Adaptive operation and maintenance monitoring method and system for multiple live broadcast rooms

Abstract

The present invention discloses an adaptive operation and maintenance monitoring method and system for multiple live broadcast rooms, which relates to the field of live broadcast room operation and maintenance technology. The key points of its technical solution include the following steps: obtaining operation data of multiple live broadcast rooms, and each live broadcast room is connected to a live broadcast platform server through a network link; wherein, the operation data includes device operation data, network status data, interaction data and display data; when an abnormality occurs in the live broadcast room condition, the device operation data, network status data, interaction data and display data are analyzed to obtain the operation status deviation interval of the live broadcast room, the operation abnormality type of the live broadcast room is judged according to the operation status deviation interval, and the performance shortfall of the live broadcast room is obtained according to the operation abnormality type; wherein, the performance shortfall is the deviation parameter between the expected live broadcast effect and the actual live broadcast effect of the live broadcast room; the effect is that through continuous adaptive operation and maintenance monitoring, it can continuously adapt to different live broadcast scenarios and emergencies.

Description

Technical Field

[0001] The present invention relates to the field of live broadcast room operation and maintenance technology, and more specifically, to an adaptive operation and maintenance monitoring method and system for multiple live broadcast rooms. Background Art

[0002] With the booming live streaming industry, the number of live streaming studios is increasing, and live streaming scenarios are becoming increasingly complex and diverse. The operation and maintenance management of multiple live streaming studios faces numerous challenges. Traditional live streaming operation and maintenance management methods rely heavily on manual inspections and simple system monitoring indicators, making it difficult to obtain comprehensive and real-time operational data from live streaming studios. For example, simply observing common metrics like the server's CPU and memory usage makes it impossible to accurately determine whether a live streaming video freeze is caused by complex factors such as device performance issues, network transmission failures, or delayed interactive data processing. Traditional monitoring methods often fail to detect subtle performance changes and potential faults, leading to the accumulation of problems and their subsequent outbreak at critical moments, disrupting the normal progress of live streaming. Summary of the Invention

[0003] In view of the deficiencies in the prior art, the present invention aims to provide an adaptive operation and maintenance monitoring method and system for multiple live broadcast rooms.

[0004] To achieve the above object, the present invention provides the following technical solutions:

[0005] A method for adaptive operation and maintenance monitoring of multiple live broadcast rooms, the method comprising the following steps:

[0006] Obtaining operational data of multiple live broadcast rooms, each of which is connected to a live broadcast platform server via a network link; wherein the operational data includes device operational data, network status data, interaction data, and display data;

[0007] When an abnormality occurs in a live broadcast room, the device operation data, network status data, interaction data, and display data are analyzed to obtain an operation status deviation interval of the live broadcast room, the operation abnormality type of the live broadcast room is determined based on the operation status deviation interval, and the performance shortfall of the live broadcast room is obtained based on the operation abnormality type; wherein the performance shortfall is a deviation parameter between the expected live broadcast effect and the actual live broadcast effect of the live broadcast room;

[0008] The amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is obtained based on the expected live broadcast effect and the actual live broadcast effect of the live broadcast room in the deviation parameter. The amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is analyzed to obtain the first operation and maintenance coefficient of the live broadcast room;

[0009] Classify the various live broadcast tasks of the live broadcast room into security tasks and non-emergency tasks, and obtain the second operation and maintenance coefficient of the live broadcast room based on the security tasks and non-emergency tasks;

[0010] The live broadcast room is resource operated and maintained according to the first operation and maintenance coefficient and the second operation and maintenance coefficient.

[0011] Preferably, it also includes:

[0012] Set the target emergency repair time for the live broadcast room and obtain the time when the live broadcast room experienced abnormal operation;

[0013] The target repair time of the live broadcast room is obtained based on the time when the abnormal operation of the live broadcast room occurs and the target emergency repair time.

[0014] Preferably, when an abnormality occurs in the live broadcast room, the device operation data, network status data, interaction data and display data are analyzed to obtain the operation status deviation interval of the live broadcast room, specifically:

[0015] Obtain the equipment operation status curve within the target repair time based on the equipment operation data;

[0016] Obtain the network transmission quality curve within the target repair time based on the network status data;

[0017] Obtain the audience interaction activity curve within the target repair time based on the interaction data;

[0018] Obtain the content display effect curve within the target repair time based on the display data;

[0019] The expected live broadcast effect range of the live broadcast room is obtained based on the equipment operation status curve, network transmission quality curve and audience interaction activity curve, and the actual live broadcast effect range of the live broadcast room is obtained based on the content display effect curve;

[0020] And according to the expected live broadcast effect range and the actual live broadcast effect range, the operating status deviation range of the live broadcast room is obtained.

[0021] Preferably, the operation abnormality type of the live broadcast room is determined according to the operation state deviation interval, and the performance deficit of the live broadcast room is obtained according to the operation abnormality type, specifically:

[0022] Setting at least one standard deviation interval, wherein each of the standard deviation intervals corresponds to an operation abnormality type, and each of the operation abnormality types corresponds to a performance shortfall;

[0023] Compare the running state deviation interval of the live broadcast room with the standard deviation interval, and mark the standard deviation interval where the running state deviation interval of the live broadcast room is located as the target deviation interval;

[0024] The operation abnormality type corresponding to the target deviation interval is marked as the operation abnormality type of the live broadcast room, and the performance shortfall corresponding to the operation abnormality type is marked as the performance shortfall of the live broadcast room.

[0025] Preferably, the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is obtained based on the expected live broadcast effect and the actual live broadcast effect of the live broadcast room in the deviation parameter, specifically:

[0026] If the expected live broadcast effect corresponding to the live broadcast room in the deviation parameter is greater than or equal to the actual live broadcast effect, the difference between the expected live broadcast effect and the actual live broadcast effect corresponding to the live broadcast room is calculated to obtain the optimization adjustment amount required to improve the live broadcast effect within the target repair time;

[0027] The average workload of optimization and adjustment per unit time is obtained based on the optimization adjustment amount and the target repair time, and the live broadcast room is optimized and adjusted based on the average workload and the optimization adjustment amount;

[0028] If the expected live broadcast effect of the live broadcast room in the deviation parameter is less than the actual live broadcast effect, the difference between the expected live broadcast effect and the actual live broadcast effect corresponding to the live broadcast room is calculated to obtain the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time.

[0029] Preferably, the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is analyzed to obtain the first operation and maintenance coefficient of the live broadcast room, specifically:

[0030] The amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is marked as guarantee demand;

[0031] Get the unit resource guarantee cost corresponding to the unit live broadcast task in the live broadcast room;

[0032] The total guarantee cost for resource guarantee for all live broadcast tasks is obtained based on the guarantee demand of the live broadcast room and the unit resource guarantee cost;

[0033] A first operation and maintenance coefficient of the live broadcast room is obtained based on the total guarantee cost.

[0034] Preferably, the various live broadcast tasks of the live broadcast room are classified into security tasks and non-urgent tasks, specifically:

[0035] Get the task type of each live broadcast task in the live broadcast room;

[0036] Classifying the various live broadcast tasks in the live broadcast room according to a preset task classification standard to obtain task categories corresponding to the various live broadcast tasks; wherein the task categories include core task categories, important task categories, and ordinary task categories;

[0037] Setting deferred tasks based on the core task category, important task category, and common task category;

[0038] Live broadcast tasks are divided into guarantee tasks and non-urgent tasks based on the delay tasks.

[0039] Preferably, the second operation and maintenance coefficient of the live broadcast room is obtained based on the analysis of the guarantee tasks and non-emergency tasks, specifically:

[0040] Obtaining a total guarantee cost for resource guarantee for the guarantee task based on the guarantee task and the unit resource guarantee cost corresponding to the unit live broadcast task in the live broadcast room;

[0041] Get the unit task delay compensation cost corresponding to the unit live broadcast task in the live broadcast room;

[0042] Obtain the total compensation cost for non-urgent tasks based on the unit task delay compensation cost corresponding to the non-urgent tasks and the unit live broadcast tasks in the live broadcast room;

[0043] A second operation and maintenance coefficient of the live broadcast room is obtained based on the total guarantee cost and the total compensation cost.

[0044] Preferably, resource operation and maintenance processing is performed on the live broadcast room according to the first operation and maintenance coefficient and the second operation and maintenance coefficient, specifically:

[0045] If the first operation and maintenance coefficient is greater than or equal to the second operation and maintenance coefficient, a first resource guarantee value corresponding to the live broadcast room is obtained according to the guarantee demand and target repair time of the live broadcast room, and resource operation and maintenance processing is performed on all live broadcast tasks of the live broadcast room according to the first resource guarantee value;

[0046] If the first operation and maintenance coefficient is less than the second operation and maintenance coefficient, the second resource guarantee value corresponding to the live broadcast room is obtained based on the guarantee task and target repair time of the live broadcast room, and resource operation and maintenance processing is performed on the guarantee task of the live broadcast room based on the second resource guarantee value.

[0047] An adaptive operation and maintenance monitoring system for multiple live broadcast rooms, comprising:

[0048] An acquisition module is configured to acquire operation data of a plurality of live broadcast rooms, each of which is connected to a live broadcast platform server via a network link; wherein the operation data includes device operation data, network status data, interaction data, and display data;

[0049] a judgment module that analyzes device operation data, network status data, interaction data, and display data when an abnormality occurs in the live broadcast room to obtain an operation status deviation interval of the live broadcast room, determines the type of operation abnormality of the live broadcast room based on the operation status deviation interval, and obtains a performance shortfall of the live broadcast room based on the operation abnormality type; wherein the performance shortfall is a deviation parameter between the expected live broadcast effect and the actual live broadcast effect of the live broadcast room;

[0050] A first analysis module obtains, based on the expected live broadcast effect and the actual live broadcast effect of the live broadcast room in the deviation parameter, an amount of guaranteed resources required to maintain the actual live broadcast effect within a target repair time, and analyzes the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time to obtain a first operation and maintenance coefficient of the live broadcast room;

[0051] The second analysis module classifies the various live broadcast tasks of the live broadcast room into security tasks and non-emergency tasks, and obtains the second operation and maintenance coefficient of the live broadcast room based on the security tasks and non-emergency tasks;

[0052] The processing module performs resource operation and maintenance processing on the live broadcast room according to the first operation and maintenance coefficient and the second operation and maintenance coefficient.

[0053] Compared with the prior art, the present invention has the following beneficial effects:

[0054] This application comprehensively obtains the equipment operation data, network status data, interaction data and display data of multiple live broadcast rooms. By obtaining these multi-dimensional and all-round data, the accuracy and comprehensiveness of fault diagnosis are improved. The operation status deviation interval obtained through analysis can accurately determine the type of operation anomaly and then clarify the performance shortfall. This judgment avoids the misjudgment and inefficient troubleshooting caused by previous experience or vague judgment, greatly saving operation and maintenance time and resources, and improving the reliability of the live broadcast system.

[0055] Based on the performance shortfall, the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is determined, and the first operation and maintenance coefficient is derived through analysis. At the same time, the live broadcast tasks are classified into guarantee tasks and non-urgent tasks. The second operation and maintenance coefficient is derived based on the task characteristics. Resource operation and maintenance processing based on the first and second operation and maintenance coefficients realizes intelligent optimization of resource allocation. In the case of limited resources, the resource requirements of guarantee tasks are given priority to ensure that the core effect of the live broadcast is not affected; for non-urgent tasks, reasonable arrangements based on the remaining resources improve resource utilization efficiency, avoid excessive investment or unreasonable allocation of resources, and ensure that the live broadcast can operate with the optimal resource configuration in different scenarios, reducing operating costs while improving the quality of the live broadcast.

[0056] This application enables the live broadcast room to respond quickly to various abnormal situations. Whether it is a sudden equipment failure, temporary network fluctuations, or a sudden surge in audience interaction, problems can be discovered in a timely manner through data monitoring and analysis, and targeted measures can be taken quickly based on the determined abnormality type and operation and maintenance coefficient. Through continuous adaptive operation and maintenance monitoring, the live broadcast system can continuously adapt to different live broadcast scenarios and emergencies, maintain a good operating state, better meet user needs, and provide strong technical support for the long-term and stable development of the live broadcast business. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 A schematic diagram of the steps of an adaptive operation and maintenance monitoring method for multiple live broadcast rooms proposed by the present invention;

[0058] Figure 2 A schematic diagram of the steps for dividing security tasks and non-emergency tasks in an adaptive operation and maintenance monitoring method for multiple live broadcast rooms proposed by the present invention;

[0059] Figure 3 The present invention proposes a module schematic diagram of an adaptive operation and maintenance monitoring system for multiple live broadcast rooms. DETAILED DESCRIPTION

[0060] Reference Figures 1 to 3 shown.

[0061] Example 1 further illustrates the adaptive operation and maintenance monitoring method for multiple live broadcast rooms proposed by the present invention.

[0062] A method for adaptive operation and maintenance monitoring of multiple live broadcast rooms, the method comprising the following steps:

[0063] Obtaining operational data from multiple live streaming rooms, each of which is connected to a live streaming platform server via a network link; the operational data includes device operational data, network status data, interaction data, and display data;

[0064] When an abnormality occurs in a live broadcast room, the device operation data, network status data, interaction data, and display data are analyzed to obtain the operation status deviation interval of the live broadcast room. The operation abnormality type of the live broadcast room is determined based on the operation status deviation interval, and the performance shortfall of the live broadcast room is obtained based on the operation abnormality type. The performance shortfall is the deviation parameter between the expected live broadcast effect and the actual live broadcast effect of the live broadcast room.

[0065] The amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is obtained based on the expected live broadcast effect and the actual live broadcast effect of the live broadcast room in the deviation parameter. The amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is analyzed to obtain the first operation and maintenance coefficient of the live broadcast room;

[0066] Classify the various live broadcast tasks of the live broadcast room into security tasks and non-emergency tasks, and obtain the second operation and maintenance coefficient of the live broadcast room based on the security tasks and non-emergency tasks;

[0067] The live broadcast room is resource operated and maintained according to the first operation and maintenance coefficient and the second operation and maintenance coefficient.

[0068] Each live broadcast room of this application is connected to the live broadcast platform server through a network link, and with the help of data collection tools or interfaces, operation data is obtained from multiple data sources such as live broadcast room equipment, network nodes, and live broadcast platform background in real time and continuously. For device operation data, the hardware performance parameters of the device, such as the usage of CPU, memory, hard disk, etc., as well as physical indicators such as device temperature and fan speed, are collected through sensors installed on the device. These data reflect the real-time working status of the device. Network status data is obtained through network monitoring tools, including network bandwidth occupancy, data transmission delay, packet loss rate, etc., which are used to evaluate the transmission quality and stability of the network. Interactive data is extracted from the database of the live broadcast platform, covering the audience's behavior records such as messages, likes, voting, and sharing during the live broadcast, reflecting the audience's participation and interests. Display data is obtained by analyzing the live video stream, such as the resolution, frame rate, encoding format, color mode, etc.

[0069] When an abnormality occurs in the live broadcast room, such as screen freezes, audio interruptions, or interactive messages not displaying, the system triggers the abnormality analysis process. First, a multi-dimensional correlation analysis is performed on the stored device operation data, network status data, interaction data, and display data. For example, if the live broadcast screen freezes, the system checks whether the device's CPU and memory usage are too high (device operation data), whether the network bandwidth is insufficient or the latency is too large (network status data), whether the server load is too high due to a sudden increase in audience interaction (interaction data), and whether the frame rate and resolution of the video stream are abnormal (display data).

[0070] Comprehensive analysis determines the operating status deviation range. For example, if analysis reveals that network latency exceeds the normal threshold of 50ms and device CPU utilization exceeds 90%, this constitutes the current live broadcast room's operating status deviation range. Based on this deviation range, the pre-set anomaly type judgment rules accurately identify the type of operating anomaly, such as network transmission anomaly or device performance bottleneck. Furthermore, by comparing the expected live broadcast effect (such as the set smooth video and real-time interactive response) with the actual live broadcast effect (performance after the anomaly), the performance shortfall is calculated, i.e., the deviation parameter between the two.

[0071] First, assess the amount of guaranteed resources needed to maintain the actual live broadcast quality within the target repair time. For example, if the performance shortfall is due to insufficient graphics processing power on the current device, resulting in a lower-than-expected frame rate, then the guaranteed resources might include increasing the computing power of the graphics processing unit (GPU), such as allocating more GPU cores or increasing the GPU's operating frequency.

[0072] The first operation and maintenance coefficient of the live broadcast room is obtained by analyzing the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time. This coefficient reflects the relative degree and comprehensive indicators of the operation and maintenance resources required to make up for performance deficiencies and maintain the live broadcast effect. It is an important basis for subsequent resource allocation and operation and maintenance decisions.

[0073] Based on factors such as the nature, importance, and time urgency of the live broadcast task, various live broadcast tasks in the live broadcast room are divided into support tasks and non-urgent tasks. Support tasks are usually tasks that play a decisive role in the normal progress and core effect of the live broadcast, such as the anchor's key explanation, the display of important products, and interactive links such as real-time raffles. If problems occur in these tasks, it will directly affect the audience's viewing experience and the achievement of the core objectives of the live broadcast. Non-urgent tasks are relatively minor tasks that can be appropriately delayed and have a smaller impact on the key effects of the live broadcast, such as the compilation and analysis of audience messages after the live broadcast, and the archiving of historical live broadcast data.

[0074] The resource requirements of support tasks and non-urgent tasks are analyzed separately, including the intensity and temporal distribution of demand for equipment, network resources, and human resources. For example, a support task might require high computing resources and network bandwidth during a live broadcast, requiring real-time response, while non-urgent tasks require relatively low resources and can be performed during idle periods during the live broadcast. Taking these factors into consideration, a second O&M coefficient is calculated using a specific evaluation model. This coefficient reflects the differences in resource requirements and O&M management characteristics of different task types.

[0075] The first and second operation and maintenance coefficients serve as key factors for resource operation and maintenance decisions. First, use the first operation and maintenance coefficient to determine the primary resource investment direction and scale required to address the performance shortfall. If the first operation and maintenance coefficient is high, it indicates a severe performance shortfall, requiring the prioritization of significant resources, such as increasing server computing resources and upgrading network equipment.

[0076] Combined with the second operation and maintenance coefficient, remaining resources are rationally allocated while ensuring that primary resource inputs meet performance repair requirements. For security tasks, sufficient resources are ensured to support them during the live broadcast, prioritizing their smooth progress. For non-urgent tasks, flexible arrangements are made based on remaining resources, such as allocating resources to complete related tasks during low-volume periods. This approach enables dynamic and optimized allocation of live broadcast room resources, ensuring the stable and efficient operation of the live broadcast system under different circumstances and improving the overall quality of live broadcast services.

[0077] Also includes:

[0078] Set the target emergency repair time for the live broadcast room and obtain the time when the live broadcast room experienced abnormal operation;

[0079] The target repair time of the live broadcast room is obtained based on the time when the abnormal operation of the live broadcast room occurs and the target emergency repair time.

[0080] This application pre-sets a reasonable target repair time based on factors such as the business type, importance, and audience size of the live broadcast room. For example, for large and popular entertainment live broadcasts, due to the large number of viewers and high real-time attention, a shorter target repair time, such as 10 minutes, is set; while for some small, highly professional but relatively small audience knowledge popularization live broadcasts, the target repair time can be appropriately relaxed to 20 minutes. This time is a reference standard for the upper limit of the time for the operation and maintenance team to carry out fault repair work, reflecting the differentiated considerations of the fault tolerance and repair urgency of different live broadcast rooms.

[0081] Through monitoring tools and sensors deployed in the live broadcast room equipment, network nodes and live broadcast platform background, the operating status of the live broadcast room is monitored in real time. If an operating abnormality is detected, such as equipment error, network interruption, screen freeze, etc., the exact time of the abnormality is immediately recorded. This time information is one of the important basic data for subsequent calculation of the target repair time.

[0082] Based on the time the live studio experienced an operational anomaly and the pre-set target repair time, a simple time calculation method was used to determine the target repair time. This means that the target repair time = the time the anomaly occurred + the target repair time. For example, if a live studio experienced network lag at 10:00 AM and the target repair time was set at 15 minutes, the target repair time for the studio would be 10:15 AM. The operations team used this as a time point and arranged a series of tasks around this time, including troubleshooting, resource allocation, and repair implementation, to ensure that the studio's normal operations were restored within the specified time.

[0083] When the live broadcast room is abnormal, the device operation data, network status data, interaction data and display data are analyzed to obtain the operation status deviation range of the live broadcast room, specifically:

[0084] Obtain the equipment operation status curve within the target repair time based on the equipment operation data;

[0085] Obtain the network transmission quality curve within the target repair time based on the network status data;

[0086] Obtain the audience interaction activity curve within the target repair time based on the interaction data;

[0087] Obtain the content display effect curve within the target repair time based on the display data;

[0088] The expected live broadcast effect range of the live broadcast room is obtained based on the equipment operation status curve, network transmission quality curve and audience interaction activity curve, and the actual live broadcast effect range of the live broadcast room is obtained based on the content display effect curve;

[0089] And according to the expected live broadcast effect range and the actual live broadcast effect range, the operating status deviation range of the live broadcast room is obtained.

[0090] This application continuously collects device operation data during the live broadcast room, such as CPU usage, memory occupancy, hard disk read and write speed, device temperature, etc. With time as the horizontal axis and various device performance indicators as the vertical axis, a device operation status curve is drawn within the target repair time. This curve dynamically reflects the changes in device performance over time. For example, if the CPU usage gradually increases over a period of time, it indicates that the device may be facing performance pressure.

[0091] Real-time network status data, including network bandwidth, latency, packet loss rate, etc., is obtained. A network transmission quality curve is drawn in chronological order, with time as the horizontal axis and the values ​​of various network indicators as the vertical axis. This curve provides an intuitive understanding of the network's transmission status within the target repair time. For example, a sudden increase in network latency may indicate network congestion or failure.

[0092] Conduct statistical analysis on interactive data (such as the number of comments, likes, and gifts sent). Plot an audience interaction activity curve, plotting the amount of interactive data per unit time as the vertical axis. This curve reflects changes in audience engagement during the live broadcast. A sudden drop in interactive activity during a certain period of time on the curve may indicate issues with the live broadcast content or format.

[0093] A content display effect curve is drawn based on display data (such as picture resolution, frame rate, color saturation, etc.). The horizontal axis is time, and the vertical axis is the value of content display-related indicators. This curve reflects the presentation quality of the live content within the target repair time. If the frame rate suddenly drops, it will cause the picture to freeze, affecting the audience's viewing experience.

[0094] An expected live broadcast effect range is determined by comprehensively analyzing the device operation status curve, network transmission quality curve, and audience interaction activity curve. This range represents the range of various indicators that should be achieved by live broadcast under ideal conditions. For example, stable device operation, network latency below a certain threshold, and active audience interaction together constitute the standard of the expected live broadcast effect range.

[0095] The device operating status curve reflects the changes in various device performance indicators over time within the target repair time, such as CPU utilization, memory usage, hard disk read / write speed, and device temperature. Under normal circumstances, the device's performance indicators should be within a reasonable range and will not negatively impact live streaming. For example, CPU utilization should generally remain low (e.g., below 80%, with the specific value adjustable based on device performance and live streaming requirements), memory usage should be stable with a certain margin, hard disk read / write speeds should be able to meet live streaming data storage and reading requirements, and device temperature should be within the normal operating temperature range (e.g., server equipment is generally between 20-25 degrees Celsius). By analyzing the curve trend and indicator range, the performance indicator fluctuation range when the device is operating normally can be determined.

[0096] The network transmission quality curve shows how indicators such as network bandwidth, latency, and packet loss rate change within the target repair time. High-quality network transmission should have stable and sufficient bandwidth (for example, HD live streaming requires at least a certain Mbps of uplink bandwidth, the specific value depends on the live broadcast quality), low network latency (generally controlled within tens of milliseconds), and a packet loss rate close to zero. To determine the value range of these indicators when the network is in good condition, for example, when live broadcast traffic is normal and there are no network failures, network latency is basically stable at a low value, and bandwidth remains at a level that meets live broadcast requirements. Based on this data, the ideal range of network transmission quality can be determined.

[0097] The audience interaction activity curve reflects the changes in interactive data such as the number of comments, likes, and gifts per unit time. During the live broadcast planning phase, a rough standard for interactive activity is usually set based on the type of broadcast, content, and expected goals. For example, a popular entertainment broadcast is expected to have a certain number of comments per minute, as well as a high number of likes and gifts. For knowledge and popular science broadcasts, a greater emphasis may be placed on audience questions and in-depth discussions. When analyzing this curve, reference is made to the data of previous successful live broadcasts of the same type and the planning expectations for the current broadcast to determine a reasonable range for audience interaction activity, such as the expected number of comments per minute and the expected average number of likes and gifts over a certain time period.

[0098] Different types of live broadcasts have different degrees of dependence on device operation, network transmission, and audience interaction. Therefore, it is necessary to assign weights to the indicators corresponding to each curve. For example, for game live broadcasts that mainly display high-definition images and real-time interaction, the device operation status (to ensure smooth images) and audience interaction activity (to measure audience participation) may have higher weights. Network transmission quality is also important but the weight can be slightly lower. For e-commerce live broadcasts, the weights of the three may be relatively balanced. The determination of the weights needs to be combined with the specific business needs and characteristics of the live broadcast, and is generally determined through correlation analysis of historical live broadcast data.

[0099] The equipment operation performance index range, network transmission quality index range, and audience interaction activity index range obtained from the above analysis are integrated according to the determined weights. For each time point or time period, a comprehensive index range is determined by comprehensively considering the index ranges of the three aspects. For example, at a certain moment, the equipment operation index is within the normal range, the network transmission index is also normal, and the audience interaction activity reaches the expected level. The index ranges of these three aspects are combined to form the expected live broadcast effect index at that moment. The expected live broadcast effect range is obtained by combining the indicators of each moment within the entire target repair time. This range covers multiple dimensions such as equipment, network, and audience interaction. It represents the comprehensive effect index range that the live broadcast room should achieve under ideal circumstances, and provides a reference standard for evaluating the actual live broadcast effect.

[0100] The actual live broadcast effect range is determined based on the content display effect curve and the actual live broadcast presentation. This range reflects the actual range of various display indicators of the live broadcast in the current state. For example, the fluctuation range of indicators such as picture resolution and frame rate during the actual live broadcast process is the actual live broadcast effect range.

[0101] Compare the expected live broadcast effect range with the actual live broadcast effect range to find the difference range between the two and obtain the operating status deviation range. This deviation range reflects the degree of deviation between the actual live broadcast effect and the expected effect. By analyzing the specific indicator differences within the deviation range, we can deeply understand the problems in the live broadcast and provide a clear direction for subsequent troubleshooting and optimization work.

[0102] The operation abnormality type of the live broadcast room is determined based on the operation status deviation interval, and the performance deficit of the live broadcast room is obtained based on the operation abnormality type, specifically:

[0103] Set at least one standard deviation interval, each standard deviation interval corresponds to an operation abnormality type, and each operation abnormality type corresponds to a performance shortfall;

[0104] Compare the running state deviation interval of the live broadcast room with the standard deviation interval, and mark the standard deviation interval where the running state deviation interval of the live broadcast room is located as the target deviation interval;

[0105] The operation abnormality type corresponding to the target deviation interval is marked as the operation abnormality type of the live broadcast room, and the performance shortfall corresponding to the operation abnormality type is marked as the performance shortfall of the live broadcast room.

[0106] This application pre-sets at least one standard deviation interval, each standard deviation interval corresponds to a specific type of operation anomaly, and each type of operation anomaly is associated with a corresponding performance shortfall. For example, standard deviation interval A is set to network delay higher than a certain threshold and bandwidth lower than a specific value, and its corresponding operation anomaly type is "poor network transmission". The performance shortfall under this anomaly type includes quantitative indicators of live screen freezes, interactive message delays, etc.; standard deviation interval B is when the device CPU usage exceeds a certain proportion and the memory usage is too high, corresponding to the "device performance bottleneck" anomaly type, and the performance shortfall is manifested as a quantitative description of frame drops, slow program response, etc. These standard deviation intervals and corresponding relationships are based on a large amount of live broadcast experience data, industry standards, and analysis and summary of common faults.

[0107] After obtaining the live broadcast room's operating status deviation interval, it is compared one by one with the pre-set standard deviation interval. During the comparison process, the various indicators of the operating status deviation interval (such as device performance indicators, network indicators, interaction indicators, etc.) are checked to see whether they meet the range requirements of a certain standard deviation interval. For example, if the live broadcast room's network latency is consistently higher than the standard value and the bandwidth is also lower than the normal level, and other indicators match, then the operating status deviation interval is consistent with the standard deviation interval A mentioned above. The matching standard deviation interval is marked as the target deviation interval.

[0108] After determining the target deviation range, the corresponding operation anomaly type is marked as the current operation anomaly type for the live broadcast room. For example, if the target deviation range is A, the operation anomaly type is "poor network transmission." At the same time, the performance shortfall corresponding to this operation anomaly type is marked as the performance shortfall for the live broadcast room. This means that the specific quantitative performance indicator deviations such as the degree of screen freezes and interactive message delays caused by poor network transmission in the current live broadcast room are clearly defined.

[0109] Based on the expected live broadcast effect and actual live broadcast effect of the live broadcast room in the deviation parameters, the guaranteed resource amount required to maintain the actual live broadcast effect within the target repair time is obtained as follows:

[0110] If the expected live broadcast effect corresponding to the live broadcast room in the deviation parameter is greater than or equal to the actual live broadcast effect, the difference between the expected live broadcast effect and the actual live broadcast effect corresponding to the live broadcast room is calculated to obtain the optimization adjustment amount required to improve the live broadcast effect within the target repair time;

[0111] The average workload of optimization and adjustment per unit time is obtained based on the optimization adjustment amount and the target repair time, and the live broadcast room is optimized and adjusted based on the average workload and the optimization adjustment amount;

[0112] If the expected live broadcast effect of the live broadcast room in the deviation parameter is less than the actual live broadcast effect, the difference between the expected live broadcast effect and the actual live broadcast effect corresponding to the live broadcast room is calculated to obtain the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time.

[0113] This application compares the expected live broadcast effect and the actual live broadcast effect of the live broadcast room in the deviation parameters. The expected live broadcast effect is the ideal live broadcast state set in the live broadcast planning stage, covering multiple indicators such as picture quality, interaction frequency, and content display effect; the actual live broadcast effect is the actual performance of the current live broadcast obtained by real-time monitoring of equipment operation data, network status data, interaction data, and display data, to judge the relationship between the two and determine whether the live broadcast effect meets or exceeds expectations.

[0114] If the expected live broadcast effect is greater than or equal to the actual live broadcast effect, it indicates that there is room for improvement. The difference between the expected and actual live broadcast effects is calculated to determine the optimization adjustment required to improve the live broadcast effect within the target repair time. For example, if the expected live broadcast resolution is 1080P, but the actual resolution is only 720P, the calculated resolution increase is part of the optimization adjustment.

[0115] Based on the optimization adjustment and the target repair time, calculate the average workload for each optimization adjustment. Assuming the target repair time is 30 minutes, the optimization adjustment is the sum of multiple tasks, such as improving image resolution and improving network latency. Dividing these tasks evenly over 30 minutes yields the workload required per unit time, which is the average workload.

[0116] Based on the average workload and optimization adjustment amount, operation and maintenance personnel and resources are arranged to optimize and adjust the live broadcast room. According to the calculated work rhythm, various optimization tasks are gradually completed within the target repair time, such as upgrading graphics processing equipment to improve resolution, optimizing network configuration to reduce latency, etc., thereby improving the live broadcast effect.

[0117] When the expected live broadcast effect is lower than the actual live broadcast effect, it indicates that the current live broadcast is performing well. To maintain this high-quality live broadcast status, the difference between the expected and actual live broadcast effects is calculated to determine the guaranteed amount of resources required to maintain the actual live broadcast effect within the target repair time. For example, if the actual audience interaction during the live broadcast far exceeds expectations, to ensure smooth interaction, it may be necessary to increase server resources, optimize interactive programs, etc. After calculating the specific amount of resources required, the corresponding resources are invested to maintain a good live broadcast effect.

[0118] The first operation and maintenance coefficient of the live broadcast room is obtained by analyzing the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time, which is:

[0119] The amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is marked as guarantee demand;

[0120] Get the unit resource guarantee cost corresponding to the unit live broadcast task in the live broadcast room;

[0121] The total guarantee cost for resource guarantee for all live broadcast tasks is obtained based on the guarantee demand of the live broadcast room and the unit resource guarantee cost;

[0122] The first operation and maintenance coefficient of the live broadcast room is obtained based on the total guarantee cost.

[0123] This application marks the guaranteed amount of resources required to maintain the actual live broadcast effect within the target repair time as the guarantee demand. For example, if the live broadcast room has a screen freeze problem caused by insufficient graphics processing power and insufficient network bandwidth, then the additional graphics processing equipment resources and network bandwidth resources required to solve these two problems constitute the guarantee demand of the live broadcast room.

[0124] Cost accounting is performed in advance for various resources in the live broadcast room to determine the unit resource guarantee cost corresponding to each live broadcast task. A unit live broadcast task can be a basic functional module of the live broadcast room or a specific business operation. For example, the cost of equipment resources and network resources required for each 10-minute product demonstration live broadcast task is calculated, and the unit resource guarantee cost of each live broadcast task is calculated. This cost data covers multiple aspects such as equipment purchase and maintenance costs, network rental costs, and labor costs, and is an important basis for subsequent calculations.

[0125] The total guarantee cost for resource guarantee of all live broadcast tasks is obtained by multiplying the determined guarantee demand and the obtained unit resource guarantee cost. This calculation method converts the guarantee demand into a specific cost value, which intuitively reflects the resource cost investment required to ensure the normal operation of the live broadcast room.

[0126] The calculated total guarantee cost is used to determine the first operation and maintenance coefficient for the live broadcast room. This coefficient can be a function of the total guarantee cost, for example, first operation and maintenance coefficient = total guarantee cost × a certain proportional factor (this proportional factor is determined based on a large amount of historical data). The first operation and maintenance coefficient comprehensively reflects the cost investment in resource guarantee for the live broadcast room, providing a quantitative basis for subsequent resource allocation and operation and maintenance decisions.

[0127] The various live broadcast tasks of the live broadcast room are classified into security tasks and non-urgent tasks, specifically:

[0128] Get the task type of each live broadcast task in the live broadcast room;

[0129] Classify the live broadcast tasks of the live broadcast room according to the pre-set task classification standard to obtain the task category corresponding to each live broadcast task; wherein the task category includes core task category, important task category and ordinary task category;

[0130] Set up deferrable tasks based on core task categories, important task categories, and common task categories;

[0131] Live broadcast tasks are divided into guarantee tasks and non-urgent tasks based on the delay tasks.

[0132] This application obtains the task types of various live broadcast tasks in the live broadcast room through live broadcast-related business process records. These task types cover various specific activities during the live broadcast process, such as the host's product introduction, interactive games with the audience, background data statistics, etc. Each task has its specific function and role.

[0133] The acquired live broadcast tasks are classified according to pre-set task classification standards. The task classification standards are usually formulated based on factors such as the importance of the task to the live broadcast effect, time urgency, and the degree of impact on the audience experience.

[0134] Core tasks are crucial to achieving the core goals of live streaming, directly impacting the audience's overall experience and the key value it delivers. For example, in e-commerce live streams, the host's detailed explanation of core products and demonstration of key product features, and in educational live streams, the teacher's imparting of key knowledge, among other tasks, can severely impact the live stream's purpose and audience satisfaction.

[0135] While important tasks don't directly determine the success of a livestream like core tasks do, they do have a significant impact on the overall effectiveness, audience retention, and engagement. For example, introducing limited-time promotions in e-commerce livestreams and answering questions in educational livestreams can enhance audience engagement and interest.

[0136] Ordinary task categories are relatively less important and have little impact on the core effect of the live broadcast, such as a simple summary after the live broadcast and the display of some minor information.

[0137] Delayable tasks are determined based on the categorized core, important, and common task categories. Generally speaking, most common tasks can be set as deferrable, as their delayed execution will not significantly impact the key objectives and core experience of the live stream. Some tasks in the important task category can also be included in the deferrable task category if a certain degree of delay is allowed in the scheduling. For example, if a planned interactive mini-game during a live stream encounters a technical issue, the game session can be temporarily delayed.

[0138] Tasks other than deferrable tasks, namely, tasks in the core task category and some important task categories that cannot be postponed, are classified as guarantee tasks. These tasks require priority in resource and operation and maintenance support to ensure their smooth execution during the live broadcast process. Delayable tasks are classified as non-urgent tasks and have a certain degree of flexibility in resource allocation and operation and maintenance processing. They can be arranged for execution based on the actual live broadcast situation and resource conditions.

[0139] The second operation and maintenance coefficient of the live broadcast room is obtained based on the analysis of security tasks and non-emergency tasks, which is:

[0140] The total guarantee cost for resource guarantee of the guarantee task is obtained based on the guarantee task and the unit resource guarantee cost corresponding to the unit live broadcast task in the live broadcast room;

[0141] Get the unit task delay compensation cost corresponding to the unit live broadcast task in the live broadcast room;

[0142] Obtain the total compensation cost for non-urgent tasks based on the unit task delay compensation cost corresponding to the non-urgent tasks and the unit live broadcast tasks in the live broadcast room;

[0143] The second operation and maintenance coefficient of the live broadcast room is obtained based on the total guarantee cost and the total compensation cost.

[0144] After determining the guarantee task, this application combines the unit resource guarantee cost corresponding to the unit live broadcast task in the live broadcast room (that is, the cost of resources required to guarantee each unit live broadcast task, covering equipment, network, manpower and other resource costs), and obtains the total guarantee cost of resource guarantee for the guarantee task through multiplication operation.

[0145] The unit delay compensation cost for each live broadcast task in the live broadcast room is determined through historical data statistics. This cost reflects the compensation cost for the potential losses caused by delaying the execution of a unit live broadcast task, such as decreased viewer satisfaction and lost business opportunities.

[0146] For example, while some tasks (non-urgent) can be delayed during a livestream, delays can lead to a range of negative consequences. For example, delaying the lucky draw portion of a livestream can reduce viewers' patience while waiting, thereby reducing their satisfaction and enthusiasm for the livestream. Delaying responses to viewers' messages can make viewers feel neglected, impacting their perception of the host and the livestream platform. Furthermore, delaying some non-urgent tasks can lead to missed opportunities and cause business losses. For example, delaying the release of promotional content related to the livestream can miss traffic peaks, reduce exposure, and reduce the flow of potential viewers. These reduced audience experience and lost business opportunities caused by task delays require a certain cost to compensate for or mitigate, resulting in a unit of task delay compensation cost.

[0147] The total compensation cost for non-urgent tasks is obtained by multiplying the determined number of non-urgent tasks and the unit task delay compensation cost.

[0148] The second O&M coefficient for a live studio is calculated by weighted summing the total support cost and total compensation cost. This coefficient reflects the studio's overall performance in terms of support mission resource investment and the risk of non-urgent mission delays, providing an important basis for decision-making on live resource O&M.

[0149] The resource operation and maintenance processing of the live broadcast room is performed according to the first operation and maintenance coefficient and the second operation and maintenance coefficient, specifically:

[0150] If the first operation and maintenance coefficient is greater than or equal to the second operation and maintenance coefficient, a first resource guarantee value corresponding to the live broadcast room is obtained based on the guarantee demand and target repair time of the live broadcast room, and resource operation and maintenance processing is performed on all live broadcast tasks of the live broadcast room based on the first resource guarantee value;

[0151] If the first operation and maintenance coefficient is less than the second operation and maintenance coefficient, the second resource guarantee value corresponding to the live broadcast room is obtained based on the guarantee task and target repair time of the live broadcast room, and resource operation and maintenance processing is performed on the guarantee task of the live broadcast room based on the second resource guarantee value.

[0152] This application first compares the first and second operation and maintenance coefficients. The first coefficient reflects the degree of resource support cost required to maintain the actual live broadcast effect, which is related to the overall performance shortfall and support requirements of the live broadcast room. The second coefficient reflects the combined cost of supporting tasks and the cost of compensating for delays in non-urgent tasks, focusing on cost considerations after task classification. By comparing these two coefficients, we can determine the focus of resource allocation.

[0153] When the first O&M coefficient is greater than or equal to the second O&M coefficient, the first resource guarantee value is calculated based on the livestream's support requirements (i.e., the amount of resources required to maintain the livestream) and the target repair duration (e.g., dividing the support requirements by the target repair duration to obtain the resource guarantee requirements per unit time). This value represents the amount of resources required to meet the overall livestream's requirements within the target repair duration.

[0154] Resource operations and maintenance are performed for all live broadcast tasks in the live broadcast room based on the first resource guarantee value. This means that resource allocation is fully guaranteed for all tasks, regardless of task type, to ensure the overall stable operation of the live broadcast. For example, if a live broadcast faces multiple issues such as equipment performance and network transmission, and the first operation and maintenance coefficient is high, resources for equipment upgrades and network optimization will be allocated to ensure the smooth execution of all live broadcast tasks.

[0155] When the first O&M coefficient is less than the second O&M coefficient, the second resource guarantee value is calculated based on the live broadcast room's guarantee mission and target repair duration. The second resource guarantee value is calculated by first determining the required resources for the guarantee mission and then combining it with the target repair duration. This value represents the amount of resources required to ensure the smooth progress of the critical mission within the target repair duration.

[0156] The resource operation and maintenance of the live broadcast room's security tasks are processed based on the second resource guarantee value. At this time, resources are focused on tasks that play a key role in the core effect of the live broadcast, and the resource requirements of non-urgent tasks are temporarily ignored or processed later. For example, in a live broadcast, if the interactive link is a security task, when the first operation and maintenance coefficient is less than the second operation and maintenance coefficient, priority is given to guaranteeing resources for the interactive link, such as ensuring the server's ability to process interactive messages and the network's stability for interactive data transmission. Non-urgent tasks such as statistical tasks after the live broadcast can be delayed when resources are limited. Example 2

[0157] The following technical features are added based on Example 1:

[0158] An adaptive operation and maintenance monitoring system for multiple live broadcast rooms, comprising:

[0159] An acquisition module is used to obtain the operating data of multiple live broadcast rooms, each of which is connected to the live broadcast platform server via a network link; the operating data includes device operating data, network status data, interaction data, and display data;

[0160] A judgment module analyzes device operation data, network status data, interaction data, and display data when an abnormality occurs in the live broadcast room to obtain an operation status deviation interval of the live broadcast room, determines the type of operation abnormality of the live broadcast room based on the operation status deviation interval, and obtains the performance shortfall of the live broadcast room based on the operation abnormality type; wherein the performance shortfall is a deviation parameter between the expected live broadcast effect and the actual live broadcast effect of the live broadcast room;

[0161] A first analysis module obtains, based on the expected live broadcast effect and the actual live broadcast effect of the live broadcast room in the deviation parameter, an amount of guaranteed resources required to maintain the actual live broadcast effect within a target repair time, and analyzes the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time to obtain a first operation and maintenance coefficient of the live broadcast room;

[0162] The second analysis module classifies the various live broadcast tasks of the live broadcast room into security tasks and non-emergency tasks, and obtains the second operation and maintenance coefficient of the live broadcast room based on the security tasks and non-emergency tasks;

[0163] The processing module performs resource operation and maintenance processing on the live broadcast room according to the first operation and maintenance coefficient and the second operation and maintenance coefficient.

[0164] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0165] Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented using software plus a necessary general-purpose hardware platform, or of course, hardware. Based on this understanding, the essence of the above technical solution, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for causing a computer device (such as a personal computer, server, or network device) to execute the methods described in each embodiment or certain portions of the embodiments.

[0166] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A method for adaptive operation and maintenance monitoring of multiple live broadcast rooms, characterized in that: The method comprises the following steps: Obtaining operation data of multiple live broadcast rooms; wherein the operation data includes device operation data, network status data, interaction data and display data; When the live broadcast room is abnormal, the device operation data, network status data, interaction data and display data are analyzed to obtain the operation status deviation range of the live broadcast room, specifically: Obtain the equipment operation status curve within the target repair time based on the equipment operation data; Obtain the network transmission quality curve within the target repair time based on the network status data; Obtain the audience interaction activity curve within the target repair time based on the interaction data; Obtain the content display effect curve within the target repair time based on the display data; The expected live broadcast effect range of the live broadcast room is obtained based on the equipment operation status curve, network transmission quality curve and audience interaction activity curve, and the actual live broadcast effect range of the live broadcast room is obtained based on the content display effect curve; And according to the expected live broadcast effect interval and the actual live broadcast effect interval, the running state deviation interval of the live broadcast room is obtained; Determine the type of operation anomaly of the live broadcast room based on the operation status deviation interval, and obtain the performance shortfall of the live broadcast room based on the operation anomaly type; wherein the performance shortfall is a deviation parameter between the expected live broadcast effect and the actual live broadcast effect of the live broadcast room; The amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is obtained based on the expected live broadcast effect and the actual live broadcast effect of the live broadcast room in the deviation parameter. The amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is analyzed to obtain the first operation and maintenance coefficient of the live broadcast room; Classify the various live broadcast tasks of the live broadcast room into security tasks and non-emergency tasks, and obtain the second operation and maintenance coefficient of the live broadcast room based on the security tasks and non-emergency tasks; The live broadcast room is resource operated and maintained according to the first operation and maintenance coefficient and the second operation and maintenance coefficient.

2. The adaptive operation and maintenance monitoring method for multiple live broadcast rooms according to claim 1 is characterized in that: Also includes: Set the target emergency repair time for the live broadcast room and obtain the time when the live broadcast room experienced abnormal operation; The target repair time of the live broadcast room is obtained based on the time when the abnormal operation of the live broadcast room occurs and the target emergency repair time.

3. The adaptive operation and maintenance monitoring method for multiple live broadcast rooms according to claim 2 is characterized in that: The operation abnormality type of the live broadcast room is determined based on the operation status deviation interval, and the performance deficit of the live broadcast room is obtained based on the operation abnormality type, specifically: Setting at least one standard deviation interval, wherein each of the standard deviation intervals corresponds to an operation abnormality type, and each of the operation abnormality types corresponds to a performance shortfall; Compare the running state deviation interval of the live broadcast room with the standard deviation interval, and mark the standard deviation interval where the running state deviation interval of the live broadcast room is located as the target deviation interval; The operation abnormality type corresponding to the target deviation interval is marked as the operation abnormality type of the live broadcast room, and the performance shortfall corresponding to the operation abnormality type is marked as the performance shortfall of the live broadcast room.

4. The adaptive operation and maintenance monitoring method for multiple live broadcast rooms according to claim 3 is characterized in that: Based on the expected live broadcast effect and actual live broadcast effect of the live broadcast room in the deviation parameters, the guaranteed resource amount required to maintain the actual live broadcast effect within the target repair time is obtained as follows: If the expected live broadcast effect of the live broadcast room in the deviation parameter is less than the actual live broadcast effect, the difference between the expected live broadcast effect and the actual live broadcast effect corresponding to the live broadcast room is calculated to obtain the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time.

5. The adaptive operation and maintenance monitoring method for multiple live broadcast rooms according to claim 4 is characterized in that: The first operation and maintenance coefficient of the live broadcast room is obtained by analyzing the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time, which is: The amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time is marked as guarantee demand; Get the unit resource guarantee cost corresponding to the unit live broadcast task in the live broadcast room; The total guarantee cost for resource guarantee for all live broadcast tasks is obtained based on the guarantee demand of the live broadcast room and the unit resource guarantee cost; A first operation and maintenance coefficient of the live broadcast room is obtained based on the total guarantee cost.

6. The adaptive operation and maintenance monitoring method for multiple live broadcast rooms according to claim 5 is characterized in that: The various live broadcast tasks of the live broadcast room are classified into security tasks and non-urgent tasks, specifically: Get the task type of each live broadcast task in the live broadcast room; Classifying the various live broadcast tasks in the live broadcast room according to a preset task classification standard to obtain task categories corresponding to the various live broadcast tasks; wherein the task categories include core task categories, important task categories, and ordinary task categories; Setting deferred tasks based on the core task category, important task category, and common task category; Live broadcast tasks are divided into guarantee tasks and non-urgent tasks based on the delay tasks.

7. The adaptive operation and maintenance monitoring method for multiple live broadcast rooms according to claim 6 is characterized in that: The second operation and maintenance coefficient of the live broadcast room is obtained based on the analysis of security tasks and non-emergency tasks, which is: Obtaining a total guarantee cost for resource guarantee for the guarantee task based on the guarantee task and the unit resource guarantee cost corresponding to the unit live broadcast task in the live broadcast room; Get the unit task delay compensation cost corresponding to the unit live broadcast task in the live broadcast room; Obtain the total compensation cost for non-urgent tasks based on the unit task delay compensation cost corresponding to the non-urgent tasks and the unit live broadcast tasks in the live broadcast room; A second operation and maintenance coefficient of the live broadcast room is obtained based on the total guarantee cost and the total compensation cost.

8. The adaptive operation and maintenance monitoring method for multiple live broadcast rooms according to claim 7 is characterized in that: The resource operation and maintenance processing of the live broadcast room is performed according to the first operation and maintenance coefficient and the second operation and maintenance coefficient, specifically: If the first operation and maintenance coefficient is greater than or equal to the second operation and maintenance coefficient, a first resource guarantee value corresponding to the live broadcast room is obtained according to the guarantee demand and target repair time of the live broadcast room, and resource operation and maintenance processing is performed on all live broadcast tasks of the live broadcast room according to the first resource guarantee value; If the first operation and maintenance coefficient is less than the second operation and maintenance coefficient, the second resource guarantee value corresponding to the live broadcast room is obtained based on the guarantee task and target repair time of the live broadcast room, and resource operation and maintenance processing is performed on the guarantee task of the live broadcast room based on the second resource guarantee value.

9. An adaptive operation and maintenance monitoring system for multiple live broadcast rooms, applied to an adaptive operation and maintenance monitoring method for multiple live broadcast rooms according to any one of claims 1 to 8, characterized in that: include: An acquisition module is configured to acquire operation data of a plurality of live broadcast rooms, each of which is connected to a live broadcast platform server via a network link; wherein the operation data includes device operation data, network status data, interaction data, and display data; a judgment module that analyzes device operation data, network status data, interaction data, and display data when an abnormality occurs in the live broadcast room to obtain an operation status deviation interval of the live broadcast room, determines the type of operation abnormality of the live broadcast room based on the operation status deviation interval, and obtains a performance shortfall of the live broadcast room based on the operation abnormality type; wherein the performance shortfall is a deviation parameter between the expected live broadcast effect and the actual live broadcast effect of the live broadcast room; A first analysis module obtains, based on the expected live broadcast effect and the actual live broadcast effect of the live broadcast room in the deviation parameter, an amount of guaranteed resources required to maintain the actual live broadcast effect within a target repair time, and analyzes the amount of guaranteed resources required to maintain the actual live broadcast effect within the target repair time to obtain a first operation and maintenance coefficient of the live broadcast room; The second analysis module classifies the various live broadcast tasks of the live broadcast room into security tasks and non-emergency tasks, and obtains the second operation and maintenance coefficient of the live broadcast room based on the security tasks and non-emergency tasks; The processing module performs resource operation and maintenance processing on the live broadcast room according to the first operation and maintenance coefficient and the second operation and maintenance coefficient.

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