Live video platform content distribution intelligent scheduling system based on cloud computing

Abstract

The invention discloses a video live broadcast platform content distribution intelligent scheduling system based on cloud computing, and relates to the field of video live broadcast. The live video content distribution efficiency is effectively improved; the system comprises a live video content updating module, an intelligent scheduling module and an early warning module. The video live broadcast content updating module is used for acquiring an optimal playing audio / video of video live broadcast of each platform; the live broadcast content of the best playing audio and video is obtained; the live broadcast content popularity of the live broadcast content is obtained; the intelligent scheduling module is provided with a platform distribution channel network, and distribution data of live broadcast content popularity are obtained through the platform distribution channel network; and the early warning module is used for carrying out early warning on the live broadcast content according to the scheduling signal.

Description

Technical Field

[0001] This invention relates to the field of video live streaming, specifically a cloud-based intelligent scheduling system for content distribution on a video live streaming platform. Background Technology

[0002] With the improvement of network infrastructure and the widespread adoption of mobile devices, live video streaming has become an important form of internet content consumption, widely used in entertainment, education, e-commerce, social networking, and other fields. Cloud computing, with its elastic scaling, high availability, and distributed storage and computing capabilities, provides strong support for the real-time transmission and distribution of massive live streams, becoming a core technology for building modern live streaming platforms. However, facing the diversity of user terminal devices (mobile phones, tablets, computers, etc.), complex and fluctuating network environments, and users' increasingly higher demands for live streaming experience (clarity, smoothness, low latency), traditional cloud-based live streaming distribution systems still face severe challenges in terms of content adaptation efficiency, intelligent resource scheduling, and the ability to warn of potential problems. Different terminal devices have significantly different requirements for video resolution, bitrate, and encoding format. Traditional methods typically rely on preset fixed multi-bitrate templates for transcoding, lacking awareness and feedback on real-time playback effects; Measurements of "popularity" often remain at the level of simple online users or total viewing time, lacking fine-grained, multi-dimensional quantitative models. The failure to effectively utilize rich live stream interaction data (bullet screen density, gift value, chat activity, content type, time period characteristics, etc.) to construct a comprehensive "live stream content popularity" metric results in valuable bandwidth and edge node resources not being accurately allocated to the most valuable live streams. The lack of accurate assessment of content popularity and intelligent scheduling based on this may result in insufficient resource allocation for popular content (causing lag), while unpopular content consumes too many resources, causing significant waste of resources. To address the aforementioned technical problems, this invention provides a cloud-based intelligent scheduling system for content distribution on a live video streaming platform. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention provides a cloud-based intelligent scheduling system for content distribution on a live video streaming platform. The objective of this invention can be achieved through the following technical solution: a cloud-based intelligent scheduling system for video live streaming platform content distribution, comprising a monitoring center, wherein the system includes a video live streaming content update module, an intelligent scheduling module, and an early warning module; The video live streaming content update module is used to obtain the best audio and video playback from various platforms; and to obtain the live streaming content with the best audio and video playback; and then to obtain the popularity of the live streaming content. The intelligent scheduling module is equipped with a platform distribution channel network, through which it obtains distribution data on the popularity of live content. The early warning module is used to issue early warnings for live broadcast content based on scheduling signals.

[0004] Furthermore, the process by which the video live streaming content update unit obtains the best audio and video playback for each platform's live streaming includes: The original audio and video of the live stream content and the original converted multi-bitrate stream are obtained through a video live streaming device; the original converted multi-bitrate stream includes the original resolution, the original bitrate, and the original encoding format; The original audio and video are converted into original playback audio and video through original conversion multi-bitrate stream; the actual playback information data of the original playback audio and video on each platform is obtained; The platform is configured to automatically update multi-bitrate units, and these units contain an adjustable multi-bitrate database corresponding to the actual playback information. The adjustable multi-bitrate database consists of actual playback information data, the platform's optimal multi-bitrate, and adjustable multi-bitrates. The adjustable multi-bitrates are configured with corresponding adjustable multi-bitrate ranges. The platform automatically updates the multi-bitrate unit to obtain actual playback information data, obtains the difference between the actual playback information data and the platform's optimal multi-bitrate, and marks it as the multi-bitrate difference; then matches the multi-bitrate difference with the corresponding adjustment multi-bitrate range, and then adjusts the actual playback information data according to the adjustment multi-bitrate to obtain the best playback audio and video of the original playback audio and video.

[0005] Furthermore, the process of acquiring the best audio and video playback content for live streams, and subsequently, the popularity of that live stream content, includes: The live stream content includes live stream metadata, live stream master data, live stream interaction data, and live stream volume control data; the live stream master data includes the live stream content type and live stream time period; the live stream volume control data includes live stream content instructions and live stream content index; the live stream interaction data includes the number of live stream viewers, the number of bullet comments, the amount of gifts, and the amount of live stream chat text. Obtain historical live stream master data from various platforms, and from this data, obtain several historical live stream content types and several historical live stream time periods for each content type. Then, obtain the number of historical time periods for each content period and sort the historical time period data from largest to smallest to determine the popularity of the corresponding live stream content type on each platform during those time periods. Set the popularity value for each type of live stream content, and the popularity value for each corresponding time period.

[0006] Furthermore, the popularity of the live stream content is obtained by using the popularity values ​​of the live stream type and time period corresponding to the live stream master data; The specific formula is as follows: ; in, This indicates the popularity of the live stream content in terms of content type L and time period t. and These represent the welcome level values ​​for different types of events and the welcome level values ​​for different time periods, respectively. and Let be the weighting coefficients corresponding to the live stream content type and the live stream time period, respectively. .

[0007] Furthermore, the live stream traffic density corresponding to the live stream content time period is obtained by measuring the number of bullet comments and the amount of text in the two days of the live stream; then, the live stream's popularity is obtained by measuring the number of online viewers, the amount of gifts received, and the live stream traffic density. The specific formula is as follows: ; in, This represents the popularity of the live stream content in terms of live stream content type L and live stream time period t; b represents the coefficient, with a value of (0, 1); n, m and u represent the number of live stream viewers, the amount of gifts received and the live stream traffic density, respectively; r1, r2 and r3 represent the weight coefficients corresponding to the number of live stream viewers, the amount of gifts received and the live stream traffic density, respectively, and r1+r2+r3=1. The sum of the live stream host's popularity data and the live stream audience's popularity data is marked as the live stream content popularity.

[0008] Furthermore, the process of setting up the platform distribution channel network in the intelligent scheduling module includes: A distribution channel is set up to connect various platforms and generate a platform distribution channel network; distribution data is set up in the distribution channel; the distribution data includes live dynamic traffic distribution, live dynamic regional distribution, and live dynamic time period distribution; The distribution data is configured with corresponding live content instructions and live content indexes. The live content instructions are used to give instructions to the distribution data, and the live content indexes are used to index the index data of the live content corresponding to the popularity of the content.

[0009] Furthermore, the process of obtaining distribution data on the popularity of live streaming content through various platform distribution channels includes: Set the optimal threshold range for the popularity of live stream content and compare it with the overall popularity of the live stream content: If no live content popularity index exists, then obtain the index data of the live content popularity index, distribute the distribution data according to the index data, and generate a scheduling signal.

[0010] Conversely, no action is taken.

[0011] Furthermore, the process by which the early warning module issues early warnings for live broadcast content based on scheduling signals includes: The system obtains scheduling signals through a preset management terminal, acquires distribution data based on the scheduling signals, and acquires early warning data through the distribution data. The early warning data includes live dynamic traffic distribution, live dynamic regional distribution, and live dynamic time period distribution.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: the video live streaming content update module obtains the best audio and video playback for each platform's live streaming; and obtains the live streaming content with the best audio and video playback; thereby obtaining the popularity of the live streaming content; furthermore, the intelligent scheduling module is equipped with a platform distribution channel network, and the distribution data of the popularity of the live streaming content is obtained through the platform distribution channel network; finally, the early warning module issues early warnings for the live streaming content based on the scheduling signal; effectively improving the distribution efficiency of video live streaming content. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0014] Figure 1 This is a schematic diagram of the present invention. Detailed Implementation

[0015] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0016] like Figure 1 As shown, a cloud-based intelligent scheduling system for video live streaming platform content distribution includes a video live streaming content update module, an intelligent scheduling module, and an early warning module. The video live streaming content update module is used to obtain the best audio and video playback from various platforms; and to obtain the live streaming content with the best audio and video playback; and then to obtain the popularity of the live streaming content. The intelligent scheduling module is equipped with a platform distribution channel network, through which it obtains distribution data on the popularity of live content. The early warning module is used to issue early warnings for live broadcast content based on scheduling signals.

[0017] Further, the process by which the video live streaming content update unit obtains the best playback audio and video for each platform's live streaming includes: The original audio and video of the live stream content and the original converted multi-bitrate stream are obtained through a video live streaming device; the original converted multi-bitrate stream includes the original resolution, the original bitrate, and the original encoding format; In the above embodiments, it should be further explained that the original audio and video collected by video live streaming devices, such as cameras and microphones, are not converted in their original form. Therefore, they may not be suitable for platforms (mobile phones, computers, tablets, etc.) to deliver live streaming content. Therefore, it is necessary to convert the original audio and video data in its original form so that it is suitable for the corresponding platform to deliver live streaming content.

[0018] The original audio and video are converted into original playback audio and video through original conversion multi-bitrate stream; the actual playback information data of the original playback audio and video on each platform is obtained; the actual playback information data includes playback clarity, playback smoothness and playback latency. The platform is configured to automatically update multi-bitrate units, and these units contain an adjustable multi-bitrate database corresponding to the actual playback information. The adjustable multi-bitrate database consists of actual playback information data, the platform's optimal multi-bitrate, and adjustable multi-bitrates. The adjustable multi-bitrates are configured with corresponding adjustable multi-bitrate ranges. The platform automatically updates the multi-bitrate unit to obtain actual playback information data, obtains the difference between the actual playback information data and the platform's optimal multi-bitrate, and marks it as the multi-bitrate difference; then matches the multi-bitrate difference with the corresponding adjustment multi-bitrate range, and then adjusts the actual playback information data according to the adjustment multi-bitrate to obtain the best playback audio and video of the original playback audio and video.

[0019] In the above embodiments, it should be further explained that different platforms need to convert the original audio and video into different multi-bitrate streams and play them on different platforms. However, since different platforms require different multi-bitrate conversion rates, when the same original audio and video needs to be played on different platforms, it is far from enough to convert it only by the original converted multi-bitrate stream. Therefore, the original converted multi-bitrate stream is adjusted by automatically updating the multi-bitrate unit on the platform with an adjustable multi-bitrate database. The adjustable multi-bitrate database can be obtained by analyzing historical data from different platforms, which will not be described in detail in this embodiment.

[0020] Further steps are needed to obtain the best audio and video playback quality for live stream content; the process of then determining the popularity of the live stream content includes: The live stream content includes live stream metadata, live stream master data, live stream interaction data, and live stream volume control data; the live stream master data includes the live stream content type and live stream time period; the live stream volume control data includes live stream content instructions and live stream content index; the live stream interaction data includes the number of live stream viewers, the number of bullet comments, the amount of gifts, and the amount of live stream chat text. The live streaming metadata includes at least the live streaming room ID, live streaming title, and category tags; Obtain historical live stream master data from various platforms, and from this data, obtain several historical live stream content types and several historical live stream time periods for each content type. Then, obtain the number of historical time periods for each content period and sort the historical time period data from largest to smallest to determine the popularity of the corresponding live stream content type on each platform during those time periods. Set the popularity value for the type of live content and the popularity value for the corresponding time period; The popularity of the live stream content is obtained by measuring the popularity values ​​of the live stream content by its type and time period. The specific formula is as follows: ; in, This indicates the popularity of the live stream content in terms of content type L and time period t. and These represent the welcome level values ​​for different types of events and the welcome level values ​​for different time periods, respectively. and Let be the weighting coefficients corresponding to the live stream content type and the live stream time period, respectively. ; The live stream traffic density corresponding to the live stream content time period is obtained by the number of bullet comments and the text volume of the two days of the live stream; then the live stream interaction data popularity is obtained by the number of live stream viewers, the amount of gifts, and the live stream traffic density. The specific formula is as follows: ; in, This represents the popularity of the live stream content in terms of live stream content type L and live stream time period t; b represents the coefficient, with a value of (0, 1); n, m and u represent the number of live stream viewers, the amount of gifts received and the live stream traffic density, respectively; r1, r2 and r3 represent the weight coefficients corresponding to the number of live stream viewers, the amount of gifts received and the live stream traffic density, respectively, and r1+r2+r3=1. The sum of the live stream host's popularity data and the live stream audience's popularity data is marked as the live stream content popularity.

[0021] It should be further explained that the intelligent scheduling module is equipped with a platform distribution channel network. The process of obtaining distribution data on the popularity of live content through the platform distribution channel network includes: A distribution channel is set up to connect various platforms and generate a platform distribution channel network; distribution data is set up in the distribution channel; the distribution data includes live dynamic traffic distribution, live dynamic regional distribution, and live dynamic time period distribution; The distribution data is configured with corresponding live content instructions and live content indexes. The live content instructions are used to give instructions to the distribution data, and the live content indexes are used to index the index data of the live content corresponding to the popularity of the content. In the above embodiments, it should be further noted that the distribution channel has an uncertain direction during the distribution process, and the distributed data does not interfere with each other; Set the optimal threshold range for the popularity of live stream content and compare it with the overall popularity of the live stream content: If no live content popularity index exists, then obtain the index data of the live content popularity index, distribute the distribution data according to the index data, and generate a scheduling signal.

[0022] Conversely, no action is taken.

[0023] The process by which the early warning module issues early warnings for live broadcast content based on scheduling signals includes: The system obtains scheduling signals through a preset management terminal, acquires distribution data based on the scheduling signals, and acquires early warning data through the distribution data. The early warning data includes live dynamic traffic distribution, live dynamic regional distribution, and live dynamic time period distribution.

[0024] Working principle: The video live streaming content update module obtains the best audio and video playback from various platforms; it also obtains the live streaming content with the best playback audio and video playback; then it obtains the popularity of the live streaming content; the intelligent scheduling module sets up a platform distribution channel network, and obtains the distribution data of the popularity of the live streaming content through the platform distribution channel network; finally, the early warning module issues early warnings for the live streaming content based on the scheduling signals.

[0025] The features and exemplary embodiments of various aspects of this application will be described in detail above. In order to make the purpose, technical solution and advantages of this application clearer, the application will be further described in detail above with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit this application. For those skilled in the art, this application can be implemented without some of the details in these specific details. The above description of the embodiments is only to provide a better understanding of this application by showing examples of this application.

[0026] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A cloud-based intelligent scheduling system for content distribution on a live video streaming platform, characterized in that, The system includes a video live streaming content update module, an intelligent scheduling module, and an early warning module; The video live streaming content update module is used to obtain the best audio and video playback for live streaming from various platforms. And obtain the best audio and video playback content for live streams; thereby obtaining the popularity of the live stream content; The intelligent scheduling module is equipped with a platform distribution channel network, which is used to obtain distribution data on the popularity of live content through the platform distribution channel network. The early warning module is used to issue early warnings for live broadcast content based on scheduling signals.

2. The intelligent scheduling system for content distribution of a cloud-based video live streaming platform according to claim 1, characterized in that, The process by which the video live streaming content update unit obtains the best audio and video playback options for live streaming from various platforms includes: The original audio and video of the live stream content and the original converted multi-bitrate stream are obtained through a video live streaming device; the original converted multi-bitrate stream includes the original resolution, the original bitrate, and the original encoding format; The original audio and video are converted into original playback audio and video through original conversion multi-bitrate stream; the actual playback information data of the original playback audio and video on each platform is obtained; The platform is configured to automatically update multi-bitrate units, and these units contain an adjustable multi-bitrate database corresponding to the actual playback information. The adjustable multi-bitrate database consists of actual playback information data, the platform's optimal multi-bitrate, and adjustable multi-bitrates. The adjustable multi-bitrates are configured with corresponding adjustable multi-bitrate ranges. The platform automatically updates the multi-bitrate unit to obtain actual playback information data, obtains the difference between the actual playback information data and the platform's optimal multi-bitrate, and marks it as the multi-bitrate difference; then matches the multi-bitrate difference with the corresponding adjustment multi-bitrate range, and then adjusts the actual playback information data according to the adjustment multi-bitrate to obtain the best playback audio and video of the original playback audio and video.

3. The intelligent scheduling system for content distribution of a cloud-based video live streaming platform according to claim 2, characterized in that, The process of obtaining the best audio and video playback quality for live stream content, and subsequently, the popularity of that live stream content, includes: The live stream content includes live stream metadata, live stream master data, live stream interaction data, and live stream volume control data; the live stream master data includes the live stream content type and live stream time period; the live stream volume control data includes live stream content instructions and live stream content index; the live stream interaction data includes the number of live stream viewers, the number of bullet comments, the amount of gifts, and the amount of live stream chat text. Obtain historical live stream master data from various platforms, and from this data, obtain several historical live stream content types and several historical live stream time periods for each content type. Then, obtain the number of historical time periods for each content period and sort the historical time period data from largest to smallest to determine the popularity of the corresponding live stream content type on each platform during those time periods. Set the popularity value for each type of live stream content, and the popularity value for each corresponding time period.

4. The intelligent scheduling system for content distribution of a cloud-based video live streaming platform according to claim 3, characterized in that, The popularity of the live stream content is obtained by measuring the popularity values ​​of the live stream content by its type and time period. The specific formula is as follows: ； in, This indicates the popularity of the live stream content in terms of content type L and time period t. and These represent the welcome level values ​​for different types of events and the welcome level values ​​for different time periods, respectively. and Let be the weighting coefficients corresponding to the live stream content type and the live stream time period, respectively. .

5. The intelligent scheduling system for content distribution of a cloud-based video live streaming platform according to claim 4, characterized in that, The live stream traffic density corresponding to the live stream content time period is obtained by the number of bullet comments and the text volume of the two days of the live stream; then the live stream interaction data popularity is obtained by the number of live stream viewers, the amount of gifts, and the live stream traffic density. The specific formula is as follows: ； in, This represents the popularity of the live stream content in terms of live stream content type L and live stream time period t; b represents the coefficient, with a value of (0, 1); n, m and u represent the number of live stream viewers, the amount of gifts received and the live stream traffic density, respectively; r1, r2 and r3 represent the weight coefficients corresponding to the number of live stream viewers, the amount of gifts received and the live stream traffic density, respectively, and r1+r2+r3=1. The sum of the live stream host's popularity data and the live stream audience's popularity data is marked as the live stream content popularity.

6. The intelligent scheduling system for content distribution of a cloud-based video live streaming platform according to claim 5, characterized in that, The process of setting up the platform distribution channel network in the intelligent scheduling module includes: A distribution channel is set up to connect various platforms and generate a platform distribution channel network; distribution data is set up in the distribution channel; the distribution data includes live dynamic traffic distribution, live dynamic regional distribution, and live dynamic time period distribution; The distribution data is configured with corresponding live content instructions and live content indexes. The live content instructions are used to give instructions to the distribution data, and the live content indexes are used to index the index data of the live content corresponding to the popularity of the content.

7. The intelligent scheduling system for content distribution of a cloud-based video live streaming platform according to claim 6, characterized in that, The process of obtaining distribution data on the popularity of live streaming content through various platform distribution channels includes: Set the optimal threshold range for the popularity of live stream content and compare it with the overall popularity of the live stream content: If the popularity of the live content does not exist, then obtain the index data of the popularity of the live content, distribute the distribution data according to the index data, and generate a scheduling signal; Conversely, no action is taken.

8. The intelligent scheduling system for content distribution of a cloud-based video live streaming platform according to claim 7, characterized in that, The process by which the early warning module issues early warnings for live broadcast content based on scheduling signals includes: The system obtains scheduling signals through a preset management terminal, acquires distribution data based on the scheduling signals, and acquires early warning data through the distribution data. The early warning data includes live dynamic traffic distribution, live dynamic regional distribution, and live dynamic time period distribution.

Images