Charging configuration optimization method and device, nonvolatile storage medium and electronic equipment

Abstract

The invention discloses a charging configuration optimization method and device, a nonvolatile storage medium and electronic equipment. The method comprises the following steps: obtaining website access data and initial charging configuration data of a network element in a charging system, the website access data comprising user access information of a plurality of websites in a preset time period; determining a mergeable configuration rule set in the initial charging configuration data, and merging the mergeable configuration rules in the mergeable configuration rule set to obtain first charging configuration data; determining a priority ranking result of the plurality of websites according to the website access data; and according to the priority ranking result of the plurality of websites, adjusting the ranking sequence of the plurality of websites in the first charging configuration data to obtain second charging configuration data. According to the content charging method and device, the technical problem that the content charging process consumes long time due to the fact that redundant charging configuration exists in the mobile gateway and part of websites cannot be matched with corresponding charging configuration rules in time is solved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of mobile communication, in particular to a charging configuration optimization method and device, a nonvolatile storage medium and an electronic device. BACKGROUND

[0002] In related technologies, when content charging is performed on related websites in a mobile communication network, the charging rules corresponding to different websites may have repeated contents, resulting in redundancy of charging configurations in a mobile gateway. Moreover, due to a large number of websites, some popular websites may not be able to match the corresponding charging configuration rules in the gateway in time. Both of the above result in a long time consumption when content charging is performed in the current mobile communication network.

[0003] At present, no effective solution has been proposed for the above problems. SUMMARY

[0004] Embodiments of the present application provide a charging configuration optimization method and device, a nonvolatile storage medium and an electronic device to at least solve the technical problem of long time consumption of content charging due to redundant charging configurations in a mobile gateway and the inability of some websites to match the corresponding charging configuration rules in time.

[0005] According to an aspect of an embodiment of the present application, a charging configuration optimization method is provided, comprising: obtaining website access data and initial charging configuration data of a network element in a charging system, wherein the website access data includes user access information of a plurality of websites in a preset time period; determining a set of mergable configuration rules in the initial charging configuration data, and performing merging processing on the mergable configuration rules in the set of mergable configuration rules to obtain first charging configuration data; determining a priority ranking result of the plurality of websites according to the website access data; and adjusting the arrangement order of the plurality of websites in the first charging configuration data according to the priority ranking result of the plurality of websites to obtain second charging configuration data.

[0006] Optionally, the step of determining the priority ranking result of the plurality of websites according to the website access data comprises: determining the access frequency and access traffic of the plurality of websites according to the website access data; performing a primary sorting on the plurality of websites according to the access frequency interval in which the access frequency of the plurality of websites is located to obtain a primary sorting result; and performing a secondary sorting on the websites corresponding to the same access frequency interval according to the access traffic of the websites corresponding to the same access frequency interval to obtain the priority ranking result.

[0007] Optionally, the step of determining the priority ranking result of the plurality of web addresses according to the web address access data comprises: determining first address information and second address information of the plurality of web addresses; determining a first information gain index between the web address access data and the first address information, and a second information gain index between the web address access data and the second address information, wherein the web address access data comprises at least one of the following: access times, access duration, traffic size, and user number; performing weighted summation on the first information gain index and the second information gain index to obtain a comprehensive gain index of the plurality of web addresses; and determining the priority ranking result of the plurality of web addresses according to the comprehensive gain index, wherein the smaller the comprehensive gain index is, the higher the priority is.

[0008] Optionally, the step of determining the set of mergable configuration rules in the initial charging configuration data comprises: determining a set of mergable configuration rule determination manners corresponding to protocol levels; and determining the set of mergable configuration rules in the configuration rules of each level corresponding to the initial charging configuration set according to the set of mergable configuration rule determination manners.

[0009] Optionally, before the step of determining the set of mergable configuration rules in the initial charging configuration data, the method further comprises: obtaining charging work order data; determining first charging configuration logic of the charging work order data and second charging configuration logic of the initial charging configuration data; and auditing the initial charging data according to the first charging configuration logic or the second charging configuration logic.

[0010] Optionally, the step of auditing the initial charging data according to the first charging configuration logic or the second charging configuration logic comprises: auditing the initial charging configuration data according to the first charging configuration logic to determine whether the initial charging configuration data and the first charging configuration logic match; and determining whether the initial charging data in each network element is consistent according to the second charging configuration logic.

[0011] Optionally, the method further comprises: obtaining service information list data in a preset time period, wherein the service information list data comprises charging configuration data corresponding to services processed in the preset time period; determining redundant configuration data in the second charging configuration data according to the service information list data, wherein the redundant configuration data is charging configuration data that does not appear in the service information list data; and deleting the redundant configuration data in the second charging configuration data to obtain third charging configuration data.

[0012] According to a further aspect of the embodiments of the present application, a charging configuration optimization apparatus is provided, comprising: a first processing module configured to acquire website access data and initial charging configuration data of network elements in a charging system, wherein the website access data comprises user access information of a plurality of websites in a preset time period; a second processing module configured to determine a set of mergable configuration rules in the initial charging configuration data, and perform merging processing on the mergable configuration rules in the set of mergable configuration rules to obtain first charging configuration data; a third processing module configured to determine a priority ranking result of the plurality of websites according to the website access data; and a fourth processing module configured to adjust the order of the plurality of websites in the first charging configuration data according to the priority ranking result of the plurality of websites to obtain second charging configuration data.

[0013] According to a further aspect of the embodiments of the present application, a nonvolatile storage medium is provided, wherein the nonvolatile storage medium stores a program, and the program controls a device in which the nonvolatile storage medium is located to perform a charging configuration optimization method when the program is executed.

[0014] According to a further aspect of the embodiments of the present application, an electronic device is provided, comprising a memory and a processor, wherein the processor is configured to execute a program stored in the memory, and the program performs a charging configuration optimization method when the program is executed.

[0015] According to a further aspect of the embodiments of the present application, a computer program product is provided, comprising a computer program, and the computer program implements a charging configuration optimization method when executed by a processor.

[0016] In the embodiments of the present application, the website access data and the initial charging configuration data of network elements in a charging system are acquired, wherein the website access data comprises user access information of a plurality of websites in a preset time period; a set of mergable configuration rules in the initial charging configuration data is determined, and merging processing is performed on the mergable configuration rules in the set of mergable configuration rules to obtain first charging configuration data; a priority ranking result of the plurality of websites is determined according to the website access data; and the order of the plurality of websites in the first charging configuration data is adjusted according to the priority ranking result of the plurality of websites to obtain second charging configuration data. In this way, the mergable configuration rules are merged to reduce redundant configurations, and the order of the websites is adjusted to avoid that a website with high priority cannot be matched to a corresponding charging configuration rule in time, so that the charging efficiency is improved, thereby achieving the technical effect of reducing the time length of a content charging process, and further solving the technical problem of long time consumption of a content charging process due to redundant charging configurations in a mobile gateway and a website that cannot be matched to a corresponding charging configuration rule in time. BRIEF DESCRIPTION OF DRAWINGS

[0017] The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application. In the drawings:

[0018] Figure 1 is a structural schematic diagram of a computer terminal (mobile device) according to an embodiment of the application;

[0019] Figure 2 is a flowchart of a charging configuration optimization method according to an embodiment of the application;

[0020] Figure 3 is a flowchart of a content charging work order data processing method according to an embodiment of the application;

[0021] Figure 4 is a flowchart of a live network configuration data processing method in a gateway according to an embodiment of the application;

[0022] Figure 5 is a process diagram of a configuration data auditing process based on work order data according to an embodiment of the application;

[0023] Figure 6 is a process diagram of a configuration data auditing process based on configuration data according to an embodiment of the application;

[0024] Figure 7 is a process diagram of a configuration optimization scheme determination process according to an embodiment of the application;

[0025] Figure 8 is a process diagram of a charging configuration rule merging optimization process according to an embodiment of the application;

[0026] Figure 9 is a process diagram of a website sorting optimization process according to an embodiment of the application;

[0027] Figure 10 is a process diagram of a redundant charging configuration rule deletion process according to an embodiment of the application;

[0028] Figure 11 is a process diagram of a verification process according to an embodiment of the application;

[0029] Figure 12 is a diagram of a comparison result according to an embodiment of the application;

[0030] Figure 13 is a flowchart of a charging configuration optimization and verification process according to an embodiment of the application;

[0031] Figure 14 Figure 1 is a structural schematic diagram of a charging configuration optimization device according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] In order to enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work should fall within the scope of protection of the present application.

[0033] It should be noted that the terms "first", "second", and the like in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily indicate a specific order or a chronological sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or device that includes a series of steps or units does not necessarily have to be limited to those steps or units clearly listed, but can include other steps or units that are not clearly listed or inherent to the process, method, product, or device.

[0034] In order to better understand the embodiments of the present application, the technical terms involved in the embodiments of the present application are explained as follows:

[0035] GGSN (Gateway GPRS Support Node, GPRS gateway support node): a network element in a 2G / 3G network, responsible for processing data transmission between a mobile device and the Internet.

[0036] PGW (Packet Data Network Gateway, packet data network gateway): a network element in a 4G LTE network, responsible for processing data transmission between a mobile device and the Internet, providing IP address allocation, user authentication, traffic control, policy management, and other functions.

[0037] UPF (User Plane Function, user plane function): a network element in a 5G network, responsible for processing data transmission between a mobile device and the Internet, providing data packet forwarding, traffic control, load balancing, and other functions.

[0038] DPI (Deep Packet Inspection): a technology for in-depth analysis of network packets, which can check and analyze the content of the packets in detail.

[0039] URL (Uniform Resource Locator): a uniform resource locator used to identify and locate resources on the Internet, including protocol, host name, port number, path and query parameters, etc. Through the URL, you can access and obtain specific resources.

[0040] Information gain method: Gini index is an index to measure the purity or uncertainty of a data set. In binary classification problems, the Gini index measures the probability that two randomly selected samples from the data set have different class labels. The Gini index ranges from 0 to 0.5, and the closer the value is to 0, the higher the purity of the data set.

[0041] As the operator's business continues to develop, there are more and more charging rules for specific content, and the configuration of mobile gateway for sensing business and packet detection is becoming more and more large, the configuration audit is difficult, the charging marking overhead is high, and the system resource occupation is more and more prominent. In order to improve the data checking efficiency and reduce the system load, it is urgent to build an intelligent optimization content charging configuration system.

[0042] In order to solve the above problems, the related solutions are provided in the embodiments of the present application, which are described in detail below.

[0043] According to the embodiments of the present application, a method embodiment of a charging configuration optimization method is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a group of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from here.

[0044] The method embodiment provided by the embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar operation device. Figure 1 A hardware structure block diagram of a computer terminal (or mobile device) for implementing the charging configuration optimization method is shown. As shown in Figure 1As shown, the computer terminal 10 (or mobile device 10) can include one or more processors 102 (the processor 102 can include, but not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it can also include a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which can be included as one of the ports of the BUS bus), a network interface, a power supply and / or a camera. Those skilled in the art can understand that Figure 1 The structure shown is only schematic, which does not limit the structure of the above-mentioned electronic device. For example, the computer terminal 10 can include more or fewer components than those shown in Figure 1 or have a different configuration than that shown in Figure 1 .

[0045] It should be noted that the one or more processors 102 and / or other data processing circuits described above can be referred to herein as "data processing circuits" in general. The data processing circuit can be embodied in whole or in part as software, hardware, firmware or any other combination. In addition, the data processing circuit can be a single independent processing module, or any one of the other elements incorporated into the computer terminal 10 (or mobile device) in whole or in part. As referred to in the embodiments of the present application, the data processing circuit serves as a processor control (for example, selection of a variable resistance terminal path connected to an interface).

[0046] The memory 104 can be used to store software programs and modules of application software, such as program instructions / data storage means corresponding to the billing configuration optimization method in the embodiments of the present application. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, that is, implements the billing configuration optimization method described above. The memory 104 can include a high-speed random access memory, and can also include a non-volatile memory such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 104 can further include a memory remotely disposed with respect to the processor 102, which can be connected to the computer terminal 10 through a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network and a combination thereof.

[0047] The transmission device 106 is configured to receive or send data via a network. The network can include a wireless network provided by a communication provider of the computer terminal 10. In one example, the transmission device 106 includes a network interface controller (NIC) that can be connected to other network devices through a base station to communicate with the Internet. In one example, the transmission device 106 can be a radio frequency (RF) module that is configured to communicate with the Internet wirelessly.

[0048] The display can be a liquid crystal display (LCD) that is touch screen type, for example, which can enable a user to interact with a user interface of the computer terminal 10 (or a mobile device).

[0049] In the above operating environment, the embodiments of the present application provide a charging configuration optimization method, as shown in the following. Figure 2 The method includes the following steps:

[0050] In step S202, the website access data and initial charging configuration data of the network element in the charging system are obtained, wherein the website access data includes user access information of a plurality of websites in a preset time period.

[0051] In some embodiments of the present application, before determining the set of mergable configuration rules in the initial charging configuration data, the method further includes: obtaining charging work order data; determining first charging configuration logic of the charging work order data and second charging configuration logic of the initial charging configuration data; and auditing the initial charging data according to the first charging configuration logic or the second charging configuration logic.

[0052] As an optional implementation, the charging work order data includes local data work order data of a to-be-audited content charging service, and the initial charging configuration data includes charging configuration data of a mobile data gateway GGSN / PGW / UPF. The network element in the charging system includes the mobile data gateway GGSN / PGW / UPF.

[0053] In some embodiments of the present application, the above-mentioned local data work order data refers to a core data carrier related to the operator content billing configuration, used to record business configuration requirements and change instructions, covering two types of work orders: content billing business change work order and content billing business addition work order. Such data needs to be obtained through automated collection, and after collection, it will be structured and parsed according to specific rules, which specifically includes parsing the addition / deletion of IP (IPv4 / IPv6) content, the addition / deletion of HOST content, and the addition / deletion of URL content, respectively, and synchronously constructing change work order data Rule to standardize the parsing standard, and finally forming IPv4 work order final state data, IPv6 work order final state data, HOST work order final state data, URL work order final state data, etc.

[0054] As an optional implementation, the billing work order data and configuration data can be structured and parsed according to the content billing configuration logic of different manufacturers.

[0055] The processing method of content billing work order data and other billing work order data in some embodiments of the present application is as shown in Figure 3 As shown in

[0056] In some embodiments of the present application, the initial billing configuration data is also called the existing network configuration data. As shown in Figure 4As shown, in processing the live network configuration data, firstly, the original configuration files of three types of core network elements, GGSN configuration data, PGW configuration data and UPF configuration data, are acquired through collection. Then, the collected configuration files are analyzed in a targeted manner. For GGSN configuration data and PGW configuration data, the APN (Access Point Name) content charging L3 / 4 layer IPv4 address, port, protocol, IPv6 address, port, protocol and HOST information are analyzed. For UPF configuration data, in addition to analyzing the related information of APN content charging L3 / 4 layer, the L7 layer URL and HOST information are also analyzed. Finally, the analysis results are converted into structured data of each network element at the APN level, specifically including APN content charging L3 / 4 layer IPv4 address, port, protocol structured data, L3 / 4 layer IPv6 address, port, protocol structured data, L3 / 4 layer HOST structured data and L7 layer URL, HOST structured data, thereby providing standardized live network configuration data support for subsequent configuration auditing, configuration optimization and other links.

[0057] In some embodiments of the present application, auditing the initial charging data according to the first charging configuration logic or the second charging configuration logic comprises: auditing the initial charging configuration data according to the first charging configuration logic to determine whether the initial charging configuration data and the first charging configuration logic match; and determining whether the initial charging data in each network element is consistent according to the second charging configuration logic.

[0058] In some embodiments of the present application, the process of auditing the initial charging configuration data according to the first charging configuration logic comprises: Figure 5The process is shown. The process first separately carries out content billing work order data processing and live network configuration data processing. In the content billing work order data processing, content billing service change work orders and service addition work orders are first collected, and then the work order data is parsed and a change work order data rule is constructed to generate IPv4 work order final state data, IPv6 work order final state data, HOST work order final state data, URL work order final state data, combined with user subscription APN data and blacklist and whitelist data. In the live network configuration data processing, configuration data of GGSN, PGW and UPF are collected, and structured data of each network element at the APN level is obtained by parsing the configuration file, including APN content billing L3 / 4 layer IPv4 address, port and protocol, IPv6 address, port and protocol, HOST and L7 layer URL and HOST structured data. Then, based on the first billing configuration logic obtained by parsing the work order content billing data, IPv4 content billing inspection, IPv6 content billing inspection, HOST content billing inspection and URL content billing inspection are carried out respectively to complete full-amount APN dimension content billing consistency check and single-user dimension content billing consistency check, and finally the inspection result is output.

[0059] Optionally, the standard for passing the inspection is that in the IPv4 content billing inspection, the APN dimension and single-user dimension IPv4 work order final state data in the parsed work order content billing data are completely consistent with the APN content billing L3 / 4 layer IPv4 address, port and protocol structured data of the corresponding APN and user in the live network configuration data, without address loss, port error or protocol mismatch; in the IPv6 content billing inspection, the IPv6 work order final state data on the work order side is completely consistent with the L3 / 4 layer IPv6 address, port and protocol structured data of the corresponding dimension on the live network side, without format inconsistency or value conflict; in the HOST content billing inspection, the HOST work order final state data on the work order side is completely consistent with the L3 / 4 layer and L7 layer HOST structured data of the corresponding dimension on the live network side, without HOST name error or association rule mismatch; in the URL content billing inspection, the URL work order final state data on the work order side is completely consistent with the L7 layer URL structured data of the corresponding dimension on the live network side, without URL address loss or format difference; at the same time, under the full-amount APN dimension, there is no difference in the above four types of inspection results corresponding to all APNs, and under the single-user dimension, there is also no difference in the above four types of inspection results corresponding to the user subscription APN association, and there is no conflict with the blacklist and whitelist data. If all the above conditions are met, it is determined that the inspection is passed.

[0060] In some embodiments of the present application, the process of determining whether the initial charging data in each network element is consistent according to the second charging configuration logic is as shown in Figure 6 As shown in the figure. The process first processes the existing network configuration data, collects the configuration data of GGSN, PGW and UPF, and then performs configuration file parsing to form structured data of each network element at the APN level, covering structured data of APN content charging L3 / 4 layer IPv4 address, port and protocol, IPv6 address, port and protocol, HOST and L7 layer URL and HOST. Then, taking the APN dimension as the core, the content charging data on all PGW / UPF is merged and processed to build a unified charging configuration audit benchmark in this dimension. Then, taking the benchmark as a reference, the content charging data of each PGW / UPF network element after parsing is compared one by one, and it is checked whether the information of each network element on the configuration items of L3 / 4 layer IPv4, IPv6, HOST and L7 layer URL, HOST is consistent, and at the same time, the user subscription APN data and blacklist data are combined to assist the checking, the full-amount APN dimension content charging consistency checking and single-user dimension content charging consistency checking are carried out, and finally the audit result is output to determine whether the content charging configurations of all PGW / UPF network elements in the same APN dimension are consistent.

[0061] Optionally, if the charging work order data under the same APN can completely cover the required configuration dimension and there is no field conflict, it is determined that the charging work order data and the second charging configuration logic match, and the audit passes. If there is a missing configuration dimension (such as missing some address or protocol information) or data conflict, it is determined that they do not match.

[0062] In some embodiments of the present application, for the work order data-based audit process (such as the audit process based on charging work order data), it also includes determining whether the initial charging configuration data and the first charging configuration logic match means that the charging work order data (including IPv4 work order final state data, IPv6 work order final state data, HOST work order final state data, URL work order final state data, and other structured data) parsed according to the logic is consistent with the corresponding APN content charging L3 / 4 layer (IPv4 address, port, protocol, IPv6 address, port, protocol, HOST) and L7 layer (URL, HOST) information in the initial charging data (existing network configuration data of mobile data gateway GGSN / PGW / UPF) to be audited, without differences such as field missing, value error, format inconsistency, and meeting the integrity requirements of customer demand configuration.

[0063] In some embodiments of the present application, as shown in Figure 7As shown, after the audit is completed, the user behavior of the DPI big data can be analyzed to obtain the frequently accessed websites and the long-term non-user accessed websites, and obtain the website access data. When obtaining the initial charging configuration data, the configuration data of the GGSN / PGW / UPF can be analyzed to obtain the main information of different terms. The term refers to the charging configuration rule in the charging configuration data. Then, the website can be sorted according to the service priority, and at least one of the sorting result and the term information is obtained to obtain three optimization schemes, which are a term merging optimization scheme, a content sorting optimization scheme and a redundant deletion optimization scheme. Then, the optimization schemes are executed.

[0064] In step S204, a set of mergable configuration rules in the initial charging configuration data is determined, and the mergable configuration rules in the set of mergable configuration rules are merged to obtain first charging configuration data.

[0065] In the technical scheme provided in step S204, determining the set of mergable configuration rules in the initial charging configuration data includes: determining a set of mergable configuration rules corresponding to a protocol level determination manner; and determining the set of mergable configuration rules in the configuration rules of each level corresponding to the initial charging configuration set according to the set of mergable configuration rules determination manner.

[0066] Optionally, different merging rules can be used for different levels. For example, for L7, the charging rules with the same URL, IP address, data with blank,: three different formats, or two formats, one of which is the charging rule with the end of are merged. For L3 and L4, the terms associated with multiple three-layer addresses / address masks corresponding to the same website code can be merged into one term.

[0067] In some embodiments of the present application, the merging optimization process of the charging configuration rule is as follows: Figure 8 ​As shown. For L3 and L4 layer data, which includes key information such as service codes, service commands, IP addresses (IPv4 and IPv6 addresses), protocol numbers, port numbers, APN names, BW types, manufacturers, and network element IPs, the merging process is based on the core criteria of "same service, same rule type, and same call relationship." Multiple Layer 3 addresses / address mask data corresponding to the same service code are integrated into the same term to generate L3 and L4 layer term merging scheme data. For L7 layer data, which covers information such as APN names, BW types, manufacturers, network element IPs, network element names, URL addresses, and manufacturer command arrangements, the merging process focuses on the format characteristics of the same URL or IP address, merging those that meet specific format conditions (such as the presence of spaces, colons, etc.). / Three ending formats, or two formats, one of which is / Data from the same URL / IP address (ending) is merged into a single term to generate L7 layer term merging scheme data. Finally, considering the different network element configuration characteristics and instruction arrangement requirements of vendors A and B, the merging results of L3 and L4 layers are integrated with those of L7 layer to form a complete term merging optimization scheme, thereby reducing the number of terms.

[0068] Step S206: Determine the priority ranking of multiple URLs based on the URL access data;

[0069] In the technical solution provided in step S206, determining the priority ranking result of multiple URLs based on URL access data includes: determining the access frequency and access traffic of multiple URLs based on URL access data; performing an initial ranking of multiple URLs based on the access frequency intervals in which the access frequencies of multiple URLs fall, to obtain an initial ranking result; and for URLs corresponding to the same access frequency interval, re-ranking the URLs corresponding to the same access frequency interval based on the access traffic of the URLs, to obtain a priority ranking result.

[0070] Optionally, for a preset time period (such as within one month), the business frequency / traffic statistics table of each website can be used to first classify and sort the business frequency in intervals of 1%, then sort the business frequency intervals by traffic volume, and output the priority sorting results.

[0071] In some embodiments of the present application, the priority ranking result of the plurality of websites is determined according to the website access data, including: determining first address information and second address information of the plurality of websites; determining a first information gain index between the website access data and the first address information, and a second information gain index between the website access data and the second address information, wherein the website access data includes at least one of the following: access times, access duration, traffic size, and user number; performing weighted summation on the first information gain index and the second information gain index to obtain a comprehensive gain index of the plurality of websites; and determining the priority ranking result of the plurality of websites according to the comprehensive gain index, wherein the smaller the comprehensive gain index is, the higher the priority is.

[0072] In some embodiments of the present application, the first address information includes the IP of the website, and the second address information includes the URL of the website. The first information gain index and the second information gain index, that is, the Gini index, can be calculated by the following formula respectively.

[0073]

[0074]

[0075] In the above formula, D: refers to a service-related data set used for calculation, specifically a data set containing the association relationship between the service IP, URL and the four variables of "usage times, usage duration, traffic size, and user number";

[0076] k: represents the index of the category to which the service IP or URL belongs in the data set, and takes a value from 1 to K;

[0077] K: represents the total number of categories to which the service IP or URL belongs in the data set;

[0078] p k : represents the proportion of the number of samples of the IP or URL belonging to the kth website in the data set D to the total number of samples in the data set D.

[0079] Gini(D, a): represents the weighted Gini index of the data set under the division of the feature (i.e., the information gain related index corresponding to the feature), which is used to measure the division effect of the feature on the data set;

[0080] a: refers to the feature variable used to divide the data set, specifically one of the four variables associated with the service IP and URL, i.e., "usage times, usage duration, traffic size, and user number";

[0081] v: represents the value index of the feature, and takes a value from 1 to V;

[0082] V: represents the number of all possible values of the feature;

[0083] D V : represents a sub-data set in the data set, whose feature value is

[0084] | D V |: represents the number of samples contained in the sub-data set;

[0085] |D| : represents the total number of samples contained in the data set;

[0086] Gini ( D v ): represents the Gini index of the sub-data set D V .

[0087] In some embodiments of the present application, the calculated Gini indexes can also be directly weighted and averaged to obtain the scores of the two indicators, and then the priority ranking is performed based on the scores from high to low. The weight calculation formula is as follows:

[0088]

[0089] It should be noted that the higher the above score is, the lower the values of the two Gini indexes corresponding to the website are.

[0090] Step S208: adjusting the arrangement order of the plurality of websites in the first charging configuration data according to the priority ranking result of the plurality of websites, to obtain second charging configuration data.

[0091] In some embodiments of the present application, the process of adjusting the arrangement order is as shown in Figure 9 . As can be seen from Figure 9 , after the priority of each website is determined, the order of the networkAddress (i.e. IP address) under each term (such as term1, term2) in the live configuration data (that is, the initial position of the website in the charging configuration data) can be extracted, and compared and analyzed with the IP / URL priority order of the corresponding website content in the above business priority ranking table. Finally, the content sorting optimization scheme is output according to the comparison result. If the IP order under the term in the configuration data is inconsistent with the priority ranking result (for example, the original configuration of term1 is IP2, IP3, IP…, which does not match the order of IP1, IP2, IP3 in the priority ranking table), the IP arrangement order under the term is adjusted to be consistent with the business priority ranking of the website content, so as to ensure that the website content with high priority (high frequency and large traffic) can be matched preferentially, and the charging marking efficiency is improved. The website content here is sorted by website as the sorting object in actual matching.

[0092] In the technical solution provided in step S208, the method further includes: acquiring service information list data in a preset time period, wherein the service information list data includes charging configuration data corresponding to services processed in the preset time period; determining redundant configuration data in the second charging configuration data according to the service information list data, wherein the redundant configuration data is charging configuration data that does not appear in the service information list data; and deleting the redundant configuration data in the second charging configuration data to obtain third charging configuration data.

[0093] In some embodiments of the present application, the process of determining and deleting redundant charging configuration data is as shown in Figure 10 As can be seen from Figure 10 , the configuration data can be structured and processed to output data including key information such as networkAddress|term|name, and the DPI data of a continuous half year is accumulated and processed to obtain full-amount user service information list. Configuration information data that does not appear in the user service list is filtered out and defined as redundant configuration.

[0094] In some embodiments of the present application, the method provided by the embodiments of the present application can be verified by the way as shown in Figure 11 As shown in Figure 11 , the network element adjusting the content charging configuration is tested by an automatic test system (the test content is a website involved in the adjustment process of the content charging configuration optimization scheme), the test number is marked, and the marked result is intelligently matched and verified with the content charging configuration data to determine the accuracy of the configuration optimization scheme. The final test result shows that the optimization scheme provided by the present application can significantly improve the accuracy.

[0095] In some embodiments of the present application, the charging system adjusted by the optimization of the present application can be evaluated by the way as shown in Figure 12 As shown in Figure 12 , the load fluctuation of the CPU of the adjusted GGSN / PGW / UPF network element can be evaluated; and the DPI data is analyzed for the service content in the term merging and sorting optimization to evaluate the time delay change of the service.

[0096] Through comparison of the indicators before and after the optimization, it is known that the CPU load of the network element is reduced by about 10%, and the service time delay is shortened by about 1ms.

[0097] The embodiments of the present application further provide a charging configuration optimization and verification process as shown in Figure 13 , which includes four steps of data collection / analysis, configuration auditing, configuration optimization, marking verification and evaluation. In the first step of data collection / analysis, the following steps are included:

[0098] 1.1 Collect local data work order data;

[0099] 1.2 Collect mobile data gateway GGSN / PGW / UPF configuration data;

[0100] 1.3 Sort out the billing configuration logic of each manufacturer's content;

[0101] 1.4 Analyze the work order and configuration data according to the configuration logic.

[0102] The second step of configuring the audit includes the following steps:

[0103] 2.1 Form comparable data according to the predetermined rule algorithm, and build a data audit model;

[0104] 2.2 Audit network element configuration based on work order data;

[0105] 2.3 Compare work order data based on network element configuration.

[0106] The third step of configuring optimization includes the following steps:

[0107] 3.1 Analyze user behavior through DPI big data;

[0108] 3.2 Frequently visited websites by users, adjust the content billing configuration to match preferentially;

[0109] 3.3 In the content billing configuration, the website with no user access for a long time is screened and feedback to the data center to check whether to delete and adjust the configuration.

[0110] The fourth step of marking verification and evaluation includes the following steps:

[0111] 4.1 Test the network element with adjusted content billing configuration through the automatic dialing test system;

[0112] 4.2 Check whether the dialing number marking matches the content billing adjustment configuration;

[0113] 4.3 Evaluate the performance before and after optimization.

[0114] The application discloses a charging configuration optimization device and a charging configuration optimization method.

[0115] The application discloses a charging configuration optimization device and a charging configuration optimization method. Figure 14 The application discloses a charging configuration optimization device and a charging configuration optimization method. Figure 14 The application discloses a charging configuration optimization device and a charging configuration optimization method.

[0116] In some embodiments of the application, before determining the set of combinable configuration rules in the initial charging configuration data, the second processing module 142 is further configured to: acquire charging work order data; determine a first charging configuration logic of the charging work order data and a second charging configuration logic of the initial charging configuration data; and perform auditing on the initial charging data according to the first charging configuration logic or the second charging configuration logic.

[0117] In some embodiments of the application, the step of performing auditing on the initial charging data according to the first charging configuration logic or the second charging configuration logic by the second processing module 142 comprises: performing auditing on the initial charging configuration data according to the first charging configuration logic to determine whether the initial charging configuration data and the first charging configuration logic match; and determining whether the initial charging data in each network element is consistent according to the second charging configuration logic.

[0118] In some embodiments of the present application, the second processing module 142 determines the set of combinable configuration rules in the initial charging configuration data, including: determining a set of combinable configuration rule determination manners corresponding to protocol levels; and determining the set of combinable configuration rules in the configuration rules of each level corresponding to the initial charging configuration set according to the set of combinable configuration rule determination manners.

[0119] In some embodiments of the present application, the third processing module 144 determines the priority ranking result of the plurality of web addresses according to the web address access data, including: determining the access frequency and access traffic of the plurality of web addresses according to the web address access data; performing a primary ranking on the plurality of web addresses according to the access frequency interval in which the access frequency of the plurality of web addresses is located, to obtain a primary ranking result; and performing a secondary ranking on the web addresses corresponding to the same access frequency interval according to the access traffic of the web addresses corresponding to the same access frequency interval, to obtain the priority ranking result.

[0120] In some embodiments of the present application, the third processing module 144 determines the priority ranking result of the plurality of web addresses according to the web address access data, including: determining the first address information and the second address information of the plurality of web addresses; determining a first information gain index between the web address access data and the first address information, and a second information gain index between the web address access data and the second address information, wherein the web address access data includes at least one of the following: access times, access duration, traffic size, and user number; performing weighted summation on the first information gain index and the second information gain index to obtain a comprehensive gain index of the plurality of web addresses; and determining the priority ranking result of the plurality of web addresses according to the comprehensive gain index, wherein the smaller the comprehensive gain index is, the higher the priority is.

[0121] In some embodiments of the present application, the fourth processing module 146 is further configured to: obtain service information list data in a preset time period, wherein the service information list data includes charging configuration data corresponding to services processed in the preset time period; determine redundant configuration data in the second charging configuration data according to the service information list data, wherein the redundant configuration data is charging configuration data that does not appear in the service information list data; and delete the redundant configuration data in the second charging configuration data to obtain third charging configuration data.

[0122] It should be noted that each module in the charging configuration optimization apparatus described above can be a program module (for example, a set of program instructions for implementing a certain specific function) or a hardware module. For the latter, it can be in the following forms, but is not limited thereto: each module is in the form of a processor, or the functions of each module are implemented by a processor.

[0123] According to an embodiment of the present application, a nonvolatile storage medium is provided, and the nonvolatile storage medium stores a program. When the program is executed, the device in which the nonvolatile storage medium is arranged performs the following charging configuration optimization method: obtaining website access data and initial charging configuration data of a network element in a charging system, wherein the website access data includes user access information of a plurality of websites in a preset time period; determining a set of mergable configuration rules in the initial charging configuration data, and performing merging processing on the mergable configuration rules in the set of mergable configuration rules to obtain first charging configuration data; determining a priority ranking result of the plurality of websites according to the website access data; and adjusting the arrangement order of the plurality of websites in the first charging configuration data according to the priority ranking result of the plurality of websites to obtain second charging configuration data.

[0124] According to an embodiment of the present application, an electronic device is also provided, which includes a memory and a processor. The processor is configured to execute a program stored in the memory. When the program is executed, the electronic device performs the following charging configuration optimization method: obtaining website access data and initial charging configuration data of a network element in a charging system, wherein the website access data includes user access information of a plurality of websites in a preset time period; determining a set of mergable configuration rules in the initial charging configuration data, and performing merging processing on the mergable configuration rules in the set of mergable configuration rules to obtain first charging configuration data; determining a priority ranking result of the plurality of websites according to the website access data; and adjusting the arrangement order of the plurality of websites in the first charging configuration data according to the priority ranking result of the plurality of websites to obtain second charging configuration data.

[0125] According to an embodiment of the present application, a computer program product is also provided, which includes a computer program. When the computer program is executed by a processor, the computer program implements the following charging configuration optimization method: obtaining website access data and initial charging configuration data of a network element in a charging system, wherein the website access data includes user access information of a plurality of websites in a preset time period; determining a set of mergable configuration rules in the initial charging configuration data, and performing merging processing on the mergable configuration rules in the set of mergable configuration rules to obtain first charging configuration data; determining a priority ranking result of the plurality of websites according to the website access data; and adjusting the arrangement order of the plurality of websites in the first charging configuration data according to the priority ranking result of the plurality of websites to obtain second charging configuration data.

[0126] In the above-described embodiments of the present application, the description of each embodiment has its own focus, and the parts not described in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0127] In several embodiments provided in the present application, it should be understood that the disclosed technology can be implemented by other ways. Among them, the above-mentioned device embodiments are only schematic, for example, the division of the units can be a logical function division, and actual implementation can have another division mode, for example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interfaces, units or modules, which can be electrical or other forms.

[0128] The units described as separate components can or can not be physically separate, and the components shown as units can or can not be physical units, that is, they can be located in one place, or they can be distributed to multiple units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0129] In addition, each functional unit in each embodiment of the present application can be integrated in one processing unit, or each unit can be physically present separately, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or in the form of a software functional unit.

[0130] The integrated unit, if realized in the form of a software functional unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the part that contributes to the related art or the whole or part of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a plurality of instructions for causing a computer device (which can be a personal computer, a server or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The foregoing storage medium includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, magnetic disk or optical disk and various program codes that can be stored in the medium.

[0131] The above is only the preferred embodiment of the present application, and it should be pointed out that for ordinary skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, which should be considered as the protection scope of the present application.

Claims

1. A billing configuration optimization method, characterized in that, include: Acquire URL access data and initial billing configuration data of network elements within the billing system, wherein the URL access data includes user access information for multiple URLs within a preset time period; Determine the set of mergeable configuration rules in the initial billing configuration data, and merge the mergeable configuration rules in the set of mergeable configuration rules to obtain the first billing configuration data; Based on the URL access data, determine the priority ranking result of the multiple URLs; Based on the priority ranking of the multiple URLs, the order of the multiple URLs in the first billing configuration data is adjusted to obtain the second billing configuration data.

2. The billing configuration optimization method according to claim 1, characterized in that, Based on the URL access data, the priority ranking results of multiple URLs are determined as follows: Based on the URL access data, determine the access frequency and access traffic of the multiple URLs; Based on the access frequency range in which the access frequency of the multiple URLs falls, the multiple URLs are initially sorted to obtain the initial sorting result; For URLs corresponding to the same access frequency range, the URLs corresponding to the same access frequency range are re-sorted according to the access traffic of the URLs to obtain the priority sorting result.

3. The billing configuration optimization method according to claim 1, characterized in that, Based on the URL access data, the priority ranking results of multiple URLs are determined as follows: Determine the first address information and the second address information of the plurality of URLs; Determine a first information gain index between the URL access data and the first address information, and a second information gain index between the URL access data and the second address information, wherein the URL access data includes at least one of the following: number of accesses, access duration, traffic volume, and number of users; The first information gain index and the second information gain index are weighted and summed to obtain the comprehensive gain index of the multiple URLs; The priority ranking of the multiple URLs is determined based on the comprehensive gain index, wherein the smaller the comprehensive gain index, the greater the priority.

4. The billing configuration optimization method according to claim 1, characterized in that, The set of mergeable configuration rules in the initial billing configuration data includes: Determine the method for determining the set of mergeable configuration rules corresponding to the protocol level; Based on the method for determining the set of merging configuration rules, the set of merging configuration rules is determined from the configuration rules of each level corresponding to the initial billing configuration set.

5. The billing configuration optimization method according to claim 1, characterized in that, Before determining the set of mergeable configuration rules in the initial billing configuration data, the method further includes: Obtain billing work order data; The first billing configuration logic for the billing work order data and the second billing configuration logic for the initial billing configuration data are determined. The initial billing data is audited based on the first billing configuration logic or the second billing configuration logic.

6. The billing configuration optimization method according to claim 5, characterized in that, Auditing the initial billing data according to the first billing configuration logic or the second billing configuration logic includes: The initial billing configuration data is audited based on the first billing configuration logic to determine whether the initial billing configuration data matches the first billing configuration logic. Based on the second billing configuration logic, it is determined whether the initial billing data in each network element is consistent.

7. The billing configuration optimization method according to claim 1, characterized in that, The method further includes: Obtain a list of business information data within a preset time period, wherein the list of business information data includes billing configuration data corresponding to the business processed within the preset time period; Based on the business information list data, redundant configuration data in the second billing configuration data is determined, wherein the redundant configuration data is billing configuration data that does not appear in the business information list data; Delete redundant configuration data from the second billing configuration data to obtain the third billing configuration data.

8. A billing configuration optimization device, characterized in that, include: The first processing module is used to acquire URL access data and initial billing configuration data of network elements in the billing system. The URL access data includes user access information for multiple URLs within a preset time period. The second processing module is used to determine the set of mergeable configuration rules in the initial billing configuration data, and to merge the mergeable configuration rules in the set of mergeable configuration rules to obtain the first billing configuration data. The third processing module is used to determine the priority ranking result of multiple URLs based on the URL access data. The fourth processing module is used to adjust the order of the multiple URLs in the first billing configuration data according to the priority sorting result of the multiple URLs, so as to obtain the second billing configuration data.

9. A non-volatile storage medium, characterized in that, The non-volatile storage medium stores a program, wherein when the program is executed, it controls the device where the non-volatile storage medium is located to execute the billing configuration optimization method according to any one of claims 1 to 7.

10. An electronic device, characterized in that, include: A memory and a processor, the processor being configured to run a program stored in the memory, wherein the program, when running, executes the billing configuration optimization method according to any one of claims 1 to 7.

11. A computer program product, characterized in that, It includes a computer program that, when executed by a processor, implements the billing configuration optimization method according to any one of claims 1 to 7.

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