CN111225387B - Mobile network analysis method, system, device and medium based on video playing - Google Patents
Mobile network analysis method, system, device and medium based on video playing Download PDFInfo
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/14—Network analysis or design
- H04L41/142—Network analysis or design using statistical or mathematical methods
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
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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
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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
Abstract
The invention discloses a mobile network analysis method, a system, equipment and a medium based on video playing, wherein the method comprises the following steps: acquiring a network video source address and basic information of a network video source corresponding to the network video source address; starting a video player, transmitting a network video source address into the video player, and starting playing; in the playing process of the network video, collecting an initial buffer state, a playing state and a pause state every other preset time until the set playing time is over, and stopping collecting; and calculating the score of the network video according to the basic information, the initial buffering state, the playing state and the blocking state of the network video source, thereby obtaining the analysis result of the mobile network. Compared with the existing network quality analysis which detects the data packet and the packet loss rate of a transmission layer and a network layer, the invention realizes the analysis of the playing quality of the network video by using an application layer detection mode of playing the network video, and directly evaluates the mobile network quality from the experience effect of a user.
Description
Technical Field
The invention relates to a mobile network analysis method, a system, equipment and a medium based on video playing, belonging to the field of multimedia network communication.
Background
With the popularization of 4G and the arrival of 5G networks, video services are one of important services of broadband networks, video often has large data volume and high requirements on network quality, and in order to provide better network services for customers, monitoring and optimization of network quality by various large network operators are in development.
An operator needs to evaluate network services, and in the existing scheme, packet loss rate is detected by analyzing a comparison bottom layer in a computer network, such as monitoring a data packet of an ip layer.
Disclosure of Invention
In view of this, the present invention provides a mobile network analysis method, system, mobile device and storage medium based on video playing, which, compared with the existing network quality analysis that detects the data packet and packet loss rate of the transport layer and network layer, uses the application layer detection mode of playing network video to analyze the playing quality of network video and directly evaluate the mobile network quality from the experience effect of the user.
The invention aims to provide a mobile network analysis method based on video playing.
The second purpose of the invention is to provide a mobile network analysis system based on video playing.
A third object of the present invention is to provide a mobile device.
It is a fourth object of the present invention to provide a storage medium.
The first purpose of the invention can be achieved by adopting the following technical scheme:
a mobile network analysis method based on video playing, the method comprising:
acquiring a network video source address and basic information of a network video source corresponding to the network video source address;
responding to a playing instruction of a user, starting a video player, transmitting a network video source address into the video player, and starting playing;
in the playing process of the network video, collecting an initial buffer state, a playing state and a pause state every other preset time until the set playing time is over, and stopping collecting;
and calculating the score of the network video according to the basic information, the initial buffering state, the playing state and the blocking state of the network video source, thereby obtaining the analysis result of the mobile network.
Further, the basic information of the network video source includes a video size and a video duration;
calculating the score of the network video according to the basic information, the initial buffering state, the playing state and the pause state of the network video source, as follows:
wherein R represents the final score; rate represents the bitrate, i.e. the video size × 8/video duration, and f (rate) represents the bitrate score; fb denotes an initial buffer time length, f (fb) denotes an initial buffer time length score; sf represents the katton frequency, and f (sf) represents the katton frequency score; sr represents the katon time length-to-occupation ratio, namely the katon state total time length/(the play state total time length + the katon state total time length), and f (sr) represents the katon time length-to-occupation ratio score; q1, q2 and q3 represent index weights.
Further, the code rate score is calculated as follows:
wherein i represents a grading number; s [ i ] represents the lowest score in the grading number i; max represents the maximum value of the code rate interval under the grading number i, and min represents the minimum value of the code rate interval under the grading number i;
when the code rate interval is [7000, + ∞), "1" is the number of the gear stage, and 10 is the lowest score;
when the code rate interval is [4000,7000), the minimum value is 4000, the maximum value can be a value close to 7000, the grading number is 2, and the lowest score is 9.5;
when the code rate interval is [2000,4000), the minimum value is 2000, the maximum value can be a value close to 4000, the grading number is 3, and the lowest score is 9;
when the code rate interval is [1000,2000), the minimum value is 1000, the maximum value can be a value close to 2000, the grading number is 4, and the lowest score is 8;
when the code rate interval is [500, 1000), the minimum value is 500, the maximum value can be a value close to 1000, the grading number is 5, and the lowest score is 7;
when the code rate interval is [100, 500), the minimum value is 100, the maximum value can be a value close to 500, the grading number is 6, and the lowest score is 6;
when the code rate interval is [0, 100), the minimum value is 0, the maximum value can be a value close to 100, the grading number is 7, and the lowest score is 4.
Further, the initial buffer duration score is calculated as follows:
wherein i represents a grading number; s [ i ] represents the highest score in the grading number i; max represents the maximum value of the initial buffering duration interval under the grading number i, and min represents the minimum value of the initial buffering duration interval under the grading number i;
when the initial buffering duration interval is [0, 100), the minimum value is 0, the maximum value can be a value close to 100, the grading number is 1, and the highest score is 10;
when the initial buffering duration interval is [100, 1000), the minimum value is 100, the maximum value can be a value close to 1000, the grading number is 2, and the highest score is 8;
when the initial buffering duration interval is [1000, 3000), the minimum value is 1000, the maximum value can be a value close to 3000, the grading number is 3, and the highest score is 6;
when the initial buffer duration interval is [3000,6000), the minimum value is 3000, the maximum value can be a value close to 6000, the grading number is 4, and the highest score is 4;
when the initial buffer duration interval is [6000,10000), the minimum value is 6000, the maximum value can be a value close to 10000, the grading number is 5, and the highest score is 2;
when the initial buffer duration interval is [10000,100000), the minimum value is 10000, the maximum value can be a value close to 100000, the grading number is 6, and the highest score is 1;
when the initial buffering time interval is greater than 100000, the grade number is 7, and the highest score is 0.
Further, the calton frequency score is calculated as follows:
wherein i represents a grading number; s [ i ] represents the highest score in the grading number i; max represents the maximum value of the stuck frequency interval under the grading number i, and min represents the minimum value of the stuck frequency interval under the grading number i;
when the Katon frequency interval is (0,0), the minimum value and the maximum value are both 0, the grading number is 1, and the highest score is 10;
when the Katon frequency interval is (0,4), the minimum value can be a value close to 0, the maximum value is 4, the grading number is 2, and the highest score is 8;
when the karton frequency is (4,8), the minimum value can be a value close to 4, the maximum value is 8, the grading number is 3, and the highest score is 6;
when the calorie-on frequency is (8,12), the minimum value can be a value close to 8, the maximum value is 12, the grading number is 4, and the highest score is 4;
when the karton frequency interval is (12,16), the minimum value can be a value close to 12, the maximum value is 16, the grading number is 5, and the highest score is 2;
when the Katon frequency interval is (16,20), the minimum value can be a value close to 16, the maximum value is 20, the grading number is 6, and the highest score is 1;
and when the pause frequency is more than 20, the grading number is 7, and the highest score is 0.
Further, the katton time length to occupation score is calculated as follows:
wherein i represents a grading number; s [ i ] represents the highest score in the grading number i; max represents the maximum value of the length-to-ratio interval under the gear number i, and min represents the minimum value of the length-to-ratio interval under the gear number i;
when the pause time length ratio interval is (0.0%, 0.0% >), the minimum value and the maximum value are both 0.0%, the step number is 1, and the highest score is 10;
when the pause time length occupation interval is (0.0%, 5.0% >), the minimum value can be a value close to 0.0%, the maximum value is 5.0%, the step number is 2, and the highest score is 8;
when the karton time length ratio interval is (5.0%, 10.0% >), the minimum value can be a value close to 5.0%, the maximum value is 10.0%, the grade number is 3, and the highest score is 6;
when the karton time length ratio interval is (10.0%, 20.0%), the minimum value can be a value close to 10.0%, the maximum value is 20.0%, the step number is 4, and the highest score is 4;
when the karton time length ratio interval is (20.0%, 30.0%), the minimum value can be a value close to 20.0%, the maximum value is 30.0%, the grade number is 5, and the highest score is 2;
when the karton time length ratio interval is (30.0%, 40.0%), the minimum value can be a value close to 30.0%, the maximum value is 40.0%, the step number is 6, and the highest score is 1;
when the length of the Ka dun hour is more than 40%, the number of the grades is 7, and the highest score is 0.
Further, the acquiring a network video source address specifically includes:
acquiring a video source address provided by a video provider server;
or the video source address is obtained through a third-party network interface.
The second purpose of the invention can be achieved by adopting the following technical scheme:
a mobile network analysis system based on video playback, the system comprising:
the acquisition module is used for acquiring the address of the network video source and the basic information of the network video source corresponding to the network video source address;
the playing module is used for responding to a playing instruction of a user, starting the video player, transmitting a network video source address into the video player and starting playing;
the collecting module is used for collecting the initial buffer state, the playing state and the pause state every other preset time in the playing process of the network video until the set playing time is over and stopping the collection;
and the calculating module is used for calculating the score of the network video according to the basic information, the initial buffering state, the playing state and the blocking state of the network video source so as to obtain the analysis result of the mobile network.
The third purpose of the invention can be achieved by adopting the following technical scheme:
a mobile device comprises a processor and a memory for storing a program executable by the processor, wherein the processor executes the program stored in the memory to realize the mobile network analysis method.
The fourth purpose of the invention can be achieved by adopting the following technical scheme:
a storage medium stores a program which, when executed by a processor, implements the mobile network analysis method described above.
Compared with the prior art, the invention has the following beneficial effects:
the invention can support the domestic mainstream video website address, support the video types of various video packaging formats and encoding formats, transmit the network video source address into the video player, begin to broadcast, in the course of broadcasting the network video, collect initial buffer state, broadcast state and stuck state every other preset time, until the end of set broadcast time, stop collecting, according to the basic information, initial buffer state, broadcast state and stuck state of the network video source, calculate the score of the network video, the score can reflect the video quality, because in the data transmission of the mobile network, the video data amount accounts for a large percentage, the requirement for network quality is high, so can assess the mobile network quality through the video quality; in addition, the invention can be integrated on the mobile device, can be independently made into APP, and can also be made into the auxiliary function of the APP, thereby being convenient for the user to test.
Drawings
In order to more clearly illustrate the embodiments or technical solutions of the present invention, the drawings used in the embodiments or technical solutions of the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the structures shown in the drawings without creative efforts.
Fig. 1 is a flowchart of a mobile network analysis method based on video playing according to embodiment 1 of the present invention.
Fig. 2 is a schematic block diagram of calculating a network video score according to embodiment 1 of the present invention.
Fig. 3 is a block diagram of a mobile network analysis system based on video playing in embodiment 2 of the present invention.
Fig. 4 is a block diagram of a mobile device according to embodiment 3 of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some embodiments of the present invention, but not all embodiments, and all other embodiments obtained by a person of ordinary skill in the art without creative efforts based on the embodiments of the present invention belong to the protection scope of the present invention.
Example 1:
as shown in fig. 1, the embodiment provides a mobile network analysis method based on video playing, which is integrated in a mobile device such as a mobile phone and a tablet computer, and includes the following steps:
s101, acquiring a network video source address and basic information of a network video source corresponding to the network video source address.
The network video source address is the network video source address which can be directly accessed and played by using a video player, and the network video source address can be obtained in two ways, namely, the network video source address is cooperated with a video provider of a domestic mainstream video website, the number of servers of the video provider is large, the bandwidth for downloading and playing the streaming media is sufficient, a plurality of network video sources are rented for testing, so that the network video source address is obtained, and a free video source address is obtained through a third-party network interface; the basic information of the network video source comprises video size, video duration, video resolution and the like.
S102, responding to a playing instruction of a user, starting a video player, transmitting a network video source address into the video player, and starting playing.
The video player is a basic player framework used when the mobile device develops an application program, and is a basis for various video playing applications, the mainstream basic player framework of the current mobile device has the functions of downloading video data, decoding, analyzing a video coding format, calculating a code rate, monitoring the data quantity change of a buffer area, monitoring playing, blocking states and the like, the video player adopted in the embodiment is an embedded video player VLC, the VLC is an open-source free multimedia player, the supported audio and video formats are various, the functions are strong, and the video player is commonly used for learning and research in the aspect of video playing.
In this step, after connecting the mobile network, the user starts the video player, and transmits the network video source address to the video player to start playing.
S103, in the playing process of the network video, collecting the initial buffer state, the playing state and the pause state every other preset time until the set playing time is over, and stopping collecting.
The playback time set in this embodiment is 60 seconds, and the preset time is 0.1 second, which are states at time points, and four states are defined: the playing method comprises an initial buffering state, a playing state, a stuck state and a stopping state, wherein if 0.1 second is in the playing state, 0.2 second is in the stuck state, and 0.4 second is in the playing state, 0.1-0.2 are all determined to be playing time intervals, 0.2-0.4 are all determined to be stuck time intervals, due to the fact that an extremely short collection interval of 0.1 second is selected, the playing time set in each test is 60 seconds, and the influence of errors existing in the processing mode on results can be ignored.
And S104, calculating the score of the network video according to the basic information, the initial buffering state, the playing state and the blocking state of the network video source, thereby obtaining the analysis result of the mobile network.
Considering that the complete test takes 60 seconds, since there are many samples, the embodiment only uses 5 seconds to describe the calculation of the network video score, and a part of the data collected during the playing process is shown below: the line showing the numbers represents the collection time point, the following b, p, s represent the state of the time point, b represents the initial buffer state, p represents the playing state, s represents the stuck state, the first number 0 in the first line represents the time point when the player clicks on, and then the playing state is acquired every 0.1 seconds.
TABLE 1 State collected during Play
It can be seen from the above data that 0-0.5 second is in the initial buffer state, 0.5-2.7 seconds is in the play state, 2.7-3.1 seconds is in the stuck state, 3.1-4.2 seconds is in the play state, 4.2-4.4 seconds is in the stuck state, and 4.4-5.0 seconds is in the play state; the statistics is as follows: buffering time delay for the first time: 0.5s, total duration of play state: 3.9s, total duration of stuck state: 0.6s, stuck times: 2 times.
Calculating the score of the network video according to the following formula:
wherein R represents the final score; rate represents the bitrate, i.e. the video size × 8/video duration, with the unit of kbps, and f (rate) represents the bitrate score; fb denotes an initial buffer duration in ms, and f (fb) denotes an initial buffer duration score; sf represents the katton frequency, in this embodiment, the katton frequency per minute, namely, the katton frequency/minute, and f (sf) represents the katton frequency score; sr represents the card pause time length ratio, namely the card pause state total time length/(the play state total time length + the card pause state total time length), and f (sr) represents the card pause time length ratio score; q1, q2 and q3 represent index weights, q1=2, q2=2, q3=1.
The code rate (definition), the initial buffering time, the pause frequency and the pause time of the video are important factors influencing the watching of a user, and the video playing quality can be calculated by quantizing the code rate, the initial buffering time, the pause frequency and the pause time of the video, as shown in fig. 2; wherein the initial buffering duration refers to the time from the time when the video player is clicked to play to the video picture presentation. This period of time includes the following process: the video player network requests the video server, the video server transmits video data to the video player, the video player decodes the data, the decoded data is placed into a buffer area, and when the buffer area reaches the data volume capable of being played, a video picture begins to appear.
After the values of the code rate, the initial buffering time length, the pause frequency and the pause time length ratio are calculated, grading and scoring are carried out according to the interval where the values are located, and grading and scoring rules are carried out according to parameters of the code rate, the initial buffering time length, the pause frequency and the pause time length ratio (two decimal numbers are reserved in the result):
1) The code rate (rate) scoring rule is shown in table 2 below, and a linear fit is required within the stage according to the following equation (1).
TABLE 2 code Rate Scoring rules
| Step number | Video resolution | Graded lowest score | Code rate interval (min, max) |
| 1 | >2K | 10.00 | [7000,+∞) |
| 2 | 2K | 9.50 | [4000,7000) |
| 3 | 1080P | 9.00 | [2000,4000) |
| 4 | 720P | 8.00 | [1000,2000) |
| 5 | 480P | 7.00 | [500,1000) |
| 6 | 360P | 6.00 | [100,500) |
| 7 | <360P | 4.00 | [0,100) |
The rate score is calculated as follows:
wherein i represents a grading number; s [ i ] represents the lowest score in the grading number i; max represents the maximum value of the code rate interval under the grading number i, and min represents the minimum value of the code rate interval under the grading number i.
2) The initial buffer length (fb) scoring rule is shown in table 3 below, and a linear fit is required within the stage according to the following equation (2).
TABLE 3 initial buffer duration scoring rules
The initial buffer duration score is calculated as follows:
wherein i represents a grading number; s [ i ] represents the highest score in the grading number i; max represents the maximum value of the initial buffer duration interval under the gear number i, and min represents the minimum value of the initial buffer duration interval under the gear number i.
3) The Calton frequency (sf) score rule is shown in Table 4 below, and a linear fit is required within the stage according to equation (3) below.
TABLE 4 Calton frequency scoring rules
| Step numbering | Frequency of calton | Highest grading value |
| 1 | (0,0] | 10.00 |
| 2 | (0,4] | 8.00 |
| 3 | (4,8] | 6.00 |
| 4 | (8,12] | 4.00 |
| 5 | (12,16] | 2.00 |
| 6 | (16,20] | 1.00 |
| 7 | >20 | 0 |
The Calton frequency score is calculated as follows:
wherein i represents a grading number; s [ i ] represents the highest score in the grading number i; max represents the maximum value of the stuck frequency interval under the gear number i, and min represents the minimum value of the stuck frequency interval under the gear number i.
4) The rule for the calton duration (sr) is shown in table 5 below, and the phase is linearly fit according to equation (4) below.
TABLE 5 Calton-time long-scoring rule
| Step numbering | Length to duty ratio of karton time | Highest grading value |
| 1 | (0.0,0.0] | 10.00 |
| 2 | (0.0,5.0％] | 8.00 |
| 3 | (5.0％,10.0％] | 6.00 |
| 4 | (10.0％,20.0％] | 4.00 |
| 5 | (20.0％,30.0％] | 2.00 |
| 6 | (30.0％,40.0％] | 1.00 |
| 7 | >40.0％ | 0 |
The katton time length to fraction score is calculated as follows:
wherein i represents a grading number; s [ i ] represents the highest score in the grading number i; max represents the maximum value of the length-to-ratio interval under the gear number i, and min represents the minimum value of the length-to-ratio interval under the gear number i;
the video size tested in this example is 469M, the video duration is 2491 seconds, and the calculation process is as follows in conjunction with table 6 below:
TABLE 6 calculated and scored values for the respective parameters
| Parameter(s) | Calculated value | Score of |
| rate | 469*1024*8/2491＝1542 | 8.54 |
| fb | 500 | 7.11 |
| sf | 2/(5/60)＝24 | 0 |
| sr | (6)/(6+39)＝0.13 | 3.4 |
The final network video score is:
the total score is 100 points, and the score of 30 points is lower, which indicates that the mobile network quality is poor.
In order to realize network fault location, location information can be collected in the testing process, video is tested at different places to observe the change of playing quality, and a fault approximate region is found out.
In order to eliminate the influence of the problems of individual video servers on the score result, a mode of testing a plurality of video addresses and automatically and circularly testing can be adopted for testing, and a large number of practices show that the network quality condition can be objectively reflected by analyzing the video quality.
Those skilled in the art can understand that all or part of the steps in the method for implementing the above embodiments may be completed by instructing the relevant hardware through a program, the corresponding program may be stored in a computer-readable storage medium, and the whole method may be made into an APP alone or an accessory function of the APP, which is convenient for a user to test.
It should be noted that although the method operations of the above-described embodiments are depicted in the drawings in a particular order, this does not require or imply that these operations must be performed in this particular order, or that all of the illustrated operations must be performed, to achieve desirable results. Rather, the depicted steps may change the order of execution. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions.
Example 2:
as shown in fig. 3, the embodiment provides a mobile network analysis system based on video playing, the system includes an obtaining module 301, a playing module 302, a collecting module 303, and a calculating module 304, and the specific functions of each module are as follows:
the obtaining module 301 is configured to obtain a network video source address and basic information of a network video source corresponding to the network video source address.
The playing module 302 is configured to respond to a playing instruction of a user, start a video player, transmit a network video source address to the video player, and start playing.
The collecting module 303 is configured to collect an initial buffer state, a playing state, and a pause state every other preset time during the playing process of the network video, and stop the collection until the set playing time is over;
the calculating module 304 is configured to calculate a score of the network video according to the basic information, the initial buffering state, the playing state, and the hiton state of the network video source, so as to obtain an analysis result of the mobile network.
The specific implementation of each module in this embodiment may refer to embodiment 1, which is not described herein any more; it should be noted that, the apparatus provided in this embodiment is only illustrated by dividing the functional modules, and in practical applications, the functions may be distributed by different functional modules according to needs, that is, the internal structure is divided into different functional modules to complete all or part of the functions described above.
Example 3:
as shown in fig. 4, the present embodiment provides a mobile device, which may be a mobile phone, a tablet computer, or the like, and includes a processor 401, a memory 402, a radio frequency circuit 403, an input unit 404, a display unit 405, a sensor 406, an audio circuit 407, a camera 408, a power supply 409, and the like, where the memory 402, the radio frequency circuit 403, the input unit 404, the display unit 405, the sensor 406, the audio circuit 407, and the camera 408 are respectively connected to the processor 401, and the power supply 409 (such as a battery) is used for supplying power to each component.
The processor 401 is a control center of the mobile device, connects various parts of the entire mobile phone by using various interfaces and lines, and performs various functions of the client 201 and processes data by running or executing a computer program stored in the memory 402 and calling data stored in the first memory 402, thereby performing overall monitoring of the mobile phone. Optionally, processor 401 may include one or more processing cores; preferably, the processor 401 may integrate an application processor, which mainly handles operating systems, user interfaces, application programs, etc., and a modem processor, which mainly handles wireless communications. It will be appreciated that the modem processor described above may not be integrated into the first processor 401.
acquiring a network video source address and basic information of a network video source corresponding to the network video source address;
responding to a playing instruction of a user, starting a video player, transmitting a network video source address into the video player, and starting playing;
in the playing process of the network video, collecting an initial buffer state, a playing state and a pause state every other preset time until the set playing time is over, and stopping collecting;
and calculating the score of the network video according to the basic information, the initial buffering state, the playing state and the blocking state of the network video source, thereby obtaining the analysis result of the mobile network.
Example 4:
the present embodiment provides a storage medium, which is a computer-readable storage medium, and stores a computer program, and when the computer program is executed by a processor, the mobile network analysis method of the foregoing embodiment 1 is implemented as follows:
acquiring a network video source address and basic information of a network video source corresponding to the network video source address;
responding to a playing instruction of a user, starting a video player, transmitting a network video source address into the video player, and starting playing;
in the playing process of the network video, collecting an initial buffer state, a playing state and a pause state every other preset time until the set playing time is over, and stopping collecting;
and calculating the score of the network video according to the basic information, the initial buffering state, the playing state and the blocking state of the network video source so as to obtain an analysis result of the mobile network.
The storage medium described in this embodiment may be a magnetic disk, an optical disk, a computer Memory, a Random Access Memory (RAM), a usb disk, a removable hard disk, or other media.
In summary, the present invention can support domestic mainstream video website addresses, support various video types of video packaging formats and encoding formats, transmit a network video source address to a video player, start playing, collect an initial buffering state, a playing state and a stuck state every other preset time in the playing process of a network video until the set playing time is over, stop collecting, calculate a score of the network video according to the basic information, the initial buffering state, the playing state and the stuck state of the network video source, the score can reflect video quality, and since the video data amount accounts for a large amount in data transmission of a mobile network and has a high requirement on the network quality, the mobile network quality can be evaluated by the video quality; in addition, the invention can be integrated on the mobile device, can be independently made into APP, and can also be made into the auxiliary function of the APP, thereby being convenient for the user to test.
The above description is only for the preferred embodiments of the present invention, but the protection scope of the present invention is not limited thereto, and any person skilled in the art can substitute or change the technical solution and the inventive concept of the present invention within the scope of the present invention.
Claims (5)
1. A mobile network analysis method based on video playing is characterized by comprising the following steps:
acquiring a network video source address and basic information of a network video source corresponding to the network video source address, wherein the basic information of the network video source comprises a video size and a video duration;
responding to a playing instruction of a user, starting a video player, transmitting a network video source address into the video player, and starting playing;
in the playing process of the network video, collecting an initial buffer state, a playing state and a pause state every other preset time until the set playing time is over, and stopping collecting;
calculating the score of the network video according to the basic information, the initial buffering state, the playing state and the pause state of the network video source, thereby obtaining the analysis result of the mobile network, as follows:
wherein R represents the final score; rate represents the bitrate, i.e. the video size × 8/video duration, and f (rate) represents the bitrate score; fb denotes an initial buffer time length, f (fb) denotes an initial buffer time length score; sf represents the katton frequency, and f (sf) represents the katton frequency score; sr represents the card pause time length ratio, namely the card pause state total time length/(the play state total time length + the card pause state total time length), and f (sr) represents the card pause time length ratio score; q1, q2 and q3 represent index weights;
the rate score is calculated as follows:
wherein, S [ i ]]Represents the lowest score in the grading number i; max i Represents the maximum value of the code rate interval min under the grading number i i Representing the minimum value of the code rate interval under the grading number i;
when the code rate interval is [7000, + ∞), "1" is the number of the gear stage, and 10 is the lowest score; when the code rate interval is [4000,7000), the grading number is 2, and the lowest score is 9.5; when the code rate interval is [2000,4000), the grading number is 3, and the lowest score is 9; when the code rate interval is [1000,2000), the grading number is 4, and the lowest score is 8; when the code rate interval is [500, 1000), the grading number is 5, and the lowest score is 7; when the code rate interval is [100, 500), the grade number is 6, and the lowest grade value is 6; when the code rate interval is [0, 100), the grading number is 7, and the lowest score is 4;
the initial buffer length score is calculated as follows:
wherein, S [ j ]]Represents the highest score in the ranking number j; max j Represents the maximum value of the initial buffer duration interval min under the grading number j j Representing the minimum value of the initial buffering duration interval under the grading number j;
when the initial buffering duration interval is [0, 100), the number of the grades is 1, and the highest score is 10; when the initial buffering duration interval is [100, 1000), the grading number is 2, and the highest score is 8; when the initial buffering time interval is [1000, 3000), the grading number is 3, and the highest score is 6; when the initial buffer duration interval is [3000,6000), the number of the grades is 4, and the highest score is 4; when the initial buffer duration interval is [6000,10000), the number of the grades is 5, and the highest score is 2; when the initial buffer duration interval is [10000,100000), the grade number is 6, and the highest score is 1; when the initial buffering duration interval is greater than 100000, the grading number is 7, and the highest score is 0;
the Calton frequency score is calculated as follows:
wherein, S [ m ]]Represents the highest score in the ranking number m; max m Represents the maximum value of the karton frequency interval under the grading number m, min m Representing the minimum value of the pause frequency interval under the grading number m;
the numerical control card-pause frequency interval is (0,0), the grading number is 1, the highest score is 10, the numerical control card-pause frequency interval is (0,4), the grading number is 2, the highest score is 8, the numerical control card-pause frequency interval is (4,8), the highest score is 6, the numerical control card-pause frequency interval is (8,12), the grading number is 4, the highest score is 4, the numerical control card-pause frequency interval is (12,16), the grading number is 5, the highest score is 2, the numerical control card-pause frequency interval is (16,20), the grading number is 6, the highest score is 1, the numerical control card-pause frequency interval is greater than 20, the grading number is 7, and the highest score is 0;
the katton time length to fraction score is calculated as follows:
wherein, S [ n ]]Represents the highest score in the grade number n; max n Represents the maximum value of the pause time length-occupying interval min under the step number n n The minimum value of the length-to-ratio interval of the Kanton time under the step number n is represented;
the division number is 1 and the highest score is 10 when the card pause time length proportion interval is (0.0%, 0.0% >), the division number is 2 and the highest score is 8 when the card pause time length proportion interval is (0.0%, 5.0% >), the division number is 3 and the highest score is 6 when the card pause time length proportion interval is (5.0%, 10.0% >), the division number is 4 and the highest score is 4 when the card pause time length proportion interval is (10.0%, 20.0% >), the division number is 5 and the highest score is 2 when the card pause time length proportion interval is (20.0%, 30.0% >), the division number is 6 and the highest score is 1 when the card pause time length proportion interval is (30.0%, 40.0% >), the division number is 7 and the highest score is 0 when the card pause time length proportion interval is greater than 40%.
2. The method of claim 1, wherein the obtaining a network video source address specifically comprises:
acquiring a video source address provided by a video provider server;
or the video source address is acquired through a third-party network interface.
3. A mobile network analysis system based on video playing, the system comprising:
the system comprises an acquisition module, a processing module and a display module, wherein the acquisition module is used for acquiring a network video source address and basic information of a network video source corresponding to the network video source address, and the basic information of the network video source comprises a video size and a video duration;
the playing module is used for responding to a playing instruction of a user, starting the video player, transmitting a network video source address into the video player and starting playing;
the collecting module is used for collecting the initial buffer state, the playing state and the pause state every other preset time in the playing process of the network video until the set playing time is over and stopping the collection;
the calculating module is used for calculating the score of the network video according to the basic information, the initial buffering state, the playing state and the pause state of the network video source, so as to obtain the analysis result of the mobile network, and the following formula is shown:
wherein R represents the final score; rate represents the bitrate, i.e. the video size × 8/video duration, and f (rate) represents the bitrate score; fb denotes an initial buffer time length, f (fb) denotes an initial buffer time length score; sf represents the katon frequency, f (sf) represents the katon frequency score; sr represents the katon time length-to-occupation ratio, namely the katon state total time length/(the play state total time length + the katon state total time length), and f (sr) represents the katon time length-to-occupation ratio score; q1, q2 and q3 represent index weights;
the rate score is calculated as follows:
wherein, S [ i ]]Represents the lowest score in the grading number i; max i Represents the maximum value of the code rate interval min under the grading number i i Representing the minimum value of the code rate interval under the grading number i;
when the code rate interval is [7000, + ∞), "1" is the number of the gear stage, and 10 is the lowest score; when the code rate interval is [4000,7000), the grading number is 2, and the lowest score is 9.5; when the code rate interval is [2000,4000), the grading number is 3, and the lowest score is 9; when the code rate interval is [1000,2000), the grading number is 4, and the lowest score is 8; when the code rate interval is [500, 1000), the grading number is 5, and the lowest score is 7; when the code rate interval is [100, 500), the grading number is 6, and the lowest score is 6; when the code rate interval is [0, 100), the grading number is 7, and the lowest score is 4;
the initial buffer length score is calculated as follows:
wherein, S [ j ]]Represents the highest score in the ranking number j; max j Represents the maximum value of the initial buffer duration interval min under the grading number j j Representing the interval of the initial buffer duration under the step number jA minimum value;
when the initial buffering duration interval is [0, 100), the number of the grades is 1, and the highest score is 10; when the initial buffering duration interval is [100, 1000), the grading number is 2, and the highest score is 8; when the initial buffering duration interval is [1000, 3000), the number of the grades is 3, and the highest score is 6; when the initial buffer duration interval is [3000,6000), the number of the grades is 4, and the highest score is 4; when the initial buffer duration interval is [6000,10000), the number of the grades is 5, and the highest score is 2; when the initial buffer duration interval is [10000,100000), the grade number is 6, and the highest score is 1; when the initial buffering duration interval is greater than 100000, the grading number is 7, and the highest score is 0;
the Calton frequency score is calculated as follows:
wherein, S [ m ]]Represents the highest score in the ranking number m; max m Represents the maximum value of the pause frequency interval min under the grading number m m Representing the minimum value of the pause frequency interval under the grading number m;
the numerical control card-pause frequency interval is (0,0), the grading number is 1, the highest score is 10, the numerical control card-pause frequency interval is (0,4), the grading number is 2, the highest score is 8, the numerical control card-pause frequency interval is (4,8), the highest score is 6, the numerical control card-pause frequency interval is (8,12), the grading number is 4, the highest score is 4, the numerical control card-pause frequency interval is (12,16), the grading number is 5, the highest score is 2, the numerical control card-pause frequency interval is (16,20), the grading number is 6, the highest score is 1, the numerical control card-pause frequency interval is greater than 20, the grading number is 7, and the highest score is 0;
the katton time length to fraction score is calculated as follows:
wherein, S [ n ]]Represents the highest score in the grade number n; max n Represents the maximum value of the pause time length-occupying interval min under the step number n n The minimum value of the length-to-length ratio interval of the Ka dun time under the step number n is represented;
the division number is 1 and the highest score is 10 when the card pause time length proportion interval is (0.0%, 0.0% >), the division number is 2 and the highest score is 8 when the card pause time length proportion interval is (0.0%, 5.0% >), the division number is 3 and the highest score is 6 when the card pause time length proportion interval is (5.0%, 10.0% >), the division number is 4 and the highest score is 4 when the card pause time length proportion interval is (10.0%, 20.0% >), the division number is 5 and the highest score is 2 when the card pause time length proportion interval is (20.0%, 30.0% >), the division number is 6 and the highest score is 1 when the card pause time length proportion interval is (30.0%, 40.0% >), the division number is 7 and the highest score is 0 when the card pause time length proportion interval is greater than 40%.
4. A mobile device comprising a processor and a memory for storing a processor-executable program, wherein the processor, when executing the program stored in the memory, implements the mobile network analysis method of any one of claims 1-2.
5. A storage medium storing a program, wherein the program, when executed by a processor, implements the mobile network analysis method of any one of claims 1-2.
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