Data processing method and device and electronic equipment

Abstract

The invention provides a data processing method and apparatus, and an electronic device. The method comprises the steps of obtaining attribute information and network parameters of multimedia of real-time communication in a communication abnormal time period; acquiring a preset feature acquisition rule; determining communication feature information of the real-time communication in the attribute information of the multimedia and the network parameters based on the feature acquisition rule; and determining an abnormal reason of the real-time communication in the communication abnormal time period based on the communication feature information.

Description

Technical Field

[0001] The embodiments of the present disclosure relate to the field of real-time communication technology, and in particular, to a data processing method, device, and electronic device. Background Art

[0002] Real-time communication (RTC) can provide high-quality, low-latency voice calls, video calls and other functions.

[0003] At present, in the process of providing RTC services to users, there may be problems with abnormal sound and picture. Electronic devices can obtain audio and video data generated during the RTC process, and process the RTC data through a preset audio and video evaluation algorithm to obtain a score corresponding to the RTC data. If the score is low, the electronic device can determine that there is a communication abnormality problem in this RTC service. However, based on the above method, when the electronic device determines that there is a communication abnormality problem in the RTC service, it can only determine the cause of the communication abnormality through manual investigation, resulting in low efficiency in determining the cause of the communication abnormality. Summary of the invention

[0004] The present disclosure provides a data processing method, device and electronic device, which are used to solve one or more problems in the prior art.

[0005] In a first aspect, the present disclosure provides a data processing method, the method comprising:

[0006] Acquiring multimedia attribute information and network parameters of real-time communication during the communication abnormality period;

[0007] Obtain preset feature acquisition rules;

[0008] Based on the feature acquisition rule, determining the communication feature information of the real-time communication in the attribute information of the multimedia and the network parameters;

[0009] Based on the communication characteristic information, an abnormal cause of the real-time communication within the communication abnormality period is determined.

[0010] In a second aspect, the present disclosure provides a data processing device, the data processing device comprising a first acquisition module, a second acquisition module, a first determination module and a second determination module, wherein:

[0011] The first acquisition module is used to acquire multimedia attribute information and network parameters of real-time communication during the communication abnormality period;

[0012] The second acquisition module is used to acquire a preset feature acquisition rule;

[0013] The first determination module is used to determine the communication characteristic information of the real-time communication from the attribute information of the multimedia and the network parameters based on the characteristic acquisition rule;

[0014] The second determination module is used to determine the abnormal cause of the real-time communication within the abnormal communication period based on the communication characteristic information.

[0015] In a third aspect, an embodiment of the present disclosure provides an electronic device including: a processor and a memory;

[0016] The memory stores computer-executable instructions;

[0017] The processor executes the computer-executable instructions stored in the memory, so that the at least one processor executes the data processing method as described in the first aspect and various possible aspects of the first aspect.

[0018] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium, in which computer execution instructions are stored. When a processor executes the computer execution instructions, the data processing method as described in the first aspect and various possible aspects of the first aspect are implemented.

[0019] The present disclosure provides a data processing method, device and electronic device, wherein the electronic device can obtain multimedia attribute information and network parameters of real-time communication during a communication abnormality period, and obtain a preset feature acquisition rule, and based on the feature acquisition rule, determine the communication feature information of the real-time communication in the multimedia attribute information and network parameters, and determine the abnormal cause of the real-time communication during the communication abnormality period based on the communication feature information. In the above method, since the electronic device can automatically determine the communication feature information associated with the communication data when the real-time communication has a communication abnormality in the multimedia attribute information and network parameters based on the preset feature acquisition rule, the electronic device can automatically, timely and accurately determine the cause of the abnormality of the real-time communication based on the communication feature information without manual participation, thereby improving the efficiency and accuracy of determining the cause of the communication abnormality and improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the embodiments of the present disclosure or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0021] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present disclosure;

[0022] Figure 2 A flowchart of a data processing method provided by an embodiment of the present disclosure;

[0023] Figure 3 A schematic diagram of the composition of communication characteristic information provided by an embodiment of the present disclosure;

[0024] Figure 4 A network feature diagram provided for an embodiment of the present disclosure;

[0025] Figure 5 A schematic diagram of determining an abnormal cause of real-time communication provided by an embodiment of the present disclosure;

[0026] Figure 6 A schematic diagram of a method for determining communication characteristic information provided by an embodiment of the present disclosure;

[0027] Figure 7 A schematic diagram of a process for determining communication characteristic information provided by an embodiment of the present disclosure;

[0028] Figure 8 A structural diagram of a data processing device provided by an embodiment of the present disclosure; and

[0029] Fig. 9 A schematic diagram of the structure of an electronic device provided in an embodiment of the present disclosure. DETAILED DESCRIPTION

[0030] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0031] To facilitate understanding, the concepts involved in the embodiments of the present disclosure are explained below.

[0032] Electronic device: is a device with wireless transceiver function. Electronic devices can be deployed on land, including indoors or outdoors, handheld, wearable or vehicle-mounted. The electronic device can be a mobile phone, a tablet computer, a computer with wireless transceiver function, a virtual reality (VR) electronic device, an augmented reality (AR) electronic device, a wireless terminal in industrial control, a vehicle-mounted electronic device, a wireless terminal in self-driving, a wireless electronic device in remote medical care, a wireless electronic device in smart grid, a wireless electronic device in transportation safety, a wireless electronic device in smart city, a wireless electronic device in smart home, a wearable electronic device, etc. The electronic device involved in the embodiments of the present disclosure can also be called a terminal, a user equipment (UE), an access electronic device, a vehicle-mounted terminal, an industrial control terminal, a UE unit, a UE station, a mobile station, a mobile station, a remote station, a remote electronic device, a mobile device, a UE electronic device, a wireless communication device, a UE agent or a UE device, etc. The electronic device can also be fixed or mobile.

[0033] In the related technologies, RTC technology can provide high-quality, low-latency voice calls, video calls, interactive live broadcasts and other rich scene functions. In the process of providing RTC services to users, there are user experience problems such as abnormal sound and abnormal picture. Therefore, it is necessary to quickly and accurately locate the cause of the abnormality and optimize it. At present, electronic devices can obtain the audio and video data generated in the RTC process, and process the RTC data through a preset audio and video evaluation algorithm to obtain the score corresponding to the RTC data. If the score is low, the electronic device can determine that there is a communication abnormality in the RTC service, and then determine the cause of the abnormality through manual investigation. This leads to low efficiency in determining the cause of the communication abnormality.

[0034] In order to solve the technical problems in the related art, the embodiment of the present disclosure provides a data processing method, where the electronic device can obtain the attribute information and network parameters of multimedia in the real-time communication during the communication abnormality period, and obtain the preset feature acquisition rules, and the electronic device can determine the parameter value range corresponding to each type of feature in the feature acquisition rules, and determine the communication feature information based on the parameter value range corresponding to each type of feature, the attribute information of the multimedia and the network parameters, and determine the abnormal cause of the real-time communication during the communication abnormality period based on the communication feature information. In the above method, since the electronic device can determine the communication feature information associated with the communication data when the communication abnormality occurs during the real-time communication process, the electronic device can accurately determine the cause of the abnormality of the real-time communication based on the communication feature information, and the electronic device can timely and accurately determine the communication feature information based on the preset feature acquisition rules, so that the efficiency and accuracy of determining the cause of the communication abnormality can be improved, and the user experience can be improved.

[0035] Next, combine Figure 1 , the application scenarios of the embodiments of the present disclosure are described.

[0036] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present disclosure. Figure 1 , including: terminal device 1, terminal device 2 and server. Among them, terminal device 1 and terminal device 2 are based on video communication. During the video communication process (the video may end or not, and the disclosed embodiment is not limited to this), the user reports that the video is stuck, and the server can obtain the video data and network parameters during the video communication process, and then determine the communication characteristic information of this video communication through the video data and network parameters, wherein the communication characteristic information may include a CPU usage rate of 90%, etc. (only for illustrative purposes, in actual application, the communication characteristic information may include multiple types). The server can determine that the cause of the video stuck is a high CPU usage rate based on the communication characteristic information. In this way, the server can quickly and accurately determine the cause of the abnormality, thereby improving the efficiency and accuracy of determining the cause of the abnormality.

[0037] It should be noted that Figure 1 The application scenarios of the embodiments of the present disclosure are merely illustrative and are not intended to limit the application scenarios of the embodiments of the present disclosure.

[0038] The technical solution of the present invention and how the technical solution of the present invention solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present invention will be described below in conjunction with the accompanying drawings.

[0039] Figure 2A flowchart of a data processing method provided by an embodiment of the present disclosure. Figure 2 , the method may include:

[0040] S201. Acquire multimedia attribute information and network parameters of real-time communication during a communication abnormality period.

[0041] The execution subject of the embodiments of the present disclosure may be an electronic device, or a data processing device provided in the electronic device. The data processing device may be implemented based on software, or the data processing device may be implemented based on a combination of software and hardware, which is not limited in the embodiments of the present disclosure. Optionally, the electronic device may be any device with end-to-end computing capabilities. For example, the electronic device may be a computer, a mobile phone, a server, etc., which is not limited in the embodiments of the present disclosure.

[0042] Among them, real-time communication can be a low-latency communication technology. For example, real-time communication can be applied to voice calls, video calls, interactive live broadcasts, retweeted live broadcasts, etc. Real-time communication can achieve high-quality, low-latency communication.

[0043] It should be noted that the multimedia in the embodiments of the present disclosure may be audio or video, or audio and video, and the embodiments of the present disclosure are not limited to this.

[0044] Optionally, multimedia data may be generated during real-time communication. For example, during real-time video communication, the electronic device may generate video data (image and audio), and during real-time voice communication, the electronic device may generate voice data (audio).

[0045] Optionally, the communication abnormality period may be a period during which the real-time communication abnormality occurs. For example, if the real-time communication abnormality occurs at time A, the communication abnormality period may be a period from 10 seconds before time A to 10 seconds after time A. If the real-time communication abnormality occurs during time period B, the communication abnormality period may be time period B or may include time period B. The embodiments of the present disclosure are not limited to this.

[0046] It should be noted that the duration of the communication abnormality period can be set arbitrarily, and the embodiments of the present disclosure do not limit this.

[0047] Optionally, the communication abnormality may include audio abnormality, picture abnormality, etc. For example, the communication abnormality may include picture freeze, audio freeze, etc. For example, during voice communication, if there is no sound for a period of time, the electronic device may determine that the voice communication has a communication abnormality; during video communication, if there is no sound, abnormal sound, no picture, or picture freeze for a period of time, the electronic device may determine that the video communication has a communication abnormality.

[0048] It should be noted that the embodiments of the present disclosure are merely illustrative of communication abnormality scenarios and are not intended to limit communication abnormality scenarios.

[0049] Optionally, the electronic device may obtain the multimedia attribute information and network parameters of the real-time communication during the communication abnormality period based on the following feasible implementation method: receiving uplink network parameters, uplink multimedia attribute information, and downlink network parameters and downlink multimedia attribute information, determining the communication abnormality period, and based on the communication abnormality period, determining the multimedia attribute information and network parameters during the communication abnormality period from the uplink network parameters, uplink multimedia attribute information, and downlink network parameters and downlink multimedia attribute information.

[0050] Optionally, the uplink network parameters may be network parameters when other devices upload information to the electronic device. For example, the uplink network parameters may be network parameters when other devices upload video data or audio data to the electronic device.

[0051] Optionally, the downlink network parameters may be network parameters when other devices download information in the electronic device. For example, the downlink network parameters may be network parameters when other devices can download video data and audio data in the electronic device.

[0052] Optionally, the attribute information of the uplink multimedia may be the attribute information of the multimedia data uploaded by other devices to the electronic device. For example, the attribute information of the uplink multimedia may be the attribute information of the media stream published by other devices. For example, the attribute information of the uplink multimedia may be the attribute information of the video data, the attribute information of the audio data, etc. uploaded by other devices to the electronic device.

[0053] Optionally, the attribute information of the downstream multimedia may be the attribute information of the multimedia data downloaded by other devices on the electronic device. For example, the attribute information of the downstream multimedia may be the attribute information of the media stream subscribed by other devices. For example, the attribute information of the downstream multimedia may be the attribute information of the video data downloaded by other devices on the electronic device, the attribute information of the audio data downloaded, etc.

[0054] Among them, the uplink network parameters may include uplink packet loss rate, round-trip time (RTT), network transmission level available bandwidth, etc., which are not limited in the embodiments of the present disclosure.

[0055] Among them, the downlink network parameters may include downlink packet loss rate, RTT, network transmission level available bandwidth, etc., which are not limited in the embodiments of the present disclosure.

[0056] The attribute information of the uplink multimedia may include at least one of the following: multimedia acquisition frame rate, multimedia encoding resolution, and multimedia transmission bit rate.

[0057] For example, the capture frame rate of the video stream can be 120 frames, that is, when the video stream is captured, 120 images are captured per second; the encoding resolution of the video stream can be 800*800, that is, the resolution of the video stream when it is played can be 800*800; the sending bit rate of the video stream can be 4000 bit rate, that is, the electronic device can transmit a 1080P, 60 frame rate video stream.

[0058] The attribute information of the downlink multimedia may include at least one of the following: multimedia playback frame rate, multimedia cache-related information, freeze duration, and multimedia reception bit rate.

[0059] For example, the playback frame rate of a video stream may be 60 frames, that is, when the playback end plays the video stream, it may include 60 images per second; the information associated with the multimedia cache may include large cache congestion information, small cache congestion information, etc.; the freeze duration may be the duration of the video freeze or the duration of the audio freeze, which is not limited in the embodiments of the present disclosure; the multimedia reception bit rate refers to the reception bit rate when the multimedia receives a video stream or an audio stream.

[0060] Optionally, the electronic device may determine the abnormal communication period based on the abnormal information fed back by the user. For example, during a video call by a user, if the video freezes, the picture is lost, or other abnormal situations occur, the user operates the video call device (clicks on the abnormal control, etc., which is not limited in the embodiments of the present disclosure), so that the video call device can send abnormal information to the electronic device, and the abnormal information may include the time when the abnormality occurred. The electronic device can determine the abnormal communication period based on the time. For example, if the electronic device receives user feedback that the video call is abnormal at time A, the electronic device can determine the period of 10 minutes before time A and 10 minutes after time A as the abnormal communication period.

[0061] For example, at the end of a video call, the user can rate the video call. If the score of the video call is low, the electronic device can determine that an abnormality has occurred in the video call, and the electronic device can determine the time period of the video call as a communication abnormality period.

[0062] It should be noted that the electronic device can determine the communication abnormality period based on any feasible implementation method, and the embodiments of the present disclosure are not limited to this.

[0063] Optionally, the electronic device can determine the multimedia attribute information and network parameters within the communication abnormality period from the uplink network parameters, the uplink multimedia attribute information, and the downlink network parameters and the downlink multimedia attribute information based on the communication abnormality period. For example, when the electronic device receives the network parameters and multimedia attribute information sent by other devices, the electronic device can also receive the timestamp corresponding to the network parameters and the multimedia attribute information. Therefore, the electronic device can determine the time when the network parameters and the multimedia attribute information appear based on the timestamp, and then determine the uplink network parameters, downlink network parameters, uplink multimedia attribute information, and downlink multimedia attribute information within the abnormal period as the multimedia attribute information and network parameters within the communication abnormality period. In this way, the electronic device can accurately filter out the multimedia attribute information and network parameters within the communication abnormality period, and then improve the accuracy of determining the cause of the abnormality.

[0064] S202: Obtain preset feature acquisition rules.

[0065] The preset feature acquisition rule is used to determine the communication feature information of the real-time communication in the network parameters and the attribute information of the multimedia. The communication feature information may include a label of the communication feature of the real-time communication. For example, the communication feature information may include a label of CPU overload, a label of insufficient sampling frame rate, etc.

[0066] Optionally, the preset feature acquisition rules may include at least one of the following features: CPU overload feature, acquisition frame rate feature, network disconnection feature, network switching feature, cache congestion feature, bandwidth feature, packet loss feature and delay feature.

[0067] For example, if the communication characteristic information of the real-time communication includes the CPU overload characteristic, it means that the CPU overload situation occurs within 10 seconds (which can be any value) during the abnormal communication period of this real-time communication.

[0068] For example, if the communication characteristic information of the real-time communication includes the acquisition frame rate characteristic, it means that during the abnormal communication period of this real-time communication, a low audio or video acquisition frame rate occurs within 10 seconds.

[0069] For example, if the communication characteristic information of the real-time communication includes a network disconnection feature, it means that during the communication abnormality period of this real-time communication, a network physical disconnection, an ICE disconnection, or an ICE connection failure occurred within 10 seconds.

[0070] For example, if the communication characteristic information of the real-time communication includes a network switching feature, it means that during the abnormal communication period of this real-time communication, a network type change or a WiFi frequency band change occurs within 10 seconds.

[0071] Among them, cache congestion characteristics, bandwidth characteristics, packet loss characteristics and delay characteristics belong to the network characteristic information in the communication characteristic information. For example, network congestion characteristics may include large cache congestion characteristics and small cache congestion characteristics; bandwidth characteristics may include low bandwidth characteristics, medium bandwidth characteristics and default normal bandwidth characteristics; packet loss characteristics may include default no packet loss characteristics, burst small packet loss characteristics, burst large packet loss characteristics, continuous small packet loss characteristics, and continuous large packet loss characteristics; delay characteristics may include default low delay characteristics, medium delay characteristics, high delay characteristics, ultra-high delay characteristics, burst single-point delay characteristics, and burst rising delay characteristics. In this way, electronic devices can mark real-time communications based on multiple characteristics, thereby improving the accuracy of determining the cause of the abnormality.

[0072] It should be noted that large, small, low, medium, high, and super high in the embodiments of the present disclosure can be determined based on multiple preset thresholds, wherein the multiple preset thresholds can be any values, and the embodiments of the present disclosure are not limited to this.

[0073] Optionally, the electronic device may obtain a preset feature acquisition rule from a database. For example, a user may pre-write a feature acquisition rule and store the feature acquisition rule in a database. When the electronic device investigates the abnormal cause of real-time communication, the electronic device may obtain the feature acquisition rule from the database.

[0074] It should be noted that the electronic device can obtain the preset feature acquisition rule based on any feasible implementation method (for example, the electronic device can receive the preset feature acquisition rule sent by other devices), and the embodiments of the present disclosure are not limited to this.

[0075] S203: Determine communication characteristic information of real-time communication from multimedia attribute information and network parameters based on characteristic acquisition rules.

[0076] Next, combine Figure 3 , the composition of communication characteristic information is explained.

[0077] Figure 3 A schematic diagram of the composition of communication characteristic information provided by an embodiment of the present disclosure. Figure 3 In the embodiment shown, audio freeze is taken as an example. Figure 3 , including: communication feature information affected by the uplink client, uplink network and media server when the audio is stuck. Among them, the uplink client will have CPU overload features and insufficient frame rate features in the audio collection scenario, and will have physical disconnection features, connection interruption features and network switching features in the ICE connection scenario. The uplink network will have network features when the audio is stuck. The media server will have cascaded weak network features and performance problem features when the audio is stuck.

[0078] It should be noted that Figure 3 The illustrated embodiment exemplarily illustrates the features of the upstream client and the upstream network when the audio is stuck. The downstream client and the downstream network are similar, and the embodiments of the present disclosure will not be described in detail here.

[0079] Next, combine Figure 4 ,right Figure 3 The network features in the illustrated embodiment are further described.

[0080] Figure 4 A network feature diagram provided by an embodiment of the present disclosure. Figure 4 , including cache congestion characteristics, bandwidth characteristics, packet loss characteristics and delay characteristics associated with network characteristics. Among them, cache congestion characteristics may include large cache congestion and small cache congestion. Bandwidth characteristics may include low bandwidth, medium bandwidth and normal bandwidth. Packet loss characteristics may include no packet loss, sudden small packet loss, sudden large packet loss, continuous small packet loss and continuous large packet loss. Delay characteristics may include low delay, medium delay, high delay, ultra-high delay (e.g., more than 2 seconds), sudden single point delay, and sudden rising delay.

[0081] Among them, the electronic device can determine the communication characteristic information of real-time communication in the attribute information of multimedia and network parameters based on the following feasible implementation methods: determine the parameter value range corresponding to each type of feature in the feature acquisition rule, and determine the communication characteristic information based on the parameter value range corresponding to each type of feature, the attribute information of multimedia and the network parameters.

[0082] Each type of feature has a corresponding parameter value range. If the multimedia attribute information or network parameter corresponding to any type of feature is within the parameter value range corresponding to the feature, the electronic device can determine that the feature exists in this real-time communication.

[0083] For example, the parameter value range of the frame rate feature can be a playback frame rate of less than 85 within 10 seconds. The electronic device can determine 10 seconds as the time window for feature acquisition and process 5 multimedia attribute information (the reporting period of multimedia attribute information is 2 seconds). If the audio playback frame rate is less than 85 within 10 seconds, the frame rate feature is 1, otherwise it is 0. In this way, the 5 multimedia attribute information can be aggregated into 1 communication feature information, and the timestamp of the communication feature information is the timestamp of the earliest event (that is, the first event in which the playback frame rate is less than 85).

[0084] S204: Determine the reason why the real-time communication is abnormal during the abnormal communication period based on the communication characteristic information.

[0085] Optionally, the communication characteristic information may include timing information. For example, the electronic device determines the communication characteristic information of real-time communication based on the multimedia attribute information and network parameters. Since the multimedia attribute information and network parameters contain timing information, the communication characteristic information may also include timing information.

[0086] Among them, the electronic device can determine the cause of the abnormality in real-time communication during the communication abnormality period based on the following feasible implementation methods: based on the timing information in the communication characteristic information, determine the time domain characteristics associated with the communication characteristic information, perform Fourier transform on the communication characteristic information to obtain frequency domain characteristics, and determine the cause of the abnormality in communication implemented during the communication abnormality period based on the time domain characteristics and the frequency domain characteristics.

[0087] Optionally, since the communication characteristic information may include timing information, the electronic device may process the communication characteristic information based on the LSTM model of the deep neural network, and further obtain time domain information associated with the communication characteristic information.

[0088] Optionally, the electronic device may extract features from the communication feature information based on the time series, and then obtain the time domain features associated with the communication feature information. For example, the electronic device may calculate the maximum value, minimum value, mean, sum, median, standard deviation, mean absolute deviation, interquartile range, etc. on the time series to obtain the time domain features associated with the communication feature information.

[0089] Optionally, the electronic device may perform Fourier transform processing on the communication characteristic information, and then extract the frequency characteristics from the Fourier transformed result. For example, the electronic device may perform fast Fourier transform processing on the communication characteristic information (time series data), and then obtain the frequency domain characteristics based on the transformed real part and imaginary part.

[0090] It should be noted that the electronic device can obtain the time domain characteristics and frequency domain characteristics associated with the communication characteristic information based on any feasible implementation method, and the embodiments of the present disclosure are not limited to this.

[0091] Optionally, the electronic device determines the abnormal cause of communication during the abnormal communication period based on the time domain characteristics and the frequency domain characteristics, which can be specifically done by inputting the time domain characteristics and the frequency domain characteristics into the detection model to obtain the abnormal cause of communication.

[0092] Among them, the detection model is a model obtained by learning multiple groups of samples, and each group of samples may include the time domain information, frequency domain information of the sample communication characteristics, and the sample abnormality cause corresponding to the sample communication characteristic information. For example, the electronic device can obtain the time domain information and frequency domain information corresponding to the sample communication characteristic information 1, and determine the sample abnormality cause corresponding to the sample communication characteristic information 1, so that a group of samples can be obtained, and the group of samples can include the time domain information and frequency domain information corresponding to the sample communication characteristic information 1, and the sample abnormality cause. Based on the above method, multiple groups of samples can be obtained.

[0093] The detection model may be a decision tree model. For example, the decision tree model may form a tree structure based on multiple if and then decision rules. The detection model may put multiple groups of samples into the root node, select an optimal feature (e.g., determined based on information gain or information gain ratio), and divide the multiple groups of samples into subsets so that the training set has the best classification under the current conditions. If multiple subsets can be optimally classified, the detection model may construct leaf nodes. If multiple subsets cannot be optimally classified, they may continue to be divided, construct corresponding nodes, and recursively process them in sequence until all samples are correctly classified.

[0094] Optionally, when the detection model training is completed, the electronic device can deploy the detection model online. For example, in the scenario where the cause of the abnormality is determined online in real time, the detection model can perform online detection in a 3-minute time period. For the determined room + user (RTC communication), the detection model can obtain the uplink and downlink network parameters and multimedia attribute information of the media audio with the flow granularity in the last 3 minutes, and cut it into a 10-second time window to extract the communication feature information, and then obtain 18 communication feature information (1 for 10 seconds, 18 for 3 minutes). The electronic device can determine the time domain features and frequency domain features of the communication feature information and use them as the input features of the detection model. After the detection model processes the time domain features and frequency domain features, the abnormal cause of the real-time communication can be obtained. For example, in an offline scenario, the processing process of the detection model is similar to that of the online scenario. The electronic device can obtain the attribute information of the multimedia audio up to the time point of user feedback, and extract the communication feature information with a 10-second window. When processing a 3-minute sample set, 18 communication feature information will be obtained. The electronic device can input the frequency domain characteristics and time domain characteristics of the communication feature information into the detection model, and the detection model can output the abnormal causes of real-time communication.

[0095] Next, combine Figure 5 , a process of determining the cause of abnormality in real-time communication is described.

[0096] Figure 5 A schematic diagram of determining the abnormal cause of real-time communication provided by an embodiment of the present disclosure. Figure 5 , including communication feature information and a detection model. The detection model is a model built based on a decision tree, and the communication feature information is determined based on the attribute information and network parameters of multimedia in the real-time communication during the communication abnormality period.

[0097] See also Figure 5 , electronic equipment ( Figure 5 The electronic device performs Fourier transform on the frequency domain features to obtain the frequency domain features associated with the communication feature information. The electronic device inputs the time domain features and the frequency domain features into the detection model, and the detection model can output the abnormal cause of the real-time communication. In this way, the electronic device can accurately describe the communication feature information based on the frequency domain features and the time domain features of the communication feature information, and the electronic device can automatically locate the abnormal cause of the real-time communication in combination with the detection model, thereby improving the efficiency and accuracy of determining the abnormal cause, and then can quickly handle the abnormality and improve the user experience.

[0098] The disclosed embodiment provides a data processing method, where an electronic device can obtain multimedia attribute information and network parameters of real-time communication during a communication anomaly period, and obtain a preset feature acquisition rule, and the electronic device can determine the parameter value range corresponding to each type of feature in the feature acquisition rule, and determine the communication feature information based on the parameter value range corresponding to each type of feature, the multimedia attribute information and the network parameters, and determine the abnormal cause of the real-time communication during the communication anomaly period based on the communication feature information. In the above method, since the electronic device can determine the communication feature information associated with the communication data when the communication anomaly occurs during the real-time communication process, the electronic device can quickly and accurately determine the cause of the abnormality in the real-time communication based on the communication feature information and the detection model, thereby improving the efficiency and accuracy of determining the cause of the communication anomaly, and can quickly handle the anomaly to improve the user experience.

[0099] exist Figure 2 Based on the embodiment shown below, combined with Figure 6 , a method for determining communication characteristic information of real-time communication in multimedia attribute information and network parameters based on feature acquisition rules in the above data processing method is described.

[0100] Figure 6 A schematic diagram of a method for determining communication characteristic information provided by an embodiment of the present disclosure. Figure 6 The method flow includes:

[0101] S601: Determine the parameter value range corresponding to each type of feature in the feature acquisition rule.

[0102] Optionally, the feature acquisition rule may include multiple types of features and parameter value ranges corresponding to each type of feature. For example, for the feature of insufficient acquisition frame rate, the parameter value range corresponding to the feature may be less than 90 frames per second within 10 seconds; for the feature of network switching, the parameter value range corresponding to the feature may be network switching or WiFi frequency band change within 10 seconds.

[0103] It should be noted that the parameter value range in the embodiment of the present disclosure can be any set range, and the embodiment of the present disclosure does not limit this. For example, based on the feature of insufficient acquisition frame rate, 10 seconds and frame rate 90 in the parameter value range are both adjustable values.

[0104] It should be noted that when the electronic device obtains the feature acquisition rule, the feature acquisition rule may include multiple parameter value ranges corresponding to multiple types of features.

[0105] S602: Determine communication feature information based on the parameter value range corresponding to each type of feature, multimedia attribute information, and network parameters.

[0106] Among them, the electronic device can determine the communication characteristic information based on the following feasible implementation method: for any type of feature, determine the attribute information or network parameters of the multimedia corresponding to the feature; if the attribute information or network parameters of the multimedia corresponding to the feature are within the parameter value range corresponding to the feature, the feature is marked as existing in the communication characteristic information; if the attribute information or network parameters of the multimedia corresponding to the feature are not within the parameter value range corresponding to the feature, the feature is marked as not existing in the communication characteristic information.

[0107] Each type of feature can correspond to a multimedia attribute information or network parameter. For example, the frame rate feature can correspond to the acquisition frame rate and playback frame rate in the multimedia attribute information, the packet loss feature can correspond to the packet loss rate in the network parameter, and the delay feature can correspond to the round-trip delay RTT in the network parameter.

[0108] Optionally, the electronic device may obtain the correspondence between the feature and the attribute information of the multimedia and the network parameters, and then determine the attribute information of the multimedia or the network parameters corresponding to each type of feature based on the correspondence. For example, the correspondence may be as follows: Figure 3 and Figure 4 In the embodiment shown, the electronic device can quickly and accurately determine the attribute information or network parameters of the multimedia corresponding to each type of feature based on the corresponding relationship. For example, for the frame rate feature, the electronic device can determine the attribute information or network parameters of the multimedia corresponding to each type of feature based on the frame rate feature and the corresponding relationship. Figure 3 The corresponding relationship shown is to obtain the acquisition frame rate within a unit time length and the playback frame rate within a unit time length in the attribute information of the multimedia.

[0109] Optionally, if the attribute information or network parameters of the multimedia corresponding to the feature are within the parameter value range corresponding to the feature, it means that the attribute information or network parameters of the multimedia match the feature acquisition rule, so the electronic device can mark the feature as present in the communication feature information. For example, the parameter value range of the frame rate feature can be: the acquisition frame rate is less than 90 frames within 10 seconds. If the acquisition frame rate acquired by the electronic device within 10 seconds is 60 frames, the electronic device can determine that the acquisition frame rate is within the parameter value range corresponding to the frame rate feature, and the electronic device can mark the frame rate feature as present (e.g., marked as 1) in the communication feature information.

[0110] Optionally, if the attribute information or network parameters of the multimedia corresponding to the feature are not within the parameter value range corresponding to the feature, it means that the attribute information or network parameters of the multimedia do not match the feature acquisition rule. Therefore, the electronic device can mark the feature as non-existent in the communication feature information. For example, the parameter value range of the frame rate feature can be: the acquisition frame rate is less than 90 frames within 10 seconds. If the acquisition frame rate obtained by the electronic device within 10 seconds is 120 frames, the electronic device can determine that the acquisition frame rate is not within the parameter value range corresponding to the frame rate feature, and the electronic device can mark the frame rate feature as non-existent (e.g., marked as 0) in the communication feature information.

[0111] Next, combine Figure 7 , the process of determining communication characteristic information of an electronic device is explained.

[0112] Figure 7 A schematic diagram of a process for determining communication characteristic information provided by an embodiment of the present disclosure. Figure 7 , including attribute information of the video within 10 seconds (exemplary illustration), network parameters within 10 seconds and feature extraction rules. Among them, the attribute information of the video may include acquisition frame rate: 120, CPU usage 95% and playback frame rate 60. Network parameters may include packet loss rate: 80%, bandwidth: 100k per second and round-trip delay: 10 milliseconds. Feature acquisition rules may include frame rate less than 90, CPU usage greater than 70%, bandwidth less than 500k per second, packet loss rate greater than 30% and round-trip delay greater than 50 milliseconds.

[0113] See also Figure 7, the electronic device can determine the communication characteristic information based on the attribute information of the video, the network parameters and the feature acquisition rules. Among them, since the CPU usage rate in the attribute information of the video is greater than 70%, the CPU overload mark in the communication characteristic information is 1, and since the acquisition frame rate in the attribute information of the video is greater than 90 and the playback frame rate is less than 90, the acquisition frame rate mark in the communication characteristic information is 0 and the playback frame rate mark is 1. Since the packet loss rate in the network parameters is greater than 30%, the bandwidth is less than 500k per second, and the round-trip delay is less than 50 milliseconds, the packet loss feature mark in the communication characteristic information is 1, the bandwidth feature mark is 1, and the delay feature mark is 0.

[0114] It should be noted that the communication characteristic information may also include timing information, which is not limited in the embodiments of the present disclosure.

[0115] In this way, the electronic device can accurately determine the communication characteristic information corresponding to the real-time communication based on the preset feature acquisition rules, multimedia attribute information and network parameters, and then accurately determine the abnormal cause of the real-time communication during the communication abnormality period according to the communication characteristic information, thereby improving the efficiency and accuracy of determining the abnormal cause, and can handle the abnormality in a timely manner to improve the user experience.

[0116] The disclosed embodiment provides a method for determining communication characteristic information, determining the parameter value range corresponding to each type of feature in the feature acquisition rule, and for any type of feature, determining the attribute information or network parameters of the multimedia corresponding to the feature, if the attribute information or network parameters of the multimedia corresponding to the feature are within the parameter value range corresponding to the feature, then the feature is marked as existing in the communication characteristic information, and if the attribute information or network parameters of the multimedia corresponding to the feature are not within the parameter value range corresponding to the feature, then the feature is marked as not existing in the communication characteristic information. In this way, the electronic device can mark the communication characteristic information of the real-time communication within the communication abnormality period based on the attribute information and network parameters of the multimedia within the communication abnormality period, and then can accurately determine the cause of the communication abnormality, thereby improving the efficiency and accuracy of determining the cause of the abnormality.

[0117] Figure 8 A schematic diagram of the structure of a data processing device provided by an embodiment of the present disclosure. Figure 8 , the data processing device 800 includes a first acquisition module 801, a second acquisition module 801, a first determination module 803 and a second determination module 804, wherein:

[0118] The first acquisition module 801 is used to acquire multimedia attribute information and network parameters of real-time communication during the communication abnormality period;

[0119] The second acquisition module 802 is used to acquire a preset feature acquisition rule;

[0120] The first determination module 803 is used to determine the communication characteristic information of the real-time communication from the attribute information of the multimedia and the network parameters based on the characteristic acquisition rule;

[0121] The second determination module 804 is configured to determine, based on the communication characteristic information, an abnormal cause of the real-time communication within the communication abnormality period.

[0122] According to one or more embodiments of the present disclosure, the first determining module 803 is specifically configured to:

[0123] Determine the parameter value range corresponding to each type of feature in the feature acquisition rule;

[0124] The communication characteristic information is determined based on the parameter value range corresponding to each type of characteristic, the attribute information of the multimedia and the network parameters.

[0125] According to one or more embodiments of the present disclosure, the first determining module 803 is specifically configured to:

[0126] For any type of feature, determine the attribute information or network parameters of the multimedia corresponding to the feature;

[0127] If the multimedia attribute information or network parameter corresponding to the feature is within the parameter value range corresponding to the feature, marking the feature as existing in the communication feature information;

[0128] If the multimedia attribute information or network parameter corresponding to the feature is not within the parameter value range corresponding to the feature, the feature is marked as not existing in the communication feature information.

[0129] According to one or more embodiments of the present disclosure, the feature acquisition rules include at least one of the following features: CPU overload feature, acquisition frame rate feature, network disconnection feature, network switching feature, cache congestion feature, bandwidth feature, packet loss feature and delay feature.

[0130] According to one or more embodiments of the present disclosure, the second determining module 804 is specifically configured to:

[0131] Determining a time domain feature associated with the communication feature information based on the timing information in the communication feature information;

[0132] Performing Fourier transform on the communication characteristic information to obtain frequency domain characteristics;

[0133] Based on the time domain features and the frequency domain features, an abnormal cause of the real-time communication within the communication abnormality period is determined.

[0134] According to one or more embodiments of the present disclosure, the second determining module 804 is specifically configured to:

[0135] Inputting the time domain features and the frequency domain features into a detection model to obtain the abnormal cause of the real-time communication;

[0136] The detection model is a model obtained by learning multiple groups of samples, and each group of samples includes time domain features, frequency domain features of sample communication feature information, and sample abnormality causes corresponding to the sample communication feature information.

[0137] According to one or more embodiments of the present disclosure, the first acquisition module 801 is specifically used to:

[0138] Receiving uplink network parameters, uplink multimedia attribute information, and downlink network parameters and downlink multimedia attribute information;

[0139] Determine the period of abnormal communication;

[0140] Based on the abnormal communication period, the attribute information and network parameters of the multimedia within the abnormal communication period are determined from the uplink network parameters, the attribute information of the uplink multimedia, and the downlink network parameters and the attribute information of the downlink multimedia.

[0141] The data processing device provided in the embodiment of the present disclosure may be used to execute the technical solution of the above method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail in this embodiment.

[0142] Fig. 9 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present disclosure. Fig. 9 , which shows a schematic diagram of the structure of an electronic device 900 suitable for implementing the embodiment of the present disclosure. The electronic device may include, but is not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, personal digital assistants (PDAs), tablet computers (Portable Android Devices, PADs), portable multimedia players (PMPs), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Fig. 9 The electronic device shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present disclosure.

[0143] like Fig. 9As shown, the electronic device 900 may include a processing device (e.g., a central processing unit, a graphics processing unit, etc.) 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage device 908 to a random access memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the electronic device 900 are also stored. The processing device 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. An input / output (I / O) interface 905 is also connected to the bus 904.

[0144] Typically, the following devices may be connected to the I / O interface 905: input devices 906 including, for example, a touch screen, a touch pad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; output devices 907 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; storage devices 908 including, for example, a magnetic tape, a hard disk, etc.; and communication devices 909. The communication device 909 may allow the electronic device 900 to communicate with other devices wirelessly or by wire to exchange data. Although Fig. 9 The electronic device 900 is shown with various devices, but it should be understood that it is not required to implement or possess all the devices shown. More or fewer devices may be implemented or possessed instead.

[0145] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through a communication device 909, or installed from a storage device 908, or installed from a ROM 902. When the computer program is executed by the processing device 901, the above-mentioned functions defined in the method of the embodiment of the present disclosure are executed.

[0146] It should be noted that the computer-readable medium disclosed above may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present disclosure, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in combination with an instruction execution system, device or device. In the present disclosure, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, in which a computer-readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium may also be any computer readable medium other than a computer readable storage medium, which may send, propagate or transmit a program for use by or in conjunction with an instruction execution system, apparatus or device. The program code contained on the computer readable medium may be transmitted using any suitable medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0147] The computer-readable medium may be included in the electronic device, or may exist independently without being incorporated into the electronic device.

[0148] The computer-readable medium carries one or more programs. When the one or more programs are executed by the electronic device, the electronic device executes the method shown in the above embodiment.

[0149] An embodiment of the present disclosure provides a computer-readable storage medium, in which computer-executable instructions are stored. When a processor executes the computer-executable instructions, various methods that may be involved in the above embodiments are implemented.

[0150] An embodiment of the present disclosure provides a computer program product, including a computer program, which implements various methods that may be involved in the above embodiments when executed by a processor.

[0151] Computer program code for performing the operations of the present disclosure may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages, such as Java, Smalltalk, C++, and conventional procedural programming languages, such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0152] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present disclosure. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some implementations as replacements, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0153] The units involved in the embodiments described in the present disclosure may be implemented by software or hardware. The name of a unit does not limit the unit itself in some cases. For example, the first acquisition unit may also be described as a "unit for acquiring at least two Internet Protocol addresses".

[0154] The functions described above herein may be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), complex programmable logic devices (CPLDs), and the like.

[0155] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0156] It should be noted that the modifications of "one" and "plurality" mentioned in the present disclosure are illustrative rather than restrictive, and those skilled in the art should understand that unless otherwise clearly indicated in the context, it should be understood as "one or more".

[0157] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only used for illustrative purposes and are not used to limit the scope of these messages or information.

[0158] It is understandable that before using the technical solutions disclosed in the embodiments of the present disclosure, the types, scope of use, usage scenarios, etc. of the personal information involved in the present disclosure should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations.

[0159] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly prompt the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can independently choose whether to provide personal information to software or hardware such as an electronic device, application, server or storage medium that performs the operation of the technical solution of the present disclosure based on the prompt message. As an optional but non-limiting implementation method, in response to receiving an active request from a user, the method of sending a prompt message to the user can be, for example, a pop-up window, and the prompt message can be presented in text in the pop-up window. In addition, the pop-up window can also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0160] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation of the present disclosure. Other methods that meet the relevant laws and regulations may also be applied to the implementation of the present disclosure.

[0161] It is understood that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of the relevant laws and regulations. The data may include information, parameters and messages, such as flow switching indication information.

[0162] The above description is only a preferred embodiment of the present disclosure and an explanation of the technical principles used. Those skilled in the art should understand that the scope of disclosure involved in the present disclosure is not limited to the technical solutions formed by a specific combination of the above technical features, but should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above disclosed concept. For example, the above features are replaced with the technical features with similar functions disclosed in the present disclosure (but not limited to) by each other to form a technical solution.

[0163] In addition, although each operation is described in a specific order, this should not be understood as requiring these operations to be performed in the specific order shown or in a sequential order. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single embodiment in combination. On the contrary, the various features described in the context of a single embodiment can also be implemented in multiple embodiments individually or in any suitable sub-combination mode.

[0164] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A data processing method, characterized in that: include: Acquiring multimedia attribute information and network parameters of real-time communication during the communication abnormality period; Obtain preset feature acquisition rules; Based on the feature acquisition rule, determining the communication feature information of the real-time communication in the attribute information of the multimedia and the network parameters; Based on the communication characteristic information, an abnormal cause of the real-time communication within the communication abnormality period is determined.

2. The method according to claim 1, characterized in that The determining, based on the feature acquisition rule, the communication feature information of the real-time communication in the attribute information of the multimedia and the network parameters comprises: Determine the parameter value range corresponding to each type of feature in the feature acquisition rule; The communication characteristic information is determined based on the parameter value range corresponding to each type of characteristic, the attribute information of the multimedia and the network parameters.

3. The method according to claim 2, characterized in that The determining the communication characteristic information based on the parameter value range corresponding to each type of characteristic, the attribute information of the multimedia and the network parameter includes: For any type of feature, determine the attribute information or network parameters of the multimedia corresponding to the feature; If the multimedia attribute information or network parameter corresponding to the feature is within the parameter value range corresponding to the feature, marking the feature as existing in the communication feature information; If the multimedia attribute information or network parameter corresponding to the feature is not within the parameter value range corresponding to the feature, the feature is marked as not existing in the communication feature information.

4. The method according to any one of claims 1 to 3, characterized in that: The feature acquisition rule includes at least one of the following features: CPU overload characteristics, acquisition frame rate characteristics, network disconnection characteristics, network switching characteristics, cache congestion characteristics, bandwidth characteristics, packet loss characteristics and delay characteristics.

5. The method according to any one of claims 1 to 3, characterized in that: The communication characteristic information includes timing information; and determining the abnormal cause of the real-time communication within the communication abnormality period based on the communication characteristic information includes: Determining a time domain feature associated with the communication feature information based on the timing information in the communication feature information; Performing Fourier transform on the communication characteristic information to obtain frequency domain characteristics; Based on the time domain features and the frequency domain features, an abnormal cause of the real-time communication within the communication abnormality period is determined.

6. The method according to claim 5, characterized in that The determining, based on the time domain features and the frequency domain features, the abnormal cause of the real-time communication within the abnormal communication period, includes: Inputting the time domain features and the frequency domain features into a detection model to obtain the abnormal cause of the real-time communication; The detection model is a model obtained by learning multiple groups of samples, and each group of samples includes time domain features, frequency domain features of sample communication feature information, and sample abnormality causes corresponding to the sample communication feature information.

7. The method according to any one of claims 1 to 3, characterized in that: The obtaining of multimedia attribute information and network parameters of real-time communication during the communication abnormality period includes: Receiving uplink network parameters, uplink multimedia attribute information, and downlink network parameters and downlink multimedia attribute information; Determine the period of abnormal communication; Based on the abnormal communication period, the attribute information and network parameters of the multimedia within the abnormal communication period are determined from the uplink network parameters, the attribute information of the uplink multimedia, and the downlink network parameters and the attribute information of the downlink multimedia.

8. A data processing device, characterized in that: It includes a first acquisition module, a second acquisition module, a first determination module and a second determination module, wherein: The first acquisition module is used to acquire multimedia attribute information and network parameters of real-time communication during the communication abnormality period; The second acquisition module is used to acquire a preset feature acquisition rule; The first determination module is used to determine the communication characteristic information of the real-time communication from the attribute information of the multimedia and the network parameters based on the characteristic acquisition rule; The second determination module is used to determine the abnormal cause of the real-time communication within the abnormal communication period based on the communication characteristic information.

9. An electronic device, characterized in that: include: Processor and memory; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the data processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions. When the processor executes the computer-executable instructions, the data processing method according to any one of claims 1 to 7 is implemented.

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