CN115103401A - Network traffic configuration method, system and device based on 5G multi-dimension - Google Patents
Network traffic configuration method, system and device based on 5G multi-dimension Download PDFInfo
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- CN115103401A CN115103401A CN202211023846.8A CN202211023846A CN115103401A CN 115103401 A CN115103401 A CN 115103401A CN 202211023846 A CN202211023846 A CN 202211023846A CN 115103401 A CN115103401 A CN 115103401A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/02—Traffic management, e.g. flow control or congestion control
- H04W28/0268—Traffic management, e.g. flow control or congestion control using specific QoS parameters for wireless networks, e.g. QoS class identifier [QCI] or guaranteed bit rate [GBR]
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W28/00—Network traffic management; Network resource management
- H04W28/16—Central resource management; Negotiation of resources or communication parameters, e.g. negotiating bandwidth or QoS [Quality of Service]
- H04W28/24—Negotiating SLA [Service Level Agreement]; Negotiating QoS [Quality of Service]
Abstract
The invention discloses a network flow configuration method based on 5G multi-dimension, which relates to the field of mobile communication, in particular to a network flow configuration method, a system and a device based on 5G multi-dimension; configuring a corresponding QoS template according to the determined service scene by determining the service scene of the user; determining corresponding GBR configuration in the QoS template according to the level information of the user, and distributing corresponding network flow to the user according to the GBR configuration; the method realizes the dynamic issuing of different QoS strategies, configures corresponding QoS templates according to different service scenes, and executes the issuing of corresponding strategy configuration when the user inquires whether the user is a subscriber or not from a signed data warehouse and meets the conditions when the user triggers the service; according to the network condition, various QoS guarantees such as region-based and service-specific channel establishment can be realized, and differentiated service quality guarantee can be more flexibly scheduled and implemented.
Description
Technical Field
The invention relates to the field of mobile communication, in particular to a network traffic configuration method, a system and a device based on 5G multi-dimension.
Background
With the development and application of 5G technology, the characteristics of high speed, low latency and large connection of 5G technology enable more vertical industries to be enabled by 5G, and meanwhile, the population dividend has gradually disappeared, so that the future 5G operation mode can be greatly different from the current 4G operation mode.
In the technical aspect, research and development investment of equipment suppliers and operators should be continuously increased, and the continuous development of the 5G technology is promoted. In the aspect of cost, an operator is guided by users, accurate deployment and maintenance optimization are carried out stage by stage, and the utilization rate of a base station is improved. In the aspect of application, operators need to adopt value management to promote application of the C terminal, lead the fusion of a CT scheme and an IT scheme, promote the application scale commercial of the early 5G industry, accelerate the maturation of a virtual private network and promote the application development of the industry.
PCC (Policy Control and Charging architecture) is a network element for Policy Control and Charging within a group of mobile communications. In the 5G core network architecture, a core Control network element of the PCC architecture is a PCF (Policy Control Function); the PCF is responsible for generating and issuing various policies, and the AMF (Access and Mobility Management Function) and the SMF (Session Management Function) are responsible for reporting the subscription information of the User and the real-time status of the network and the UE (User Equipment) to the PCF, and the PCF may synthesize the information reported by the AMF and the SMF and the policy of the operator to issue the final policy.
In the prior art, a QoS (Quality of Service) scheme based on PCC mainly provides differentiated services for different users or different services of the same user, and essentially defines priority to preempt resources, which cannot provide exact guarantee; even if GBR (Guaranteed Bit Rate) service is adopted, service experience cannot be Guaranteed under the condition of extreme congestion of a network.
Disclosure of Invention
The invention aims to avoid the defects in the prior art and provides a network flow configuration method which can meet differentiated services and guarantee the service experience of each user when the flow is congested.
The purpose of the invention is realized by the following technical scheme:
therefore, according to an aspect of the present disclosure, there is provided a method for configuring network traffic based on 5G multi-dimension, comprising the following steps:
determining a service scene of a user;
configuring a corresponding QoS template according to the determined service scene;
determining the level information of the user by calling the subscription user information in the subscription data warehouse;
determining corresponding GBR configuration in a QoS template according to the level information of the user, and distributing corresponding network flow to the user according to the GBR configuration;
wherein the GBR configuration comprises: and when the network is congested, accelerating or limiting the network flow of the user according to the level information of the user.
Specifically, the method for accelerating or limiting the network traffic of the user comprises the following steps:
and determining the service type corresponding to the service scene of the user, judging the service type, and judging the service type to be speed-limiting service or acceleration service.
More specifically, if the service is determined to be an acceleration service, the method includes the following acceleration determination steps:
determining the information of a local city where the user is located according to the IP address of the user;
judging whether the user is in a control city according to the city information, if so, not accelerating the acceleration service; and if not, generating an acceleration request.
More specifically, the acceleration determining step further includes the steps of:
calculating an acceleration request time difference: according to the acceleration log of the user, the time of an acceleration request sent by the user during the last acceleration is obtained; calculating the time difference between the current acceleration request and the acceleration request sent in the last acceleration;
and judging whether the acceleration request time difference is greater than a set time difference threshold value or not, and if so, initiating acceleration.
Specifically, if the speed limit service is determined, the method includes the following speed limit determination steps:
and judging whether the speed limit times of the user are more than or equal to a set daily speed limit time threshold or not according to the speed limit log of the user, and if so, not limiting the speed of the user.
Additionally, if the speed limit service is judged, the method comprises the following speed limit judging steps:
determining a cell where a user is located according to the IP address of the user, and acquiring the daily speed limit number of the user in the cell;
and judging whether the speed limit number of the day is more than or equal to the set speed limit number threshold of the day, if so, not limiting the speed of the user.
According to another aspect of the disclosure, a traffic configuration device of a network traffic configuration method based on 5G multi-dimension is provided, which includes: the system comprises a service identification module, a template setting module, a user identification module and a configuration module;
the service identification module is used for identifying a service scene and a service category corresponding to the service scene;
the template setting module is prestored with a QoS template and GBR configuration corresponding to the QoS template;
the user identification module is used for identifying the level information of the user;
the configuration module is used for determining corresponding GBR configuration in the QoS template according to the level information of the user and distributing corresponding network flow to the user according to the GBR configuration.
According to another aspect of the disclosure, a network traffic configuration system based on 5G multi-dimension is provided, where a PCC architecture is adopted, the PCC architecture includes a PCF, and the PCF is embedded with the above-mentioned traffic configuration device.
According to yet another aspect of the present disclosure, a computing device is provided, which includes a memory, a processor and computer instructions stored in the memory and executable on the processor, wherein the processor executes the instructions to implement the steps of the method for configuring network traffic based on 5G multi-dimension as above.
According to another aspect of the present disclosure, a computer readable storage medium is provided, which stores computer instructions that, when executed by a processor, implement the steps of the above 5G multi-dimension based network traffic configuration method.
The invention has the beneficial effects that: a network flow configuration method based on 5G multi-dimension determines the service scene of a user and configures a corresponding QoS template according to the determined service scene; determining the level information of the user by calling the subscribed user information in the signed data warehouse; determining corresponding GBR configuration in the QoS template according to the level information of the user, and distributing corresponding network flow to the user according to the GBR configuration; the method realizes the dynamic issuing of different QoS strategies, configures corresponding QoS templates according to different service scenes, and executes the issuing of corresponding strategy configuration when the user inquires whether the user is a subscriber or not from a signed data warehouse and meets the conditions when the user triggers the service; according to the network condition, various QoS guarantees such as region-based and service-specific channel establishment can be realized, and differentiated service quality guarantee can be more flexibly scheduled and implemented.
Drawings
The invention may be better understood by describing exemplary embodiments of the present disclosure in conjunction with the following drawings, in which:
FIG. 1 is a schematic flow chart of a method for configuring network traffic based on 5G multi-metrics according to an embodiment of the disclosure;
FIG. 2 is a schematic diagram of program modules of a flow configuration apparatus according to the disclosed embodiment of the invention;
FIG. 3 is a diagram illustrating a hardware configuration of a computing device according to an embodiment of the disclosure;
fig. 4 is a schematic diagram of a PCC architecture in accordance with a disclosed embodiment of the invention;
fig. 5 is a network architecture diagram of a 5G multi-dimension based network traffic configuration system according to an embodiment of the present disclosure.
Detailed Description
While specific embodiments of the invention will be described below, it should be noted that in the course of the detailed description of these embodiments, in order to provide a concise and concise description, all features of an actual implementation may not be described in detail. It should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions are often made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another. Moreover, it should be appreciated that such a development effort might be complex and tedious, but would nevertheless be a routine undertaking of design, fabrication, and manufacture for those of ordinary skill having the benefit of this disclosure, without departing from the scope of the present disclosure.
Unless otherwise defined, technical or scientific terms used in the claims and the specification should have the ordinary meaning as understood by those of ordinary skill in the art to which the invention belongs. The use of "first," "second," and similar terms in the description and in the claims of the present application does not denote any order, quantity, or importance, but rather the terms are used to distinguish one element from another. The terms "a" or "an," and the like, do not denote a limitation of quantity, but rather denote the presence of at least one. The word "comprise" or "comprises", and the like, means that the element or item listed before "comprises" or "comprising" covers the element or item listed after "comprising" or "comprises" and its equivalent, and does not exclude other elements or items. The terms "connected" or "coupled" and the like are not restricted to physical or mechanical connections, nor are they restricted to direct or indirect connections.
Example one
Referring to fig. 1, the present embodiment provides a method for configuring network traffic based on 5G multi-metrics, which is characterized by comprising the following steps:
s1: determining a service scene of a user;
s2: configuring a corresponding QoS template according to the determined service scene;
s3: determining the level information of the user by calling the subscribed user information in the signed data warehouse;
s4: determining corresponding GBR configuration in a QoS template according to the level information of the user, and distributing corresponding network flow to the user according to the GBR configuration;
wherein the GBR configuration comprises: and when the network is congested, accelerating or limiting the network flow of the user according to the level information of the user.
Specifically, when the occupied PRB (Physical Resource Block) is greater than 80% and the CCE (Channel Control Element) is less than 400W, it is determined that the network is congested.
In this embodiment, a QoS template is defined in an HSS (Home Subscriber Server), and a higher level ARP (Address Resolution Protocol) and a QCI (QoS Class Identifier, which are a scale value used for measuring a specific packet forwarding behavior provided for a service data stream, such as a packet loss rate and a packet delay budget) are configured. Because the QoS grade of the user is higher than that of the ordinary user, the transmission access delay and the resource allocation of the high-grade user in the network can be preferentially ensured, and therefore better service experience is obtained. Because the attribute is the attribute signed by the user, the access priority of the high-level user is always higher than that of the ordinary user at any time and any place.
Specifically, in this embodiment, the GBR configuration includes: a first GBR, a second GBR, a third GBR, and a fourth GBR; wherein the first GBR is more than the second GBR and more than the third GBR and more than or equal to the fourth GBR and less than or equal to the MBR; the mbr (maximum Bit rate) parameter is used to define the upper rate limit that GBR Bear can reach under the condition of sufficient resources.
The first GBR is set as a first-level ladder, only a small GBR is configured by means of the scheduling priority of the GBR load, so that when the network is congested, the network can meet the service requirements of the group people preferentially, and then the service requirements of other common users can be met by using the residual resources. The first GBR may be set to a minimum value, e.g. 1kbps, serving the user by means of the scheduling priority of the GBR bearer. The MBR is set to the user package rate upper limit.
The second GBR is set as a two-stage ladder and is used for distributing the first guaranteed special load QCI and configuring a larger GBR, so that when the network is congested, the network preferentially meets the service requirements of the group of people, and then the remaining resources are utilized to meet the service requirements of other common users. The second GBR setting can be set to 50kbps according to the service experience setting, so that the user can smoothly receive and send WeChat short messages, and can also be set to 2Mbps, so that the user can smoothly watch standard definition videos. The larger the second GBR setting, the smaller the number of high-end users that can be accommodated in the unit area. The MBR is set to the upper user package rate limit.
The third GBR is set as a two-stage ladder and used for distributing the second guaranteed special load QCI and configuring a larger GBR, the MBR correspondingly set is slightly larger than the third GBR, and the phenomenon that other user experiences are deteriorated due to part of factory scheduling reasons is avoided.
And the fourth GBR is set as a two-stage ladder and is used for distributing the third guaranteed special load QCI and configuring the GBR matched with the service, so that when the network is congested, the network guarantees the service requirements of the part of group people. Wherein, the service can not be provided by the service with the rate larger than the MBR.
Wherein the user level includes: common users, first level users, second level users and third level users; the first GBR, the second GBR, the third GBR and the fourth GBR respectively correspond to a common user, a first-level user, a second-level user and a third-level user.
According to different service quality scenes, corresponding QoS and GBR templates are configured in the PCF, when a user triggers a service, the PCF inquires whether the user is a subscription user or not (namely, the user level is confirmed) from the UDR, and the PCF executes and issues corresponding policy configuration according to the conditions. By a dynamic mode, various QoS and acceleration guarantees such as region-based establishment of a service dedicated channel and the like can be realized according to the condition of a network, and differentiated service quality guarantee can be more flexibly scheduled and implemented.
Specifically, in the step S4, the accelerating or speed limiting of the network traffic of the user includes the following steps:
and determining the service type corresponding to the service scene of the user, judging the service type, and judging the service type to be speed-limiting service or acceleration service.
Further, in the step S4, it is determined whether to initiate acceleration according to the current time, the service type, the level information of the user, and the IP address; or judging whether to initiate speed limit according to the application type, the level information of the user, the daily speed limit times and the number of the community daily speed limit persons.
If the acceleration service is judged, the method comprises the following acceleration judgment steps:
s10: judging whether the user is a user allowed to accelerate or not according to the level information of the user, and if so, entering the next step; if not, not accelerating the acceleration service;
s11: judging whether the current time period is an acceleration time period or not, if so, entering the next step; if not, not accelerating the acceleration service;
s12: determining the information of a local city where the user is located according to the IP address of the user;
s13: judging whether the user is in a control city according to the city information, if so, not accelerating the acceleration service; if not, generating an acceleration request;
s14: calculating an acceleration request time difference: according to the acceleration log of the user, the time of an acceleration request sent by the user during the last acceleration is obtained; calculating the time difference between the current acceleration request and the acceleration request sent in the last acceleration;
s15: judging whether the acceleration request time difference is greater than a set time difference threshold value or not, and if so, initiating acceleration;
specifically, if the time difference of the acceleration request is less than 20S (the first time difference threshold), it is determined that the request is too frequent, and the acceleration service is not accelerated; if the time difference of the acceleration request is greater than 20S (the first time difference threshold value) and less than 2760S (the second time difference threshold value), judging that the user is in an acceleration state, and not performing new operation on the user; if the time difference of the acceleration request is greater than 2760S (a second threshold), initiating acceleration;
more specifically, acceleration is realized by configuring a guaranteed dedicated load QCI corresponding to the user level;
s16: according to the judgment result of the step S15, the acceleration log of the user is updated.
If the speed limit service is judged, the method comprises the following speed limit judging steps:
s20: judging whether the user is a user allowed to limit the speed or not according to the level information of the user, and if so, entering the next step; if not, the speed limit service is not limited;
s21: judging whether the speed limit times of the user are greater than or equal to a set daily speed limit time threshold or not according to the speed limit log of the user, and if so, not limiting the speed of the user; if not, entering the next step;
s22: determining a cell where a user is located according to the IP address of the user, and acquiring the daily speed limit number of the user in the cell;
s23: judging whether the number of the speed-limited people per day is more than or equal to a set threshold value of the number of the speed-limited people per day, if so, not limiting the speed of the user, and if not, initiating the speed limitation;
s24: and updating the speed limit log of the user according to the judgment result of the step S23.
Referring to fig. 2, a flow configuration device is shown, in this embodiment, a flow configuration device may include or be divided into one or more program modules, and the one or more program modules are stored in a storage medium and executed by one or more processors to implement the present invention and implement the above-mentioned network flow configuration method based on 5G multi-metrics. The program modules referred to herein may be a series of computer program instruction segments that perform particular functions and may be more suitable than the program itself for describing the execution of a flow configuration device on a storage medium. The following description will specifically describe the functions of the program modules of the present embodiment:
the service identification module is used for identifying the service scene and the service category corresponding to the service scene.
The template setting module is prestored with a QoS template and GBR configuration corresponding to the QoS template.
The user identification module is used for identifying the level information of the user.
The configuration module is used for determining corresponding GBR configuration in the QoS template according to the level information of the user, issuing a corresponding execution instruction according to the GBR configuration and the current network state (whether congestion occurs), and distributing corresponding network flow for the user.
A network flow configuration system based on 5G multi-dimension adopts a PCC architecture, the PCC architecture comprises a PCF, and the PCF is internally provided with the flow configuration device. Specifically, as shown in fig. 4, the PCC architecture further includes the following functional modules: application function, network data analysis function, unified data storage, network opening function, charging function, access and mobility management function, session management function, and user plane function.
As shown in fig. 5, in this embodiment, a specific network traffic configuration flow is as follows:
1. a user (a user in the province, an OTT user or a roaming user) jumps to an acceleration interface of an intelligent acceleration APP through an APP (application program) and requests acceleration aiming at a specified application (namely a corresponding service scene);
2. the intelligent acceleration APP initiates authentication information to a BOSS (service operation support system), the BOSS confirms whether a user orders an acceleration service (namely confirms the user level of the user), and if the authentication is not passed, the user jumps to an ordering interface; if the authentication is passed, the intelligent acceleration APP is informed to allow the user to accelerate;
3. the intelligent acceleration APP initiates an acceleration request to an acceleration Control system AAC (Application Access Control) through a public network, and carries TCP service flow and user parameters which need to be accelerated by a user;
4. the AAC performs RESTful-to-RX conversion, then sends DRA (Diameter Routing Agent, Routing Agent node), and forwards the DRA to PCRF (or PCF) where the user is located through a session binding function;
5. an AAC platform of the acceleration control system acquires a PCRF (policy and charging rules Function) where a User is located by inquiring UPF (User Plane Function), and transfers the PCRF to a home PCRF for special load establishment through DRA;
the PCRF calculates an acceleration strategy according to AAC report information of an acceleration control system, and issues a Gx message carrying QCI =3\ ARP \ MBR \ GBR and other bandwidth rules to UPF for carrying out special load guarantee on the service flow which needs to be accelerated by the user;
7. through mutual negotiation and confirmation of the UPF, the Enode-B and the terminal, the establishment of a special-load resource acceleration pipeline with QCI =3 is finally completed aiming at the service designated by the user;
8. and the low-delay guarantee of the user specified service is realized.
The embodiment also provides a computing device, such as a smart phone, a tablet computer, a notebook computer, a desktop computer, a rack server, a blade server, a tower server or a rack server (including an independent server or a server cluster composed of a plurality of servers) capable of executing programs, and the like. The computing device 20 of the present embodiment includes at least, but is not limited to: a memory 21, a processor 22, which may be communicatively coupled to each other via a system bus, as shown in FIG. 3. It is noted that FIG. 3 only shows computing device 20 having components 21-22, but it is understood that not all of the shown components are required to be implemented, and that more or fewer components may alternatively be implemented.
In the present embodiment, the memory 21 (i.e., a readable storage medium) includes a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, and the like. In some embodiments, the storage 21 may be an internal storage unit of the computing device 20, such as a hard disk or a memory of the computing device 20. In other embodiments, the memory 21 may also be an external storage device of the computing device 20, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card), or the like, provided on the computing device 20. Of course, memory 21 may also include both internal and external storage devices for computing device 20. In this embodiment, the memory 21 is generally used for storing an operating system and various application software installed on the computing device 20, such as a program code of a flow configuration apparatus of the first embodiment. Further, the memory 21 may also be used to temporarily store various types of data that have been output or are to be output.
The present embodiment also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a Random Access Memory (RAM), a Static Random Access Memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application mall, etc., on which a computer program is stored, which when executed by a processor implements corresponding functions. The computer readable storage medium of this embodiment is used to store a traffic configuration device, and when executed by a processor, the traffic configuration device implements a network traffic configuration method based on 5G multi-dimension according to the first embodiment.
In summary, according to the exemplary embodiment, the present invention implements differentiated user experience through a GBR and QCI combined scheme, designs a user-level bandwidth scheduling priority mechanism according to a QoS scheduling mechanism, provides high-quality services for limited high-end users, provides an ultra-fast internet service, and ensures an experience rate of users, and meanwhile, optimizes user delay to a certain extent by limiting the total number of high-end users in the same area, and the existing device can support related configuration, and has low optimization cost.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and alternate implementations are included within the scope of the preferred embodiment of the present invention in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the present invention.
It will be understood by those skilled in the art that all or part of the steps carried out in the method of implementing the above embodiments may be implemented by hardware related instructions of a program, which may be stored in a computer readable medium, and the program, when executed, includes one or a combination of the steps of the method embodiments.
In the description of the specification, reference to the description of "one embodiment," "some embodiments," "an example," "a specific example" or "some examples" or the like means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the scope of the present invention, and all equivalent structures or equivalent processes performed by the present invention or directly or indirectly applied to other related technical fields are also included in the scope of the present invention.
Claims (10)
1. A network flow configuration method based on 5G multi-dimension is characterized by comprising the following steps:
determining a service scene of a user;
configuring a corresponding QoS template according to the determined service scene;
determining the level information of the user by calling the subscribed user information in a signed data warehouse;
determining corresponding GBR configuration in the QoS template according to the level information of the user, and allocating corresponding network flow to the user according to the GBR configuration;
wherein the GBR configuration comprises: and when the network is congested, accelerating or limiting the network flow of the user according to the level information of the user.
2. The method according to claim 1, wherein the step of accelerating or limiting the network traffic of the user comprises the following steps:
and determining the service type corresponding to the service scene of the user, judging the service type and judging the service type to be speed-limiting service or acceleration service.
3. The method according to claim 2, wherein if the service is determined to be an acceleration service, the method comprises the following acceleration determining steps:
determining the information of a local city where the user is located according to the IP address of the user;
judging whether the user is in a control city according to the city information, if so, not accelerating the acceleration service; and if not, generating an acceleration request.
4. The method according to claim 3, wherein the accelerating step further comprises the steps of:
calculating an acceleration request time difference: according to the acceleration log of the user, the time of an acceleration request sent by the user during the last acceleration is obtained; calculating the time difference between the current acceleration request and the acceleration request sent in the last acceleration;
and judging whether the acceleration request time difference is larger than a set time difference threshold value, and if so, initiating acceleration.
5. The method for configuring network traffic based on 5G multi-dimension as claimed in claim 2, wherein if it is determined to be a speed limit service, the method comprises the following speed limit determining steps:
and judging whether the speed limit times of the user are more than or equal to a set daily speed limit time threshold or not according to the speed limit log of the user, and if so, not limiting the speed of the user.
6. The method for configuring network traffic based on 5G multi-dimension according to claim 2 or 5, wherein if the traffic is determined to be a speed limit service, the method comprises the following speed limit determination steps:
determining a cell where a user is located according to the IP address of the user, and acquiring the daily speed limit number of the cell;
and judging whether the speed limit number of the day is more than or equal to a set speed limit number threshold of the day, if so, not limiting the speed of the user.
7. A traffic configuration apparatus adopting the 5G multi-dimension based network traffic configuration method according to any one of claims 1 to 6, comprising: the system comprises a service identification module, a template setting module, a user identification module and a configuration module;
the service identification module is used for identifying a service scene and a service category corresponding to the service scene;
the template setting module is prestored with a QoS template and GBR configuration corresponding to the QoS template;
the user identification module is used for identifying the level information of the user;
the configuration module is used for determining corresponding GBR configuration in the QoS template according to the level information of the user and distributing corresponding network flow to the user according to the GBR configuration.
8. A system for configuring network traffic based on 5G multi-dimension, which employs a PCC architecture, wherein the PCC architecture includes a PCF having the traffic configuration apparatus of claim 7 built therein.
9. A computing device comprising a memory, a processor and computer instructions stored on the memory and executable on the processor, wherein the processor when executing the instructions implements the steps of the method of any one of claims 1 to 6.
10. A computer-readable storage medium storing computer instructions, which when executed by a processor, perform the steps of the method of any one of claims 1 to 6.
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