The first terminal 711 continues to perform service interaction with the second terminal 712.

[0168] Step S813 : The first user plane function entity 721 updates the original single-user management policy to the obtained multi-user management policy, and then uses the multi-user management policy to manage the data traffic of the first terminal 711 .

[0169] In step S814 , the first user plane function entity 721 continuously forwards the service data code stream sent by the first terminal 711 and the second terminal 712 to the target network 770 , so that the second terminal 712 can obtain the service data code stream sent by the first terminal 711 through the target network 770 .

[0170] In this embodiment, by introducing a network data analysis functional entity and multiple data acquisition control functional entities (such as a first data acquisition control functional entity and a second data acquisition control functional entity), it is possible to timely obtain business data of multiple terminals, analyze the business data of each terminal, determine the business feature data and business content data corresponding to each terminal, and thus determine that the business types of the first terminal and the second terminal are the same; the network data analysis functional entity is used to analyze the business feature data and business content data of the first terminal, as well as the business feature data and business content data of the second terminal, to determine the business correlation between the first terminal and the second terminal, and when it is determined that the business correlation between the first terminal and the second terminal is mutually correlated, a multi-user management strategy is generated, and the data traffic of the first terminal and the second terminal is managed based on the multi-user management strategy, which can improve the statistical accuracy of the data traffic of the first terminal and the second terminal, so that the first terminal and the second terminal determine their usage fees based on the correct quantity traffic statistical information, and provide effective communication quality assurance services for the first terminal and the second terminal, etc., to improve the user experience.

[0171] It should be clear that the present invention is not limited to the specific configurations and processes described in the above embodiments and shown in the figures. For the convenience and brevity of description, a detailed description of the known methods is omitted here, and the specific working processes of the systems, modules and units described above can refer to the corresponding processes in the aforementioned method embodiments, which will not be repeated here.

[0172] Fig. 9 A structural diagram showing an exemplary hardware architecture of a computing device capable of implementing the method and apparatus for managing multi-user data traffic according to an embodiment of the present invention.

[0173] like Fig. 9 As shown, the computing device 900 includes an input device 901, an input interface 902, a central processing unit 903, a memory 904, an output interface 905, and an output device 906. The input interface 902, the central processing unit 903, the memory 904, and the output interface 905 are connected to each other via a bus 907, and the input device 901 and the output device 906 are connected to the bus 907 via the input interface 902 and the output interface 905, respectively, and then connected to other components of the computing device 900.

[0174] Specifically, the input device 901 receives input information from the outside and transmits the input information to the central processing unit 903 through the input interface 902; the central processing unit 903 processes the input information based on the computer executable instructions stored in the memory 904 to generate output information, temporarily or permanently stores the output information in the memory 904, and then transmits the output information to the output device 906 through the output interface 905; the output device 906 outputs the output information to the outside of the computing device 900 for user use.

[0175] In one embodiment, Fig. 9 The computing device shown may be implemented as an electronic device, which may include: a memory configured to store a program; and a processor configured to run the program stored in the memory to execute the multi-user data traffic management method described in the above embodiment.

[0176] In one embodiment, Fig. 9 The computing device shown can be implemented as a management system for multi-user data traffic, which may include: a memory configured to store a program; a processor configured to run the program stored in the memory to execute the multi-user data traffic management method described in the above embodiment.

[0177] The above is only an exemplary embodiment of the present application and is not intended to limit the scope of protection of the present application. In general, various embodiments of the present application can be implemented in hardware or special circuits, software, logic or any combination thereof. For example, some aspects can be implemented in hardware, while other aspects can be implemented in firmware or software that can be executed by a controller, a microprocessor or other computing device, although the present application is not limited thereto.

[0178] Embodiments of the present application may be implemented by a processor executing computer program instructions, such as in a processor entity, or by hardware, or by a combination of software and hardware. The computer program instructions may be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.

[0179] The block diagram of any logic flow in the accompanying drawings of the present application can represent program steps, or can represent interconnected logic circuits, modules and functions, or can represent a combination of program steps and logic circuits, modules and functions. The computer program can be stored on a memory. The memory can have any type suitable for the local technical environment and can be implemented using any suitable data storage technology, such as but not limited to read-only memory (ROM), random access memory (RAM), optical memory device and system (digital versatile disc DVD or CD disc), etc. Computer-readable media may include non-transient storage media. The processor can be any type suitable for the local technical environment, such as but not limited to a general-purpose computer, a special-purpose computer, a microprocessor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a programmable logic device (FGPA) and a processor based on a multi-core processor architecture.

[0180] By way of exemplary and non-limiting examples, a detailed description of exemplary embodiments of the present application has been provided above. However, various modifications and adjustments to the above embodiments will be apparent to those skilled in the art when considered in conjunction with the accompanying drawings and claims, but will not depart from the scope of the present invention. Therefore, the proper scope of the present invention will be determined according to the claims.

Claims

1. A method for managing multi-user data traffic, characterized in that: include: Acquire service content data and service feature data of multiple terminals, wherein the service feature data includes service type, and the service content data and the service feature data are data extracted from a data code stream acquired by a data acquisition control function entity; Filtering at least two terminals with the same service type from the multiple terminals, and analyzing service content data of the at least two terminals to determine service relevance of the at least two terminals; According to the service relevance of the at least two terminals, a preset management strategy matching the service relevance is adopted to manage the data traffic of the at least two terminals.

2. The method according to claim 1, characterized in that The managing the data traffic of the at least two terminals by using a preset management strategy matching the service relevance according to the service relevance of the at least two terminals includes: In the case where it is determined that the service associations of the at least two terminals are mutually associated, using a multi-user management strategy to uniformly manage the data traffic of the at least two terminals; When it is determined that the service associations of the at least two terminals are irrelevant, a single user management strategy is adopted to manage the data traffic of each of the terminals respectively.

3. The method according to claim 2, characterized in that The multi-user management strategy includes a multi-user billing statistics strategy and a multi-user communication service quality assurance strategy; The adopting a multi-user management strategy to uniformly manage the data traffic of the at least two terminals includes: According to the multi-user billing statistical strategy, counting the data traffic used by the at least two terminals in the process of performing the services of the same service type, and determining the corresponding fees based on the statistically obtained data traffic; According to the multi-user communication service quality assurance strategy, a communication quality assurance service is provided for the at least two terminals.

4. The method according to claim 1, characterized in that The analyzing the service content data of the at least two terminals to determine the service relevance of the at least two terminals includes: Matching the service content data of the at least two terminals based on a string matching method to obtain a matching result; The service association of the at least two terminals is determined according to the matching result.

5. The method according to claim 1, characterized in that The analyzing the service content data of the at least two terminals to determine the service relevance of the at least two terminals includes: Based on the service processing order of each terminal, sampling the service content data of each terminal respectively to obtain the sampled data of each terminal; Performing hash processing on the sampled data of each terminal respectively to determine the hash value of the sampled data of each terminal; The hash values ​​of the sampled data of the at least two terminals are compared, and the service association of the at least two terminals is determined based on the comparison result.

6. The method according to claim 1, characterized in that The analyzing the service content data of the at least two terminals to determine the service relevance of the at least two terminals includes: Inputting the service content data and / or service feature data of the at least two terminals into a target classification model for identification, and determining the service relevance of the at least two terminals; The target classification model is a model corresponding to the business type selected from a plurality of preset classification models in a preset classification model library.

7. The method according to claim 6, characterized in that Each of the business types corresponds to a preset classification model, and the preset classification model is a model obtained by training an initial classification model based on positive sample data and reverse sample data. The positive sample data is sample business data with the same preset business type, and the reverse sample data is sample business data with a different preset business type from the positive sample data.

8. The method according to any one of claims 1 to 7, characterized in that Before screening out at least two terminals with the same service type from the multiple terminals, after acquiring service content data and service feature data of the multiple terminals, the method further includes: The service feature data is used as a keyword and the service content data is used as key information, and the service content data and service feature data of the multiple terminals are respectively stored in a database.

9. The method according to any one of claims 1 to 7, characterized in that The service feature data further includes: at least one of timestamp information, an identification SUPI of the terminal, and policy and charging control rule PCC information; The service type includes: at least one of a video service type, a voice service type, a data upload service type, a data download service type, and a live broadcast service type.

10. A method for managing multi-user data traffic, characterized in that: include: Acquire service content data and service feature data of a target terminal, wherein the service feature data includes a service type; Sending the service content data and service feature data of the target terminal to the network data analysis function entity; In response to the preset management policy fed back by the network data analysis function entity, the data traffic of the target terminal is managed according to the preset management policy, wherein the preset management policy is a policy that matches the business association of at least two terminals, and the at least two terminals include the target terminal.

11. The method according to claim 10, characterized in that The target terminal is communicatively connected with a user plane function entity, and the acquiring of service content data and service feature data of the target terminal includes: Based on the message subscription method, the user plane function entity obtains the data code stream of the target terminal connected to the communication interface; Parsing the data code stream of the target terminal to obtain service content data and service feature data of the target terminal; The managing the data traffic of the target terminal according to the preset management policy includes: The preset management policy is forwarded to the user plane function entity, so that the user plane function entity manages the data traffic of the target terminal according to the preset management policy.

12. An electronic device, characterized in that: include: one or more processors; A memory having one or more programs stored thereon, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the method for managing multi-user data traffic as described in any one of claims 1 to 9, or the method for managing multi-user data traffic as described in any one of claims 10 to 11.

13. A readable storage medium, characterized in that: The readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for managing multi-user data traffic as described in any one of claims 1 to 9, or the method for managing multi-user data traffic as described in any one of claims 10 to 11.

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