Video playing method and device, electronic equipment and storage medium

Abstract

The invention discloses a video playing method and device, electronic equipment and a storage medium, and belongs to the technical field of communication, and the method comprises the steps: obtaining a corresponding state parameter under the condition that streaming media video playing lags; wherein the state parameters comprise at least one of the following items: a current communication network quality parameter, a current video transmission parameter and historical lagging information; determining a lagging reason according to the state parameters; wherein the lagging reason comprises network abnormity; and executing a network recovery strategy corresponding to the network abnormity based on the lagging reason.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of communication, and particularly relates to a video playing method and device, electronic equipment and storage medium. BACKGROUND

[0002] The streaming media video technology is a video content distribution mode based on the Internet, and users can realize real-time transmission and playing without completely downloading video files. This mode has been widely applied to various terminal devices. However, in actual use, the video playing of the terminal device still generally exists the phenomenon of lag, which leads to poor playing quality of the streaming media video and poor influence on the watching experience of users. SUMMARY

[0003] The embodiments of the present application aim to provide a video playing method, device, electronic equipment and storage medium, which can effectively cope with the video lag problem caused by network exception, thereby improving the playing quality of the streaming media video.

[0004] In a first aspect, the embodiments of the present application provide a video playing method, executed by a terminal, comprising: In the case that the streaming media video playing occurs lag, corresponding state parameters are acquired; wherein the state parameters comprise at least one of the following: current communication network quality parameters, current video transmission parameters, historical lag information; According to the state parameters, a lag reason is determined; wherein the lag reason comprises network exception; Based on the lag reason, a network recovery strategy corresponding to the network exception is executed.

[0005] In a second aspect, the embodiments of the present application provide a video playing device, executed by a terminal, comprising: An acquisition module is configured to acquire corresponding state parameters in the case that the streaming media video playing occurs lag; wherein the state parameters comprise at least one of the following: current communication network quality parameters, current video transmission parameters, historical lag information; A determination module is configured to determine a lag reason according to the state parameters; wherein the lag reason comprises network exception; A processing module is configured to execute a network recovery strategy corresponding to the network exception based on the lag reason.

[0006] In a third aspect, the embodiments of the present application provide electronic equipment, which comprises a processor and a memory. The memory stores programs or instructions that can be run on the processor. When the programs or instructions are executed by the processor, the steps of the video playing method according to the first aspect are implemented.

[0007] In a fourth aspect, an embodiment of the present application provides a readable storage medium, the readable storage medium storing a program or instructions, the program or instructions being executed by a processor to implement steps of the video playing method according to the first aspect.

[0008] In a fifth aspect, an embodiment of the present application provides a chip, the chip including a processor and a communication interface, the communication interface being coupled to the processor, and the processor being configured to run a program or instructions to implement the video playing method according to the first aspect.

[0009] In a sixth aspect, an embodiment of the present application provides a computer program product, the program product being stored in a storage medium, and the program product being executed by at least one processor to implement the video playing method according to the first aspect.

[0010] In an embodiment of the present application, in a case where the streaming video playing is stuck, a corresponding state parameter is acquired, wherein the state parameter includes at least one of the following: a current communication network quality parameter, a current video transmission parameter, and historical stuck information; a stuck reason is determined according to the state parameter, wherein the stuck reason includes network abnormality; and a network recovery strategy corresponding to the network abnormality is executed based on the stuck reason.

[0011] It can be seen that, in the embodiment of the present application, the communication network quality, the video transmission parameter, and the historical stuck information are comprehensively analyzed to accurately diagnose the stuck reason and avoid blind optimization; after the accurate diagnosis, a special network recovery strategy is triggered to be executed, thereby improving the recovery efficiency and success rate, which can effectively cope with the video stuck problem caused by network abnormality, ensures the efficiency and accuracy of the recovery measures, makes the video playing more smooth and the stuck recovery more rapid, and provides a stable and high-quality watching experience for users. BRIEF DESCRIPTION OF DRAWINGS

[0012] Figure 1 is one of flowcharts of a video playing method provided by an embodiment of the present application; Figure 2 is another one of flowcharts of a video playing method provided by an embodiment of the present application; Figure 3 is a structural block diagram of a video playing device provided by an embodiment of the present application; Figure 4 is a structural schematic diagram of an electronic device provided by an embodiment of the present application; Figure 5 is a hardware structural schematic diagram of an electronic device for implementing various embodiments of the present application. DETAILED DESCRIPTION

[0013] Clearly, the described embodiments are only some, but not all of embodiments of the present application. Based on the embodiments in the present application, all the embodiments obtained by a person of ordinary skill in the art belong to the scope of protection of the present application.

[0014] The terms "first", "second", and the like in the specification of the present application are used to distinguish similar objects, and are not used to describe a specific order or sequence. It should be understood that the terms used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present application can be implemented in an order other than that illustrated or described herein, and the objects distinguished by "first", "second", etc. are generally of a kind and do not limit the number of objects, for example, the first object can be one or more. In addition, "and / or" in the specification means at least one of the connected objects, and the character " / ", generally represents a "or" relationship between the objects before and after.

[0015] For ease of understanding, some related concepts involved in the embodiments of the present application and the association between the concepts and video stuttering will be introduced first.

[0016] Reference Signal Received Power (RSRP) is the average received power obtained by the terminal measuring the reference signal transmitted by the base station, and its unit of measurement is dBm. This parameter is negative, and the numerical value is inversely related to signal strength, that is, the smaller the absolute value, the higher the signal strength. When the reference signal received power is lower than the preset threshold, it indicates that the wireless signal strength has decayed to a critical state, and the terminal is difficult to maintain stable signal demodulation with the base station. In this case, other channel quality indicators are usually accompanied by coordinated degradation, resulting in a significant reduction in data transmission rate or communication link interruption, thereby inducing streaming video stuttering phenomenon.

[0017] Reference Signal Received Quality (RSRQ) is a quantitative evaluation of the quality of reference signal received power after taking into account interference factors. This parameter is calculated by the ratio of reference signal received power to total interference and noise power in the receive band, and is used to represent the purity of signal transmission. When there is strong co-channel interference, even if the reference signal received power indicator is good, the bit error rate will still rise due to signal pollution, the effective data transmission throughput will decrease, and then video stream loading delay and stuttering will be induced.

[0018] Signal to Interference plus Noise Ratio (SINR) refers to the ratio of the received useful signal power to the sum of the interference signal and background noise power, with the unit of measurement being dB. As a core parameter for evaluating wireless channel quality, this index directly determines the selection efficiency of the physical layer modulation and coding scheme. When the signal to interference plus noise ratio is lower than a certain threshold, the physical layer transmission rate cannot meet the video stream code rate requirement, causing the playback buffer to continuously decrease until it is exhausted, triggering the streaming video stuttering.

[0019] Physical layer uplink and downlink Block Error Rate (BLER) refers to the statistical probability of errors existing after the physical layer data block is decoded. This parameter includes two dimensions: downlink and uplink. Downlink block error rate directly affects video data reception quality, and uplink block error rate affects the transmission reliability of terminal confirmation signaling. High block error rate means that the probability of data packet retransmission increases significantly, not only introducing additional transmission delay, but also occupying limited wireless resources, leading to a decrease in effective throughput and an increase in network jitter, thus exacerbating the streaming video stuttering phenomenon or prolonging the stuttering recovery time.

[0020] Recent Radio Link Failure (RLF) refers to the cumulative frequency of complete interruption of the connection between the terminal and the base station within a preset time window. This failure is usually triggered by serious events such as continuous loss of synchronization and random access failure. When a radio link failure occurs, the terminal needs to perform cell reselection, link reconstruction, and other recovery processes, during which data transmission is completely interrupted, causing persistent stuttering, buffer interruption, or even connection termination in streaming video playback. Frequent radio link failures indicate that the network connection is in an extremely unstable state.

[0021] Downlink scheduling information refers to the control signaling sent by the base station to the terminal to indicate the allocation of downlink resources. In the streaming video transmission scenario, if the downlink scheduling information is abnormal (including but not limited to insufficient resource allocation, missing scheduling instructions, or transmission delay), it will directly cause the video data packets to be unable to be accurately received on time, thereby triggering streaming video stuttering.

[0022] Media Access Control layer buffer depth refers to the instantaneous data carrying capacity of the data buffer queue located in the media access control sublayer of the communication protocol stack in the terminal. This buffer serves as an interface between the underlying wireless data transmission and the upper protocol stack, and is responsible for temporarily storing media access control protocol data units to be sent or received. When the depth value of the media access control layer buffer is consistently low or close to zero, it indicates that the wireless link data transmission rate cannot meet the upper application requirements, which is the root cause and precursor indicator of streaming video stuttering caused by the interruption of video application buffer data supply.

[0023] The maximum transmit power reduction refers to the maximum transmit power reduction that the terminal can implement under the premise of maintaining normal connection of the base station. The parameter indirectly reflects the uplink quality condition: a smaller reduction value (i.e., a higher transmit power needs to be maintained) indicates that the uplink channel quality is deteriorated, and there is a risk of connection stability. Although video playing mainly relies on the downlink, deterioration of the uplink channel quality can cause abnormal transmission of control signaling (such as an acknowledgement message and a retransmission request), thereby affecting the downlink data scheduling efficiency, and ultimately causing the streaming video to freeze.

[0024] The real-time network throughput refers to the amount of data successfully received by the terminal from the streaming server per unit of time, and the unit of measurement is megabits per second or megabytes per second. The parameter directly reflects the instantaneous transmission capability of the network. When the real-time network throughput is continuously lower than the encoding code rate of the current video segment, the video player buffer will continuously decrease until the streaming video freezes.

[0025] The first packet delay refers to the time interval from the initiation of a data request by the video player to the reception of the first data packet, and the unit of measurement is milliseconds. The parameter has important indicative significance in the video playing start or freeze recovery stage: a long first packet delay will directly delay the buffer initialization process, resulting in an increase in the black screen duration or a delay in the freeze recovery. In addition, a continuously high first packet delay can be an early warning indicator of network congestion or transmission path deterioration, indicating the possible decline in throughput and the subsequent risk of streaming video freeze.

[0026] The buffer of the video application refers to a temporary data storage area created and maintained by the video player application program in the user space. Its function is to cache the video data units that have been successfully received from the network but have not been submitted to the decoder for processing. The real-time data stock of the buffer, i.e., the buffer depth, is a core state parameter representing the continuity of video streaming playing. When the buffer depth falls below the zero threshold, the decoder causes a video rendering interruption because there is no data available, i.e., the streaming video freezes.

[0027] Next, the video playing method provided by the embodiments of the present application will be described in detail in combination with the drawings.

[0028] It should be noted that the video playing method provided by the embodiments of the present application is applicable to a terminal, which can include a smartphone, a tablet computer, a smart watch, a personal digital assistant, and the like, and the embodiments of the present application do not limit the terminal.

[0029] Figure 1 is one of the flowcharts of the video playing method provided by the embodiments of the present application, as shown in Figure 1As shown, the method can include the following steps: step 101, step 102 and step 103.

[0030] In step 101, in the case of a stall of the streaming video playback, a corresponding state parameter is acquired; wherein the state parameter includes at least one of the following: a current communication network quality parameter, a current video transmission parameter, and historical stall information.

[0031] In some embodiments, before the above-mentioned step 101, a stall detection step: step 100, for determining whether the streaming video playback stalls, can also be performed.

[0032] Specifically, the above-mentioned step 100 determines based on at least one of the following conditions: The data inventory of the video application buffer is lower than a preset data inventory threshold; The video rendering frame rate is continuously lower than a preset frame rate threshold within a first preset time length; The actual transmission rate of the streaming video is continuously lower than a rate threshold determined according to the required minimum bit rate of the playback content within a second preset time length.

[0033] In the embodiments of the present application, the preset data inventory threshold, the preset frame rate threshold and the preset rate threshold are critical parameters representing the continuity of video playback, and their specific values can be configured according to actual network conditions and business requirements.

[0034] In the embodiments of the present application, by introducing the data inventory of the video application buffer as a basis for judgment, the real-time balance state between the data consumption of the player of the video application and the network supply can be directly reflected, the monitoring is performed from the essential level of playback continuity, and false positives caused by indirect parameter fluctuations are avoided.

[0035] In the embodiments of the present application, by introducing the constraint of the continuous time length in the judgment conditions of the frame rate and the transmission rate, interference signals caused by network transient jitter or terminal short-term load fluctuations are effectively filtered out, unnecessary recovery processes are prevented from being triggered, and thus the stability and accuracy of the terminal decision are improved.

[0036] In the embodiments of the present application, by comparing the actual transmission rate with the minimum bit rate required to ensure smooth playback, the data transmission efficiency level is directly evaluated, the fundamental contradiction affecting the playback continuity is grasped, and a more direct and efficient stall judgment basis is provided.

[0037] In the embodiments of the present application, by comprehensively monitoring the buffer state of the monitoring data, the picture rendering performance and the network transmission efficiency, a multi-dimensional frame freezing perception mechanism is constructed, which significantly improves the comprehensiveness and reliability of frame freezing detection, effectively overcomes the missed or mistaken judgment problems caused by single criterion, and can accurately identify frame freezing phenomena caused by various reasons.

[0038] In the embodiments of the present application, the accurate frame freezing determination result provides a reliable trigger signal for subsequent frame freezing cause analysis and recovery strategy execution, ensures that the intelligent optimization process is activated only when necessary, and avoids resource overhead caused by invalid operations.

[0039] In summary, in the embodiments of the present application, by constructing a multi-dimensional, robust and playback essence-based frame freezing perception layer, high-quality input is provided for downstream cause diagnosis and recovery operation, ensuring that the entire method is triggered efficiently only when necessary, thereby ultimately improving the processing efficiency and user experience of the overall scheme.

[0040] In the embodiments of the present application, the current communication network quality parameter is a bottom-layer wireless signal index from a terminal baseband chip, which is used to objectively evaluate the health status of the physical channel and the link layer. The current communication network quality parameter can be embodied as a parameter set containing multiple network state indicators. The parameter set comprehensively and accurately quantifies the wireless connection state between the terminal and the network from different protocol layers and angles, and determines whether the streaming video frame freezing is caused by abnormal wireless connection quality between the terminal and the base station through the wireless connection state.

[0041] In some embodiments, the current communication network quality parameter can include at least one of the following: reference signal received power, reference signal received quality, signal to interference plus noise ratio, physical layer uplink and downlink block error rate, recent wireless link failure statistical number, downlink scheduling information, medium access control layer buffer depth, and maximum transmission power reduction.

[0042] In the embodiments of the present application, since the above-mentioned parameters are all related to video frame freezing, by integrating the above-mentioned full-stack parameters such as physical layer, link layer, network scheduling layer and connection stability, a panoramic network diagnosis view is constructed, which overcomes the partiality of diagnosis and improves the accuracy and reliability of frame freezing cause positioning. In addition, some parameters can provide forward-looking early warning to help the terminal change from "passive response" to "active prevention"; at the same time, the rich parameter set ensures that the scheme has strong adaptability and robustness in complex network environments.

[0043] In the embodiments of the present application, the current video transmission parameter is a direct index reflecting the application layer data transmission experience, and represents whether the video stream is being successfully received. The current video transmission parameter can be embodied as a key performance indicator directly reflecting the streaming media video data transmission performance. Such a parameter focuses on the data transmission experience of the application layer, and serves as an intuitive bridge connecting the underlying network state and the upper layer playback experience, thereby providing a direct and quantitative basis for determining whether the video freezing is related to network abnormalities.

[0044] In some embodiments, the current video transmission parameter can include at least one of the following: real-time network throughput, first packet time. Such a parameter can be used to determine whether the streaming media video freezing is related to network abnormalities.

[0045] In the embodiments of the present application, by monitoring whether the real-time network throughput is continuously lower than the video code rate, it can be directly determined whether the network bandwidth has become a bottleneck. By monitoring whether the first packet time is abnormally high, it can be directly determined whether the network path or connection has a delay problem, which realizes the quick and direct association from "freezing occurs" to "suspected network cause", and provides an efficient and accurate triggering condition for immediately starting a deeper network diagnosis (such as obtaining a communication network quality parameter).

[0046] In the embodiments of the present application, the real-time network throughput and the first packet time are introduced as the current video transmission parameter, which can quickly and directly associate the freezing phenomenon with the decline of network transmission performance, and cooperates with the underlying network parameters to form a complete and accurate diagnosis capability from "phenomenon" to "root cause", and finally ensures the pertinence and efficiency of the recovery strategy, and significantly improves the user experience.

[0047] In the embodiments of the present application, the historical freezing information is a "experience library" accumulated by the terminal, which records the processing experience and results of past freezing in a specific network environment (such as the same cell).

[0048] In some embodiments, the historical freezing information can include at least one of the following: freezing time, recovery time, freezing cause, terminal communication network quality parameter, network cell information, executed network recovery strategy and its effectiveness.

[0049] In the embodiments of the present application, the historical freezing information is constructed as a structured experience knowledge base, which is not a simple log record, but a systematic storage of the key features of each past freezing event and its whole processing process, thereby providing data support for future intelligent decision-making.

[0050] In the embodiments of the present application, the freezing time and the recovery time record the occurrence time and duration of the freezing event, which is helpful for analyzing the periodical regularity of freezing.

[0051] In the embodiments of the present application, the frame freezing cause records the root cause determined through multi-dimensional parameter analysis (such as network anomaly).

[0052] In the embodiments of the present application, the terminal communication network quality parameter and the camping cell information jointly constitute a complete portrait of the wireless network environment in which the terminal is located when frame freezing occurs.

[0053] In the embodiments of the present application, the network recovery strategy performed and its effectiveness record the specific action taken for a specific frame freezing (such as switching data cards) and whether the action successfully solves the problem.

[0054] In the embodiments of the present application, the historical frame freezing information converts each frame freezing event into a learning opportunity, enabling the terminal to remember what network environment, what cause of frame freezing, and what measures are effective after frame freezing.

[0055] In the embodiments of the present application, when similar network environment (such as the same cell, similar network quality parameters) and frame freezing cause are detected in a new frame freezing event, the terminal can preferentially recommend or directly execute the recovery strategy verified to be effective in history, thereby shortening the recovery time and avoiding the extension of frame freezing due to the attempt of invalid strategy.

[0056] In the embodiments of the present application, by continuously recording the result of each action (strategy effectiveness), a complete closed loop of "perception-decision-execution-feedback" is formed. The longer the terminal is used, the richer the historical experience accumulated, and the higher the accuracy and efficiency of decision making, thereby having the ability of self-learning and self-optimization.

[0057] In the embodiments of the present application, the optimal recovery strategy may be different for different geographical locations (cells), different times, and different network failure modes. The historical frame freezing information enables the terminal to make fine and scenario-based matching. For example, when frame freezing caused by weak signal occurs in cell A, strategy X is effective; while similar frame freezing occurs in cell B, strategy Y may be more optimal. Such personalized decision making based on historical data improves the adaptability and robustness of the terminal in complex and variable network environment.

[0058] In the embodiments of the present application, the structured historical frame freezing information is introduced, enabling the terminal to make accurate decisions using historical experience and continuously evolve through closed-loop learning, and ultimately achieve faster and more accurate frame freezing recovery, thereby providing users with continuously optimized viewing experience.

[0059] In summary, in the embodiments of the present application, by acquiring state parameters such as current communication network quality parameter, current video transmission parameter, and historical frame freezing information, full-stack data fusion from "physical layer" to "application layer" to "historical experience" is achieved, thereby providing comprehensive and three-dimensional data basis for accurate diagnosis.

[0060] In step 102, a cause of the freezing is determined according to the state parameters; wherein the cause of the freezing includes network anomaly.

[0061] In the embodiments of the present application, the network anomaly refers to a network state in which the data transmission rate is reduced or interrupted due to factors such as insufficient wireless signal strength, excessive network interference, or unstable base station connection, which is the main cause of the streaming video freezing.

[0062] In the embodiments of the present application, the acquired multi-dimensional state parameters are comprehensively analyzed by using a preset algorithm or rule (for example, threshold comparison, grade division, majority voting principle, historical pattern matching), and finally the judgment of the root cause of the freezing is output.

[0063] In the embodiments of the present application, the cause of the freezing can be clearly distinguished as "network anomaly" and other causes (such as server problems), achieving accurate positioning from "phenomenon" (freezing) to "root cause" (network anomaly). It is no longer simply classified as a category, but can identify those problems that need to be solved through network intervention.

[0064] In step 103, a network recovery strategy corresponding to the network anomaly is executed based on the cause of the freezing.

[0065] In the embodiments of the present application, if the cause of the freezing is determined as "network anomaly", the network recovery strategy corresponding thereto is triggered for execution instead of the application layer strategy, ensuring the pertinence of the recovery action.

[0066] In the embodiments of the present application, the network recovery strategy can be embodied as a series of remedial measures for different levels of network anomalies, constituting a measure set with gradually increasing intervention intensity from slight adjustment to complete reconstruction of connection.

[0067] In some embodiments, the network recovery strategy can include: dual-card data acceleration, switching data cards, switching terminal residence to other cells, and replacing the terminal current residence network standard; wherein the network recovery strategies are executed in order according to the execution priority.

[0068] In the embodiments of the present application, the use of the multi-card capability of the terminal for data aggregation can improve the overall bandwidth, which is suitable for the scenario where the current network capacity is insufficient but the connection is still stable.

[0069] In the embodiments of the present application, switching data cards or switching residence cells can avoid specific local network failures or weak coverage problems by changing different network access points (such as switching from A operator network to B operator network, or from the current cell with poor signal to the adjacent cell with strong signal).

[0070] In the embodiments of the present application, a more stable underlying connection is reconstructed by downgrading or upgrading the network connection mode (e.g., switching to a more stable 4G network when the 5G signal is unstable), which is suitable for solving the connection instability caused by insufficient optimization or compatibility problems of a specific network mode.

[0071] In the embodiments of the present application, the network recovery strategies are executed in turn according to a preset execution priority order, which is usually set based on factors such as execution speed of the strategy, degree of interruption to user experience, and resource consumption, forming a progressive recovery principle of "first trying a simple and quick solution, and then trying a complex and thorough solution if the former is invalid".

[0072] Exemplarily, the network recovery strategies can include, in turn from high priority to low priority: dual-card data acceleration, switching data cards, switching terminal residence to other cells, and changing the network mode of the terminal currently residing.

[0073] In the embodiments of the present application, the strategy with fast execution speed and small interference (e.g., enabling dual-card acceleration) is set as high priority, which can first try to solve the problem at the lowest cost. If successful, the user can almost imperceptibly recover the smooth playback. This "minimum cost first" principle avoids directly executing "heavy" operations (such as temporary network disconnection caused by switching network modes), ensuring that the impact of the recovery process on user experience is minimized.

[0074] In some embodiments, different network recovery strategies are tried in turn according to the execution priority order; after executing each strategy, it is detected whether the stuttering is recovered; if the stuttering is recovered, the subsequent strategies are stopped from being executed and the strategy is recorded as an effective strategy; if the stuttering is not recovered, the strategy of the next priority is tried to be executed.

[0075] As can be seen, in the embodiments of the present application, the clear priority order provides a clear and orderly decision path for the terminal, overcoming the inefficiency problem of random and irregular attempts. The terminal can try the strategies step by step, so as to systematically and efficiently locate the most effective solution under the current network environment, thereby improving the recovery success rate and shortening the overall recovery time. Figure 1

[0076] In summary, in the embodiments of the present application, the network recovery strategies and their priority execution mechanism jointly constitute an efficient, intelligent, and user-friendly recovery system, which ensures that the terminal can find and execute the most effective solution at the fastest speed and with the least interference, thereby quickly eliminating the video stuttering caused by network anomalies and fundamentally improving the final experience of streaming video playback.

[0077] ​In some embodiments, considering that the historical stall record usually records an effective stall recovery strategy, the step 103 can specifically include the following steps: step 1031 and step 1032.

[0078] In step 1031, a target network recovery strategy is determined from a plurality of candidate network recovery strategies according to the stall reason and the historical stall information; wherein the target network recovery strategy is determined based on a recovery strategy recorded in the historical stall information and verified as effective for the same stall reason under the same or similar network environment. Wherein the similar network environment means that the similarity of the network environment is greater than a certain threshold.

[0079] In the embodiments of the present application, after determining that the stall reason is network anomaly, instead of simply trying all recovery strategies in a fixed order, an intelligent decision layer based on historical experience is introduced. This mechanism uses the "success experience" accumulated in the historical stall information to directly select the "target network recovery strategy" most likely to be effective in the current specific scenario from the candidate strategies and execute it.

[0080] Exemplarily, the current scenario: the terminal occurs playing stall in A cell, and the diagnosis reason is "network anomaly (signal interference)".

[0081] The terminal queries the historical record and finds that in A cell, for "network anomaly (signal interference)", there are the following records in history: Strategy 1 (dual-card data acceleration): try 3 times, effective 0 times; Strategy 2 (switch data card): try 5 times, effective 1 time; Strategy 3 (switch to B cell): try 10 times, effective 8 times.

[0082] Based on the historical record, the terminal finds that the success rate of strategy 3 (switch to B cell) is much higher than that of other strategies, so it determines it as the "target network recovery strategy" this time.

[0083] In step 1032, the target network recovery strategy is executed.

[0084] Continuing the above example, the terminal will immediately start executing strategy 3: starting the cell reselection process, switching from the current A cell with poor signal to the B cell with stable signal which has historically been effective in solving such problems.

[0085] It can be seen that, in the embodiment of the application, the best strategy is directly located through the historical lag information, the invalid trial and error link is skipped, the time from diagnosis to successful recovery is shortened, the user can return to smooth playing faster, unnecessary network connection interruption, signal re-search and other operations caused by executing invalid strategies are avoided, and terminal resources and battery power are saved. In addition, each successful recovery is recorded and the historical information is enriched, so that the longer the terminal is used, the more accurate and efficient the decision is, and the terminal has self-learning and self-optimization capabilities.

[0086] As can be seen from the above embodiment, in the case where the streaming media video playing lags, the corresponding state parameters are obtained; wherein the state parameters include at least one of the following: current communication network quality parameters, current video transmission parameters, historical lag information; according to the state parameters, the lag reason is determined; wherein the lag reason includes network anomaly; based on the lag reason, the network recovery strategy corresponding to the network anomaly is executed. It can be seen that, in the embodiment of the application, the lag reason is accurately diagnosed by comprehensively analyzing the communication network quality, the video transmission parameters and the historical lag information, and blind optimization is avoided; after accurate diagnosis, the special network recovery strategy is triggered and executed, the recovery efficiency and success rate are improved, the video lag problem caused by network anomaly can be effectively dealt with fundamentally, the efficiency and accuracy of the recovery measures are ensured, the video playing is smoother, the lag recovery is faster, and a stable and high-quality viewing experience is provided for the user.

[0087] In some embodiments provided by the application, the video playing method can further include the following step 104 after the step 103.

[0088] In step 104, the lag time, the recovery time, the lag reason, the terminal communication network quality parameter, the network cell information, the executed network recovery strategy and its effectiveness of this time lag are recorded to update the historical lag information.

[0089] In the embodiment of the application, the whole process of each lag event is converted into structured experience data for future decision reference, all data are systematically collected and used to update the historical lag information, thereby continuously enriching and optimizing the local knowledge base of the terminal, so that the longer the terminal is used, the more accurate and rapid the decision to deal with lag is, and the terminal has continuous self-optimization capability.

[0090] In the embodiment of the application, when similar environmental characteristics (such as the same cell, similar network quality parameters) and lag reasons in the historical record are detected in a new lag event, the recovery strategy verified to be effective in history can be preferentially selected, which avoids the inefficient process of trying one by one in a fixed order, realizes the transition from "trial and error" to "accurate prediction", and can shorten the lag recovery time.

[0091] It can be seen that, in the embodiments of the present application, through the complete processing mode of "accurate diagnosis - directional recovery - closed-loop learning", a closed-loop learning system is formed, so that the terminal can make decisions faster and more accurately when encountering similar scenarios.

[0092] In some embodiments provided by the present application, the above step 101 can be embodied as a condition triggered intelligent process, rather than indiscriminately obtaining all parameters, and accordingly can include the following step: step 1011.

[0093] In step 1011, in the case of a streaming video playback stall, the current video transmission parameters are obtained; if the current video transmission parameters meet the preset condition, the current communication network quality parameters or historical stall information are triggered to be obtained; wherein the preset condition is used to indicate that the stall is related to network anomalies, and the preset condition includes at least one of the following: real-time network throughput is lower than a preset throughput threshold, first packet time exceeds a preset delay threshold.

[0094] In the embodiments of the present application, when a video stall occurs, the most direct and minimum overhead current video transmission parameters (such as real-time network throughput, first packet time) are first obtained, which directly reflect the data transmission experience of the application layer; Then, it is judged whether these parameters meet the preset condition, which is to quickly judge whether the stall is likely to be related to network anomalies, for example, if the real-time network throughput is lower than the preset throughput threshold, it indicates that the available bandwidth is insufficient to support the video stream, which is a strong indication of network problems, and for example, if the first packet time exceeds the preset delay threshold, it indicates that there is high delay in establishing a connection or network path, which is also a typical feature of network anomalies; Only when the above preset condition is met, the terminal obtains more deep and relatively large overhead parameters, that is, the current communication network quality parameters (for accurate cause positioning) or the historical stall information (for experience reference). If the above preset condition is not met, it may indicate that the stall is caused by other reasons (such as the server or the application itself), thereby avoiding unnecessary network detection.

[0095] It can be seen that, in the embodiments of the present application, by introducing a condition triggering mechanism, an efficient two-level diagnosis process is constructed: first, high-level video transmission parameters are used for rapid screening, and only when preliminary evidence points to network anomalies, deep network quality detection is started. This method not only greatly improves the diagnosis response speed, but also effectively avoids unnecessary terminal resource consumption.

[0096] In some embodiments provided in the present application, in the case that the state parameter comprises a current communication network quality parameter, the step 102 can be embodied as a multi-parameter, hierarchical level quantization decision process, and accordingly can comprise the following steps: step 1021, step 1022 and step 1023.

[0097] In step 1021, the value of each current communication network quality parameter is compared with the corresponding preset threshold interval to determine the quality level to which each current communication network quality parameter belongs; wherein the quality level is used to indicate the advantages and disadvantages of network quality, and the higher the level is, the worse the network quality is.

[0098] In the embodiments of the present application, a plurality of network quality parameters (such as RSRP, SINR, BLER, etc.) of different dimensions and different meanings can be standardized. By comparing the value of each parameter with its corresponding preset threshold interval, all parameters are uniformly mapped to quality levels with the same semantics.

[0099] In the embodiments of the present application, a plurality of numerical intervals are preset for each parameter, and each interval corresponds to a quality level; wherein the level value is used to represent the advantages and disadvantages of network quality, and the larger the value is, the worse the quality is.

[0100] For example, for the reference signal received power, it can be configured that when the value is lower than -115 dBm, it is mapped to level 5, representing the worst quality; and when the value is higher than -85 dBm, it is mapped to level 1, representing the best quality. For the recent wireless link failure statistical number, it can be configured that when the number is greater than 4 times, it is mapped to level 5, representing the worst stability; and when the number is 0 times, it is mapped to level 1, representing the best stability. In the comprehensive judgment stage, when the comprehensive quality level determined according to the level of each parameter is in the poor interval (for example, level 4 or level 5), it is determined that the current network quality is poor, and the conclusion that the freezing reason is network anomaly is output.

[0101] In the embodiments of the present application, all kinds of parameters are uniformly converted into level signals, so that the terminal does not need to process the complex physical meaning and dimension of the original data, and the decision logic is simplified. This "leveling - majority voting" model is very clear, stable, easy to implement and maintain on the terminal, and ensures the consistency of the judgment standard in different scenarios and different devices.

[0102] In step 1022, the majority voting principle is adopted to determine the current comprehensive network quality level according to the quality levels of all current communication network quality parameters.

[0103] In the embodiments of the present application, according to the results of the individual quality grades of all parameters, and using the majority voting principle, a current comprehensive network quality grade is determined, so that the overall judgment tends to be determined by the grade indicated by the majority of parameters. For example, if more than 5 of the 9 parameters are in "grade 4" (poor), the comprehensive grade is determined as "grade 4".

[0104] In step 1023, if the current comprehensive network quality grade is higher than or equal to the preset abnormal grade threshold, it is determined that the freezing reason is network abnormality.

[0105] In the embodiments of the present application, if the comprehensive network quality grade is higher than or equal to the preset abnormal grade threshold, it means that the network quality has been poor to a certain extent, and at this time it is determined that the freezing reason is network abnormality.

[0106] In the embodiments of the present application, by comprehensively considering all relevant parameters and following the "majority voting" principle, the over-reliance on a single parameter is effectively reduced. Even if individual parameters have measurement abnormalities, as long as the majority of parameters show consistent trends, the final conclusion is still reliable, which significantly improves the anti-interference ability and robustness of the freezing reason diagnosis.

[0107] As can be seen, in the embodiments of the present application, by normalizing the grades of multiple parameters and applying the majority voting principle, a robust, standard, quantifiable and interpretable network abnormality diagnosis core engine is constructed, which ensures the accuracy and reliability of the freezing reason judgment, and provides an important basis for subsequent execution of accurate recovery strategies.

[0108] In some embodiments provided by the present application, in the case that the state parameters include current communication network quality parameters and historical freezing information, the above step 102 can be embodied as a real-time diagnosis and historical experience integrated intelligent decision-making process, and accordingly can include the following steps: step 1024, step 1025 and step 1026.

[0109] In step 1024, a current comprehensive network quality grade is determined according to the current communication network quality parameters.

[0110] In the embodiments of the present application, first, based on the obtained current communication network quality parameters (such as RSRP, SINR, etc.), a current comprehensive network quality grade is determined through a preset algorithm (for example, the grade division and majority voting principle in the above steps 1021 and 1022). The grade is a quantitative evaluation of the real-time wireless environment health status of the terminal.

[0111] In step 1025, the current camping cell information is obtained, and the historical freezing reason under the camping cell information is queried from the historical freezing information.

[0112] In the embodiments of the present application, the current network camping cell information (such as cell ID) is obtained, which is used as a key index to query the recorded historical stall reasons under the same or similar network camping cell information from the historical stall information database.

[0113] In the embodiments of the present application, by combining the key information of the network camping cell, the diagnosis has the geographical location awareness ability, which can learn the problem mode of different cells, thereby realizing the location-based personalized and accurate reason positioning, and enhancing the practicability and robustness in the complex heterogeneous network environment.

[0114] In step 1026, the current stall reason is determined based on the current comprehensive network quality level and the stall reason in the queried historical record.

[0115] In the embodiments of the present application, instead of simply taking the historical reason as the current conclusion, the current comprehensive network quality level (reflecting the real-time condition) and the queried historical stall reason (reflecting the experience law) are analyzed and judged comprehensively, thereby determining the current stall reason.

[0116] For example, a user is watching a video using the streaming media application of the terminal, and suddenly stalls. In this case, the streaming media client first tries to apply the application layer optimization strategy (such as reducing the code rate), but the stall problem cannot be solved, at which time the client notifies the terminal system to intervene in the network quality monitoring.

[0117] The terminal obtains the current network camping cell, for example, cell A, and the current communication network quality parameters such as RSRP, SINR, etc. According to the current communication network quality parameters, the current comprehensive network quality level is calculated, for example, level 3 (moderate deviation), which is a critical state, neither very good (level 1-2) nor extremely poor (level 4-5), and it is difficult to get an accurate conclusion only by this result.

[0118] The terminal queries the historical database and finds that the stall records about cell A are as follows: Record 1: the stall reason is network anomaly (signal interference), the network quality level at that time is level 4, and the recovery strategy is to switch to cell B (successful); Record 2: the stall reason is network anomaly (high base station load), the network quality level at that time is level 3, and the recovery strategy is to enable dual-card acceleration (successful).

[0119] After the fusion decision analysis, the terminal finds that in the historical stall records of cell A, when the network quality level is level 3 or level 4, the root cause is "network anomaly". Since the current comprehensive network quality level is also level 3, the historical experience shows that when the network quality in cell A is moderate deviation, the problem is extremely likely to come from the network side.

[0120] The terminal comprehends the current network state (level 3) and the historical rule (level 3 / 4 corresponding network exception), and determines the current stall reason as "network exception" with high confidence, effectively solving the decision difficulty when the real-time parameter is in the "critical state", and using the historical rule to compensate for the uncertainty of real-time data, to ensure accurate identification of network side problems.

[0121] Further, the terminal can perform more detailed comparison: although the current comprehensive level is level 3, the internal parameter characteristics show that the SINR (signal to interference ratio) is particularly poor, and the SINR poor condition in the historical record corresponds to "network exception (high interference)". The terminal combines the geographical location "in cell A" and the real-time details "current SINR characteristics", and refers to the similar historical mode, to further refine the reason to "network exception (high interference)", to realize more refined root cause positioning, and provide accurate guidance for subsequent selection of "switching cells" as the most targeted recovery strategy.

[0122] It can be seen that, in the embodiment of the application, by fusing real-time network state and historical experience information, a more intelligent, more accurate and more context-aware stall reason diagnosis process is constructed, which can not only handle obvious network failures, but also identify complex network problems with regional characteristics, thereby providing reliable decision basis for subsequent recovery strategies, and finally ensuring that users obtain continuous optimized video viewing experience.

[0123] Figure 2 is a flowchart of a video playing method provided by an embodiment of the application, in the embodiment of the application, a step-by-step diagnosis and recovery mechanism can be used, to preferentially attempt application layer optimization, and to start bottom layer network recovery after invalidation, as shown in Figure 2 The method can include the following steps: step 201, step 202, step 203 and step 204.

[0124] In step 201, when the streaming video playing occurs stall, the application layer optimization strategy is executed; wherein the application layer optimization strategy includes at least one of the following: reducing the video code rate, switching the video encoding format, adjusting the rendering resolution, switching the content distribution network node, and reinitiating the connection request to the server.

[0125] In the embodiment of the application, when the streaming video stall is detected, the application layer optimization strategy is first executed. These strategies are directly controlled by the streaming media application or the client, without the special permission of the operating system or the modem of the terminal, and have fast implementation speed and low cost.

[0126] In step 202, if streaming video playback still experiences stuttering after the application layer optimization strategy is executed, the corresponding status parameters are obtained; wherein, the status parameters include at least one of the following: current communication network quality parameters, current video transmission parameters, and historical stuttering information.

[0127] In this embodiment, if the lag issue persists after the application layer optimization strategy is executed, it indicates that the root cause may not be in the application layer or the server side, but rather a deeper network connection quality problem. Only then is the process of obtaining the corresponding status parameters initiated. This step typically requires calling system-level APIs to obtain underlying network information (such as RSRP, RSRQ, SINR, etc.) from the modem, and requires higher access privileges.

[0128] In this embodiment, a collaborative mechanism is constructed between the underlying communication layer and the business application layer. Through cross-layer information interaction and recording, accurate identification of streaming media stuttering caused by communication issues is achieved. Based on this, the solution synchronously executes the corresponding network recovery method for the identified network-related stuttering, thereby forming a closed-loop process from diagnosis to recovery.

[0129] In step 203, the cause of the lag is determined based on the status parameters; among which, the cause of the lag includes network anomalies.

[0130] In step 204, based on the cause of the lag, a network recovery strategy corresponding to the network anomaly is executed.

[0131] The content of steps 203 and 204 in the embodiments of this application is the same as that of... Figure 1 Steps 102 and 103 in the illustrated embodiment are similar and will not be repeated here.

[0132] As can be seen, in this embodiment, by adopting a hierarchical optimization mechanism, the application-layer strategy, which does not require system permissions, is executed first. This enables a rapid response to and resolution of most common lag issues, significantly reducing the user-perceived recovery latency. This approach not only complies with the permission management specifications of mobile operating systems but also avoids frequent triggering of high-power-consuming low-level network operations, effectively reducing terminal resource overhead and system power consumption. Furthermore, by using the network-side recovery strategy as a subsequent trigger, it is only activated when application-layer optimization is ineffective. This avoids over-responding to minor fluctuations, maintaining the stability of the communication link, and ensuring the eventual repairability of severe lag issues. This step-by-step, progressively more complex processing flow achieves a precise match between device resource investment and the severity of the problem, achieving an optimal balance between processing efficiency, resource consumption, and user experience while ensuring recovery effectiveness.

[0133] The video playing method provided in the embodiments of the present application can be executed by a video playing device. The video playing device is taken as an example in the embodiments of the present application to illustrate the video playing device provided in the embodiments of the present application.

[0134] Figure 3 is a structural block diagram of a video playing device provided in the embodiments of the present application, as shown in the figure, the video playing device 300 can include an acquisition module 301, a determination module 302 and a processing module 303. Figure 3 The acquisition module 301 is configured to acquire corresponding state parameters in the case that the streaming video playing occurs lagging. The determination module 302 is configured to determine the lagging reason according to the state parameters. The processing module 303 is configured to execute a network recovery strategy corresponding to the network exception based on the lagging reason.

[0135] From the above embodiments, it can be seen that in the case that the streaming video playing occurs lagging, corresponding state parameters are acquired; the state parameters include at least one of the following: current communication network quality parameters, current video transmission parameters and historical lagging information; the lagging reason is determined according to the state parameters; the lagging reason includes network exception; and a network recovery strategy corresponding to the network exception is executed based on the lagging reason.

[0136] It can be seen that in the embodiments of the present application, the communication network quality, the video transmission parameters and the historical lagging information are comprehensively analyzed to accurately diagnose the lagging reason and avoid blind optimization; after accurate diagnosis, a special network recovery strategy is triggered to be executed to improve the recovery efficiency and success rate, which can effectively deal with the video lagging problem caused by network exception, ensures the efficiency and accuracy of the recovery measures, makes the video playing more smooth and the lagging recovery more rapid, and provides stable and high-quality watching experience for users.

[0137] Optionally, as one embodiment, the processing module 303 is further configured to execute an application layer optimization strategy in the case that the streaming video playing occurs lagging; the application layer optimization strategy includes at least one of the following: reducing the video code rate, switching the video encoding format, adjusting the rendering resolution, switching the content distribution network node and reinitiating a connection request to the server. The acquisition module 301 is specifically configured to acquire corresponding state parameters in the case that the streaming video playing still occurs lagging after the execution of the application layer optimization strategy.

[0138] ​Optionally, as an embodiment, the processing module 303 is specifically configured to determine a target network recovery strategy from a plurality of candidate network recovery strategies according to the frame freezing reason and the historical frame freezing information; wherein the target network recovery strategy is determined based on a recovery strategy recorded in the historical frame freezing information and verified as effective for the same frame freezing reason under the same or similar network environment; and the target network recovery strategy is executed.

[0139] Optionally, as an embodiment, the acquisition module 301 is specifically configured to acquire a current video transmission parameter; and if the current video transmission parameter meets a preset condition, trigger acquisition of a current communication network quality parameter or historical frame freezing information; wherein the preset condition is used to indicate that frame freezing is related to network anomaly, and the preset condition includes at least one of the following: real-time network throughput is lower than a preset throughput threshold, and first packet time exceeds a preset delay threshold.

[0140] Optionally, as an embodiment, the current communication network quality parameter includes at least one of the following: reference signal received power, reference signal received quality, signal to interference plus noise ratio, physical layer uplink and downlink block error rate, recent wireless link failure statistical number, downlink scheduling information, medium access control layer buffer depth, and maximum transmission power reduction; The current video transmission parameter includes at least one of the following: real-time network throughput and first packet time. The historical frame freezing information includes at least one of the following: frame freezing time, recovery time, frame freezing reason, terminal communication network quality parameter, network cell information, executed network recovery strategy, and effectiveness thereof.

[0141] Optionally, as an embodiment, the state parameter includes the current communication network quality parameter. The determination module 302 is specifically configured to compare a value of each current communication network quality parameter with a corresponding preset threshold interval, determine a quality level to which each current communication network quality parameter belongs; wherein the quality level is used to indicate the advantages and disadvantages of network quality, and the higher the level is, the worse the network quality is; according to quality levels of all current communication network quality parameters, determine a current comprehensive network quality level by using majority voting principle; and if the current comprehensive network quality level is higher than or equal to a preset abnormal level threshold, determine that the frame freezing reason is network anomaly.

[0142] Optionally, as an embodiment, the state parameter includes the current communication network quality parameter and the historical frame freezing information. The determining module 302 is specifically configured to determine a current comprehensive network quality level according to the current communication network quality parameter; acquire current network camping cell information, and query historical stall reasons under the network camping cell information from the historical stall information; and determine a current stall reason based on the current comprehensive network quality level and the stall reason in the queried historical record.

[0143] Optionally, as an embodiment, the network recovery strategy includes: dual-card data acceleration, switching data cards, switching terminal camping to other cells, and replacing the terminal current network camping mode; wherein, the network recovery strategy is executed in order according to the execution priority.

[0144] Optionally, as an embodiment, the video playing device 300 can further include: The recording module is configured to record the stall time, recovery time, stall reason, terminal communication network quality parameter, network camping cell information, executed network recovery strategy and effectiveness of this time stall, so as to update the historical stall information.

[0145] The video playing device in the embodiments of the present application can be an electronic device, or a component in an electronic device, such as an integrated circuit or a chip. The electronic device can be an electronic device, or a device other than an electronic device. Exemplarily, the electronic device can be a mobile phone, a tablet computer, a notebook computer, a palm computer, a vehicle-mounted electronic device, a Mobile Internet Device (MID), an Augmented Reality (AR) / Virtual Reality (VR) device, a robot, a wearable device, an Ultra-Mobile Personal Computer (UMPC), a netbook, or a Personal Digital Assistant (PDA), etc., and can also be a server, a Network Attached Storage (NAS), a Personal Computer (PC), a Television (TV), a teller machine, or a self-service machine, etc., and the embodiments of the present application are not limited in this regard.

[0146] The video playing device in the embodiments of the present application can be a device with an operating system. The operating system can be an Android operating system, can be an iOS operating system, or can be a possible operating system, and the embodiments of the present application are not limited in this regard.

[0147] The video playing device provided by the embodiments of the present application can realize each process realized by the method embodiments, and thus details are not repeated here.

[0148] Optionally, as shown in Figure 4 The embodiments of the present application also provide an electronic device 400, including a processor 401 and a memory 402, the memory 402 stores programs or instructions which can run on the processor 401, when the programs or instructions are executed by the processor 401, each step of the above-mentioned video playing method embodiments is realized, and the same technical effects can be achieved, and thus details are not repeated here.

[0149] It should be noted that the electronic device in the embodiments of the present application includes the mobile electronic device and the non-mobile electronic device.

[0150] Figure 5 is a hardware structure schematic diagram of an electronic device for implementing various embodiments of the present application. The electronic device 500 includes but is not limited to: a radio frequency unit 501, a network module 502, an audio output unit 503, an input unit 504, a sensor 505, a display unit 506, a user input unit 507, an interface unit 508, a memory 509, and a processor 510, etc.

[0151] Those skilled in the art can understand that the electronic device 500 can also include a power supply (such as a battery) for supplying power to each component, and the power supply can be logically connected to the processor 510 through a power management system, so as to realize the functions of managing charging, discharging, and power consumption management through the power management system. Figure 5 The electronic device structure shown in the above-mentioned embodiments does not constitute a limitation on the electronic device, and the electronic device can include more or fewer components than the diagram, or combine certain components, or different component arrangements, and thus details are not repeated here.

[0152] The processor 510 is configured to: acquire a corresponding state parameter in the case that the streaming video playing occurs lag; the state parameter includes at least one of the following: a current communication network quality parameter, a current video transmission parameter, and historical lag information; determine a lag reason according to the state parameter; the lag reason includes network anomaly; and execute a network recovery strategy corresponding to the network anomaly based on the lag reason.

[0153] It can be seen that in the embodiments of the present application, the communication network quality, the video transmission parameters and the historical stall information are comprehensively analyzed to accurately diagnose the stall reason and avoid blind optimization. After accurate diagnosis, a special network recovery strategy is triggered to execute to improve the recovery efficiency and success rate, which can fundamentally effectively cope with the video stall problem caused by network anomalies, ensures the efficiency and accuracy of the recovery measures, makes the video play more smooth and the stall recovery more rapid, and provides a stable and high-quality viewing experience for users.

[0154] Optionally, as an embodiment, the processor 510 is specifically configured to execute an application layer optimization strategy in the case that the streaming video play stalls; wherein the application layer optimization strategy comprises at least one of the following: reducing the video code rate, switching the video encoding format, adjusting the rendering resolution, switching the content distribution network node, and reinitiating the connection request to the server; in the case that the streaming video play still stalls after executing the application layer optimization strategy, the corresponding state parameters are acquired.

[0155] Optionally, as an embodiment, the processor 510 is specifically configured to determine a target network recovery strategy from a plurality of candidate network recovery strategies according to the stall reason and the historical stall information; wherein the target network recovery strategy is determined based on a recovery strategy recorded in the historical stall information and verified as effective for the same stall reason under the same or similar network environment; and the target network recovery strategy is executed.

[0156] Optionally, as an embodiment, the processor 510 is specifically configured to acquire the current video transmission parameters; if the current video transmission parameters meet a preset condition, the current communication network quality parameters or the historical stall information are acquired; wherein the preset condition is used to indicate that the stall is related to network anomalies, and the preset condition comprises at least one of the following: the real-time network throughput is lower than a preset throughput threshold, and the first packet time exceeds a preset delay threshold.

[0157] Optionally, as an embodiment, the current communication network quality parameters comprise at least one of the following: reference signal received power, reference signal received quality, signal to interference plus noise ratio, physical layer uplink and downlink block error rate, recent wireless link failure statistical number, downlink scheduling information, medium access control layer buffer depth, and maximum transmission power reduction; The current video transmission parameters comprise at least one of the following: real-time network throughput and first packet time. The historical stall information comprises at least one of the following: stall time, recovery time, stall reason, terminal communication network quality parameters, network cell information, executed network recovery strategy and effectiveness thereof.

[0158] Optionally, as an embodiment, the state parameter comprises the current communication network quality parameter. The processor 510 is specifically configured to compare the value of each current communication network quality parameter with a corresponding preset threshold interval, determine a quality level to which each current communication network quality parameter belongs, wherein the quality level is used to indicate the advantages and disadvantages of network quality, and the higher the level is, the worse the network quality is; determine a current comprehensive network quality level according to the quality levels of all the current communication network quality parameters by using a majority voting principle; and determine that the cause of the lag is network anomaly if the current comprehensive network quality level is higher than or equal to a preset anomaly level threshold.

[0159] Optionally, as an embodiment, the state parameter comprises the current communication network quality parameter and the historical lag information. The processor 510 is specifically configured to determine a current comprehensive network quality level according to the current communication network quality parameter; acquire current camped cell information, and query historical lag causes under the camped cell information from the historical lag information; and determine a current lag cause based on the current comprehensive network quality level and the lag causes in the queried historical record.

[0160] Optionally, as an embodiment, the network recovery strategy comprises: dual-card data acceleration, switching data cards, switching terminal camping to other cells, and replacing the terminal current camping network mode; wherein the network recovery strategy is executed in turn according to the execution priority order.

[0161] Optionally, as an embodiment, the processor 510 is further configured to record the lag time, the recovery time, the lag cause, the terminal communication network quality parameter, the camped cell information, the executed network recovery strategy and its effectiveness of this time lag, so as to update the historical lag information.

[0162] It should be understood that in the embodiments of the present application, the input unit 504 can include a graphics processing unit (GPU) 5041 and a microphone 5042. The graphics processing unit 5041 processes image data of a still image or a video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 506 can include a display panel 5061, which can be configured in the form of a liquid crystal display, an organic light-emitting diode, etc. The user input unit 507 includes at least one of a touch panel 5071 and an input device 5072. The touch panel 5071 is also called a touch screen. The touch panel 5071 can include two parts of a touch detection device and a touch controller. The input device 5072 can include, but is not limited to, a physical keyboard, function keys (such as volume control keys, on-off keys, etc.), trackballs, mice, joysticks, and the like, which will not be described here.

[0163] The memory 509 can be used to store software programs and various data. The memory 509 can mainly include a first storage area storing programs or instructions and a second storage area storing data, wherein the first storage area can store an operating system, application programs or instructions required by at least one function (such as a sound playing function, an image playing function, etc.), etc. In addition, the memory 509 can include a volatile memory or a non-volatile memory, or the memory 509 can include both volatile and non-volatile memories. The non-volatile memory can be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM) or a flash memory. The volatile memory can be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDR SDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchlink dynamic random access memory (SLDRAM) and a direct memory bus random access memory (Direct Rambus RAM, DRRAM). The memory 509 in the embodiments of the present application includes but is not limited to these and any other suitable types of memory.

[0164] The processor 510 can include one or more processing units; optionally, the processor 510 integrates an application processor and a modem processor, wherein the application processor mainly processes operations related to an operating system, a user interface, and an application program, and the modem processor mainly processes a wireless communication signal, such as a baseband processor. It can be understood that the above-mentioned modem processor can also not be integrated into the processor 510.

[0165] The embodiment of the present application further provides a readable storage medium, and the readable storage medium stores a program or an instruction. The program or the instruction is executed by a processor to realize various processes of the above-mentioned video playing method embodiment, and the same technical effects can be achieved. To avoid repetition, details are not described herein.

[0166] The processor is a processor in the electronic device in the above-mentioned embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and the like.

[0167] The embodiment of the present application further provides a chip, and the chip includes a processor and a communication interface. The communication interface is coupled with the processor. The processor is configured to execute a program or an instruction to realize various processes of the above-mentioned video playing method embodiment, and the same technical effects can be achieved. To avoid repetition, details are not described herein.

[0168] It should be understood that the chip mentioned in the embodiment of the present application can also be referred to as a system-level chip, a system chip, a chip system, or a system-on-chip chip, and the like.

[0169] The embodiment of the present application further provides a computer program product. The program product is stored in a storage medium. The program product is executed by at least one processor to realize various processes of the above-mentioned video playing method embodiment, and the same technical effects can be achieved. To avoid repetition, details are not described herein.

[0170] It should be noted that, in the present document, the terms "comprises", "comprising", or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can include other elements not expressly listed or inherent to such process, method, article, or apparatus. An element proceeded by "comprises... a" does not, without more constraints, exclude the presence of additional identical elements in the process, method, article, or apparatus that comprises the element. Furthermore, it should be noted that the methods and apparatuses of the present embodiments are not limited by the order of the steps or the sequence for performing the steps, as some steps can occur simultaneously, in other steps can occur sequentially, or in between other steps can occur at a time different than other steps, unless expressly limited by the context of the corresponding claim. Moreover, the features of the examples described can be combined in examples unless expressly excluded in the specific context.

[0171] From the above description of the embodiments, it is clear that the above-described method of the embodiments can be realized by means of software and a general-purpose hardware platform, of course, it can also be realized by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present application can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a plurality of instructions for making an electronic device (such as a mobile phone, computer, server, or network device) execute the method of each embodiment of the present application.

[0172] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-described specific embodiments, and the above-described specific embodiments are merely illustrative, rather than limiting, and a person of ordinary skill in the art can make many forms under the inspiration of the present application without departing from the scope of the present application and the scope of protection of the claims.

Claims

1. A video playing method, characterized in that, The method is executed by a terminal, and the method comprises: In the case that the streaming media video playback is stalled, corresponding state parameters are acquired; wherein the state parameters comprise at least one of the following: current communication network quality parameters, current video transmission parameters, historical stall information; According to the state parameters, a stall reason is determined; wherein the stall reason comprises network anomalies; Based on the stall reason, a network recovery strategy corresponding to the network anomalies is executed.

2. The method of claim 1, wherein, Before the corresponding state parameters are acquired, the method further comprises: In the case that the streaming media video playback is stalled, an application layer optimization strategy is executed; wherein the application layer optimization strategy comprises at least one of the following: reducing video code rate, switching video encoding format, adjusting rendering resolution, switching content distribution network node, reinitiating a connection request to a server; The corresponding state parameters are acquired, comprising: In the case that the streaming media video playback is still stalled after the application layer optimization strategy is executed, the corresponding state parameters are acquired.

3. The method of claim 1, wherein, The network recovery strategy corresponding to the network anomalies is executed based on the stall reason, comprising: According to the stall reason and the historical stall information, a target network recovery strategy is determined from a plurality of candidate network recovery strategies; wherein the target network recovery strategy is determined based on a recovery strategy recorded in the historical stall information, which is verified as effective for the same stall reason under the same or similar network environment; The target network recovery strategy is executed.

4. The method of claim 1, wherein, The corresponding state parameters are acquired, comprising: Current video transmission parameters are acquired; If the current video transmission parameters meet a preset condition, current communication network quality parameters or historical stall information are acquired; Wherein the preset condition is used to indicate that the stall is related to network anomalies, and the preset condition comprises at least one of the following: real-time network throughput is lower than a preset throughput threshold, first packet time exceeds a preset delay threshold.

5. The method of any one of claims 1-4, wherein: The current communication network quality parameters comprise at least one of the following: reference signal received power, reference signal received quality, signal to interference plus noise ratio, physical layer uplink block error rate, recent radio link failure statistical number, downlink scheduling information, medium access control layer buffer depth, maximum transmission power reduction; The current video transmission parameters comprise at least one of the following: real-time network throughput, first packet time; The historical stall information comprises at least one of the following: stall time, recovery time, stall reason, terminal communication network quality parameters, camped cell information, executed network recovery strategy and effectiveness thereof.

6. The method of claim 5, wherein, The state parameters comprise the current communication network quality parameters; According to the state parameters, the stall reason is determined, comprising: The value of each current communication network quality parameter is compared with a corresponding preset threshold interval to determine the quality level to which each current communication network quality parameter belongs; wherein the quality level is used to indicate the advantages and disadvantages of network quality, and the higher the level is, the worse the network quality is. determine a current comprehensive network quality level according to quality levels of all the current communication network quality parameters by using a majority voting principle; if the current comprehensive network quality level is higher than or equal to a preset abnormal level threshold, determine that the cause of the freezing is network abnormality.

7. The method of claim 5, wherein, the state parameters include the current communication network quality parameters and the historical freezing information; the determining of the freezing cause according to the state parameters comprises: determining a current comprehensive network quality level according to the current communication network quality parameters; obtaining current camped cell information, and querying the historical freezing cause under the camped cell information from the historical freezing information; determining the current freezing cause based on the current comprehensive network quality level and the freezing cause in the queried historical record.

8. The method of claim 1, wherein, the network recovery strategy comprises: dual-card data acceleration, switching data cards, switching terminal camping to other cells, and replacing the terminal current camped network mode; wherein the network recovery strategy is executed in order according to the execution priority.

9. The method of claim 1, wherein, after the network recovery strategy corresponding to the network abnormality is executed based on the freezing cause, the method further comprises: recording the freezing time, recovery time, freezing cause, terminal communication network quality parameter, camped cell information, executed network recovery strategy and effectiveness thereof of this freezing, so as to update the historical freezing information.

10. A video playback device, comprising: executed by a terminal, the apparatus comprises: an obtaining module, configured to obtain corresponding state parameters in the case of freezing of streaming media video playing; wherein the state parameters include at least one of the following: current communication network quality parameters, current video transmission parameters, and historical freezing information; a determining module, configured to determine a freezing cause according to the state parameters; wherein the freezing cause includes network abnormality; a processing module, configured to execute a network recovery strategy corresponding to the network abnormality based on the freezing cause.

11. The apparatus of claim 10, wherein the processing module is further configured to execute an application layer optimization strategy in the case of freezing of streaming media video playing; wherein the application layer optimization strategy includes at least one of the following: reducing video code rate, switching video encoding format, adjusting rendering resolution, switching content distribution network node, and reinitiating a connection request to a server; the obtaining module is specifically configured to obtain corresponding state parameters in the case of freezing of the streaming media video playing after the application layer optimization strategy is executed.

12. The apparatus of claim 10, wherein the processing module is specifically configured to determine a target network recovery strategy from a plurality of candidate network recovery strategies according to the freezing cause and the historical freezing information; wherein the target network recovery strategy is determined based on a recovery strategy recorded in the historical freezing information and verified as effective for the same freezing cause under the same or similar network environment; and the target network recovery strategy is executed.

13. The apparatus of claim 10, wherein The acquisition module is specifically configured to acquire a current video transmission parameter; if the current video transmission parameter meets a preset condition, a current communication network quality parameter or historical stalling information is acquired; The preset condition is used to indicate that stalling is related to network anomaly, and the preset condition includes at least one of the following: real-time network throughput is lower than a preset throughput threshold, and a first packet time exceeds a preset delay threshold.

14. An electronic device, comprising: The electronic device includes a processor and a memory, the memory stores programs or instructions executable on the processor, and the programs or instructions are executed by the processor to implement the steps of the video playing method according to any one of claims 1 to 9.

15. A readable storage medium, characterized by, The readable storage medium stores programs or instructions, and the programs or instructions are executed by the processor to implement the steps of the video playing method according to any one of claims 1 to 9.

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