CN118449863A - Dynamic bandwidth resource management method and device - Google Patents
Dynamic bandwidth resource management method and device Download PDFInfo
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- CN118449863A CN118449863A CN202410903695.8A CN202410903695A CN118449863A CN 118449863 A CN118449863 A CN 118449863A CN 202410903695 A CN202410903695 A CN 202410903695A CN 118449863 A CN118449863 A CN 118449863A
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- 238000007726 management method Methods 0.000 title claims abstract description 29
- 238000000034 method Methods 0.000 claims abstract description 11
- 238000012545 processing Methods 0.000 claims description 11
- YHXISWVBGDMDLQ-UHFFFAOYSA-N moclobemide Chemical compound C1=CC(Cl)=CC=C1C(=O)NCCN1CCOCC1 YHXISWVBGDMDLQ-UHFFFAOYSA-N 0.000 claims description 8
- 238000012549 training Methods 0.000 claims description 6
- 238000004590 computer program Methods 0.000 claims description 5
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Classifications
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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
- H04L41/08—Configuration management of networks or network elements
- H04L41/0896—Bandwidth or capacity management, i.e. automatically increasing or decreasing capacities
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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
- H04L41/147—Network analysis or design for predicting network behaviour
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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
- H04N21/234—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
- H04N21/2343—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving reformatting operations of video signals for distribution or compliance with end-user requests or end-user device requirements
-
- 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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- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Multimedia (AREA)
- Computer Networks & Wireless Communication (AREA)
- Compression Or Coding Systems Of Tv Signals (AREA)
Abstract
The application provides a dynamic bandwidth resource management method and device, electronic equipment and storage medium, wherein the method comprises the following steps: predicting the bandwidth demand of the cloud application user by utilizing a pre-trained bandwidth demand prediction model; when the bandwidth requirement is greater than a first value, adjusting coding parameters of the cloud application picture to reduce the data volume of the coded cloud application picture; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data volume of the coded cloud application picture, wherein the first value is larger than or equal to the second value, so that bandwidth resources can be effectively managed, the utilization efficiency of the bandwidth resources is improved, the overall bandwidth cost is reduced, and meanwhile, high-quality user experience is ensured.
Description
Technical Field
The present invention relates to the field of cloud applications, and in particular, to a dynamic bandwidth resource management method and apparatus, an electronic device, and a storage medium.
Background
With the popularity and development of cloud application services (such as cloud gaming services), cloud application service providers face increasing challenges, particularly in terms of bandwidth management and cost control. Cloud application services, as a high bandwidth demanding service, rely on a stable and fast network connection to ensure a smooth application experience. However, because cloud application customers are typically active during certain periods of time (e.g., evening or weekend), resulting in a high peak superposition effect of bandwidth usage that cloud application service providers face during peak periods, such superposition effects create extreme bandwidth demand peaks, resulting in cloud application service providers facing high bandwidth costs. Meanwhile, in the off-peak period, a large amount of bandwidth resources are not fully utilized, and resource waste is caused.
Therefore, how to provide a solution to effectively manage bandwidth resources, improve the utilization efficiency of bandwidth resources, reduce the overall bandwidth cost, and ensure high-quality user experience is a technical problem to be solved.
Disclosure of Invention
Aiming at the technical problems existing in the prior art, the embodiment of the application provides a dynamic bandwidth resource management method and device, electronic equipment and a storage medium.
In a first aspect, an embodiment of the present application provides a dynamic bandwidth resource management method, which is applied to a cloud server, and includes:
Predicting the bandwidth demand of the cloud application user by utilizing a pre-trained bandwidth demand prediction model;
When the bandwidth requirement is greater than a first value, adjusting coding parameters of the cloud application picture to reduce the data volume of the coded cloud application picture; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data quantity of the coded cloud application picture, wherein the first value is larger than or equal to the second value.
In a second aspect, an embodiment of the present application further provides a dynamic bandwidth resource management device, which is applied to a cloud server, and includes:
the prediction unit is used for predicting the bandwidth demand of the cloud application user by using a pre-trained bandwidth demand prediction model;
The adjusting unit is used for adjusting the coding parameters of the cloud application picture when the bandwidth requirement is larger than the first value so as to reduce the data quantity of the coded cloud application picture; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data quantity of the coded cloud application picture, wherein the first value is larger than or equal to the second value.
In a third aspect, embodiments of the present application also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the dynamic bandwidth resource management method according to the first aspect.
In a fourth aspect, an embodiment of the present application further provides an electronic device, including: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating over the bus when the electronic device is running, the processor executing the machine-readable instructions to perform the steps of the dynamic bandwidth resource management method according to the first aspect.
In summary, the dynamic bandwidth resource management method and device, the electronic device and the storage medium provided by the embodiment of the application predict the bandwidth demands of cloud application users by utilizing a pre-trained bandwidth demand prediction model; when the bandwidth requirement is greater than a first value, adjusting coding parameters of the cloud application picture to reduce the data volume of the coded cloud application picture; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data volume of the coded cloud application picture, namely, in the peak period, smoothing the bandwidth requirement peak value by adjusting the coding parameters of the cloud application picture, and in the non-peak period, improving the quality of the cloud application picture by adjusting the coding parameters of the cloud application picture, the whole scheme can effectively manage bandwidth resources, improve the utilization efficiency of the bandwidth resources, reduce the total bandwidth cost and ensure high-quality user experience.
Drawings
Fig. 1 is a schematic flow chart of an embodiment of a dynamic bandwidth resource management method according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an embodiment of a dynamic bandwidth resource management device according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present application more apparent, the technical solutions of the embodiments of the present application will be clearly and completely described with reference to the accompanying drawings in the embodiments of the present application, and it should be understood that the drawings in the present application are for the purpose of illustration and description only and are not intended to limit the scope of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. A flowchart, as used in this disclosure, illustrates operations implemented according to some embodiments of the present application. It should be understood that the operations of the flow diagrams may be implemented out of order and that steps without logical context may be performed in reverse order or concurrently. Moreover, one or more other operations may be added to or removed from the flow diagrams by those skilled in the art under the direction of the present disclosure.
In addition, the described embodiments are only some, but not all, embodiments of the application. The components of the embodiments of the present application generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the application, as presented in the figures, is not intended to limit the scope of the application, as claimed, but is merely representative of selected embodiments of the application. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present application.
It should be noted that the term "comprising" will be used in embodiments of the application to indicate the presence of the features stated hereafter, but not to exclude the addition of other features.
Referring to fig. 1, a flow chart of a dynamic bandwidth resource management method according to an embodiment of the present application is shown, where the dynamic bandwidth resource management method is applied to a cloud server, and includes:
S10, predicting the bandwidth demand of a cloud application user by using a pre-trained bandwidth demand prediction model;
In this embodiment, it should be noted that, the input of the bandwidth demand prediction model may be the actual bandwidth usage of the cloud application user in the plurality of time periods, and the output may be the bandwidth demand of the cloud application user in the current time period. If the actual bandwidth usage of the cloud application user in each of the past 5 hours is input into the bandwidth demand prediction model, the bandwidth demand of the cloud application user in the current one hour can be predicted. The cloud application user may be a user accessing an instance of the same IDC (INTERNETDATACENTER ) room for cloud play. The network operators may be distinguished or not distinguished for the prediction of the bandwidth requirements of the cloud application users and the processing measures in the subsequent step S11.
S11, when the bandwidth requirement is greater than a first value, adjusting coding parameters of the cloud application picture to reduce the data volume of the coded cloud application picture; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data quantity of the coded cloud application picture, wherein the first value is larger than or equal to the second value.
In this embodiment, it should be noted that the first value and the second value may be set as required. When the bandwidth requirement is larger than the first value, reducing the data volume of the coded cloud application picture, and reducing the use amount of the bandwidth; when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, the data volume of the coded cloud application picture is increased, and the bandwidth usage amount can be increased. The gap between the bandwidth peak value and the bandwidth valley value can be reduced by reducing the bandwidth usage amount in the peak value period and increasing the bandwidth usage amount in the non-peak value period, the bandwidth resource usage efficiency is improved, the user experience is ensured, and the bandwidth cost is reduced.
According to the dynamic bandwidth resource management method provided by the embodiment of the application, the bandwidth demand of the cloud application user is predicted by utilizing the pre-trained bandwidth demand prediction model; when the bandwidth requirement is greater than a first value, adjusting coding parameters of the cloud application picture to reduce the data volume of the coded cloud application picture; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data volume of the coded cloud application picture, namely, in the peak period, smoothing the bandwidth requirement peak value by adjusting the coding parameters of the cloud application picture, and in the non-peak period, improving the quality of the cloud application picture by adjusting the coding parameters of the cloud application picture, the whole scheme can effectively manage bandwidth resources, improve the utilization efficiency of the bandwidth resources, reduce the total bandwidth cost and ensure high-quality user experience.
Based on the foregoing method embodiment, the bandwidth demand prediction model is an ARIMA model (Autoregressive Integrated Moving Average Model, autoregressive moving average model),
Before the predicting the bandwidth demand of the cloud application user by using the pre-trained bandwidth demand prediction model, the method may further include:
And performing at least one differential processing on the bandwidth usage of the historical multiple cloud application users, and training an ARIMA model by utilizing the bandwidth usage after the differential processing.
In this embodiment, it should be noted that, at least one difference process is performed on the bandwidth usage amounts of the plurality of cloud application users in the history, so as to transform the original sequence composed of the bandwidth usage amounts of the plurality of cloud application users in the history into a stable sequence.
On the basis of the foregoing method embodiment, the adjusting the coding parameters of the cloud application picture to reduce the data size of the coded cloud application picture may include:
Increasing the coding proportion of the picture frames of the non-I frames; and/or
The code rate and/or resolution of encoding the first designated area in the cloud application picture is reduced.
In this embodiment, it should be noted that, in the peak period of the predicted bandwidth usage, in order to reduce the peak of the bandwidth usage, the amount of data sent to the terminal by the cloud server may be reduced, where specific measures include at least one of increasing the coding proportion of the picture frames other than the I frame, reducing the code rate of coding the first designated area in the cloud application picture, and reducing the resolution of coding the first designated area in the cloud application picture. I-frames, also known as intra pictures (intra pictures) or key frames, are a coded frame of full frame compression that can be decoded without reference to other pictures, and can be used to reconstruct a complete image using only the I-frame data. Increasing the coding proportion of picture frames other than I frames means that the proportion of non-I frames coded is increased, but the non-I frames are not complete image frames, and the amount of data is smaller, so that the amount of data sent to the terminal can be reduced. The first designated area may be an entire frame of cloud application screen area, or a partial area such as a non-user interest area (e.g., a background area) and/or a dark scene area. The identification of the non-user attention area and the dark scene area in the cloud application picture can adopt the prior art, and the content is not the core of the application and is not repeated here. Reducing the code rate and/or resolution of encoding the first designated area in the cloud application picture means that the amount of data of encoded data obtained by encoding the cloud application picture by the encoder of the cloud server is reduced, and thus, the amount of data transmitted to the terminal is naturally also reduced. The adjustment amount of the processing measure in this embodiment may be determined by referring to the coding parameter that is better for the user experience under a certain historical bandwidth usage (e.g., 80% of the peak bandwidth of the past month). When the code rate and the resolution are adjusted, the code rate and the resolution can be alternately reduced according to the corresponding designated step length. The processing measures in this embodiment may add constraints, such as for low priority users or non-critical cloud applications.
On the basis of the foregoing method embodiment, the adjusting the coding parameters of the cloud application picture to increase the data size of the coded cloud application picture may include:
Reducing the coding proportion of picture frames other than I frames; and/or
The code rate and/or resolution and/or frame rate of encoding the second designated area in the cloud application picture is increased.
In this embodiment, it should be noted that, in correspondence to the previous embodiment in which the amount of data sent by the cloud server to the terminal needs to be reduced, the present embodiment needs to increase the amount of data sent by the cloud server to the terminal, specifically, the coding proportion of the picture frames other than the I frame may be reduced, that is, the coded I frame is increased, and the amount of data of the I frame is larger, so that the amount of data sent to the terminal may be increased. The second designated area may be an entire frame of cloud application screen area, or a user attention area and/or other partial areas (dark scene area, background area, etc.). Increasing the code rate and/or resolution of encoding the second designated area in the cloud application picture can increase the data amount of encoded data obtained after encoding the cloud application picture, so that the data amount sent to the terminal can be increased. Besides increasing the code rate and/or resolution and/or frame rate of encoding the second designated area in the cloud application picture, the redundancy proportion of FEC (Forward Error Correction ) can be increased, the transmission speed of encoded data can be increased, and the like, so that bandwidth resources can be fully utilized, and user experience can be improved. Specifically, increasing the FEC redundancy ratio can reduce the packet loss rate under the weak network condition; increasing the data transmission speed can increase the smoothness of the cloud application picture display.
Referring to fig. 2, a schematic structural diagram of a dynamic bandwidth resource management device according to an embodiment of the present application is shown, where the device is applied to a cloud server, and includes:
A prediction unit 20, configured to predict a bandwidth demand of a cloud application user by using a pre-trained bandwidth demand prediction model;
An adjusting unit 21, configured to adjust an encoding parameter of the cloud application picture to reduce a data amount of the encoded cloud application picture when the bandwidth requirement is greater than the first value; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data quantity of the coded cloud application picture, wherein the first value is larger than or equal to the second value.
According to the dynamic bandwidth resource management device provided by the embodiment of the application, the bandwidth demand of the cloud application user is predicted by utilizing a pre-trained bandwidth demand prediction model by means of the prediction unit 20; when the bandwidth requirement is larger than a first value, the adjusting unit 21 adjusts the coding parameters of the cloud application picture to reduce the data quantity of the coded cloud application picture; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data volume of the coded cloud application picture, namely, in the peak period, smoothing the bandwidth requirement peak value by adjusting the coding parameters of the cloud application picture, and in the non-peak period, improving the quality of the cloud application picture by adjusting the coding parameters of the cloud application picture, the whole scheme can effectively manage bandwidth resources, improve the utilization efficiency of the bandwidth resources, reduce the total bandwidth cost and ensure high-quality user experience.
Based on the foregoing embodiment of the apparatus, the bandwidth requirement prediction model is an ARIMA model, and the apparatus may further include:
And the training unit is used for performing at least one differential processing on the bandwidth usage of the historical multiple cloud application users before the prediction unit works, and training an ARIMA model by utilizing the bandwidth usage after the differential processing.
On the basis of the foregoing apparatus embodiment, the adjusting unit may be configured to:
when the bandwidth requirement is larger than a first value, increasing the coding proportion of the picture frames of the non-I frames; and/or
The code rate and/or resolution of encoding the first designated area in the cloud application picture is reduced.
On the basis of the foregoing apparatus embodiment, the adjusting unit may be configured to:
when the bandwidth requirements of at least two times of continuous prediction are smaller than a second value, reducing the coding proportion of the picture frames of the non-I frames; and/or
The code rate and/or resolution and/or frame rate of encoding the second designated area in the cloud application picture is increased.
The implementation process of the dynamic bandwidth resource management device provided by the embodiment of the application is consistent with the dynamic bandwidth resource management method provided by the embodiment of the application, and the achieved effect is the same as that of the dynamic bandwidth resource management method provided by the embodiment of the application, and the details are not repeated here.
According to the scheme, the coding strategy of the cloud application picture is adaptively adjusted according to the predicted bandwidth demand, the use efficiency of bandwidth resources can be maximized, resource overload in a peak period and resource idling in an off-peak period are avoided, and user experience is maintained or improved while cost is reduced, so that a cloud application service provider can effectively manage and optimize bandwidth use while ensuring good user experience quality, and dual optimization of service quality and cost effectiveness is realized.
As shown in fig. 3, an electronic device provided in an embodiment of the present application includes: a processor 30, a memory 31 and a bus 32, said memory 31 storing machine readable instructions executable by said processor 30, said processor 30 and said memory 31 communicating via bus 32 when the electronic device is running, said processor 30 executing said machine readable instructions to perform the steps of the dynamic bandwidth resource management method as described above.
Specifically, the above-mentioned memory 31 and the processor 30 can be general-purpose memories and processors, and are not particularly limited herein, and the above-mentioned dynamic bandwidth resource management method can be performed when the processor 30 runs a computer program stored in the memory 31.
Corresponding to the above dynamic bandwidth resource management method, the embodiment of the present application further provides a computer readable storage medium, where a computer program is stored, and when the computer program is executed by a processor, the steps of the above dynamic bandwidth resource management method are performed.
The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily appreciate variations or alternatives within the scope of the present application. Therefore, the protection scope of the application is subject to the protection scope of the claims.
Claims (10)
1. A dynamic bandwidth resource management method applied to a cloud server, comprising the following steps:
Predicting the bandwidth demand of the cloud application user by utilizing a pre-trained bandwidth demand prediction model;
When the bandwidth requirement is greater than a first value, adjusting coding parameters of the cloud application picture to reduce the data volume of the coded cloud application picture; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data quantity of the coded cloud application picture, wherein the first value is larger than or equal to the second value.
2. The method of claim 1, wherein the bandwidth demand prediction model is an ARIMA model,
Before the bandwidth demand of the cloud application user is predicted by using the pre-trained bandwidth demand prediction model, the method further comprises the following steps:
And performing at least one differential processing on the bandwidth usage of the historical multiple cloud application users, and training an ARIMA model by utilizing the bandwidth usage after the differential processing.
3. The method according to claim 1 or 2, wherein adjusting the coding parameters of the cloud application picture to reduce the data amount of the coded cloud application picture comprises:
Increasing the coding proportion of the picture frames of the non-I frames; and/or
The code rate and/or resolution of encoding the first designated area in the cloud application picture is reduced.
4. The method according to claim 1 or 2, wherein adjusting the coding parameters of the cloud application picture to increase the data amount of the coded cloud application picture comprises:
Reducing the coding proportion of picture frames other than I frames; and/or
The code rate and/or resolution and/or frame rate of encoding the second designated area in the cloud application picture is increased.
5. A dynamic bandwidth resource management device applied to a cloud server, comprising:
the prediction unit is used for predicting the bandwidth demand of the cloud application user by using a pre-trained bandwidth demand prediction model;
The adjusting unit is used for adjusting the coding parameters of the cloud application picture when the bandwidth requirement is larger than the first value so as to reduce the data quantity of the coded cloud application picture; or when the bandwidth requirements of at least two times of continuous prediction are smaller than the second value, adjusting the coding parameters of the cloud application picture to increase the data quantity of the coded cloud application picture, wherein the first value is larger than or equal to the second value.
6. The apparatus of claim 5, wherein the bandwidth demand prediction model is an ARIMA model, the apparatus further comprising:
And the training unit is used for performing at least one differential processing on the bandwidth usage of the historical multiple cloud application users before the prediction unit works, and training an ARIMA model by utilizing the bandwidth usage after the differential processing.
7. The apparatus according to claim 5 or 6, wherein the adjusting unit is configured to:
when the bandwidth requirement is larger than a first value, increasing the coding proportion of the picture frames of the non-I frames; and/or
The code rate and/or resolution of encoding the first designated area in the cloud application picture is reduced.
8. The apparatus according to claim 5 or 6, wherein the adjusting unit is configured to:
when the bandwidth requirements of at least two times of continuous prediction are smaller than a second value, reducing the coding proportion of the picture frames of the non-I frames; and/or
The code rate and/or resolution and/or frame rate of encoding the second designated area in the cloud application picture is increased.
9. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, performs the steps of the dynamic bandwidth resource management method according to any of claims 1 to 4.
10. An electronic device, comprising: a processor, a storage medium and a bus, the storage medium storing machine-readable instructions executable by the processor, the processor and the storage medium communicating over the bus when the electronic device is running, the processor executing the machine-readable instructions to perform the steps of the dynamic bandwidth resource management method according to any one of claims 1 to 4.
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