CN114979721A - 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
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- 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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- 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
Abstract
The application discloses a video slicing method, a video slicing device, video slicing equipment and a storage medium, wherein the method comprises the following steps: acquiring first associated data of a corresponding slice of a video played by a client in a preset area, and acquiring second associated data associated with the slice by a server in the preset area; the first associated data comprise the stuck data of the client, the first network quality data and the load condition, and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server; determining a comprehensive Caton index of the preset area according to the first associated data and the second associated data; and if the comprehensive stuck index is larger than a preset threshold value, discarding the current slicing party corresponding to the video. The method and the device for smoothly playing the client video realize smooth playing of the client video.
Description
Technical Field
The present application relates to the field of communications computer technologies, and in particular, to a video slicing method, apparatus, device, and storage medium.
Background
At present, a server performs slicing and other processing on an original video through a corresponding slicing scheme, and then sends an obtained video slice to a client for playing by the client.
However, in the process of playing the video slice processed by the corresponding slicing scheme, the slicing scheme of the server needs to be adjusted by the katon index, so that the client smoothly plays the video, and the user experience is enhanced.
In the prior art, the pause index is usually obtained only according to the pause times and the playing average frame rate, however, the pause index is only calculated according to the pause times and the playing average frame rate, the data source is single, and the influence of other factors on the pause condition cannot be clearly and accurately reflected.
Disclosure of Invention
The present application mainly aims to provide a video slicing method, apparatus, device and storage medium, and aims to solve the technical problem that in the prior art, it is difficult to accurately adjust a video slicing scheme, so that the video playing at a client is not smooth.
To achieve the above object, the present application provides a video slicing method, including:
acquiring first associated data of a corresponding slice of a video played by a client in a preset area, and acquiring second associated data associated with the slice by a server in the preset area;
the first associated data comprise the stuck data of the client, the first network quality data and the load condition, and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server;
determining a comprehensive Caton index of the preset area according to the first associated data and the second associated data;
if the comprehensive Cartin index is larger than a preset threshold value, discarding the current slicing scheme corresponding to the video, and determining a target slicing scheme so as to complete slicing of the video based on the target slicing scheme.
Optionally, the step of determining the comprehensive katon index of the preset area according to the first associated data and the second associated data includes:
determining a client terminal blockage index of the client terminal according to the first correlation data;
determining a comprehensive evaluation coefficient of the server according to the second associated data;
and determining the comprehensive stuck index of the preset area according to the client stuck index and the comprehensive evaluation coefficient.
Optionally, the step of determining a client stuck index of the client according to the first association data includes:
determining the number of the morton slices reported by the client from the morton data;
determining the number of all clients which are stuck on any stuck slice, the number of times of each client stuck on any stuck slice and the total stuck duration of each client on any stuck slice from the stuck data;
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 equipment performance index of the client on any Kanton slice according to the network type;
calculating a client terminal stuck index according to the stuck slice number, the number of all the clients, the stuck times, the stuck duration, the network transmission index, the network delay index and the hardware equipment performance index;
the step of determining a comprehensive evaluation coefficient of the server according to the second associated data includes:
determining the used bandwidth of the server side from the second network quality data;
and calculating a 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 a 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 valid slicing scheme includes:
determining the average slice size and the average comprehensive Carton index of the video to be sliced from all historical effective slicing schemes;
obtaining the effective slice size and the effective comprehensive Caton 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 stuck index, the effective slicing size of the first effective slicing scheme and the effective comprehensive stuck index of the first effective slicing scheme;
determining whether the first effective slicing scheme is a target slicing scheme based on the first slice size;
determining a target slicing scheme from the historical effective slicing schemes based on the first slice size, the first effective slicing scheme, the current slicing scheme, and a current slice size of the current slicing scheme if the first effective slicing scheme is not the target slicing scheme.
Optionally, the step of determining a 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 comprises:
determining a selection direction of the target slicing scheme based on the first slice size, the first effective slicing scheme, the current slicing scheme, and a current slice size of the current slicing 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 stuck index, the effective slice sizes of the other effective slice schemes, and the effective integrated stuck indexes of the other effective slice schemes;
determining whether the other effective slicing scheme is a target slicing scheme based on the second slice size;
if the other effective slicing schemes are not the target slicing schemes, the step of determining the other effective slicing schemes from the historical effective slicing schemes based on the selection direction is returned in an iteration mode until the target slicing schemes are determined from the historical effective slicing schemes.
Optionally, 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 step of determining the target slicing scheme from the historical effective slicing schemes includes:
if the other effective slicing schemes are not the target slicing scheme and the slice size adjustment variation quantity of the adjacent effective slicing schemes in the time dimension with preset times is smaller than the preset variation quantity, acquiring a preset disturbance value;
and iteratively returning to the step of determining other effective slicing schemes from the historical effective slicing schemes based on the selection direction and the preset disturbance value until a target slicing scheme is determined from the historical effective slicing schemes.
The present application further provides a video slicing apparatus, the video slicing apparatus includes:
the acquisition module is used for acquiring first associated data of a corresponding slice of a video played by a client in a preset area and acquiring second associated data of a server in the preset area and the slice;
the first associated data comprise the stuck data of the client, the first network quality data and the load condition, and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server;
the first determining module is used for determining the comprehensive stuck 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 current slicing scheme corresponding to the video and determining a target slicing scheme if the comprehensive Cartin index is larger than a preset threshold value so as to finish slicing the video based on the target slicing scheme.
The present application further provides a video slicing apparatus, the video slicing apparatus is an entity node apparatus, the video slicing apparatus includes: a memory, a processor and a program of the video slicing method stored on the memory and executable on the processor, which program, when executed by the processor, may implement the steps of the video slicing method as described above.
The present application also provides a storage medium having stored thereon a program for implementing the above-described video slicing method, which when executed by a processor implements the steps of the above-described video slicing method.
The present application also provides a computer program product, comprising a computer program which, when executed by a processor, performs the steps of the video slicing method described above.
Compared with the prior art that the video slicing scheme of the client is difficult to adjust accurately due to the fact that the video slicing scheme of the client is difficult to adjust only to obtain the stuck index through calculation of the stuck times and the playing average frame rate, the comprehensive evaluation stuck index is determined by fusing first associated data of the client and second associated data of the server in a preset area (the first associated data comprises the stuck data of the client, first network quality data and load conditions, the second associated data comprises second network quality data of the server and the number of the clients connected with the server), namely the comprehensive evaluation stuck index is obtained based on more dimensional data of the client and the server, so that whether the slicing scheme of the current video is reasonable or not can be reflected more accurately based on the comprehensive evaluation stuck index, that is, optimization deviation of the subsequent segmentation scheme is not caused by deviation of the stuck index, but instead, the subsequent segmentation scheme can be adjusted in a targeted manner, that is, if the integrated stuck index is greater than a preset threshold, a new target slicing scheme (accurately adjusting the slicing scheme of the video) can be determined accurately in a targeted manner, so that slicing of the video is completed based on the target slicing scheme, and smooth playing of the client video is realized.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present 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 needed to be used in the description of the embodiments or the prior art will be briefly described below, and it is obvious for those skilled in the art to obtain other drawings without inventive exercise.
Fig. 1 is a schematic flow chart of a first embodiment of a video slicing method according to the present application;
fig. 2 is a schematic flowchart of a refinement step of step S20 in the video slicing method of the present application;
FIG. 3 is a schematic diagram of an apparatus configuration of a hardware operating environment according to an embodiment of the present application;
fig. 4 is a schematic diagram of a first scene related to the video slicing method of the present application;
fig. 5 is a schematic diagram of a second scene related to the video slicing method according to the present application.
The implementation of the objectives, functional features, and advantages of the present application will be further described with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of and not restrictive on the broad application.
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 associated data of a corresponding slice of a video played by a client in a preset area, and acquiring second associated data of a server in the preset area associated with the slice;
the first associated data comprise the stuck data of the client, the first network quality data and the load condition, and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server;
step S20, determining a comprehensive Caton index of the preset area according to the first associated data and the second associated data;
and step S30, if the comprehensive Cartin index is larger than a preset threshold value, discarding the current slicing scheme corresponding to the video, and determining a target slicing scheme 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 apparatus, the video slicing apparatus belongs to a video slicing device, the video slicing device belongs to a video slicing system, and the video slicing device belongs to the video slicing system and includes a server side and a client side.
In this embodiment, the application scenario for which the method is applied is as follows:
firstly: in the prior art, the pause index is usually obtained only according to the pause times and the playing average frame rate, however, the pause index is only calculated according to the pause times and the playing average frame rate, the data source is single, and the influence of other factors on the pause condition cannot be clearly and accurately reflected.
In the application, the comprehensive evaluation stuck index is obtained based on data of more dimensions of the client and the server, so that whether the slicing scheme of the current video is reasonable or not can be reflected more accurately based on the comprehensive evaluation stuck index, that is, optimization deviation caused by the deviation of the stuck index cannot be caused in optimization of a subsequent slicing scheme, and instead, the comprehensive evaluation stuck index can be adjusted in a targeted manner, that is, if the comprehensive stuck index is greater than a preset threshold, a new target slicing scheme (the slicing scheme of the video is adjusted accurately) can be determined accurately 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.
Secondly, the method comprises the following steps: in the prior art, a fixed and single slicing scheme is generally applied to different areas and different video playing scenes, so that the playing in different areas and/or different playing scenes is blocked.
In the method, areas served by slicing are taken as units, and respective optimal target slicing schemes are provided for different areas according to analysis of respective comprehensive Cartin indexes of different preset areas, so that customization of slicing scheme area levels is realized.
Thirdly, the steps of: in the prior art, different external conditions such as personnel flow in a preset area, network technology equipment upgrading and the like are changed, and the change is difficult to be reflected on a slicing scheme, so that the problem of playing card pause exists.
According to the method and the device, different external condition changes such as personnel flow and network technical equipment upgrading in the preset area can be timely and accurately fed back to the first associated data and the second associated data, and therefore 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 users.
Fourthly: in the prior art, the slicing scheme can only be adjusted through mechanical, long offline and online tests according to past experience and technology of related personnel (which are easy to change).
According to the method and the device, the target slicing scheme is generated by comprehensively calculating the historical effective slicing scheme in the preset area, 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 corresponding slice size of the adjacent slicing scheme is smaller than the corresponding value).
In the application, the slice scheme is prevented from falling into local optimum by introducing the disturbance factor, so that the smoothness of user playing is improved by global optimum.
The method comprises the following specific steps:
step S10, acquiring first associated data of a corresponding slice of a video played by a client in a preset area, and acquiring second associated data of a server in the preset area associated with the slice;
the first associated data comprise the stuck data of the client, the first network quality data and the load condition, and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server;
in this embodiment, it should be noted that the preset area may be a city or an urban area in the city, and the preset area may also correspond to a base station, that is, the jurisdiction of a certain base station is a preset area.
The method for acquiring first associated data of a corresponding slice of a video played by a client in a preset area comprises the following steps:
acquiring first associated data of a corresponding slice of a video played by a client in a preset area in real time;
or acquiring first associated data of a corresponding slice of a video played by a client in a preset area at preset time intervals.
Or when detecting that the first associated data of the corresponding slice of the video played by the client in the preset area changes, acquiring the first associated data of the corresponding slice of the video played by the client in the preset area.
As an example, the first association data comprises a stuck data of the client, a first network quality data and a load condition.
As an example, the morton data of the client includes morton data of each client (in a unit time period), which includes morton times, morton time, a slice position corresponding to a playing slice when the morton occurs, and the like, the first network quality data of the client is a network quality condition, which includes 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, and an excessive value are removed from the first associated data.
In this embodiment, second associated data associated with the slice at the server end in the preset area is also obtained.
The obtaining of second associated data associated with the slice by the server side in the preset area comprises:
acquiring second associated data of the server end in the preset area and the slice in real time;
or acquiring second associated data associated with the slice by the server end in the preset area at preset time intervals.
Or when detecting that the first associated data of the corresponding slice of the video played by the client in the preset area changes, acquiring second associated data associated with the slice by the server in the preset area.
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 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, and an excessive value are removed from the second associated data.
Step S20, determining a comprehensive Caton 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 katon index of the preset area is obtained.
The method for obtaining the comprehensive Cartesian index of the preset area comprises the following steps:
the first method is as follows: converting the first associated data and the second associated data into feature vectors, inputting the feature vectors into a preset index determination model, and determining a comprehensive stuck 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.
The second method comprises the following steps: and substituting the first correlation data and the second correlation data into a calculation formula of a preset comprehensive stuck index, and determining the comprehensive stuck index of the preset area based on the calculation formula of the preset comprehensive stuck index.
In a third mode, the step of determining the comprehensive katon index of the preset area according to the first associated data and the second associated data includes:
step S21, determining the client terminal blockage index of the client terminal according to the first correlation data;
in this embodiment, the client stuck exponent of the client is determined according to the first correlation data and a client stuck exponent model.
Wherein the step of determining the client stuck index of the client according to the first correlation data comprises:
step A1, determining the number of chudune slices reported by the client from the chudune data;
step A2, determining the number of all clients stuck on any stuck slice, the number of times of each client stuck on any stuck slice and the total stuck duration of each client on any stuck slice from the stuck data;
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 equipment performance index of the client on any one Kanton slice according to the network type;
step A4, calculating a client pause index according to the pause slice number, the number of all clients, the pause times, the pause time, the network transmission index, the network delay index and the hardware equipment performance index;
specifically, the calculation formula of the client 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 (all clients) reporting stuck in the mth slice (any stuck slice), λ i For each person's stuck number on that slice (the number of stuck times on any one stuck slice by each client), t i For the total length of time each person is stuck on slice i (the total length of time each client is stuck on any one stuck slice), δ i ＝|b i ||d i ||h i |，δ i ∈(0,1]And | 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 combining 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 (default to 1, which is different according to the performance of the device used by the user) on the slice i.
In a specific implementation, according to a network type of a client, determining a network transmission index, a network delay index, and a hardware device performance index of the client on any morton slice, where the network transmission index, the network delay index, and the hardware device performance index are as follows: 3G, 4G, WIFI, etc., network transmission and delay thresholds, etc. may be adjusted.
Step S22, determining a comprehensive evaluation coefficient of the server according to the second associated data;
in this embodiment, a comprehensive evaluation coefficient η of the server is determined according to the second correlation data.
Specifically, the step of determining a comprehensive evaluation coefficient of the server according to the second associated data includes:
step B1, determining the used bandwidth of 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 the present embodiment, η ∈ (0, 1)]The comprehensive evaluation coefficient is generated by comprehensive calculation of threshold connection number/client connection number, threshold bandwidth/use bandwidth, CPU utilization rate and the like, and each value is (0, 1)]And | a | represents that the value is 1 when the value of a2 is more than 1 (wherein a2 represents that in the above formula
)。
And step S23, determining the comprehensive stuck index of the preset area according to the client stuck index and the comprehensive evaluation coefficient.
In this embodiment, the comprehensive calton index calculation formula is as follows:
g ═ η C 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, if the comprehensive Cartin index is larger than a preset threshold value, discarding the current slicing scheme corresponding to the video, and determining a target slicing scheme 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 current slicing scheme corresponding to the video, and determining a target slicing scheme based on the current slicing scheme or a 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 of the client is difficult to adjust accurately due to the fact that the video slicing scheme of the client is difficult to adjust only to obtain the stuck index through calculation of the stuck times and the playing average frame rate, the comprehensive evaluation stuck index is determined by fusing first associated data of the client and second associated data of the server in a preset area (the first associated data comprises the stuck data of the client, first network quality data and load conditions, the second associated data comprises second network quality data of the server and the number of the clients connected with the server), namely the comprehensive evaluation stuck index is obtained based on more dimensional data of the client and the server, so that whether the slicing scheme of the current video is reasonable or not can be reflected more accurately based on the comprehensive evaluation stuck index, that is, optimization deviation of the subsequent segmentation scheme is not caused by deviation of the stuck index, but instead, the subsequent segmentation scheme can be adjusted in a targeted manner, that is, if the integrated stuck index is greater than a preset threshold, a new target slicing scheme (accurately adjusting the slicing scheme of the video) can be determined accurately in a targeted manner, so that slicing of the video is completed based on the target slicing scheme, and smooth playing of the client video is realized.
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, obtaining 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 region, so as to improve the accuracy of generating the target slicing scheme, improve the optimization rate of the slicing scheme, that is, the size of a new slice, and generate the target slicing scheme by comprehensively calculating the previous N times effective slicing schemes (the historical effective slicing schemes) in the current region (in the preset region).
The step of generating the target slicing scheme according to the historical valid slicing scheme comprises:
step S321, determining the average slice size and average comprehensive Katon index of the video to be sliced from all historical effective slicing schemes;
step S322, obtaining the effective slice size and the effective comprehensive stuck 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 slicing size based on the average slicing size, the average comprehensive stuck index, the effective slicing size of the first effective slicing scheme and the effective comprehensive stuck 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;
step S325, 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 slice size, the first effective slicing scheme, the current slicing scheme, and the current slicing size of the current slicing scheme.
It should be noted that a plurality of slicing schemes may also be stored in the preset area, and the slicing schemes are actively changed when the user frequently reports the katton, but in this embodiment, the same resolution of all users in the preset area is the default to use the same slice.
Specifically, the determination formula of the target slicing scheme is as follows:
specifically, as in equation (4) above, the average slice size for slicing the video is determined from all of the historically valid slicing schemes
And average integrated Caton index
For example,
the average slice size and average integrated calton index for the N slicing schemes, respectively.
As in equation (4) above, the effective slice size and effective composite Carton index for each historical effective slice scheme is obtained, specifically S t ，G t The effective slice size and the effective integrated carron index for each historical effective slice scheme, respectively.
As in equation (4) above, T is the number of available slicing schemes (T is proposed to be 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 slicing size based on the average slicing size, the average comprehensive stuck index, the effective slicing size of the first effective slicing scheme, and the effective comprehensive stuck index of the first effective slicing scheme, wherein S is the slicing size to be calculated (the slicing size to be calculated at this time may be the first slicing size or other slicing sizes), and S is the slice size to be calculated l It is possible to calculate the last slice size for the current calculation region (within the preset region), and then calculate whether S meets the requirement based on the last slice size for the current calculation region (within the preset region), and if S does not meet the requirement (when S is the first slice size, the first effective slice scheme is not the target slice scheme), determine the target slice scheme 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. If S meets the requirement, the history is judged to be correctAnd determining the first effective slicing scheme as the target slicing scheme in the effective slicing schemes.
In this embodiment, whether S meets the requirement is determined according to whether the integrated stuck index corresponding to S is greater than a preset threshold.
The step of determining a 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 a current slicing size of the current slicing 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, based on the selection direction, determining other effective slicing schemes from the historical effective slicing schemes;
step C3, obtaining a second slice size based on the average slice size, the average integrated Cartin index, the effective slice sizes of the other effective slice schemes, and the effective integrated Cartin indices of the other effective slice schemes;
a step C4 of determining whether the other effective slicing scheme is a target slicing scheme based on the second slice size;
and step C5, if the other effective slicing scheme is not the target slicing scheme, iteratively returning to the step of determining other effective slicing schemes 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 effective 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 stuck index determined by the current slice size and the first integrated stuck 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 in a reverse direction from the historical effective slicing schemes, for example, if the current integrated katon index is 12 schemes, if the first integrated katon index is 13 schemes, determining the other effective slicing schemes in a direction from 12 to 1, if the first integrated katon index is less than the current integrated katon index, determining other effective slicing schemes in a forward direction from the historical effective slicing schemes, for example, if the current integrated katon index is 12 schemes, and if the first integrated katon index is 13 schemes, determining the other effective slicing schemes in a direction from 13 to T, for example, 20.
And obtaining a second slice size based on the average slice size, the average comprehensive stuck index, the effective slice sizes of the other effective slice schemes and the effective comprehensive stuck indexes of the other effective slice schemes, determining whether the other effective slice schemes are target slice schemes or not based on the second slice size, if the other effective slice schemes are not the target slice schemes, iteratively returning to the step of determining 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 this embodiment, the target slice scheme is selected in order, and the efficiency is improved.
Further, based on the foregoing embodiment of the present application, another embodiment of the present application is provided, where if the other effective slicing scheme is not the target slicing scheme, the step of 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 step of determining the target slicing scheme from the historical effective slicing schemes includes:
step D1, if the other effective slicing schemes are not the target slicing scheme and the slice size adjustment variation of the adjacent effective slicing schemes in the time dimension with the preset times is smaller than the preset variation, 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 selection direction and the preset disturbance value until a target slicing scheme is determined from the historical effective slicing schemes.
In the present embodiment, it is preferred that,
in the present embodiment, formula (5) differs from formula (4) in that σ is added, specifically, σ is a random disturbance value, and σ ∈ [ -0.25S l ，0.25S l ]And preventing the local optimal solution from being trapped, when the slice size adjustment variation of the continuous M (value suggestion 3 to 8) times of adjacent slice schemes is smaller than delta S, namely: | St-St-1<Δ S, the σ increment is increased.
In this embodiment, in the application, a disturbance factor is introduced to avoid that the slicing scheme falls into local optimum, so that global optimum is achieved to improve the fluency of user playing.
Referring to fig. 3, fig. 3 is a schematic device structure diagram of a hardware operating 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, a memory 1005, and a communication bus 1002. The communication bus 1002 is used for realizing connection communication between the processor 1001 and the memory 1005. The memory 1005 may be a high-speed RAM memory or a non-volatile memory (e.g., a magnetic disk memory). The memory 1005 may alternatively be a memory device separate from the processor 1001 described above.
Optionally, the video slicing apparatus may further include a rectangular user interface, a network interface, a camera, RF (Radio Frequency) circuitry, a sensor, audio circuitry, a WiFi module, and the like. The rectangular user interface may comprise a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional rectangular user interface may also comprise 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).
Those skilled in the art will appreciate that the video slicing apparatus configuration shown in fig. 3 does not constitute a limitation of the video slicing apparatus, and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
As shown in fig. 3, a memory 1005, which is a storage medium, may include therein 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 apparatus, supporting the operation of the video slicing program as well as other software and/or programs. The network communication module is used to enable communication between components within the memory 1005, as well as with other hardware and software in the video slicing system.
In the video slicing apparatus shown in fig. 3, the processor 1001 is configured to execute a video slicing program stored in the memory 1005 to implement the steps of the video slicing method described in any one of the above.
The specific implementation of the video slicing apparatus of the present application is substantially the same as that of the embodiments of the video slicing method described above, and is not described herein again.
The present application further provides a video slicing apparatus, the video slicing apparatus includes:
the acquisition module is used for acquiring first associated data of a corresponding slice of a video played by a client in a preset area and acquiring second associated data of a server in the preset area and the slice;
the first associated data comprise the stuck data of the client, the first network quality data and the load condition, and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server;
the first determining module is used for determining the comprehensive stuck 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 current slicing scheme corresponding to the video and determining a target slicing scheme if the comprehensive Cartin 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:
a first determining unit, configured to determine a client stuck index of the client according to the first association data;
the second determining unit is used for determining a comprehensive evaluation coefficient of the server according to the second associated data;
and the third determining unit is used for determining the comprehensive stuck index of the preset area according to the client stuck index and the comprehensive evaluation coefficient.
Optionally, the first determining unit includes:
the first determining subunit is used for determining the number of the morton slices reported by the client from the morton data;
the second determining subunit is used for determining the number of all clients which are stuck on any one stuck slice from the stuck data, and determining the number of times of each client stuck on any one stuck slice and the total stuck duration of each client on any one stuck slice;
a third determining subunit, configured to determine a network type of the client from the first network quality data and the load condition, and determine, according to the network type, a network transmission index, a network delay index, and a hardware device performance index of the client on any one of the morton slices;
the first calculating subunit is used for calculating a client terminal stuck index according to the stuck slice number, the number of all the clients, the stuck times, the stuck duration, the network transmission index, the network delay index and the hardware equipment performance index;
a fourth determining subunit, configured to determine, according to the second associated data, a comprehensive evaluation coefficient of the server, where the step includes:
a fifth determining subunit, configured to determine, from the second network quality data, a used bandwidth of the server;
and the second calculating subunit is used for calculating a 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:
the acquisition unit is used for acquiring 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, from all the historical valid slicing schemes, an average slice size and an average integrated katon index for slicing the video;
the first obtaining subunit is used for obtaining the effective slice size and the effective comprehensive Cartin index of each historical effective slice scheme;
a second obtaining subunit, 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 comprehensive stuck index, the effective slice size of the first effective slicing scheme, and the effective comprehensive stuck index of the first effective slicing scheme;
a seventh determining subunit, configured to determine whether the first effective slicing scheme is a target slicing scheme based on the first slice size;
an eighth determining subunit, configured to determine, if the first effective slicing scheme is not the target slicing scheme, the target slicing scheme from the historical effective slicing schemes based on the first slice size, the first effective slicing scheme, the current slicing scheme, and a current slice size of the current slicing scheme.
Optionally, the eighth determining subunit is configured to implement:
determining a selection direction of the target slicing scheme based on the first slice size, the first effective slicing scheme, the current slicing scheme, and a current slice size of the current slicing 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 stuck index, the effective slice sizes of the other effective slice schemes, and the effective integrated stuck indexes of the other effective slice schemes;
determining whether the other effective slicing scheme is a target slicing scheme based on the second slice size;
if the other effective slicing schemes are not the target slicing schemes, the step of determining the other effective slicing schemes from the historical effective slicing schemes based on the selection direction is returned in an iteration mode until the target slicing schemes are determined from the historical effective slicing schemes.
Optionally, the eighth determining subunit is configured to implement:
if the other effective slicing schemes are not the target slicing scheme and the slice size adjustment variation quantity of the adjacent effective slicing schemes in the time dimension with preset times is smaller than the preset variation quantity, acquiring a preset disturbance value;
and iteratively returning to the step of determining other effective slicing schemes from the historical effective slicing schemes based on the selection direction and the preset disturbance value until a target slicing scheme is determined from the historical effective slicing schemes.
The specific implementation of the video slicing apparatus of the present application is substantially the same as the embodiments of the video slicing method, and is not described herein again.
The present application provides a storage medium, and the storage medium stores one or more programs, which are also executable by one or more processors for implementing the steps of the video slicing method described in any one of the above.
The specific implementation of the storage medium of the present application is substantially the same as that of the embodiments of the video slicing method, and is not described herein again.
The present application also provides a computer program product, comprising a computer program which, when executed by a processor, performs the steps of the video slicing method described above.
The specific implementation of the computer program product of the present application is substantially the same as the embodiments of the video slicing method described above, and is not described herein again.
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 an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A video slicing method, the video slicing method comprising:
acquiring first associated data of a corresponding slice of a video played by a client in a preset area, and acquiring second associated data associated with the slice by a server in the preset area;
the first associated data comprise the stuck data of the client, the first network quality data and the load condition, and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server;
determining a comprehensive Caton index of the preset area according to the first associated data and the second associated data;
if the comprehensive Cartin index is larger than a preset threshold value, discarding the current slicing scheme corresponding to the video, and determining a target slicing scheme so as to complete slicing of the video based on the target slicing scheme.
2. The video slicing method of claim 1, wherein said step of determining a combined katon index of said preset region based on said first associated data and said second associated data comprises:
determining a client terminal blockage index of the client terminal according to the first correlation data;
determining a comprehensive evaluation coefficient of the server according to the second correlation data;
and determining the comprehensive stuck index of the preset area according to the client stuck index and the comprehensive evaluation coefficient.
3. The video slicing method of claim 2, wherein said step of determining a client stuck index of said client based on said first association data comprises:
determining the number of the morton slices reported by the client from the morton data;
determining the number of all clients which are stuck on any stuck slice, the number of times of each client stuck on any stuck slice and the total stuck duration of each client on any stuck slice from the stuck data;
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 equipment performance index of the client on any Kanton slice according to the network type;
calculating a client terminal stuck index according to the stuck slice number, the number of all the clients, the stuck times, the stuck duration, 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 correlation data includes:
determining the used bandwidth of the server side from the second network quality data;
and calculating a 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 step of determining a target slicing scheme comprises:
acquiring a historical effective slicing scheme of the preset area;
and generating the target slicing scheme according to the historical effective slicing scheme.
5. The video slicing method of claim 4, wherein said step of generating said target slicing scheme based on said historically valid slicing scheme comprises:
determining the average slice size and the average comprehensive Carton index of the video to be sliced from all historical effective slicing schemes;
obtaining the effective slice size and the effective comprehensive Caton 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 stuck index, the effective slicing size of the first effective slicing scheme and the effective comprehensive stuck index of the first effective slicing scheme;
determining whether the first effective slicing scheme is a target slicing scheme based on the first slice size;
determining a target slicing scheme from the historical effective slicing schemes based on the first slice size, the first effective slicing scheme, the current slicing scheme, and a current slice size of the current slicing scheme if the first effective slicing scheme is not the target slicing scheme.
6. The video slicing method of claim 5, wherein said step of determining a target slicing scheme from said historical active slicing schemes based on said first slicing size, said first active slicing scheme, said current slicing scheme, and a current slicing size of said current slicing scheme comprises:
determining a selection direction of the target slicing scheme based on the first slice size, the first effective slicing scheme, the current slicing scheme, and a current slice size of the current slicing 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 Cartesian index, the effective slice sizes of the other effective slice schemes, and the effective integrated Cartesian indices of the other effective slice schemes;
determining whether the other effective slicing scheme is a target slicing scheme based on the second slice size;
if the other effective slicing schemes are not the target slicing schemes, the step of determining the other effective slicing schemes from the historical effective slicing schemes based on the selection direction is returned in an iteration mode until the target slicing schemes are determined from the historical effective slicing schemes.
7. The method of video slicing of claim 5 wherein if said other available slicing scheme is not the target slicing scheme, iteratively returning to the step of determining other available slicing schemes from said historical available slicing schemes based on said pick direction until the step of determining the target slicing scheme from said historical available slicing schemes comprises:
if the other effective slicing schemes are not the target slicing scheme and the slice size adjustment variation quantity of the adjacent effective slicing schemes in the time dimension with preset times is smaller than the preset variation quantity, acquiring a preset disturbance value;
and iteratively returning to the step of determining other effective slicing schemes from the historical effective slicing schemes based on the selection direction and the preset disturbance value until a target slicing scheme is determined from the historical effective slicing schemes.
8. A video slicing apparatus, the video slicing apparatus comprising:
the acquisition module is used for acquiring first associated data of a corresponding slice of a video played by a client in a preset area and acquiring second associated data associated with the slice by a server in the preset area;
the first associated data comprise the stuck data of the client, the first network quality data and the load condition, and the second associated data comprise the second network quality data of the server and the number of the clients connected with the server;
the first determining module is used for determining the comprehensive stuck 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 current slicing scheme corresponding to the video and determining a target slicing scheme if the comprehensive Cartin index is larger than a preset threshold value so as to finish slicing the video based on the target slicing scheme.
9. A video slicing apparatus, characterized in that the video slicing apparatus comprises: 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 7.
10. 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 as claimed in any one of claims 1 to 7.
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