Business area positioning methods, devices, equipment and storage media

Abstract

This application provides a service area positioning method, apparatus, device, and storage medium. First, it acquires communication data and service quality index data corresponding to each user terminal. The communication data includes user signaling data. Then, based on the service quality index data corresponding to each user terminal, it identifies the users conducting live streaming services through the user terminals, i.e., the live streaming users. Next, based on the user signaling data corresponding to the live streaming users, it determines the live streaming activity volume of the base station cell corresponding to the live streaming users. Finally, it determines the live streaming service area based on the live streaming activity volume. By using user signaling data and service quality index data as references, it achieves accurate positioning of the live streaming service area, providing data support to meet the higher requirements for network performance rates and latency sensitivity needed to conduct live streaming services in the area, thereby improving user experience.

Description

Technical Field

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

[0002] With the rapid development of 5G network construction, and driven by the promotional effects of e-commerce, social media platforms, and news, the influencer economy has experienced rapid growth. This has led to a rapid expansion of the livestreaming population, making livestreaming potentially possible anytime, anywhere. The development of livestreaming inevitably places higher demands on network performance, speed, and latency sensitivity.

[0003] However, current network monitoring hotspots are still limited to traditional areas such as commercial streets and popular tourist attractions. The reference for locating these hotspots is only network O-domain traffic data, which has a single data source, outdated methods, and poor real-time performance. This cannot meet the higher requirements of live streaming services for network performance, speed, and latency sensitivity, thus reducing the user experience of live streaming. Summary of the Invention

[0004] This application provides a business area positioning method, apparatus, device, and storage medium to solve the technical problems in the prior art where the data source for locating business areas is singular, the positioning methods are outdated and have poor real-time performance, thus failing to meet the needs of live streaming services.

[0005] Firstly, this application provides a business area positioning method, including:

[0006] Acquire communication data and service quality index data corresponding to each user terminal, wherein the communication data includes user signaling data;

[0007] Live streaming users are determined based on the service quality index data corresponding to each user terminal, and the live streaming users include users who conduct live streaming services through the user terminal.

[0008] The amount of live streaming activity in the base station cell corresponding to the live streaming user is determined based on the user signaling data corresponding to the live streaming user, and the live streaming service area is determined based on the amount of live streaming activity.

[0009] In one possible design, after determining the live streaming service area based on the live streaming activity volume, the following is also included:

[0010] The live streaming service area is updated according to a preset time period to track the location change data of the live streaming service area;

[0011] Based on the location change data, determine whether there is abnormal network load behavior in the live streaming service area;

[0012] If so, a network anomaly report is generated based on the abnormal network load behavior, and network repair is implemented through the network anomaly report.

[0013] In one possible design, after determining the live streaming service area based on the live streaming activity volume, the following is also included:

[0014] Generate a list of live streaming users within the live streaming service area, and push customized live streaming packages to each live streaming user in the list; and / or

[0015] Based on the service quality index data of all live streaming users, determine whether the corresponding base station cell of all live streaming users is a problem cell, and generate network early warning data based on the judgment result.

[0016] In one possible design, determining live stream users based on the service quality index data corresponding to each user terminal includes:

[0017] Select business quality indicator data that meet the preset indicator standards from the business quality indicator data corresponding to each user terminal. The preset indicator standards include one or more of the following: rate standard, duration standard, and traffic standard that must be met to carry out live streaming business.

[0018] The live streaming users are determined based on the selected business quality indicator data.

[0019] In one possible design, the step of filtering service quality indicator data that meets preset indicator standards from the service quality indicator data corresponding to each user terminal includes:

[0020] Filter the user uplink rates that meet the rate standard from the service quality index data corresponding to each user terminal;

[0021] Filter the user uplink rate that meets the duration standard from the service quality indicator data corresponding to each user terminal;

[0022] Filter the user uplink rate that meets the traffic standard from the service quality index data corresponding to each user terminal;

[0023] The uplink speed of the selected users is determined as the selected service quality indicator data.

[0024] In one possible design, if the preset indicator standards include at least two of the rate standard, the duration standard, and the traffic standard, determining the live stream user based on the selected service quality indicator data includes:

[0025] The user type of the user terminal corresponding to the filtered business quality indicator data is determined as the live broadcast user.

[0026] In one possible design, if the preset indicator standards include one of the rate standard, the duration standard, and the traffic standard, the step of determining the live stream user based on the selected service quality indicator data includes:

[0027] The user type of the user terminal corresponding to the filtered business quality indicator data is determined as the candidate user;

[0028] The model of the user terminal of the candidate user is identified based on the user billing data corresponding to the candidate user;

[0029] If the candidate user's terminal model is the target model, then the candidate user is determined to be the live stream user;

[0030] The communication data also includes user billing data corresponding to the candidate user.

[0031] In one possible design, determining the live streaming activity volume of the base station cell corresponding to the live streaming user based on the user signaling data corresponding to the live streaming user includes:

[0032] The live streaming time period for the live streaming user is determined based on the user signaling data corresponding to the live streaming user.

[0033] The latitude and longitude of the base station cell within each preset duration during the live broadcast time period are determined based on the user signaling data corresponding to the live broadcast user, so as to obtain multiple location points during the live broadcast time period;

[0034] Obtain the sum of the distances from each of the plurality of location points to all other location points;

[0035] The location point corresponding to the minimum sum of multiple distances is determined as the target location point for the live broadcast time period;

[0036] The amount of live streaming activity of the corresponding base station cell of the live streaming user is determined based on the target location point during the live streaming time period.

[0037] In one possible design, determining the live streaming activity volume of the base station cell corresponding to the live streaming user based on the target location point during the live streaming time period includes:

[0038] The base station cell corresponding to the live stream user is determined based on the target location point during the live stream time period.

[0039] Obtain all live streaming users within the cell corresponding to the live streaming user, and calculate the live streaming activity volume of the cell corresponding to the live streaming user based on the number of all live streaming users and the live streaming duration within a day.

[0040] In one possible design, determining the live streaming service area based on the live streaming activity volume includes:

[0041] The amount of live streaming activity per unit area is obtained based on the aforementioned amount of live streaming activity.

[0042] A heat map is generated based on the amount of live streaming activity per unit area.

[0043] The coverage area of ​​the heat map on the geographical area corresponding to the base station cell of the live broadcast user is determined as the live broadcast service area.

[0044] In one possible design, after generating the heat map based on the live activity volume per unit area, the following is also included:

[0045] The heat map uses different colors to represent different live streaming activity volumes.

[0046] Secondly, this application provides a business area positioning device, comprising:

[0047] The acquisition module is used to acquire communication data and service quality indicator data corresponding to each user terminal, wherein the communication data includes user signaling data;

[0048] The first processing module is used to determine live streaming users based on the service quality index data corresponding to each user terminal, wherein the live streaming users include users who conduct live streaming services through the user terminal.

[0049] The second processing module is used to determine the live streaming activity volume of the base station cell corresponding to the live streaming user based on the user signaling data corresponding to the live streaming user, so as to determine the live streaming service area based on the live streaming activity volume.

[0050] In one possible design, the service area positioning device further includes: a third processing module; the third processing module is used for:

[0051] The live streaming service area is updated according to a preset time period to track the location change data of the live streaming service area;

[0052] Based on the location change data, determine whether there is abnormal network load behavior in the live streaming service area;

[0053] If so, a network anomaly report is generated based on the abnormal network load behavior, and network repair is implemented through the network anomaly report.

[0054] In one possible design, the third processing module is further configured to:

[0055] Generate a list of live streaming users within the live streaming service area, and push customized live streaming packages to each live streaming user in the list; and / or

[0056] Based on the service quality index data of all live streaming users, determine whether the corresponding base station cell of all live streaming users is a problem cell, and generate network early warning data based on the judgment result.

[0057] In one possible design, the first processing module includes:

[0058] The first processing submodule is used to filter business quality indicator data that meet preset indicator standards from the business quality indicator data corresponding to each user terminal. The preset indicator standards include one or more of the following: rate standard, duration standard, and traffic standard that must be met to carry out live streaming business.

[0059] The second processing submodule is used to determine the live streaming users based on the filtered business quality indicator data.

[0060] In one possible design, the first processing submodule is specifically used for:

[0061] Filter the user uplink rates that meet the rate standard from the service quality index data corresponding to each user terminal;

[0062] Filter the user uplink rate that meets the duration standard from the service quality indicator data corresponding to each user terminal;

[0063] Filter the user uplink rate that meets the traffic standard from the service quality index data corresponding to each user terminal;

[0064] The uplink speed of the selected users is determined as the selected service quality indicator data.

[0065] In one possible design, if the preset indicator standard includes at least two of the rate standard, the duration standard, and the flow rate standard, the second processing submodule is specifically used for:

[0066] The user type of the user terminal corresponding to the filtered business quality indicator data is determined as the live broadcast user.

[0067] In one possible design, if the preset indicator standard includes one of the rate standard, the duration standard, and the traffic standard, the second processing submodule is specifically used for:

[0068] The user type of the user terminal corresponding to the filtered business quality indicator data is determined as the candidate user;

[0069] The model of the user terminal of the candidate user is identified based on the user billing data corresponding to the candidate user;

[0070] If the candidate user's terminal model is the target model, then the candidate user is determined to be the live stream user;

[0071] The communication data also includes user billing data corresponding to the candidate user.

[0072] In one possible design, the second processing module is specifically used for:

[0073] The live streaming time period for the live streaming user is determined based on the user signaling data corresponding to the live streaming user.

[0074] The latitude and longitude of the base station cell within each preset duration during the live broadcast time period are determined based on the user signaling data corresponding to the live broadcast user, so as to obtain multiple location points during the live broadcast time period;

[0075] Obtain the sum of the distances from each of the plurality of location points to all other location points;

[0076] The location point corresponding to the minimum sum of multiple distances is determined as the target location point for the live broadcast time period;

[0077] The amount of live streaming activity of the corresponding base station cell of the live streaming user is determined based on the target location point during the live streaming time period.

[0078] In one possible design, the second processing module is further configured to:

[0079] The base station cell corresponding to the live stream user is determined based on the target location point during the live stream time period.

[0080] Obtain all live streaming users within the cell corresponding to the live streaming user, and calculate the live streaming activity volume of the cell corresponding to the live streaming user based on the number of all live streaming users and the live streaming duration within a day.

[0081] In one possible design, the second processing module is further configured to:

[0082] The amount of live streaming activity per unit area is obtained based on the aforementioned amount of live streaming activity.

[0083] A heat map is generated based on the amount of live streaming activity per unit area.

[0084] The coverage area of ​​the heat map on the geographical area corresponding to the base station cell of the live broadcast user is determined as the live broadcast service area.

[0085] In one possible design, the second processing module is further configured to:

[0086] The heat map uses different colors to represent different live streaming activity volumes.

[0087] Thirdly, this application provides an electronic device, including: a processor, and a memory communicatively connected to the processor;

[0088] The memory stores computer-executed instructions;

[0089] The processor executes computer execution instructions stored in the memory to implement any of the possible service area positioning methods provided in the first aspect.

[0090] Fourthly, this application provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement any of the possible service area positioning methods provided in the first aspect.

[0091] Fifthly, this application provides a computer program product, including computer execution instructions, which, when executed by a processor, are used to implement any of the possible business area positioning methods provided in the first aspect.

[0092] This application provides a service area positioning method, apparatus, device, and storage medium. First, it acquires communication data and service quality index data corresponding to each user terminal. The communication data includes user signaling data. Then, based on the service quality index data corresponding to each user terminal, it identifies the users conducting live streaming services through the user terminals, i.e., the live streaming users. Next, based on the user signaling data corresponding to the live streaming users, it determines the live streaming activity volume of the base station cell corresponding to the live streaming users. Finally, it determines the live streaming service area based on the live streaming activity volume. By using user signaling data and service quality index data as references, it achieves accurate positioning of the live streaming service area, providing data support to meet the higher requirements for network performance rates and latency sensitivity needed to conduct live streaming services in the area, thereby improving user experience. Attached Figure Description

[0093] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0094] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0095] Figure 2 A flowchart illustrating a business area positioning method provided for the implementation of this application;

[0096] Figure 3 A flowchart illustrating another business area positioning method provided in an embodiment of this application;

[0097] Figure 4 A flowchart illustrating another business area positioning method provided in an embodiment of this application;

[0098] Figure 5 A flowchart illustrating another business area positioning method provided in this application embodiment;

[0099] Figure 6 A flowchart illustrating another business area positioning method provided in this application embodiment;

[0100] Figure 7 This is a schematic diagram of the structure of a business area positioning device provided in an embodiment of this application;

[0101] Figure 8 A schematic diagram of another business area positioning device provided in this application embodiment;

[0102] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0103] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of methods and apparatus consistent with some aspects of this application as detailed in the appended claims.

[0104] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a particular order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented, for example, in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0105] With the rapid expansion of the live streaming population, live streaming services can be conducted anytime, anywhere. This inevitably places higher demands on network performance, speed, and latency sensitivity. However, current network monitoring hotspots remain limited to traditional areas such as commercial streets and popular tourist attractions. The data used to locate these hotspots is solely based on network O-domain traffic data, which has a single data source, outdated methods, and poor real-time performance. All of these fail to meet the higher requirements of live streaming services for network performance, speed, and latency sensitivity, thus reducing the user experience.

[0106] To address the aforementioned problems in the existing technology, this application provides a service area positioning method, apparatus, device, and storage medium. The inventive concept of the service area positioning method provided in this application is as follows: First, communication data and service quality index data corresponding to each user terminal within a certain geographical range are acquired. Based on the service characteristics of live streaming services, the users conducting live streaming services through the acquired service quality index data of each user terminal are first identified, i.e., the live streaming users. Then, the live streaming activity volume of the base station cell corresponding to the live streaming user is determined based on the user signaling data. Finally, the scene boundary for conducting live streaming services is determined based on the live streaming activity volume, i.e., the live streaming service area is located. By using user signaling data and service quality index data as references, accurate positioning of the live streaming service area is achieved, thereby providing data support for meeting the higher requirements of network performance speed and latency sensitivity needed for conducting live streaming services in the live streaming service area, and thus improving user experience.

[0107] The following describes exemplary application scenarios of the embodiments of this application.

[0108] Figure 1 This is a schematic diagram illustrating an application scenario provided by an embodiment of this application. For example... Figure 1 As shown, the electronic device 100 is configured to execute the service area positioning method provided in this application embodiment. First, it acquires the communication data and service quality index data corresponding to each user terminal within a certain geographical range. Then, based on the acquired service quality index data corresponding to each user terminal, it determines the user conducting the live broadcast service, i.e., the live broadcast user 200. Next, based on the user signaling data corresponding to the live broadcast user in the communication data, it determines the live broadcast activity volume of the base station cell corresponding to the live broadcast user 200. Then, based on the live broadcast activity volume, it determines the live broadcast service area, thereby achieving accurate positioning of the live broadcast service area. This provides data support for meeting the higher requirements of network performance rate and latency sensitivity needed to conduct live broadcast services in the live broadcast service area. For example, it can accurately push customized packages that are conducive to conducting live broadcast services to the live broadcast user 200, and / or effectively monitor the network load of the base station 300 corresponding to the live broadcast service area, thereby improving the user experience.

[0109] It should be noted that the geographical range described above can be set according to the operator's network coverage and regulatory requirements, such as the area under the jurisdiction of a prefecture-level city. Base station 300 can include, but is not limited to, base stations using 2G / 3G / 4G / 5G network standards.

[0110] Furthermore, the electronic device 100 can be a computer, laptop computer, tablet computer, server, or server cluster, etc. This application embodiment does not limit the type of electronic device 100. Figure 1 The electronic device 100 in the example is a computer.

[0111] It should be noted that the above application scenarios are merely illustrative, and the business area positioning methods, devices, equipment, and storage media provided in the embodiments of this application include, but are not limited to, the above application scenarios.

[0112] Figure 2 A flowchart illustrating a business area positioning method provided for the implementation of this application. Figure 2 As shown in the embodiments of this application, the business area positioning method includes:

[0113] S101: Obtain communication data and service quality index data corresponding to each user terminal.

[0114] The communication data includes user signaling data.

[0115] For example, operators can obtain communication data and service quality index data for each user terminal within a certain geographical range, such as the jurisdiction of a current prefecture-level city.

[0116] Communication data includes user signaling data, which may be, for example, S1-MME data.

[0117] S1-MME data refers to the information exchanged between the eNodeB and the MME (Mobility Management Entity) via the S1 interface. It is used to transmit Session Management (SM) and Mobility Management (MM) information, i.e., signaling plane or control plane information. User terminal attachment, location area updates, and resource requests within the wireless network all generate S1-MME data records. S1-MME data contains many fields, including various information about the user's wireless network usage, such as the user's mobile phone number, signaling start time, base station cell identifier (ECI, E-UTRAN Cell Identifier), and base station cell latitude and longitude.

[0118] Business quality indicator data includes key performance indicators (KPIs) and key quality indicators (KQIs) on the network side corresponding to user terminals, which can reflect the current network coverage quality and perceived performance data.

[0119] For example, service quality metrics data may include network coverage quality metrics such as user uplink throughput, user uplink rate, physical resource block (PRB) utilization, reference signal received power (RSRP), and signal to interference plus noise ratio (SINR), as well as user-perceived metrics such as call completion rate, congestion rate, and latency.

[0120] S102: Determine the live streaming users based on the service quality index data corresponding to each user terminal.

[0121] Among them, live streaming users include users who conduct live streaming business through user terminals.

[0122] After obtaining the communication data and service quality index data corresponding to each user terminal, based on the business characteristics of the live streaming business, the users who conduct live streaming business through the user terminal are determined according to the service quality index data corresponding to each user terminal, that is, the live streaming users.

[0123] Current live streaming services primarily utilize RTMP (Real-Time Message Protocol). Based on the live streaming service architecture, the front-end first collects the video and audio data of the broadcaster (the live streamer), then uploads it to a server cluster, and finally distributes it to viewers in different locations. It's clear that a key characteristic of live streaming is that the video and audio data uploaded by users relies on uplink bandwidth. Since service quality indicators (SMIs) can reflect uplink bandwidth, users conducting live streaming through their respective terminals can be identified based on their SMI data.

[0124] S103: Determine the live streaming activity volume of the base station cell corresponding to the live streaming user based on the user signaling data corresponding to the live streaming user, and determine the live streaming service area based on the live streaming activity volume.

[0125] After determining that the user type corresponding to the user terminal is a live streaming user, the live streaming activity volume of the base station cell corresponding to the live streaming user is further determined based on the user signaling data corresponding to the live streaming user in the user signaling data corresponding to each user terminal.

[0126] Among them, the base station cell corresponding to the live streaming user refers to the base station cell where the live streaming user conducts live streaming services. By analyzing the user signaling data corresponding to the live streaming user, the base station cell where the live streaming user conducts live streaming services is determined, and then the live streaming activity volume corresponding to the base station cell conducting live streaming services is determined. The base station cell with a large amount of live streaming activity indicates that the live streaming users conducting live streaming services in the geographical area covered by that base station cell are more concentrated. The area where live streaming users are concentrated is determined as the live streaming service area, realizing the positioning of the live streaming service area.

[0127] As described above, the service area positioning method provided in this application, when locating a live streaming service area, firstly determines the target users whose user type is live streaming user based on the service quality index data, then determines the live streaming activity volume of the base station cell corresponding to the live streaming user based on the user signaling data corresponding to the live streaming user, and finally locates the live streaming service area based on the live streaming activity volume. The reference basis for locating the live streaming service area is not a single data point; the reference basis has good real-time performance and conforms to the characteristics of live streaming services, thus making the positioning of the live streaming service area more accurate.

[0128] Furthermore, by identifying the live streaming service area, it's possible to monitor network load and anomalies within that area. This allows for tracking changes in network load and other unusual conditions, assisting in the analysis of network anomaly causes, providing early warnings of network problems, and ensuring network performance, speed, and latency-sensitive network quality. Moreover, identifying the live streaming service area provides access to all live streaming users within that area, enabling the precise delivery of customized packages tailored to live streaming needs, thus enhancing user experience. Therefore, identifying the live streaming service area provides data support to meet the higher requirements for network performance, speed, and latency sensitivity needed for live streaming operations, ultimately improving user experience.

[0129] The service area positioning method provided in this application first acquires communication data and service quality index data corresponding to each user terminal. The communication data includes user signaling data. Then, based on the service quality index data corresponding to each user terminal, the user conducting live streaming service through the user terminal, i.e., the live streaming user, is determined. Next, based on the user signaling data corresponding to the live streaming user, the live streaming activity volume of the base station cell corresponding to the live streaming user is determined. Finally, the live streaming service area is determined based on the live streaming activity volume. By using user signaling data and service quality index data as references, accurate positioning of the live streaming service area is achieved, providing data support to meet the higher requirements for network performance speed and latency sensitivity needed to conduct live streaming services in the live streaming service area, thereby improving user experience.

[0130] In one possible design, after step S103, the service area positioning method provided in this application embodiment further includes, as follows: Figure 3 The steps are shown. Figure 3 This is a flowchart illustrating another business area positioning method provided in an embodiment of this application. Figure 3 As shown, the embodiments of this application include:

[0131] S201: Update the live streaming service area according to a preset time period to track the location change data of the live streaming service area;

[0132] S202: Determine whether there is abnormal network load behavior in the live streaming service area based on location change data;

[0133] S203: If so, generate a network anomaly report based on abnormal network load behavior, and implement network repair through the network anomaly report.

[0134] To monitor and track changes in the live streaming service area in real time, a preset time period can be set, such as every 15 minutes, to update the live streaming service area and obtain its positional change data. Based on this positional change data, it can then be determined whether there is any abnormal network load behavior in the live streaming service area. If so, a network anomaly report is generated, and network repairs are implemented based on the report, assisting in the analysis of the cause of the network anomaly.

[0135] Optionally, the large screen outputs location change data of the live streaming service area to refresh the live streaming service area in real time at a high frequency.

[0136] It's understandable that updating the live streaming service area according to a preset time cycle involves cyclically acquiring user signaling data and service quality index data from user terminals within the live streaming service area. This updates the number of users conducting live streaming services through these terminals and the live streaming service area itself, thereby obtaining location change data for the live streaming service area. Since changes in the live streaming service area may be caused by abnormal network load behavior, such as hot events leading to abnormal network load, location change data can be used to determine whether abnormal network load behavior exists in the live streaming service area. If so, timely network repairs can be implemented to ensure normal network operation.

[0137] Based on the above embodiments, optionally, after step S103, the business area positioning method provided in this application embodiment may further include generating a list of live streaming users within the live streaming business area, and pushing customized live streaming packages to each live streaming user in the live streaming user list; and / or

[0138] Based on the service quality index data of all live streaming users, determine whether the corresponding base station cell of each live streaming user is a problem cell, and generate network early warning data based on the judgment results to ensure user experience.

[0139] Figure 4 This is a flowchart illustrating another business area positioning method provided in an embodiment of this application. Figure 4 As shown in the embodiments of this application, the business area positioning method includes:

[0140] S301: Obtain communication data and service quality index data corresponding to each user terminal.

[0141] The communication data includes user signaling data.

[0142] The possible implementation methods, principles and effects of step S301 are similar to those of step S101. For details, please refer to the above description, which will not be repeated here.

[0143] S302: Filter the service quality indicator data that meets the preset indicator standards from the service quality indicator data corresponding to each user terminal.

[0144] The service quality indicator data corresponding to each user terminal is filtered to select service quality indicator data that meet the preset indicator standards.

[0145] Since live streaming services rely on uplink bandwidth, which can be reflected through service quality metrics data, preset metric standards can be set. Based on these standards, service quality metrics data that meet the preset metric standards can be selected from the service metric data corresponding to each user terminal.

[0146] The preset performance indicators include one or more of the following: speed standards, duration standards, and traffic standards that must be met to conduct live streaming business. These preset performance indicators are also based on the characteristics of live streaming business.

[0147] For example, in standard mode, when a user's upload speed is below 1Mb / s, the retransmission rate increases sharply to over 10%, leading to numerous retransmissions and severe buffering. Therefore, the speed standard in the preset metrics can be defined as a user upload speed of at least 1Mb / s. Furthermore, live streaming typically involves continuous service requests; therefore, the duration standard in the preset metrics can be defined as a sustained high upload speed (1Mb / s) within each 15-minute interval. Additionally, for live streaming in standard definition mode, equivalent to a server bitrate of 10Mbps, the upload traffic can be calculated based on the live stream duration. Assuming a 15-minute live stream, the upload traffic would be 15 * 10Mbps * 60 / 8 = 1.1GB. Therefore, the traffic standard in the preset metrics can be defined as upload traffic exceeding 1GB within every 15 minutes.

[0148] In one possible design, step S302 could be implemented in the following ways:

[0149] Filter the uplink speeds of users that meet the rate standards from the service quality index data corresponding to each user terminal, for example, filter out uplink speeds exceeding 1Mb / s.

[0150] Filter the user uplink rate that meets the duration standard from the service quality index data corresponding to each user terminal. For example, filter the user uplink rate of users that continuously have high uplink rate services exceeding 1Mb / s in each time interval.

[0151] Filter the user uplink rate that meets the traffic standard from the service quality index data corresponding to each user terminal. For example, filter the user uplink rate that generates more than 1GB of traffic in every 15 minutes.

[0152] The selected user upload speeds are then used as the selected business quality indicator data.

[0153] S303: Determine live streaming users based on the selected business quality indicator data.

[0154] Based on the selected business quality indicator data, live streaming users are identified to determine who are engaged in live streaming business.

[0155] Optionally, if the preset indicator standard includes at least two of the following: rate standard, duration standard, and flow rate standard, step S303 may be implemented in the following ways:

[0156] The user type of the user terminal corresponding to the selected business quality indicator data is determined as a live streaming user.

[0157] Optionally, if the preset indicator standard includes one of the following: rate standard, duration standard, and flow rate standard, step S303 may be implemented as follows: Figure 5 As shown. Figure 5 This is a flowchart illustrating another business area positioning method provided in an embodiment of this application. Figure 5 As shown, the embodiments of this application include:

[0158] S401: Determine the user type of the user terminal corresponding to the selected business quality indicator data as the candidate user;

[0159] S402: Identify the model of the user terminal of the candidate user based on the user billing data corresponding to the candidate user;

[0160] S403: If the candidate user's terminal model is the target model, then the candidate user is determined to be a live broadcast user.

[0161] If the preset indicator standards include one of the following: rate standard, duration standard, and traffic standard, then the live streaming user needs to be identified in conjunction with the user terminal model.

[0162] For example, firstly, the user type corresponding to the selected business quality indicator data is determined as the candidate user. Then, the model of the candidate user's user terminal is identified based on the user billing data corresponding to the candidate user. If the model of the candidate user's user terminal is the target model, such as the target model being a mobile phone model with a 3D beauty function, then the candidate user is determined as a live streaming user.

[0163] In step S301, the communication data corresponding to each user terminal obtained includes the user billing data corresponding to the candidate user. The user billing data may include, for example, the user's mobile phone number (msisdn), user package data, user billing data, and user's mobile phone EM model (emsi).

[0164] Thus, by using steps S302 and S303 to determine the users who conduct live streaming services through the user terminals based on the service quality index data corresponding to each user terminal, the live streaming users are identified.

[0165] S304: Determine the live streaming time period for the live streaming user to conduct live streaming business based on the user signaling data corresponding to the live streaming user.

[0166] S305: Determine the latitude and longitude of the base station cell within each preset duration during the live broadcast period based on the user signaling data corresponding to the live broadcast user, so as to obtain multiple location points during the live broadcast period.

[0167] As described in the foregoing embodiments, the user signaling data includes the signaling start time. For a live streaming user, the live streaming time period can be determined based on the signaling start time. Furthermore, the user signaling data also includes the latitude and longitude of the base station cell. Therefore, after determining the live streaming time period, the latitude and longitude of the base station cell are obtained for each preset duration during the live streaming period, and these are then used as location points within the live streaming time period. For example, during the live streaming period, the latitude and longitude of the base station cell recorded most frequently within each 15-minute interval are recorded, and these recorded latitude and longitude are used as location points within the live streaming time period to obtain multiple location points within the live streaming time period, such as (A1, A2…An).

[0168] S306: Get the sum of the distances from each of the multiple location points to all other location points.

[0169] S307: Determine the location point corresponding to the minimum sum of multiple distances as the target location point for the live broadcast time period.

[0170] Calculate the sum of distances from each of the multiple location points to all other location points. Determine the location point corresponding to the minimum sum of the calculated distances as the target location point for the live broadcast period. Use this target location point as the live broadcast activity point for this live broadcast period.

[0171] S308: Determine the amount of live streaming activity for the corresponding base station cell of the live streaming user based on the target location point during the live streaming time period.

[0172] After obtaining the target location for the live broadcast time period, the live broadcast activity volume of the corresponding base station cell is further determined based on the target location. The live broadcast activity volume is used to characterize the degree of live broadcast aggregation.

[0173] In one possible design, step S308 could be implemented in the following ways:

[0174] First, the corresponding base station cell for the live stream user is determined based on the target location point during the live stream time period. Specifically, the target location point is one of multiple location points corresponding to the base station cell dimension. Knowing the target location point, the base station cell corresponding to the live stream user can be determined. Then, all live stream users within the corresponding base station cell are obtained. Based on the number of all live stream users and the live stream duration within a day, the live stream activity volume of the corresponding base station cell is calculated, which is the live stream activity volume of the corresponding base station cell.

[0175] Optionally, the live streaming activity volume of a base station cell can be the product of the number of all live streaming users in the base station cell within a day and the live streaming duration, and this product can be used to determine the live streaming activity volume of the base station cell, so as to quantify the live streaming activity volume of the base station cell.

[0176] Thus, through steps S304 to S308, the live streaming activity volume of the base station cell corresponding to the live streaming user is determined based on the user signaling data corresponding to the live streaming user.

[0177] S309: Determine the live streaming business area based on the volume of live streaming activities.

[0178] The area where live streaming activity is concentrated is identified as the live streaming service area. Therefore, after obtaining the live streaming activity of the base station cell corresponding to the live streaming user, the live streaming service area is determined based on the live streaming activity, thus realizing the positioning of the live streaming service area.

[0179] In one possible design, step S309 could be implemented as follows: Figure 6 As shown. Figure 6 This is a flowchart illustrating another business area positioning method provided in an embodiment of this application. Figure 6 As shown, the embodiments of this application include:

[0180] S3091: Obtain the amount of live streaming activity per unit area based on the amount of live streaming activity.

[0181] The live streaming activity volume of the corresponding base station cell for each live streaming user is distributed across a 100m*100m grid using a Thiessen chart, based on the network coverage area of ​​the base station cell. This yields the live streaming popularity value per unit area, which is also the live streaming activity volume per unit area. The Thiessen chart is generated based on the geographical area corresponding to the network coverage area of ​​the base station cell.

[0182] S3092: Generate a heat map based on the amount of live streaming activity per unit area.

[0183] On the city map of the area covered by the network coverage of the base station cell, a heat map is drawn based on the amount of live streaming activity per unit area to represent the concentration of live streaming users on the city map.

[0184] Optionally, different colors can be used to display different levels of live streaming activity on the heat map to differentiate the degree of user concentration. For example, the area with the highest live streaming activity in the heat map can be designated as Level 1, marked in red; the area with 10%-20% activity can be designated as Level 2, marked in purple; the area with 20%-30% activity can be designated as Level 3, marked in yellow; the area with 30%-40% activity can be designated as Level 4, marked in blue; the area with 40%-60% activity can be designated as Level 5, marked in green; and the area corresponding to the remaining live streaming activity (i.e., 60%-100%) can be designated as Level 6, marked in gray, thus forming a heat map with different colors displaying different levels of live streaming activity.

[0185] S3093: The coverage area of ​​the heat map on the geographical area corresponding to the base station cell of the live broadcast user is determined as the live broadcast service area.

[0186] A heat map was constructed on the city map of the area covered by the network coverage of the base station cell. This heat map visually displays the boundaries of areas where live streaming users congregate. Therefore, the coverage area of ​​the heat map within the geographical region corresponding to the base station cell of the live streaming user is defined as the live streaming service area, thus locating the live streaming service area. The geographical region corresponding to the base station cell of the live streaming user is also the area represented by the city map of the area covered by the network coverage of the base station cell.

[0187] This application provides a service area positioning method. Based on the characteristics of live streaming services, preset indicator standards are set. Live streaming users are identified by combining these preset indicator standards with user billing data from communication data and service quality indicator data for each user terminal. Then, the live streaming activity volume of the corresponding base station cell is determined based on the user signaling data of the live streaming user. Furthermore, a heat map is constructed based on the live streaming activity volume to identify the boundaries of the live streaming user aggregation area and locate the live streaming service area. By using user signaling data and service quality indicator data as references, accurate positioning of the live streaming service area is achieved, providing data support to meet the higher requirements for network performance speed and latency sensitivity needed to conduct live streaming services in the area, thereby improving user experience.

[0188] Figure 7 This is a schematic diagram of a service area positioning device provided in an embodiment of this application. Figure 7 As shown, the service area positioning device 500 provided in this application embodiment includes:

[0189] The acquisition module 501 is used to acquire communication data and service quality indicator data corresponding to each user terminal. The communication data includes user signaling data.

[0190] The first processing module 502 is used to determine the live streaming users based on the business quality index data corresponding to each user terminal. The live streaming users include users who conduct live streaming business through the user terminal.

[0191] The second processing module 503 is used to determine the live streaming activity volume of the base station cell corresponding to the live streaming user based on the user signaling data corresponding to the live streaming user, so as to determine the live streaming service area based on the live streaming activity volume.

[0192] exist Figure 7 On this basis, Figure 8 This is a schematic diagram of another service area positioning device provided in an embodiment of this application. Figure 8 As shown, the service area positioning device 500 provided in this embodiment of the application further includes: a third processing module 504. The third processing module 504 is used for:

[0193] The live streaming service area is updated according to a preset time period to track changes in the location of the live streaming service area.

[0194] Determine whether there is abnormal network load behavior in the live streaming service area based on location change data;

[0195] If so, generate a network anomaly report based on abnormal network load behavior, and implement network repair through the network anomaly report.

[0196] In one possible design, the third processing module 504 is also used for:

[0197] Generate a list of live streaming users within the live streaming service area, and push customized live streaming packages to each live streaming user in the list; and / or

[0198] Based on the service quality index data of all live streaming users, determine whether the corresponding base station cell of each live streaming user is a problem cell, and generate network early warning data based on the judgment results.

[0199] In one possible design, the first processing module 502 includes:

[0200] The first processing submodule is used to filter business quality indicator data that meet the preset indicator standards from the business quality indicator data corresponding to each user terminal. The preset indicator standards include one or more of the following: rate standard, duration standard, and traffic standard that must be met to carry out live streaming business.

[0201] The second processing submodule is used to determine live streaming users based on the filtered business quality indicator data.

[0202] In one possible design, the first processing submodule is specifically used for:

[0203] Filter the uplink speed of users that meet the rate standard from the service quality indicator data corresponding to each user terminal;

[0204] Filter the user uplink rate that meets the duration standard from the service quality indicator data corresponding to each user terminal;

[0205] Filter the user uplink rate that meets the traffic standards from the service quality indicator data corresponding to each user terminal;

[0206] The uplink speed of the selected users is determined as the selected business quality indicator data.

[0207] In one possible design, if the preset performance indicators include at least two of the following: rate standard, duration standard, and flow rate standard, the second processing submodule is specifically used for:

[0208] The user type of the user terminal corresponding to the selected business quality indicator data is determined as a live streaming user.

[0209] In one possible design, if the preset performance indicators include one of the following: rate standard, duration standard, and traffic standard, the second processing submodule is specifically used for:

[0210] The user type of the user terminal corresponding to the selected business quality indicator data is determined as the candidate user.

[0211] Identify the model of the user terminal of the candidate user based on the user billing data corresponding to the candidate user;

[0212] If the candidate user's terminal model matches the target model, then the candidate user is determined to be a live streaming user.

[0213] The communication data also includes user billing data corresponding to the candidate users.

[0214] In one possible design, the second processing module 503 is specifically used for:

[0215] The live streaming time period for a live streaming user is determined based on the user signaling data corresponding to the live streaming user.

[0216] The latitude and longitude of the base station cell within each preset duration during the live broadcast period are determined based on the user signaling data corresponding to the live broadcast user, so as to obtain multiple location points during the live broadcast period.

[0217] Get the sum of the distances from each of the multiple location points to all other location points;

[0218] The location point corresponding to the minimum sum of multiple distances is determined as the target location point for the live broadcast period.

[0219] The amount of live streaming activity for the corresponding base station cell of the live streaming user is determined based on the target location point during the live streaming time period.

[0220] In one possible design, the second processing module 503 is also used for:

[0221] Determine the corresponding base station cell for the live stream user based on the target location during the live stream time period;

[0222] Obtain all live streaming users within the cell corresponding to the live streaming user, and calculate the live streaming activity volume of the cell corresponding to the live streaming user based on the total number of live streaming users and the live streaming duration within a day.

[0223] In one possible design, the second processing module 503 is also used for:

[0224] The amount of live streaming activity per unit area is calculated based on the volume of live streaming activities.

[0225] A heat map is generated based on the amount of live streaming activity per unit area;

[0226] The coverage area of ​​the heat map on the geographical area corresponding to the base station cell of the live broadcast user is determined as the live broadcast service area.

[0227] In one possible design, the second processing module 503 is also used for:

[0228] The heat map uses different colors to represent different live streaming activity volumes.

[0229] The business area positioning device provided in this application embodiment can execute each step of the business area positioning method in the above method embodiment. Its implementation principle and technical effect are similar, and will not be repeated here.

[0230] Figure 9 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 9 As shown, the electronic device 600 may include a processor 601 and a memory 602 communicatively connected to the processor 601.

[0231] The memory 602 is used to store programs. Specifically, the program may include program code, which includes computer-executable instructions.

[0232] The memory 602 may include high-speed RAM memory, and may also include non-volatile memory (MoM-volatile memory), such as at least one disk storage device.

[0233] The processor 601 is used to execute computer execution instructions stored in the memory 602 to implement the business area positioning method.

[0234] The processor 601 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0235] Optionally, the memory 602 can be either standalone or integrated with the processor 601. When the memory 602 is a device independent of the processor 601, the electronic device 600 may further include:

[0236] Bus 603 is used to connect processor 601 and memory 602. The bus can be an industry standard architecture (ISA) bus, a peripheral component (PCI) bus, or an extended industry standard architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc., but this does not mean there is only one bus or one type of bus.

[0237] Optionally, in a specific implementation, if the memory 602 and the processor 601 are integrated on a single chip, the memory 602 and the processor 601 can communicate through an internal interface.

[0238] This application also provides a computer-readable storage medium, which may include various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk. Specifically, the computer-readable storage medium stores computer-executable instructions, which are used in the various steps of the methods in the above embodiments.

[0239] This application also provides a computer program product, including computer execution instructions that, when executed by a processor, implement the steps of the methods described above.

[0240] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0241] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A business area positioning method, characterized in that, include: Acquire communication data and service quality index data corresponding to each user terminal, wherein the communication data includes user signaling data; Live streaming users are determined based on the service quality index data corresponding to each user terminal, and the live streaming users include users who conduct live streaming services through the user terminal. The amount of live streaming activity in the base station cell corresponding to the live streaming user is determined based on the user signaling data corresponding to the live streaming user, and the live streaming service area is determined based on the amount of live streaming activity. The live streaming service area is updated according to a preset time period to track the location change data of the live streaming service area; Based on the location change data, determine whether there is abnormal network load behavior in the live streaming service area; If so, a network anomaly report is generated based on the abnormal network load behavior, and network repair is implemented through the network anomaly report.

2. The business area positioning method according to claim 1, characterized in that, After determining the live streaming service area based on the live streaming activity volume, the method further includes: Generate a list of live streaming users within the live streaming service area, and push customized live streaming packages to each live streaming user in the list; and / or Based on the service quality index data of all live streaming users, determine whether the corresponding base station cell of all live streaming users is a problem cell, and generate network early warning data based on the judgment result.

3. The business area positioning method according to claim 1 or 2, characterized in that, The step of determining live streaming users based on the service quality index data corresponding to each user terminal includes: Select business quality indicator data that meet the preset indicator standards from the business quality indicator data corresponding to each user terminal. The preset indicator standards include one or more of the following: rate standard, duration standard, and traffic standard that must be met to carry out live streaming business. The live streaming users are determined based on the selected business quality indicator data.

4. The business area positioning method according to claim 3, characterized in that, The step of filtering service quality indicator data that meets preset indicator standards from the service quality indicator data corresponding to each user terminal includes: Filter the user uplink rates that meet the rate standard from the service quality index data corresponding to each user terminal; Filter the user uplink rate that meets the duration standard from the service quality indicator data corresponding to each user terminal; Filter the user uplink rate that meets the traffic standard from the service quality index data corresponding to each user terminal; The uplink speed of the selected users is determined as the selected service quality indicator data.

5. The business area positioning method according to claim 4, characterized in that, If the preset indicator standards include at least two of the rate standard, the duration standard, and the traffic standard, determining the live stream users based on the selected service quality indicator data includes: The user type of the user terminal corresponding to the filtered business quality indicator data is determined as the live broadcast user.

6. The business area positioning method according to claim 4, characterized in that, If the preset indicator standards include one of the rate standard, the duration standard, and the traffic standard, the step of determining the live stream users based on the selected business quality indicator data includes: The user type of the user terminal corresponding to the filtered business quality indicator data is determined as the candidate user; The model of the user terminal of the candidate user is identified based on the user billing data corresponding to the candidate user; If the candidate user's terminal model is the target model, then the candidate user is determined to be the live stream user; The communication data also includes user billing data corresponding to the candidate user.

7. The business area positioning method according to claim 1 or 2, characterized in that, The step of determining the live streaming activity volume of the base station cell corresponding to the live streaming user based on the user signaling data corresponding to the live streaming user includes: The live streaming time period for the live streaming user is determined based on the user signaling data corresponding to the live streaming user. The latitude and longitude of the base station cell within each preset duration during the live broadcast time period are determined based on the user signaling data corresponding to the live broadcast user, so as to obtain multiple location points during the live broadcast time period; Obtain the sum of the distances from each of the plurality of location points to all other location points; The location point corresponding to the minimum sum of multiple distances is determined as the target location point for the live broadcast time period; The amount of live streaming activity of the corresponding base station cell of the live streaming user is determined based on the target location point during the live streaming time period.

8. The business area positioning method according to claim 7, characterized in that, Determining the live streaming activity volume of the base station cell corresponding to the live streaming user based on the target location point during the live streaming time period includes: The base station cell corresponding to the live stream user is determined based on the target location point during the live stream time period. Obtain all live streaming users within the cell corresponding to the live streaming user, and calculate the live streaming activity volume of the cell corresponding to the live streaming user based on the number of all live streaming users and the live streaming duration within a day.

9. The business area positioning method according to claim 8, characterized in that, The step of determining the live streaming business area based on the live streaming activity volume includes: The amount of live streaming activity per unit area is obtained based on the aforementioned amount of live streaming activity. A heat map is generated based on the amount of live streaming activity per unit area. The coverage area of ​​the heat map on the geographical area corresponding to the base station cell of the live broadcast user is determined as the live broadcast service area.

10. The business area positioning method according to claim 9, characterized in that, After generating the heat map based on the live activity volume per unit area, the method further includes: The heat map uses different colors to represent different live streaming activity volumes.

11. A business area positioning device, characterized in that, include: The acquisition module is used to acquire communication data and service quality indicator data corresponding to each user terminal, wherein the communication data includes user signaling data; The first processing module is used to determine live streaming users based on the service quality index data corresponding to each user terminal, wherein the live streaming users include users who conduct live streaming services through the user terminal. The second processing module is used to determine the live streaming activity volume of the base station cell corresponding to the live streaming user based on the user signaling data corresponding to the live streaming user, so as to determine the live streaming service area based on the live streaming activity volume. The third processing module is used to update the live streaming service area according to a preset time period in order to track the location change data of the live streaming service area. Based on the location change data, determine whether there is abnormal network load behavior in the live streaming service area; If so, a network anomaly report is generated based on the abnormal network load behavior, and network repair is implemented through the network anomaly report.

12. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory to implement the service area positioning method as described in any one of claims 1-10.

13. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the service area positioning method as described in any one of claims 1-10.

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