CN114979721B - Video slicing method, device, equipment and storage medium - Google Patents

Abstract

This application discloses a video slicing method, device, equipment and storage medium. The method includes: obtaining the first associated data of the corresponding slice of the video played by the client in the preset area, and obtaining the first associated data between the server and the video in the preset area. The second associated data associated with the slice; wherein, the first associated data includes the client's lagging data, first network quality data and load conditions, and the second associated data includes the second network quality of the server. data and the number of clients connected to the server; determine the comprehensive lag index of the preset area according to the first associated data and the second associated data; if the comprehensive lag index is greater than the preset threshold, Discard the video corresponding to the current slice. This application enables smooth playback of client videos.

Description

Video slicing method, device, equipment and storage medium

Technical field

The present application relates to the field of communication computer technology, and in particular to a video slicing method, device, equipment and storage medium.

Background technique

Currently, the server performs slicing and other processing on the original video through the corresponding slicing scheme, and then sends the obtained video slices to the client for the client to play.

However, when the client plays the video slices processed by the corresponding slicing scheme, the server-side slicing scheme needs to be adjusted through the lag index so that the client can play the video smoothly and enhance the user experience.

In the existing technology, the freeze index is usually calculated only based on the number of freezes and the average playback frame rate. However, the freeze index is calculated only based on the number of freezes and the average playback frame rate. The data comes from a single source and cannot clearly and accurately reflect other factors. The impact of freezing on the situation, the freezing index obtained based on this method will cause deviations in the optimization of subsequent slicing plans, that is, it is difficult to accurately adjust the video slicing plan, resulting in unsmooth video playback on the client.

Contents of the invention

The main purpose of this application is to provide a video slicing method, device, equipment and storage medium, aiming to solve the technical problem that the existing technology is difficult to accurately adjust the video slicing scheme, resulting in unsmooth video playback on the client.

To achieve the above objectives, this application provides a video slicing method, which includes:

Obtain the first associated data of the corresponding slice of the video played by the client in the preset area, and obtain the second associated data of the server associated with the slice in the preset area;

Wherein, the first associated data includes the client's lagging data, first network quality data and load conditions, and the second associated data includes the second network quality data of the server and the client connected to the server. number;

Determine a comprehensive stuck index of the preset area according to the first associated data and the second associated data;

If the comprehensive freezing index is greater than the preset threshold, the current slicing scheme corresponding to the video is discarded, and a target slicing scheme is determined to complete slicing the video based on the target slicing scheme.

Optionally, the step of determining the comprehensive stuck index of the preset area based on the first correlation data and the second correlation data includes:

Determine the client lagging index of the client according to the first associated data;

Determine the comprehensive evaluation coefficient of the server according to the second associated data;

The comprehensive lag index of the preset area is determined according to the client lag index and the comprehensive evaluation coefficient.

Optionally, the step of determining the client lag index of the client based on the first associated data includes:

Determine the number of stuck slices reported by the client from the stuck data;

Determine the number of all clients that are stuck on any stuck slice from the stuck data, and determine the number of times each client is stuck on any stuck slice and the number of times each client is stuck on any stuck slice. The total lag time on a lag slice;

Determine the network type of the client from the first network quality data and load conditions, and determine the network transmission index, network delay index and network delay index of the client on any stuck slice according to the network type. Hardware equipment performance index;

According to the number of stuck slices, the number of all clients, the number of stuck times, the stuck duration, the network transmission index, the network delay index and the hardware device performance index, calculate the client Caton index;

The step of determining the comprehensive evaluation coefficient of the server based on the second associated data includes:

Determine the used bandwidth of the server side from the second network quality data;

According to the number of clients connected to the server and the used bandwidth, a comprehensive evaluation coefficient corresponding to the server is calculated.

Optionally, the step of determining the target slicing scheme includes:

Obtain the historical effective slicing scheme of the preset area;

The target slicing plan is generated based on the historical effective slicing plan.

Optionally, the step of generating the target slicing scheme according to the historical effective slicing scheme includes:

Determine the average slice size and average comprehensive stuttering index for slicing the video from all historical effective slicing plans;

Obtain the effective slice size and effective comprehensive lag index of each historical effective slicing plan;

A first effective slicing plan is selected from the historical effective slicing plans based on the average slice size, the average comprehensive stuttering index, the effective slice size of the first effective slicing plan, and the effective synthesis of the first effective slicing plan. Caton index, get the first slice size;

Based on the first slice size, determine whether the first effective slicing scheme is a target slicing scheme;

If the first effective slicing plan is not the target slicing plan, based on the first slice size, the first effective slicing plan, the current slicing plan and the current slice size of the current slicing plan, from the history Determine the target tiling scheme among the valid tiling schemes.

Optionally, the target slice is determined from the historical effective slicing plan based on the first slice size, the first effective slicing plan, the current slicing plan and the current slice size of the current slicing plan. Program steps include:

Determine the selection direction of the target slicing plan based on the first slice size, the first effective slicing plan, the current slicing plan, and the current slice size of the current slicing plan;

Based on the selection direction, determine other effective slicing plans from the historical effective slicing plans;

Obtain the second slice size based on the average slice size, the average comprehensive lag index, the effective slice size of the other effective slicing schemes, and the effective comprehensive lag index of the other effective slicing schemes;

Based on the second slice size, determine whether the other valid slicing scheme is the target slicing scheme;

If the other valid slicing schemes are not the target slicing scheme, iterate back to the step of determining other valid slicing schemes from the historical valid slicing schemes based on the selection direction until the target slicing scheme is determined from the historical valid slicing schemes. .

Optionally, if the other valid slicing scheme is not the target slicing scheme, iteratively returns to the step of determining other valid slicing schemes from the historical valid slicing schemes based on the selection direction, until the step of determining other valid slicing schemes from the historical valid slicing schemes is The steps in the plan to determine the target tiling plan include:

If the other valid slicing scheme is not the target slicing scheme, and there is a preset number of valid slicing schemes adjacent in the time dimension whose slice size adjustment changes are less than the preset change, obtain the preset disturbance value;

Iterate back to the step of determining other valid slicing schemes from the historical valid slicing schemes based on the selection direction and the preset disturbance value until the target slicing scheme is determined from the historical valid slicing schemes.

This application also provides a video slicing device, which includes:

The acquisition module is used to obtain the first associated data of the corresponding slice of the video played by the client in the preset area, and obtain the second associated data associated with the slice by the server in the preset area;

Wherein, the first associated data includes the client's lagging data, first network quality data and load conditions, and the second associated data includes the second network quality data of the server and the client connected to the server. number;

A first determination module, configured to determine the comprehensive stuck index of the preset area according to the first associated data and the second associated data;

The second determination module is configured to discard the current slicing scheme corresponding to the video if the comprehensive freezing index is greater than a preset threshold, and determine a target slicing scheme to complete slicing the video based on the target slicing scheme.

This application also provides a video slicing device. The video slicing device is an entity node device. The video slicing device includes: a memory, a processor, and the program stored on the memory and capable of running on the processor. A program of a video slicing method. When the program of the video slicing method is executed by a processor, the steps of the video slicing method as described above can be implemented.

The present application also provides a storage medium on which a program for implementing the above video slicing method is stored. When the program for the video slicing method is executed by a processor, the steps of the above video slicing method are implemented.

This application also provides a computer program product, including a computer program, which implements the steps of the above video slicing method when executed by a processor.

This application provides a video slicing method, device, equipment and storage medium. Unlike the existing technology, which only calculates the lag index based on the number of lags and the average playback frame rate, it is difficult to accurately adjust the video slicing scheme, causing customers to Compared with the unsmooth video playback on the client, in this application, the first associated data of the client in the preset area and the second associated data of the server are merged (the first associated data includes the lag data of the client, the first network quality data and load conditions, the second associated data includes the second network quality data of the server and the number of clients connected to the server) to determine the comprehensive evaluation of the stuck index, that is, the comprehensive evaluated stuck index is based on the client More dimensional data is obtained from both the client and the server. Therefore, based on this comprehensive evaluation, the lag index can more accurately reflect whether the current video slicing scheme is reasonable. That is, the optimization of the subsequent slicing scheme will not be affected by the lag index. Deviation causes optimization deviation, but can be adjusted in a targeted manner. That is, if the comprehensive stuck index is greater than the preset threshold, a new target slicing plan can be accurately determined in a targeted manner (accurately adjust the slicing plan of the video ) to complete slicing of the video based on the target slicing scheme to achieve smooth playback of the client video.

Description of drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the application and together with the description, serve to explain the principles of the application.

In order to more clearly explain the embodiments of the present application or the technical solutions in the prior art, the following will briefly introduce the drawings needed to describe the embodiments or the prior art. Obviously, for those of ordinary skill in the art, It is said that other drawings can be obtained based on these drawings without exerting creative labor.

Figure 1 is a schematic flow chart of the first embodiment of the video slicing method of the present application;

Figure 2 is a schematic flowchart of the detailed steps of step S20 in the video slicing method of the present application;

Figure 3 is a schematic diagram of the equipment structure of the hardware operating environment involved in the embodiment of the present application;

Figure 4 is a schematic diagram of the first scene involved in the video slicing method of this application;

Figure 5 is a schematic diagram of the second scene involved in the video slicing method of this application.

The realization of the purpose, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings.

Detailed ways

It should be understood that the specific embodiments described here are only used to explain the present application and are not used to limit the present application.

An embodiment of the present application provides a video slicing method. In the first embodiment of the video slicing method of the present application, referring to Figure 1, the video slicing method includes:

Step S10, obtain the first associated data of the corresponding slice of the video played by the client in the preset area, and obtain the second associated data associated with the slice by the server in the preset area;

Wherein, the first associated data includes the client's lagging data, first network quality data and load conditions, and the second associated data includes the second network quality data of the server and the client connected to the server. number;

Step S20: Determine the comprehensive stuck index of the preset area according to the first associated data and the second associated data;

Step S30: If the comprehensive freezing index is greater than a preset threshold, discard the current slicing plan corresponding to the video, and determine a target slicing plan to complete slicing the video based on the target slicing plan.

In this embodiment, the video slicing method is applied to a video slicing device. The video slicing device belongs to a video slicing device. The video slicing device belongs to a video slicing system. The video slicing device belongs to a video slicing system including a server and a client. end.

In this embodiment, the application scenarios are:

First: The freeze index in the existing technology is usually calculated only based on the number of freezes and the average playback frame rate. However, the freeze index is calculated only based on the number of freezes and the average playback frame rate. The data comes from a single source and cannot reflect clearly and accurately. In addition to the impact of other factors on the stuttering situation, the stuttering index obtained based on this method will cause deviations in the optimization of subsequent slicing plans, that is, it is difficult to accurately adjust the video slicing plan, resulting in unsmooth video playback on the client.

In this application, the comprehensive evaluation of the lag index is based on more dimensional data from the client and the server. Therefore, based on the comprehensive evaluation of the lag index, it can more accurately reflect whether the current video slicing scheme is reasonable, that is, subsequent The optimization of the segmentation plan will not cause optimization deviation due to the deviation of the stuck index. On the contrary, it can be adjusted in a targeted manner. That is, if the comprehensive stuck index is greater than the preset threshold, the new stuck index can be accurately determined in a targeted manner. Target slicing scheme (accurately adjust the slicing scheme of the video) to complete slicing of the video based on the target slicing scheme to achieve smooth playback of the client video.

Second: In the existing technology, a fixed and single slicing scheme is usually applied to different regions and different video playback scenarios, resulting in the problem of playback lag in different regions and/or different playback scenarios.

In this application, the area of the slicing service is taken as a unit, and based on the analysis of the comprehensive lag index of different preset areas, the best target slicing scheme is provided for different areas to achieve regional-level customization of the slicing scheme.

Third: In the existing technology, changes in different external conditions such as the flow of people in the preset area and the upgrade of network technology equipment are difficult to reflect in the slicing scheme, resulting in the problem of playback lag.

In this application, changes in different external conditions such as personnel movement and network technology equipment upgrades in the preset area can be timely and accurately fed back to the first associated data and the second associated data. Therefore, based on the first associated data and the second associated data, The associated data enables dynamic adjustment of the slicing plan, making the slicing plan adjustment more flexible and more suitable for different user needs, providing users with a continuously optimized playback experience.

Fourth: In the existing technology, the slicing plan can only be adjusted through mechanical and lengthy offline and online testing based on the past experience and technology of relevant personnel (which are subject to change).

In this application, the target slicing plan is generated by comprehensively calculating the historical effective slicing plans in the preset area, reducing the single-introduction deviation value, improving the accuracy of the target slicing plan generation, and improving the optimization speed of the slicing plan.

Fifth: In the existing technology, the slicing scheme is easy to fall into local optimality (the change in slice size corresponding to the adjacent slicing scheme is smaller than the corresponding value).

In this application, a disturbance factor is introduced to prevent the slicing scheme from falling into a local optimum, thereby achieving a global optimum and improving the smoothness of user playback.

Specific steps are as follows:

Step S10, obtain the first associated data of the corresponding slice of the video played by the client in the preset area, and obtain the second associated data associated with the slice by the server in the preset area;

Wherein, the first associated data includes the client's lagging data, first network quality data and load conditions, and the second associated data includes the second network quality data of the server and the client connected to the server. number;

In this embodiment, it should be noted that the preset area can be a city or an urban area within the city. The preset area can also correspond to a base station. That is, the jurisdiction of a certain base station is a preset area. area.

Obtaining the first associated data of the corresponding slice of the video played by the client in the preset area includes:

Obtain the first associated data of the corresponding slice of the video played by the client in the preset area in real time;

Or the first associated data of the corresponding slice of the video played by the client in the preset area is obtained every preset time period.

Or when a change in the first associated data of the corresponding slice of the video played by the client in the preset area is detected, the first associated data of the corresponding slice of the video played by the client in the preset area is obtained.

As an example, the first associated data includes the client's lagging data, first network quality data, and load conditions.

As an example, the client's lag data includes the lag data of each client (within a unit period), including the number of lags, the lag time, and the slice position of the corresponding playback slice when the lag occurs. The client The first network quality data on the client is network quality status, including network type, network bandwidth, network delay, etc. The load status includes client CPU usage, client memory usage, etc.

In this embodiment, after obtaining the first associated data, preliminary filtering and cleaning are performed on the first associated data, that is, as shown in Figure 4 and Figure 5, garbled characters, negative values, and excessive values are removed from the first associated data. Abnormal data such as large values.

In this embodiment, second association data associated with the slice on the server side in the preset area is also obtained.

Wherein, obtaining the second association data associated with the slice on the server side in the preset area includes:

Obtain in real time the second associated data associated with the slice on the server side in the preset area;

Or the second association data associated with the slice on the server side in the preset area is obtained every preset time period.

Or when a change in the first associated data of the corresponding slice of the video played by the client in the preset area is detected, the second associated data associated with the slice by the server in the preset area is obtained.

In this embodiment, the second associated data includes second network quality data (network bandwidth, network delay, etc.) of the server and the number of clients connected to the server.

In this embodiment, after the second associated data is obtained, the second associated data is initially filtered and cleaned, that is, as shown in Figure 4 and Figure 5, garbled characters, negative values, and excessive values are removed from the second associated data. Abnormal data such as large values.

Step S20: Determine the comprehensive stuck index of the preset area according to the first associated data and the second associated data;

In this embodiment, the first associated data and the second associated data are comprehensively considered, and then the comprehensive stuck index of the preset area is obtained.

Among them, the method of obtaining the comprehensive stuck index of the preset area includes:

Method 1: Convert the first associated data and the second associated data into feature vectors, input the feature vectors into a preset index determination model, and determine the comprehensive card of the preset area based on the index determination model. Dayton index, wherein the index determination model is obtained by iteratively training a preset basic model based on training data with preset labels, and the index determines the degree of influence of each feature vector during the training process of the model.

Method 2: Substitute the first associated data and the second associated data into the calculation formula of the preset comprehensive lag index, and determine the comprehensive lag of the preset area based on the calculation formula of the preset comprehensive lag index. Dayton index.

Method 3: The step of determining the comprehensive stuck index of the preset area based on the first associated data and the second associated data includes:

Step S21: Determine the client lagging index of the client according to the first associated data;

In this embodiment, the client lag index of the client is determined based on the first associated data and the client lag index model.

Wherein, the step of determining the client lag index of the client based on the first associated data includes:

Step A1: Determine the number of stuck slices reported by the client from the stuck data;

Step A2: Determine the number of all clients that are stuck on any stuck slice from the stuck data, and determine the number of times each client is stuck on any stuck slice and the number of times each client is stuck on any stuck slice. The total lag duration on any of the lag slices;

Step A3: Determine the network type of the client from the first network quality data and load conditions, and determine the network transmission index and network delay of the client on any stuck slice according to the network type. Time index and hardware device performance index;

Step A4: According to the number of stuck slices, the number of all clients, the number of stuck times, the stuck duration, the network transmission index, the network delay index and the hardware device performance index, Calculate client lag index;

Specifically, the calculation formula of the client lag index is as follows:

In the above formula, N is the total number of slices, M is the number of reported lag slices, K is the number of people (the number of all clients) who reported lag in the m-th slice (any lag slice), and λ _i is the number of lags reported by each person. The number of lags in this slice (the number of lags for each client on any of the lag slices), t _i is the total lag time for each person on slice i (the number of lags for each client on any of the lag slices). The total lag duration on the lag slice), δ _i = |b _i ||d _i ||h _i |, δ _i ∈ (0,1], |a1| means that when the value of a1 is greater than 1, the value is 1 (where a1 represents bi, di or hi).

In the above formula 1, hi ( Different values are taken according to the performance of the device used by the user, and the default is 1).

In specific implementation, according to the network type of the client, the network transmission index, network delay index and hardware device performance index of the client on any of the stuck slices are determined, such as: 3G, 4G, WIFI and other different Network type, network transmission and delay thresholds will be adjusted.

Step S22: Determine the comprehensive evaluation coefficient of the server based on the second associated data;

In this embodiment, the comprehensive evaluation coefficient η of the server is determined based on the second associated data.

Specifically, the step of determining the comprehensive evaluation coefficient of the server based on the second associated data includes:

Step B1: Determine the used bandwidth of the server from the second network quality data;

Step B2: Calculate the comprehensive evaluation coefficient corresponding to the server based on the number of clients connected to the server and the used bandwidth.

In this embodiment, eta ∈ (0, 1] is the comprehensive evaluation coefficient of the server, which is generated by comprehensive calculations such as the number of threshold connections/number of client connections, threshold bandwidth/used bandwidth, CPU usage, etc., and the value of each item is is (0, 1], |a| means that when a2 value is greater than 1, the value is 1 (where a2 means in the above formula ).

Step S23: Determine the comprehensive lag index of the preset area based on the client lag index and the comprehensive evaluation coefficient.

In this embodiment, the comprehensive lag index calculation formula is as follows:

G=ηC formula (3);

C is the client freezing index calculated in formula (1), and eta is the comprehensive evaluation coefficient calculated in formula (2).

Step S30: If the comprehensive freezing index is greater than a preset threshold, discard the current slicing plan corresponding to the video, and determine a target slicing plan to complete slicing the video based on the target slicing plan.

In this embodiment, if the comprehensive freezing index is less than or equal to the preset threshold, the current slicing scheme corresponding to the video is valid.

In this embodiment, if the comprehensive freezing index is greater than the preset threshold, the current slicing scheme corresponding to the video is discarded, and the target slicing scheme is determined based on the current slicing scheme or the historical slicing scheme to complete the processing based on the target slicing scheme. Slices of said video.

This application provides a video slicing method, device, equipment and storage medium. Unlike the existing technology, which only calculates the lag index based on the number of lags and the average playback frame rate, it is difficult to accurately adjust the video slicing scheme, causing customers to Compared with the unsmooth video playback on the client, in this application, the first associated data of the client in the preset area and the second associated data of the server are merged (the first associated data includes the lag data of the client, the first network quality data and load conditions, the second associated data includes the second network quality data of the server and the number of clients connected to the server) to determine the comprehensive evaluation of the stuck index, that is, the comprehensive evaluated stuck index is based on the client More dimensional data is obtained from both the client and the server. Therefore, based on this comprehensive evaluation, the lag index can more accurately reflect whether the current video slicing scheme is reasonable. That is, the optimization of the subsequent slicing scheme will not be affected by the lag index. Deviation causes optimization deviation, but can be adjusted in a targeted manner. That is, if the comprehensive stuck index is greater than the preset threshold, a new target slicing plan can be accurately determined in a targeted manner (accurately adjust the slicing plan of the video ) to complete slicing of the video based on the target slicing scheme to achieve smooth playback of the client video.

Further, based on the first embodiment of the present application, another embodiment of the present application is provided. In this embodiment, the step of determining the target slicing scheme includes:

Step S31, obtain the historical effective slicing scheme of the preset area;

Step S32: Generate the target slicing plan according to the historical effective slicing plan.

In this embodiment, the target slicing plan is generated by comprehensively calculating the historical effective slicing plans in the preset area, thereby improving the accuracy of the target slicing plan generation and improving the optimization speed of the slicing plan, that is, the new slice size. Assume that the previous N effective slicing plans (historical effective slicing plans) within the area are comprehensively calculated and generated.

The step of generating the target slicing plan according to the historical effective slicing plan includes:

Step S321: Determine the average slice size and average comprehensive stuttering index for slicing the video from all historical effective slicing plans;

Step S322, obtain the effective slice size and effective comprehensive stuck index of each historical effective slice plan;

Step S323: Select a first effective slicing plan from the historical effective slicing plans based on the average slice size, the average comprehensive stuttering index, the effective slice size of the first effective slicing plan, and the first effective slicing plan. The effective comprehensive stuttering index is used to obtain the first slice size;

Step S324: Based on the first slice size, determine whether the first effective slicing plan is a target slicing plan;

Step S325: If the first effective slicing plan is not the target slicing plan, based on the first slice size, the first effective slicing plan, the current slicing plan and the current slice size of the current slicing plan, from The target slicing scheme is determined among the historical valid slicing schemes.

It should be noted that multiple slicing plans can also be stored in the preset area, and the slicing plans are actively changed when users frequently report freezes. However, in this embodiment, all users with the same resolution in the preset area use the same slice by default.

Specifically, the formula for determining the target slicing scheme is:

Specifically, as shown in the above formula (4), the average slice size for slicing the video is determined from all historical effective slicing plans. and average comprehensive lag index/> For example,/> are respectively the average slice size and the average comprehensive stuttering index of N slicing plans.

As shown in the above formula (4), the effective slice size and effective comprehensive stuck index of each historical effective slicing scheme are obtained. Specifically, S _t and G _t are the effective slice size and effective comprehensive stuck index of each historical effective slicing scheme respectively. index.

As shown in the above formula (4), T is the number of existing effective slicing plans (T is recommended to be more than 10).

As shown in the above formula (4), the first effective slicing plan is selected from the historical effective slicing plan based on the average slice size, the average comprehensive stuttering index, the effective slice size of the first effective slicing plan and the third effective slicing plan. The effective comprehensive stuck index of an effective slicing scheme is used to obtain the first slice size. Specifically, S is the slice size that needs to be calculated (the slice size that needs to be calculated this time can be the first slice size or other slice sizes), S _l can be the last slice size of the current calculation area (within the preset area). Based on the last slice size of the current calculation area (within the preset area), calculate whether S meets the requirements. If S does not meet the requirements (where S is the first slice size, the first valid slicing scheme is not the target slicing scheme), based on the first slice size, the first valid slicing scheme, the current slicing scheme and the current slice size of the current slicing scheme , determine the target slicing scheme from the historical effective slicing scheme. If S meets the requirements, the first valid slicing scheme is determined as the target slicing scheme from the historical valid slicing schemes.

In this embodiment, whether S meets the requirements is determined based on whether the comprehensive stuck index corresponding to S is greater than the preset threshold.

the step of determining a target slicing plan from the historical effective slicing plans based on the first slice size, the first effective slicing plan, the current slicing plan and the current slice size of the current slicing plan, include:

Step C1: Determine the selection direction of the target slicing plan based on the first slice size, the first effective slicing plan, the current slicing plan, and the current slice size of the current slicing plan;

Step C2: Based on the selection direction, determine other effective slicing plans from the historical effective slicing plans;

Step C3: Obtain the second slice size based on the average slice size, the average comprehensive lag index, the effective slice size of the other effective slicing schemes, and the effective comprehensive lag index of the other effective slicing schemes;

Step C4: Based on the second slice size, determine whether the other valid slicing scheme is the target slicing scheme;

Step C5: If the other valid slicing scheme is not the target slicing scheme, iterate back to the step of determining other valid slicing schemes from the historical valid slicing schemes based on the selection direction until the other valid slicing schemes are determined from the historical valid slicing schemes. Target tiling scheme.

In this embodiment, the selection direction of the target slicing plan is determined based on the first slice size, the first effective slicing plan, the current slicing plan, and the current slice size of the current slicing plan, also That is, in this embodiment, the selection direction for selecting the target slicing scheme is determined based on the current comprehensive lag index determined by the current slice size and the first comprehensive lag index of the first slice size.

Specifically, if the first comprehensive lag index is greater than the current comprehensive lag index, then other effective slicing plans are reversely determined from the historical effective slicing plans. For example, the current comprehensive lag index is a 12 plan. If the first comprehensive lag index If the stutter index is 13, then other valid slicing schemes are determined to be 12 in the direction of 1. If the first comprehensive stutter index is smaller than the current comprehensive stutter index, then other valid slicing schemes are positively determined from the historical valid slicing schemes, for example , the current comprehensive lag index is the 12 solution, if the first comprehensive lag index is the 13 solution, then determine other effective slicing solutions to be 13 in the direction of T such as 20.

Based on the average slice size, the average comprehensive lag index, the effective slice size of the other effective slicing schemes, and the effective comprehensive lag index of the other effective slicing schemes, a second slice size is obtained, based on the second slice size , determine whether the other valid slicing scheme is the target slicing scheme, and if the other valid slicing scheme is not the target slicing scheme, iteratively return to the step of determining other valid slicing schemes from the historical valid slicing scheme based on the selection direction. , until the target slicing scheme is determined from the historical valid slicing schemes.

In this embodiment, the target slicing scheme is selected in an orderly manner to improve efficiency.

Further, based on the above-mentioned embodiments of the present application, another embodiment of the present application is provided. If the other valid slicing scheme is not the target slicing scheme, iteratively returns to the historical valid slicing scheme based on the selection direction. The step of determining other valid tiling schemes, up to the step of determining the target tiling scheme from the historical valid tiling schemes, includes:

Step D1: If the other valid slicing schemes are not the target slicing scheme, and there are a preset number of valid slicing schemes adjacent in the time dimension whose slice size adjustment changes are less than the preset change amount, obtain a preset disturbance value. ;

Step D2: Iteratively return to the step of determining other effective slicing plans from the historical effective slicing plans based on the selection direction and the preset disturbance value until the target slicing plan is determined from the historical effective slicing plans.

In this embodiment,

In this embodiment, the difference between formula (5) and formula (4) lies in the addition of σ. Specifically, σ is a random disturbance value, σ∈[-0.25S _l , 0.25S _l ], to prevent falling into a local minimum. Optimal solution: when the change in slice size adjustment for M consecutive (3 to 8) consecutive adjacent slicing plans is less than ΔS, that is, when |St-St-1|<ΔS, increase the σ increment.

In this embodiment, in this application, a disturbance factor is introduced to prevent the slicing scheme from falling into a local optimum, thereby achieving a global optimum and improving the smoothness of user playback.

Referring to Figure 3, Figure 3 is a schematic diagram of the equipment structure of the hardware operating environment involved in the embodiment of the present application.

As shown in Figure 3, the video slicing device may include: a processor 1001, such as a CPU, a memory 1005, and a communication bus 1002. Among them, the communication bus 1002 is used to realize connection communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may optionally be a storage device independent of the aforementioned processor 1001.

Optionally, the video slicing device may also include a rectangular user interface, a network interface, a camera, an RF (Radio Frequency, radio frequency) circuit, a sensor, an audio circuit, a WiFi module, and so on. The rectangular user interface may include a display screen (Display) and an input sub-module such as a keyboard (Keyboard). The optional rectangular user interface may also include standard wired interfaces and wireless interfaces. Optional network interfaces may include standard wired interfaces and wireless interfaces (such as WI-FI interfaces).

Those skilled in the art can understand that the structure of the video slicing device shown in Figure 3 does not constitute a limitation on the video slicing device, and may include more or fewer components than shown, or some components may be combined, or different components may be used. layout.

As shown in Figure 3, memory 1005, which is a storage medium, may include an operating system, a network communication module, and a video slicing program. The operating system is a program that manages and controls the hardware and software resources of the video slicing device and supports the operation of the video slicing program and other software and/or programs. The network communication module is used to implement communication between components within the memory 1005, as well as communication with other hardware and software in the video slicing system.

In the video slicing device shown in Figure 3, the processor 1001 is used to execute the video slicing program stored in the memory 1005 to implement the steps of any of the above video slicing methods.

The specific implementation of the video slicing device of the present application is basically the same as the above embodiments of the video slicing method, and will not be described again here.

This application also provides a video slicing device, which includes:

The acquisition module is used to obtain the first associated data of the corresponding slice of the video played by the client in the preset area, and obtain the second associated data associated with the slice by the server in the preset area;

Wherein, the first associated data includes the client's lagging data, first network quality data and load conditions, and the second associated data includes the second network quality data of the server and the client connected to the server. number;

A first determination module, configured to determine the comprehensive stuck index of the preset area according to the first associated data and the second associated data;

The second determination module is configured to discard the current slicing scheme corresponding to the video if the comprehensive freezing index is greater than a preset threshold, and determine a target slicing scheme to complete slicing the video based on the target slicing scheme.

Optionally, the first determining module includes:

A first determining unit configured to determine the client lagging index of the client based on the first associated data;

a second determination unit, configured to determine the comprehensive evaluation coefficient of the server based on the second associated data;

The third determination unit is configured to determine the comprehensive lag index of the preset area according to the client lag index and the comprehensive evaluation coefficient.

Optionally, the first determining unit includes:

The first determining subunit is used to determine the number of stuck slices reported by the client from the stuck data;

The second determination subunit is used to determine the number of all clients that are stuck on any stuck slice from the stuck data, and determine the number of stalls of each client on any stuck slice; The total lag time of each client on any of the lag slices;

A third determination subunit, configured to determine the network type of the client from the first network quality data and load conditions, and determine the network type of the client on any stuck slice according to the network type. Transmission index, network delay index and hardware device performance index;

A first calculation subunit, configured to calculate the number of stuck slices, the number of all clients, the number of stuck times, the stuck duration, the network transmission index, the network delay index and the Hardware device performance index, calculate client lag index;

The fourth determination subunit, used for the step of determining the comprehensive evaluation coefficient of the server based on the second associated data, includes:

The fifth determination subunit is used to determine the used bandwidth of the server side from the second network quality data;

The second calculation subunit is used to calculate the comprehensive evaluation coefficient corresponding to the server according to the number of clients connected to the server and the used bandwidth.

Optionally, the second determination module includes:

An acquisition unit, configured to acquire the historical effective slicing scheme of the preset area;

A generating unit, configured to generate the target slicing plan according to the historical effective slicing plan.

Optionally, the generating unit includes:

The sixth determination subunit is used to determine the average slice size and the average comprehensive stuttering index for slicing the video from all historical valid slicing schemes;

The first acquisition subunit is used to obtain the effective slice size and effective comprehensive stuck index of each historical effective slicing scheme;

The second acquisition subunit is used to select a first effective slicing plan from the historical effective slicing plan, based on the average slice size, the average comprehensive stuttering index, the effective slice size of the first effective slicing plan and the The effective comprehensive stuck index of the first effective slicing scheme is used to obtain the first slice size;

A seventh determination subunit, configured to determine whether the first effective slicing scheme is a target slicing scheme based on the first slice size;

The eighth determination subunit is configured to determine, if the first valid slicing scheme is not the target slicing scheme, based on the first slice size, the first valid slicing scheme, the current slicing scheme and the current slicing scheme. The current tile size determines the target tiling scheme from the historical valid tiling schemes.

Optionally, the eighth determination subunit is used to implement:

Determine the selection direction of the target slicing plan based on the first slice size, the first effective slicing plan, the current slicing plan, and the current slice size of the current slicing plan;

Based on the selection direction, determine other effective slicing plans from the historical effective slicing plans;

Obtain the second slice size based on the average slice size, the average comprehensive lag index, the effective slice size of the other effective slicing schemes, and the effective comprehensive lag index of the other effective slicing schemes;

Based on the second slice size, determine whether the other valid slicing scheme is the target slicing scheme;

If the other valid slicing schemes are not the target slicing scheme, iterate back to the step of determining other valid slicing schemes from the historical valid slicing schemes based on the selection direction until the target slicing scheme is determined from the historical valid slicing schemes. .

Optionally, the eighth determination subunit is used to implement:

If the other valid slicing scheme is not the target slicing scheme, and there is a preset number of valid slicing schemes adjacent in the time dimension whose slice size adjustment changes are less than the preset change, obtain the preset disturbance value;

Iterate back to the step of determining other valid slicing schemes from the historical valid slicing schemes based on the selection direction and the preset disturbance value until the target slicing scheme is determined from the historical valid slicing schemes.

The specific implementation of the video slicing device of the present application is basically the same as the above embodiments of the video slicing method, and will not be described again here.

Embodiments of the present application provide a storage medium, and the storage medium stores one or more programs. The one or more programs can also be executed by one or more processors to implement any of the above. The steps of the video slicing method.

The specific implementation of the storage medium of this application is basically the same as the above embodiments of the video slicing method, and will not be described again here.

This application also provides a computer program product, including a computer program, which implements the steps of the above video slicing method when executed by a processor.

The specific implementation of the computer program product of the present application is basically the same as the above embodiments of the video slicing method, and will not be described again here.

It should be noted that, in this document, the terms "comprising", "comprises" or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article or device that includes a series of elements not only includes those elements, It also includes other elements not expressly listed or inherent in the process, method, article or apparatus. Without further limitation, an element defined by the statement "comprises a..." does not exclude the presence of additional identical elements in a process, method, article or apparatus that includes that element.

The above serial numbers of the embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments.

Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus the necessary general hardware platform. Of course, it can also be implemented by hardware, but in many cases the former is better. implementation. Based on this understanding, the technical solution of the present invention can be embodied in the form of a software product in essence or the part that contributes to the existing technology. The computer software product is stored in a storage medium (such as ROM/RAM, disk, CD), including several instructions to cause a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in various embodiments of the present invention.

The above are only preferred embodiments of the present invention, and do not limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the description and drawings of the present invention may be directly or indirectly used in other related technical fields. , are all similarly included in the scope of patent protection of the present invention.

Claims (8)

1. A video slicing method, the video slicing method comprising:

acquiring first association data of corresponding slices of video played by a client in a preset area, and acquiring second association data of a server in the preset area and the slices;

the first association data comprise the cartoon data of the client, first network quality data and load conditions, and the second association data comprise second network quality data of the server and the number of clients connected with the server;

determining the comprehensive katon index of the preset area according to the first association data and the second association data;

if the comprehensive katon index is larger than a preset threshold, discarding the video corresponding to the current slicing scheme, and determining a target slicing scheme to finish slicing the video based on the target slicing scheme;

The step of determining a target slicing scheme includes:

acquiring a historical effective slicing scheme of the preset area;

generating the target slicing scheme according to the historical effective slicing scheme;

the step of generating the target slicing scheme according to the historical effective slicing scheme comprises the following steps:

determining average slice size and average integrated katon index of slicing the video from all historical effective slicing schemes;

acquiring the effective slice size and the effective comprehensive katon index of each historical effective slice scheme;

selecting a first effective slicing scheme from the historical effective slicing schemes, and obtaining a first slicing size based on the average slicing size, the average comprehensive katon index, the effective slicing size of the first effective slicing scheme and the effective comprehensive katon index of the first effective slicing scheme;

determining, based on the first slice size, whether the first active slice scheme is a target slice scheme;

and if the first effective slicing scheme is not the target slicing scheme, determining the target slicing scheme from the historical effective slicing schemes based on the first slicing size, the first effective slicing scheme, the current slicing scheme and the current slicing size of the current slicing scheme.

2. The video slicing method of claim 1, wherein said step of determining a composite katon index for said predetermined region based on said first correlation data and said second correlation data comprises:

determining a client-side katana index of the client according to the first association data;

determining a comprehensive evaluation coefficient of the server according to the second association data;

and determining the comprehensive katon index of the preset area according to the client katon index and the comprehensive evaluation coefficient.

3. The video slicing method of claim 2, wherein said step of determining a client-side katana index of said client based on said first correlation data comprises:

determining the number of the cartoon slices reported by the client from the cartoon data;

determining the number of all clients which are stuck on any stuck slice from the stuck data, and determining the number of stuck times of each client on any stuck slice and the total stuck time of each client on any stuck slice;

determining the network type of the client from the first network quality data and the load condition, and determining a network transmission index, a network delay index and a hardware device performance index of the client on any one of the katon slices according to the network type;

Calculating a client-side jamming index according to the jamming section number, the number of all client-sides, the jamming times, the jamming time length, the network transmission index, the network delay index and the hardware equipment performance index;

the step of determining the comprehensive evaluation coefficient of the server according to the second association data comprises the following steps:

determining the bandwidth used by the server from the second network quality data;

and calculating the comprehensive evaluation coefficient corresponding to the server according to the number of the clients connected with the server and the use bandwidth.

4. The video slicing method of claim 1, wherein said determining a target slicing scheme from said historical effective slicing scheme based on said first slice size, said first effective slicing scheme, said current slicing scheme, and a current slice size of said current slicing scheme comprises:

determining a selection direction of the target slice scheme based on the first slice size, the first effective slice scheme, the current slice scheme and the current slice size of the current slice scheme, wherein if a first comprehensive katon index is greater than the current comprehensive katon index, other effective slice schemes are reversely determined from the historical effective slice scheme, and if the first comprehensive katon index is less than the current comprehensive katon index, other effective slice schemes are positively determined from the historical effective slice scheme;

Determining other effective slicing schemes from the historical effective slicing schemes based on the selection direction;

obtaining a second slice size based on the average slice size, the average integrated katon index, the effective slice sizes of the other effective slice schemes, and the effective integrated katon index of the other effective slice schemes;

determining, based on the second slice size, whether the other valid slice scheme is a target slice scheme;

and if the other effective slicing scheme is not the target slicing scheme, iteratively returning to the step of determining the other effective slicing scheme from the historical effective slicing schemes based on the selection direction until the target slicing scheme is determined from the historical effective slicing schemes.

5. The video slicing method of claim 4, wherein if said other active slicing scheme is not a target slicing scheme, iterating back to determining other active slicing schemes from said historical active slicing schemes based on said selection direction until a target slicing scheme is determined from said historical active slicing schemes, comprising:

if the other effective slicing schemes are not target slicing schemes, and the slice size adjustment variable quantity of the adjacent effective slicing schemes in the time dimension with the preset times is smaller than the preset variable quantity, acquiring a preset disturbance value;

And iterating back to the step of determining other effective slicing schemes from the historical effective slicing schemes based on the selected direction and the preset disturbance value until a target slicing scheme is determined from the historical effective slicing schemes.

6. A video slicing device, the video slicing device comprising:

the acquisition module is used for acquiring first association data of corresponding slices of video played by a client in a preset area and acquiring second association data of the server in the preset area associated with the slices;

the first association data comprise the cartoon data of the client, first network quality data and load conditions, and the second association data comprise second network quality data of the server and the number of clients connected with the server;

the first determining module is used for determining the comprehensive katon index of the preset area according to the first associated data and the second associated data;

the second determining module is used for discarding the video corresponding to the current slicing scheme and determining a target slicing scheme if the comprehensive katon index is larger than a preset threshold value so as to finish slicing the video based on the target slicing scheme;

The video slicing device is used for realizing:

acquiring a historical effective slicing scheme of the preset area;

generating the target slicing scheme according to the historical effective slicing scheme;

the video slicing device is used for realizing:

determining average slice size and average integrated katon index of slicing the video from all historical effective slicing schemes;

acquiring the effective slice size and the effective comprehensive katon index of each historical effective slice scheme;

selecting a first effective slicing scheme from the historical effective slicing schemes, and obtaining a first slicing size based on the average slicing size, the average comprehensive katon index, the effective slicing size of the first effective slicing scheme and the effective comprehensive katon index of the first effective slicing scheme;

determining, based on the first slice size, whether the first active slice scheme is a target slice scheme;

and if the first effective slicing scheme is not the target slicing scheme, determining the target slicing scheme from the historical effective slicing schemes based on the first slicing size, the first effective slicing scheme, the current slicing scheme and the current slicing size of the current slicing scheme.

7. A video slicing apparatus, the video slicing apparatus comprising: a memory, a processor and a program stored on the memory for implementing the video slicing method,

the memory is used for storing a program for realizing the video slicing method;

the processor is configured to execute a program implementing the video slicing method to implement the steps of the video slicing method according to any one of claims 1 to 5.

8. A storage medium having stored thereon a program for implementing a video slicing method, the program being executable by a processor to implement the steps of the video slicing method of any one of claims 1 to 5.