CN114979721B - Video slicing method, device, equipment and storage medium - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/24—Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth, upstream requests
- H04N21/2402—Monitoring of the downstream path of the transmission network, e.g. bandwidth available
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/24—Monitoring of processes or resources, e.g. monitoring of server load, available bandwidth, upstream requests
- H04N21/2405—Monitoring of the internal components or processes of the server, e.g. server load
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/44209—Monitoring of downstream path of the transmission network originating from a server, e.g. bandwidth variations of a wireless network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/40—Client devices specifically adapted for the reception of or interaction with content, e.g. set-top-box [STB]; Operations thereof
- H04N21/43—Processing of content or additional data, e.g. demultiplexing additional data from a digital video stream; Elementary client operations, e.g. monitoring of home network or synchronising decoder's clock; Client middleware
- H04N21/442—Monitoring of processes or resources, e.g. detecting the failure of a recording device, monitoring the downstream bandwidth, the number of times a movie has been viewed, the storage space available from the internal hard disk
- H04N21/4424—Monitoring of the internal components or processes of the client device, e.g. CPU or memory load, processing speed, timer, counter or percentage of the hard disk space used
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
- H04N21/83—Generation or processing of protective or descriptive data associated with content; Content structuring
- H04N21/845—Structuring of content, e.g. decomposing content into time segments
- H04N21/8456—Structuring of content, e.g. decomposing content into time segments by decomposing the content in the time domain, e.g. in time segments
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Abstract
The application discloses a video slicing method, a device, equipment and a storage medium, wherein the method comprises the following steps: 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; and discarding the video corresponding to the current slicing party if the comprehensive katon index is larger than a preset threshold. The method and the device realize smooth playing of the client video.
Description
Technical Field
The present disclosure relates to the field of communications computers, and in particular, to a video slicing method, apparatus, device, and storage medium.
Background
At present, the server performs processing such as slicing on an original video through a corresponding slicing scheme, and then sends the obtained video slice to the client for playing.
However, in the process of playing the video slice obtained after processing by the corresponding slice scheme, the slice scheme of the server side needs to be adjusted by the katon index, so that the client side can smoothly play the video, and the user experience is enhanced.
The jamming index in the prior art is usually obtained by calculating only the jamming times and the playing average frame rate, however, the jamming index is calculated only the jamming times and the playing average frame rate, the data source is single, the influence of other factors on the jamming condition cannot be clearly and accurately reflected, the jamming index obtained based on the method can cause deviation for the optimization of the subsequent segmentation scheme, namely, the video slicing scheme is difficult to accurately adjust, so that the video playing of the client is not smooth.
Disclosure of Invention
The main purpose of the application is to provide a video slicing method, a device, equipment and a storage medium, and aims to solve the technical problem that in the prior art, the slicing scheme of a video is difficult to accurately adjust, so that video playing of a client is unsmooth.
To achieve the above object, the present application provides a video slicing method, including:
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;
and 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.
Optionally, the step of determining the integrated katon index of the preset area according to the first association data and the second association data includes:
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.
Optionally, the step of determining the client-side katana index of the client according to the first association data includes:
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.
Optionally, the step of determining the target slicing scheme includes:
acquiring a historical effective slicing scheme of the preset area;
and generating the target slicing scheme according to the historical effective slicing scheme.
Optionally, the step of generating the target slicing scheme according to the historical effective slicing scheme includes:
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.
Optionally, the step of determining a target slice scheme from the historical effective 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 includes:
determining a selection direction of the target slice scheme based on the first slice size, the first valid slice scheme, the current slice scheme, and a current slice size of the current 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.
Optionally, if the other effective slicing scheme is not the target slicing scheme, iterating back to the step of determining the other effective slicing scheme from the historical effective slicing schemes based on the selection direction until the step of determining the target slicing scheme from the historical effective slicing schemes includes:
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.
The application also provides a 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;
and 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 application also provides a video slicing device, which is a physical node device, comprising: the video slicing method comprises a memory, a processor and a program of the video slicing method stored in the memory and capable of running on the processor, wherein the program of the video slicing method can realize the steps of the video slicing method when being executed by the processor.
The present application also provides a storage medium having stored thereon a program for implementing the video slicing method described above, which when executed by a processor implements the steps of the video slicing method described above.
The present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the video slicing method described above.
Compared with the prior art that the video slicing scheme is difficult to accurately adjust due to the fact that the katon index is obtained only according to the katon times and the play average frame rate, in the video slicing method, device and storage medium, in the video slicing method, compared with the prior art that the client video playing is not smooth, the video slicing scheme is difficult to accurately adjust due to the fact that the katon index is obtained through the calculation of the katon times and the play average frame rate, in the video slicing method, the first associated data comprise the katon data of the client, first network quality data and loading conditions of the client and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server, namely, the comprehensive evaluation katon index is obtained based on the client and the data with more dimensions of the server, therefore, whether the slicing scheme of the current video can be more accurately reflected based on the comprehensive evaluation katon index is reasonable, namely, optimization of the subsequent slicing scheme cannot cause optimization deviation due to the katon index, on the fact that the video slicing scheme is more accurate, if the comprehensive evaluation is greater than the preset, namely, the video slicing scheme can be accurately adjusted according to the video slicing scheme is accurately based on the video slicing scheme.
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 illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings that are required to be used in the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
Fig. 1 is a schematic flow chart of a first embodiment of a video slicing method of the present application;
fig. 2 is a schematic diagram of a refinement step flow of step S20 in the video slicing method of the present application;
FIG. 3 is a schematic diagram of a device architecture of a hardware operating environment according to an embodiment of the present application;
fig. 4 is a schematic view of a first scene related to the video slicing method of the present application;
fig. 5 is a schematic diagram of a second scenario involved in the video slicing method of the present application.
The implementation, functional features and advantages of the present application will be further described with reference to the accompanying drawings in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the present application.
An embodiment of the present application provides a video slicing method, in a first embodiment of the video slicing method of the present application, referring to fig. 1, the video slicing method includes:
step S10, 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;
step S20, determining the comprehensive katon index of the preset area according to the first association data and the second association data;
and step S30, discarding the video corresponding to the current slicing scheme and determining a target slicing scheme if the integrated katon index is greater than a preset threshold value so as to finish slicing the video based on the target slicing scheme.
In this embodiment, the video slicing method is applied to a video slicing device, the video slicing device belongs to a video slicing apparatus, the video slicing apparatus belongs to a video slicing system, and the video slicing apparatus belongs to the video slicing system and comprises a server side and a client side.
In this embodiment, the application scenario aimed at is:
first: the jamming index in the prior art is usually obtained by calculating only the jamming times and the playing average frame rate, however, the jamming index is calculated only the jamming times and the playing average frame rate, the data source is single, the influence of other factors on the jamming condition cannot be clearly and accurately reflected, the jamming index obtained based on the method can cause deviation for the optimization of the subsequent segmentation scheme, namely, the video slicing scheme is difficult to accurately adjust, so that the video playing of the client is not smooth.
In the application, the comprehensive evaluation katon index is obtained based on the data of more dimensionalities of the client and the server, so that whether the slicing scheme of the current video is reasonable or not can be accurately reflected based on the comprehensive evaluation katon index, namely, optimization of a subsequent slicing scheme cannot cause optimization deviation due to deviation of the katon index, and instead, the method can be used for adjusting in a targeted manner, namely, if the comprehensive katon index is larger than a preset threshold, a new target slicing scheme (accurately adjusting the slicing scheme of the video) can be accurately determined in a targeted manner, so that slicing of the video is completed based on the target slicing scheme, and smooth playing of the video of the client is realized.
Second,: in the prior art, a fixed and single slicing scheme is generally applied to different areas and different video playing scenes, so that playing clamping problems exist in different areas and/or different playing scenes.
In the method, the region of the slicing service is taken as a unit, and respective optimal target slicing schemes are provided for different regions according to analysis of respective comprehensive katon indexes of different preset regions, so that the customization of the slicing scheme region level is realized.
Third,: in the prior art, different external condition changes such as personnel flow in a preset area, network technical equipment upgrading and the like are difficult to embody on a slicing scheme, so that the problem of playing clamping exists.
In the method, the device and the system for adjusting the slicing scheme, different external condition changes such as personnel flow in a preset area and network technology equipment upgrading can be timely and accurately fed back to the first associated data and the second associated data, so that dynamic adjustment of the slicing scheme is achieved based on the first associated data and the second associated data, the slicing scheme is adjusted more flexibly, different user requirements are met, and continuous optimized playing experience is brought to a user.
Fourth,: in the prior art, the slicing scheme can only be adjusted through mechanical, long off-line and on-line tests according to the past experience and technology of related personnel (easy to move).
In the method, the target slicing scheme is generated by comprehensively calculating the historical effective slicing scheme in the preset area, so that the single-time introduced deviation value is reduced, the accuracy of generating the target slicing scheme is improved, and the optimization rate of the slicing scheme is improved.
Fifth,: in the prior art, the slicing scheme is easy to fall into local optimum (the variation of the sizes of the corresponding slices of the adjacent slicing schemes is smaller than the corresponding value).
In the method, the device and the system, the disturbance factor is introduced to avoid the slicing scheme from being in local optimum, so that the fluency of playing of a user is improved in global optimum.
The method comprises the following specific steps:
step S10, 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;
in this embodiment, it should be noted that the preset area may be a city, or may be an urban area within a city, and the preset area may also correspond to the base station, that is, the jurisdiction of a certain base station is a preset area.
The method for obtaining the first associated data of the corresponding slice of the video played by the client in the preset area comprises the following steps:
acquiring first associated data of corresponding slices of video played by a client in a preset area in real time;
or acquiring first associated data of corresponding slices of the video played by the client in a preset area every preset time period.
Or when the change of the first associated data of the corresponding slice of the client-side playing video in the preset area is detected, the first associated data of the corresponding slice of the client-side playing video in the preset area is obtained.
As an example, the first association data includes katon data, first network quality data, and a load condition of the client.
As an example, the click-on data of the client includes the click-on data of each client (in a unit period), including the click-on times, the click-on time, and the slice positions of the corresponding play slices when the click-on occurs, and the like, the first network quality data of the client is a network quality condition, including a network type, a network bandwidth, a network delay, and the like, and the load condition includes a client cpu usage rate, a client memory usage rate, and the like.
In this embodiment, after the first associated data is obtained, the first associated data is subjected to preliminary filtering and cleaning, that is, as shown in fig. 4 and 5, abnormal data such as a messy code, a negative value, an excessive value, and the like are removed from the first associated data.
In this embodiment, second association data associated with the slice at the server side in the preset area is also obtained.
The obtaining the second association data associated with the slice at the server side in the preset area includes:
acquiring second association data associated with the slice at a server side in the preset area in real time;
or acquiring second association data associated with the slice at the server side in the preset area every preset time period.
Or when detecting the change of the first association data of the corresponding slice of the video played by the client in the preset area, acquiring the second association data of the server in the preset area associated with the slice.
In this embodiment, the second association data includes second network quality data (network bandwidth, network delay, etc.) of the server side and the number of clients connected to the server side.
In this embodiment, after the second associated data is obtained, the second associated data is subjected to preliminary filtering and cleaning, that is, as shown in fig. 4 and 5, abnormal data such as a messy code, a negative value, an excessive value, and the like are removed from the second associated data.
Step S20, determining the comprehensive katon index of the preset area according to the first association data and the second association data;
In this embodiment, the first association data and the second association data are comprehensively considered, and then, the comprehensive katon index of the preset area is obtained.
The method for obtaining the comprehensive katon index of the preset area comprises the following steps:
mode one: converting the first association data and the second association data into feature vectors, inputting the feature vectors into a preset index determination model, and determining the comprehensive katon index of the preset area based on the index determination model, wherein the index determination model is obtained by performing iterative training on a preset basic model based on training data with preset labels, and the influence degree of each feature vector is determined in the training process of the index determination model.
Mode two: substituting the first associated data and the second associated data into a calculation formula of a preset comprehensive katon index, and determining the comprehensive katon index of the preset area based on the calculation formula of the preset comprehensive katon index.
In a third mode, the step of determining the comprehensive katon index of the preset area according to the first association data and the second association data includes:
step S21, determining a client-side katon index of the client according to the first association data;
In this embodiment, according to the first association data and the client-side katana index model, a client-side katana index of the client is determined.
The step of determining the client-side katana index of the client according to the first association data includes:
a1, determining the number of the cartoon slices reported by the client from the cartoon data;
step A2, 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;
step A3, determining the network type of the client from the first network quality data and the load condition, and determining the network transmission index, the network delay index and the hardware device performance index of the client on any one of the katon slices according to the network type;
step A4, calculating a client-side jamming index according to the jamming section number, the number of all client-sides, the jamming times, the jamming duration, the network transmission index, the network delay index and the hardware equipment performance index;
Specifically, the calculation formula of the client-side katon index is as follows:
in the above formula, N is the total number of slices, M is the number of reported stuck slices, K is the number of people (the number of all clients) reporting stuck on the mth slice (any stuck slice), and lambda i For each person's number of jams in the slice (number of jams of each client on any of the jams slices), t i For the total length of the click on slice i for each person (total length of the click on any one of the click slices for each client), δ i ＝|b i ||d i ||h i |，δ i ∈(0,1]The value "a1" represents a value of 1 when the value of a1 is greater than 1 (where a1 represents bi, di, or hi).
In the above formula 1, hi is generated by integrating the network transmission index bi (user network transmission rate/network transmission rate threshold), the network delay index di (user network delay time/network delay threshold) and the hardware index (taking different values according to the device performance used by the user, defaulting to 1) on the slice i by the user.
In specific implementation, according to the network type of the client, determining a network transmission index, a network delay index and hardware device performance index of the client on any one of the katon slices, for example: different network types such as 3G, 4G, WIFI, etc., network transmission and delay thresholds, etc., may be adjusted.
Step S22, determining the comprehensive evaluation coefficient of the server according to the second association data;
in this embodiment, according to the second association data, a comprehensive evaluation coefficient η of the server is determined.
Specifically, the step of determining the comprehensive evaluation coefficient of the server according to the second association data includes:
step B1, determining the bandwidth used by the server from the second network quality data;
and step B2, calculating a comprehensive evaluation coefficient corresponding to the server according to the number of the clients connected with the server and the use bandwidth.
In this embodiment, η ε (0, 1]The comprehensive evaluation coefficient of the server is generated by comprehensive calculation of threshold connection number/client connection number, threshold bandwidth/use bandwidth, CPU use rate and the like, and each item takes the value of (0, 1)]And |a| represents a value of 1 when a2 is greater than 1 (wherein a2 represents the above formula)。
Step S23, determining the comprehensive katon index of the preset area according to the client katon index and the comprehensive evaluation coefficient.
In this embodiment, the comprehensive katon index calculation formula is as follows:
g=ηc formula (3);
c is the client-side katon index calculated in the formula (1), and eta is the comprehensive evaluation coefficient calculated in the formula (2).
And step S30, discarding the video corresponding to the current slicing scheme and determining a target slicing scheme if the integrated katon index is greater than a preset threshold value so as to finish slicing the video based on the target slicing scheme.
In this embodiment, if the integrated katon index is less than or equal to a preset threshold, the video is valid corresponding to the current slicing scheme.
In this embodiment, if the integrated katon index is greater than a preset threshold, discarding the video corresponding to the current slicing scheme, and determining a target slicing scheme based on the current slicing scheme or the historical slicing scheme, so as to complete slicing of the video based on the target slicing scheme.
Compared with the prior art that the video slicing scheme is difficult to accurately adjust due to the fact that the katon index is obtained only according to the katon times and the play average frame rate, in the video slicing method, device and storage medium, in the video slicing method, compared with the prior art that the client video playing is not smooth, the video slicing scheme is difficult to accurately adjust due to the fact that the katon index is obtained through the calculation of the katon times and the play average frame rate, in the video slicing method, the first associated data comprise the katon data of the client, first network quality data and loading conditions of the client and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server, namely, the comprehensive evaluation katon index is obtained based on the client and the data with more dimensions of the server, therefore, whether the slicing scheme of the current video can be more accurately reflected based on the comprehensive evaluation katon index is reasonable, namely, optimization of the subsequent slicing scheme cannot cause optimization deviation due to the katon index, on the fact that the video slicing scheme is more accurate, if the comprehensive evaluation is greater than the preset, namely, the video slicing scheme can be accurately adjusted according to the video slicing scheme is accurately based on the video slicing scheme.
Further, based on the first embodiment in the present application, another embodiment of the present application is provided, in which the step of determining the target slicing scheme includes:
step S31, acquiring a historical effective slicing scheme of the preset area;
and step S32, generating the target slicing scheme according to the historical effective slicing scheme.
In this embodiment, the target slicing scheme is generated by comprehensively calculating the historical effective slicing scheme in the preset area, so that the accuracy of generating the target slicing scheme is improved, the optimization rate of the slicing scheme, that is, the new slicing size is improved, and the target slicing scheme is generated by comprehensively calculating the effective slicing scheme (the historical effective slicing scheme) N times before the current area (in the preset area).
The step of generating the target slicing scheme according to the historical effective slicing scheme comprises the following steps:
step S321, determining the average slice size and the average comprehensive katon index of slicing the video from all the historical effective slicing schemes;
step S322, obtaining the effective slice size and the effective comprehensive katon index of each historical effective slice scheme;
step S323, selecting a first effective slicing scheme from the historical effective slicing schemes, and obtaining a first slice size based on the average slice size, the average integrated katon index, the effective slice size of the first effective slicing scheme, and the effective integrated katon index of the first effective slicing scheme;
Step S324, determining whether the first effective slicing scheme is a target slicing scheme based on the first slice size;
in step S325, if the first valid slice scheme is not the target slice scheme, a target slice scheme is determined from the historical valid slice schemes based on the first slice size, the first valid slice scheme, the current slice scheme, and the current slice size of the current slice scheme.
It should be noted that, a plurality of slicing schemes can be stored in the preset area, and the slicing schemes can be actively replaced when the user frequently reports the card, but in this embodiment, all users in the preset area use the same slice by default with the same resolution.
Specifically, the determination formula of the target slicing scheme is:
specifically, as in equation (4) above, slicing video is determined from all historical effective slicing schemesAverage slice size of the sheetAnd average Integrated katon index->For example, a->The average slice size and average integrated katon index for the N slicing schemes, respectively.
Obtaining the effective slice size and the effective composite katon index of each historical effective slice scheme as in equation (4) above, specifically S t ，G t The effective slice size and the effective composite katon index for each historical effective slice scheme are separately.
As in the above equation (4), T is the number of available slicing schemes (tsrop 10 or more).
Selecting a first effective slicing scheme from the historical effective slicing schemes according to the above formula (4), and obtaining a first slice size based on the average slice size, the average integrated katon index, the effective slice size of the first effective slicing scheme, and the effective integrated katon index of the first effective slicing scheme, specifically, S is a slice size to be calculated (the slice size to be calculated this time may be the first slice size or other slice sizes), S l And if the S is not satisfactory (when the S is the first slice size, the first effective slice scheme is not the target slice scheme), and the target slice scheme is determined from the historical effective slice schemes 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. And if the S meets the requirement, determining the first effective slicing scheme as a target slicing scheme from the historical effective slicing schemes.
In this embodiment, whether S meets the requirement is determined according to whether the integrated katon index corresponding to S is greater than a preset threshold.
The step of determining a target slice scheme from the historical effective slice scheme based on the first slice size, the first effective slice scheme, the current slice scheme, and a current slice size of the current slice scheme, comprises:
step C1, determining a selection direction of the target slicing scheme 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;
step C2, determining other effective slicing schemes from the historical effective slicing schemes based on the selection direction;
step C3, obtaining a second slice size based on the average slice size, the average integrated jamming index, the effective slice sizes of the other effective slice schemes and the effective integrated jamming indexes of the other effective slice schemes;
step C4, based on the second slice size, determining whether the other valid slice schemes are target slice schemes;
and step C5, 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.
In this embodiment, the selection direction of the target slice scheme is determined based on the first slice size, the first valid slice scheme, the current slice scheme, and the current slice size of the current slice scheme, that is, in this embodiment, the selection direction of the target slice scheme is determined according to the current integrated katon index determined by the current slice size and the first integrated katon index of the first slice size.
Specifically, if the first integrated katon index is greater than the current integrated katon index, determining other effective slicing schemes reversely from the historical effective slicing schemes, for example, the current integrated katon index is 12 schemes, if the first integrated katon index is 13 schemes, determining other effective slicing schemes to be 12 to 1, if the first integrated katon index is less than the current integrated katon index, determining other effective slicing schemes positively from the historical effective slicing schemes, for example, the current integrated katon index is 12 schemes, and if the first integrated katon index is 13 schemes, determining other effective slicing schemes to be 13 to T as 20.
And 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 whether the other effective slice schemes are target slice schemes based on the second slice size, and if the other effective slice schemes are not target slice schemes, iterating back to the step of determining the other effective slice schemes from the historical effective slice schemes based on the selection direction until the target slice schemes are determined from the historical effective slice schemes.
In the embodiment, a target slicing scheme is selected orderly, and efficiency is improved.
Further, based on the foregoing embodiments of the present application, another embodiment of the present application is provided, and if the other valid slice scheme is not the target slice scheme, the step of iteratively returning to the step of determining the other valid slice scheme from the historical valid slice schemes based on the selection direction until the step of determining the target slice scheme from the historical valid slice schemes includes:
step D1, 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 preset times is smaller than the preset variable quantity, acquiring a preset disturbance value;
and D2, iteratively returning 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.
In the present embodiment of the present invention, in the present embodiment,
in the present embodiment, the difference between the formula (5) and the formula (4) is that sigma is added, specifically, sigma is a random disturbance value, sigma epsilon [ -0.25S l ，0.25S l ]Preventing the local optimal solution from being trapped, when the slice size adjustment variation of the adjacent slice scheme is smaller than delta S for M times (the value is suggested to be 3 to 8), namely: st-St-1|<At Δs, the σ increment is increased.
In this embodiment, in the present application, a disturbance factor is introduced to avoid the slicing scheme from falling into local optimum, so as to achieve global optimum and improve the fluency of user playing.
Referring to fig. 3, fig. 3 is a schematic device structure diagram of a hardware running environment according to an embodiment of the present application.
As shown in fig. 3, the video slicing apparatus may include: a processor 1001, such as a CPU, memory 1005, and a communication bus 1002. Wherein a communication bus 1002 is used to enable connected communication between the processor 1001 and a 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 also optionally be a storage device separate from the processor 1001 described above.
Optionally, the video slicing device may further include a rectangular user interface, a network interface, a camera, RF (Radio Frequency) circuitry, sensors, audio circuitry, wiFi modules, and the like. The rectangular user interface may include a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also include a standard wired interface, a wireless interface. The network interface may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface).
It will be appreciated by those skilled in the art that the video slicing device structure shown in fig. 3 is not limiting of the video slicing device and may include more or fewer components than shown, or certain components in combination, or a different arrangement of components.
As shown in fig. 3, an operating system, a network communication module, and a video slicing program may be included in the memory 1005 as one type of storage medium. An operating system is a program that manages and controls the hardware and software resources of a video slicing device, supporting the running of video slicing programs and other software and/or programs. The network communication module is used to enable communication between components within the memory 1005 and with other hardware and software in the video slicing system.
In the video slicing apparatus shown in fig. 3, a processor 1001 is configured to execute a video slicing program stored in a memory 1005, to implement the steps of the video slicing method described in any one of the above.
The specific implementation manner of the video slicing device is basically the same as that of each embodiment of the video slicing method, and is not repeated here.
The application also provides a 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;
and 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.
Optionally, the first determining module includes:
the first determining unit is used for determining a client-side katon index of the client-side according to the first association data;
the second determining unit is used for determining the comprehensive evaluation coefficient of the server according to the second associated data;
and the third determining unit is used for determining the comprehensive katon index of the preset area according to the client katon index and the comprehensive evaluation coefficient.
Optionally, the first determining unit includes:
The first determining subunit is used for determining the number of the cartoon slices reported by the client from the cartoon data;
a second determining subunit, configured to determine, from the jamming data, the number of all clients that are jammed on any one of the jamming slices, and determine the number of times that each client is jammed on the any one of the jamming slices, and a total time length that each client is jammed on the any one of the jamming slices;
a third determining subunit, configured to determine a network type of the client from the first network quality data and a load condition, and determine a network transmission index, a network delay index and a hardware device performance index of the client on the any one of the katon slices according to the network type;
the first calculating subunit is configured to calculate a client-side katana index according to the katana slice number, the number of all client-sides, the katana times, the katana duration, the network transmission index, the network delay index, and the hardware device performance index;
a fourth determining subunit, configured to determine, according to the second association data, a comprehensive evaluation coefficient of a server, where the step includes:
a fifth determining subunit, configured to determine a usage bandwidth of the server from the second network quality data;
And the second calculating subunit is used for calculating the comprehensive evaluation coefficient corresponding to the server according to the number of the clients connected with the server and the use bandwidth.
Optionally, the second determining module includes:
an acquisition unit, configured to acquire a historical effective slicing scheme of the preset area;
and the generating unit is used for generating the target slicing scheme according to the historical effective slicing scheme.
Optionally, the generating unit includes:
a sixth determining subunit, configured to determine an average slice size and an average integrated katon index for slicing the video from all the historical effective slicing schemes;
the first acquisition subunit is used for acquiring the effective slice size and the effective comprehensive katon index of each historical effective slice scheme;
the second obtaining subunit is configured to select a first effective slicing scheme from the historical effective slicing schemes, and obtain a first slice size based on the average slice size, the average integrated katon index, the effective slice size of the first effective slicing scheme, and the effective integrated katon index of the first effective slicing scheme;
a seventh determining subunit configured to determine, based on the first slice size, whether the first valid slice scheme is a target slice scheme;
An eighth determination subunit is configured to determine, if the first valid slice scheme is not the target slice scheme, a target slice scheme from the historical valid slice schemes based on the first slice size, the first valid slice scheme, the current slice scheme, and the current slice size of the current slice scheme.
Optionally, the eighth determining subunit is configured to implement:
determining a selection direction of the target slice scheme based on the first slice size, the first valid slice scheme, the current slice scheme, and a current slice size of the current 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.
Optionally, the eighth determining subunit is configured to implement:
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.
The specific implementation manner of the video slicing device is basically the same as the above embodiments of the video slicing method, and will not be repeated here.
Embodiments of the present application provide a storage medium, and the storage medium stores one or more programs, which may also be executed by one or more processors to implement the steps of the video slicing method described in any one of the above.
The specific implementation manner of the storage medium is basically the same as that of each embodiment of the video slicing method, and is not repeated here.
The present application also provides a computer program product comprising a computer program which, when executed by a processor, implements the steps of the video slicing method described above.
The specific implementation manner of the computer program product of the present application is substantially the same as that of the above embodiments of the video slicing method, and will not be repeated here.
It should be noted that, in this 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 may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein or in the alternative, which may be employed directly or indirectly in other related arts.
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.
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