CN117834956A - Live video acceleration system and method for resource distribution and source return - Google Patents
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/239—Interfacing the upstream path of the transmission network, e.g. prioritizing client content requests
- H04N21/2393—Interfacing the upstream path of the transmission network, e.g. prioritizing client content requests involving handling client 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]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/21—Server components or server architectures
- H04N21/218—Source of audio or video content, e.g. local disk arrays
- H04N21/2187—Live feed
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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
- H04N21/231—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion
- H04N21/23106—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion involving caching operations
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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
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/262—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists
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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
- H04N21/25—Management operations performed by the server for facilitating the content distribution or administrating data related to end-users or client devices, e.g. end-user or client device authentication, learning user preferences for recommending movies
- H04N21/262—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists
- H04N21/26208—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists the scheduling operation being performed under constraints
- H04N21/26216—Content or additional data distribution scheduling, e.g. sending additional data at off-peak times, updating software modules, calculating the carousel transmission frequency, delaying a video stream transmission, generating play-lists the scheduling operation being performed under constraints involving the channel capacity, e.g. network bandwidth
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Abstract
The invention provides a live video acceleration system and a method for resource distribution and source return, comprising the following steps: the data request module is used for identifying live video access requests sent by different users and determining request contents of the different users and request heat values of the same live video stream; the resource distribution back source module is used for performing condition traversal on the live video content in the distributed cache node and the back source server when the request heat value reaches a preset threshold value, and synchronously distributing the request live video content to each user terminal by adopting a difference distribution back source strategy; the resource scheduling management module is used for monitoring the state trend of the live video content in each distributed cache node and the back source server in real time based on the issuing result, and carrying out load balancing adjustment on the live video content in the distributed cache nodes and the back source server based on the state trend of the live video content. The video access efficiency and accuracy are improved, the bandwidth consumption is reduced, and the viewing experience of the user is greatly improved.
Description
Technical Field
The invention relates to the technical field of data communication, in particular to a live video acceleration system and method for resource distribution and source return.
Background
At present, with the continuous development of the Internet, live videos are gradually rising, and the live videos are favored by the masses by acquiring more abundant contents and more efficient information;
compared with the traditional video, the live video has the content attribute and the social attribute, and the interactivity, the social property and the convenience of the live video are further enhanced by the burst of mobile live video, so that the live video can more effectively exert the social function of the live video;
however, when live video is emerging, the method has defects such as large user scale, frequent hot events, high user watching experience requirement, incapability of caching, higher transmission delay, large bandwidth consumption, unbalanced use and the like, so that problems of some live video occur, and the experience of watching the live video by a user is greatly reduced;
therefore, in order to overcome the defects, the invention provides a live video acceleration system and a live video acceleration method for distributing resources back to a source.
Disclosure of Invention
The invention provides a live video acceleration system and a method for resource distribution and source return, which are used for accurately and effectively determining specific live video contents which are required to be accessed by different users by identifying and analyzing live video access requests sent by different users, and secondly, uniformly processing requests of different users by determining request heat values of the same live video stream by different users, so that the efficiency of processing live video access requests of the users is improved, and finally, when the request heat values reach a preset threshold value, live video contents in a distributed cache node and a source return server are traversed according to the request contents of different users, so that live video contents required by different users are accurately and effectively issued to each user terminal by adopting a differential distribution source return strategy, the video access efficiency and accuracy are improved, the bandwidth consumption is reduced, the stable operation of the system is ensured, and the viewing experience of the users is greatly improved.
The invention provides a live video acceleration system of a resource distribution back source, which comprises the following components:
the data request module is used for identifying live video access requests sent by different users and determining request contents of the different users and request heat values of the same live video stream based on the identification results;
the resource distribution back source module is used for performing condition traversal on the live video content in the distributed cache node and the back source server based on the request content when the request heat value reaches a preset threshold value, and synchronously distributing the request live video content to each user terminal by adopting a difference distribution back source strategy based on a condition traversal result;
and the resource scheduling management module is used for monitoring the state trend of the live video content in each distributed cache node and the back source server in real time based on the issuing result, and carrying out load balancing adjustment on the live video content in the distributed cache nodes and the back source server based on the state trend of the live video content.
Preferably, a live video acceleration system of a resource distribution back source, a data request module, includes:
the request monitoring unit is used for acquiring the request proxy server, deploying the request proxy server at a preset program entrance, and monitoring live video access requests sent by different users at different time points in real time based on deployment results;
The request preprocessing unit is used for carrying out structural splitting on the monitored live video access request, extracting a request header in the live video access request, analyzing the request header and extracting a user terminal identifier and a user identifier;
the request caching unit is used for constructing a request index list based on the user terminal identification and the user identification, constructing index links of the live video access request, the user terminal identification and the user identification, and caching live video access requests sent by different users based on the index links.
Preferably, a live video acceleration system of a resource distribution back source, a data request module, includes:
the request analysis unit is used for extracting request protocols of live video access requests sent by different users and verifying access services of the live video access requests based on protocol characteristics of the request protocols;
a request identification unit for:
when the verification is passed, extracting request bodies in different live video access requests, and performing format conversion on the request bodies to obtain live video access request messages;
extracting key index parameters in the live video access request message, and determining context information of the live video access request message based on target semantics of the key index parameters;
And determining resource parameters of the live video access request based on the context information, determining a live platform, a live stream address and a live video type required by the user based on the resource parameters, obtaining request contents of different users, and completing identification of the live video access request.
Preferably, a live video acceleration system of a resource distribution back source, a data request module, includes:
a statistics unit for:
extracting semantic characterizations of request contents of different users, and determining live video access types of the different users based on the semantic characterizations;
grouping different users in the same access time period based on the live video access type as a classification index, and marking a corresponding user group by taking the live video access type as a group identifier;
and the request heat value determining unit is used for determining the statistic of the users in each user group based on the marking result and determining the request heat value of different users for the corresponding live video stream based on the statistic of the users in each user group.
Preferably, a live video acceleration system of a resource distribution back source, the resource distribution back source module includes:
the condition triggering unit is used for synchronously triggering a resource source returning mechanism when the request heat value reaches a preset threshold value, analyzing condition traversal based on a triggering result, and determining traversal priority and traversal termination conditions of the distributed cache nodes and the source returning server, wherein the priority of the distributed cache nodes is higher than that of the source returning server;
A traversing unit for:
performing first traversal on the distributed cache nodes based on the traversal priority, and selectively performing second traversal on the back source server based on a first traversal result;
when a first traversal is performed for a distributed cache node:
extracting tree structure characteristics of the distributed cache nodes, and determining traversing paths of each cache node in the distributed cache nodes based on the tree structure characteristics;
traversing the distributed cache nodes based on the traversing paths, matching the traversing result of each cache node with traversing termination conditions, and feeding back the request live video content corresponding to the traversing result to different user terminals when the traversing result is matched with the traversing termination conditions;
when the traversing of the distributed cache node is completed and no matching result exists with the traversing termination condition, synchronously triggering second traversing of the source returning server, and generating a data access index based on the request content;
a data query engine is called based on the data access index to query the live video resources in the back source server, and the request live video content is obtained based on the query result;
and after synchronously caching the requested live video content at the distributed caching nodes, feeding back the requested live video content corresponding to the traversing result to different user terminals, recording the query result in a source return server, constructing a resource query verification strategy based on the recording result, and rejecting the query request when repeated query exists after a preset time period.
Preferably, a live video acceleration system of a resource distribution back source, a traversing unit, includes:
the result acquisition subunit is used for acquiring the request live video content obtained from the source return server and the position attribute of the distributed cache node, and determining the coverage area of the distributed cache node based on the position attribute;
a resource cache subunit configured to:
determining actual geographic positions of different users based on communication terminal addresses of different user terminals, and determining target cache nodes based on the actual geographic positions and the relative position relation of coverage areas;
the central server corresponding to the target cache node is used as a data forwarding center to be in butt joint with the back source server, and the request live video content is distributed and issued to the target cache node for caching according to the central server based on the butt joint result;
and the data distribution subunit is used for converting the requested live video content into a real-time live video stream based on the caching result and transmitting the real-time live video stream to different user terminals based on a preset streaming transmission protocol.
Preferably, a live video acceleration system of a resource distribution back source, the resource distribution back source module includes:
The link bandwidth acquisition unit is used for acquiring the link bandwidth of the corresponding communication link issued to each user terminal in real time when the live video content is synchronously issued to each user terminal;
an average bandwidth determining unit, configured to calculate an average bandwidth of the communication link based on the link bandwidth of the communication link corresponding to each user terminal;
a speed determining unit for:
determining an average speed required when the requested live video content is synchronously issued to each user terminal according to the average bandwidth;
acquiring a historical average speed when the historical request live video content is synchronously issued to each user terminal;
an optimization reminding unit for:
comparing the average speed required by synchronously issuing the current request live video content to each user terminal with the historical average speed;
and when the comparison result shows that the average speed required by the current request live video content to be synchronously issued to each user terminal is smaller than the historical average speed, generating a reminding instruction, and sending the reminding instruction to the management terminal for optimized reminding.
Preferably, a live video acceleration system of a resource distribution back source, a resource scheduling management module, includes:
a historical data analysis unit for:
Acquiring historical access data of each distributed cache node and each back source server, and splitting the historical access data based on an observation time period to respectively obtain parameter comparison groups of each distributed cache node and each back source server;
performing analogy analysis on the historical access data in each parameter comparison group to obtain the change trend of the data in each observation time period and the access behavior characteristics of the user, and determining the access mutation quantity of the user to the hot content based on the change trend of the data in each observation time period and the access behavior characteristics of the user;
the model construction unit is used for extracting configuration parameters of each distributed cache node and the back source server, determining auxiliary analysis indexes based on the configuration parameters, and constructing a load state prediction model based on the change trend of data in each observation time period, the access behavior characteristics of the user, the access mutation quantity of the user to the hot content and the auxiliary analysis indexes;
the state prediction unit is used for acquiring the operation parameters of the live video content in each distributed cache node and the back source server, inputting the operation parameters of the live video content into the load state prediction model for analysis, and obtaining the state trend of the live video content in each distributed cache node and the back source server.
Preferably, a live video acceleration system of a resource distribution back source, a resource scheduling management module, includes:
the state analysis unit is used for acquiring the obtained state trend of the live video content in each distributed cache node and the live video content in the live video content server at the current moment, the access flow of different users to each distributed cache node and the live video content server, and determining theoretical load values of each distributed cache node and the live video content server based on the access flow and the state trend of the live video content;
the load balancing unit is used for carrying out self-adaptive capacity scaling on each distributed cache node and the back source server based on the theoretical load value and carrying out dynamic mobilization on the live video content based on the self-adaptive capacity scaling result;
and the dynamic monitoring unit is used for polling the loads of the distributed cache nodes and the back source server based on a preset time interval after dynamic mobilization, dynamically triggering a load balancing adjustment mechanism based on polling results, and completing the real-time dynamic load balancing adjustment of the live video content in the distributed cache nodes and the back source server.
The invention provides a live video acceleration method of a resource distribution back source, which comprises the following steps:
Step 1: identifying live video access requests sent by different users, and determining request contents of the different users and request heat values of the same live video stream based on identification results;
step 2: when the request heat value reaches a preset threshold, performing conditional traversal on the live video content in the distributed cache node and the back source server based on the request content, and synchronously transmitting the request live video content to each user terminal by adopting a differential distribution back source strategy based on a conditional traversal result;
step 3: and monitoring the state trend of the live video content in each distributed cache node and the back source server in real time based on the issuing result, and carrying out load balancing adjustment on the live video content in the distributed cache nodes and the back source server based on the state trend of the live video content.
Compared with the prior art, the invention has the following beneficial effects:
1. the live video access requests sent by different users are identified and analyzed, the accurate and effective determination of specific live video contents required to be accessed by the different users is realized, secondly, the unified processing of the requests of the different users is realized by determining the request heat values of the same live video stream by the different users, the processing efficiency of the live video access requests of the users is improved, finally, when the request heat values reach a preset threshold value, the live video contents in the distributed cache nodes and the back source server are traversed according to the request contents of the different users, the accurate and effective issuing of the live video contents required by the different users to each user terminal by adopting a differential distribution back source strategy is realized, the video access efficiency and accuracy are improved, the bandwidth consumption is reduced, the load balancing adjustment of the live video contents in each distributed cache node and the back source server is ensured, the stable operation of the system is ensured, and the viewing experience of the users is greatly improved.
2. The method comprises the steps of triggering a resource source returning mechanism when a request heat value reaches a preset threshold value, analyzing condition traversal according to a triggering result, accurately and effectively determining traversal priorities and traversal termination conditions of a distributed cache node and a source returning server, secondly, traversing the distributed cache node and the source returning server under corresponding conditions according to the traversal priorities, matching each traversal result with the traversal termination conditions, stopping traversal in time when the traversal termination conditions are met, improving traversal efficiency and accuracy, and finally, recording traversal query results in the source returning server after traversing the source returning server, so that traversal query can be directly performed in the corresponding distributed cache node when a user requests again, the efficiency of traversal query is ensured, different types of live video contents are accurately and reliably issued to corresponding user terminals, and bandwidth consumption is reduced.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objects and other advantages of the invention may be realized and obtained by means of the instrumentalities particularly pointed out in the specification.
The technical scheme of the invention is further described in detail through the drawings and the embodiments.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate the invention and together with the embodiments of the invention, serve to explain the invention. In the drawings:
fig. 1 is a block diagram of a live video acceleration system with a resource distribution back to a source in an embodiment of the present invention;
fig. 2 is a block diagram of a data request module in a live video acceleration system with a resource distribution back to a source according to an embodiment of the present invention;
fig. 3 is a flowchart of a live video acceleration method of resource distribution and source return in an embodiment of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, it being understood that the preferred embodiments described herein are for illustration and explanation of the present invention only, and are not intended to limit the present invention.
Example 1:
the embodiment provides a live video acceleration system for distributing resources back to a source, as shown in fig. 1, including:
the data request module is used for identifying live video access requests sent by different users and determining request contents of the different users and request heat values of the same live video stream based on the identification results;
The resource distribution back source module is used for performing condition traversal on the live video content in the distributed cache node and the back source server based on the request content when the request heat value reaches a preset threshold value, and synchronously distributing the request live video content to each user terminal by adopting a difference distribution back source strategy based on a condition traversal result;
and the resource scheduling management module is used for monitoring the state trend of the live video content in each distributed cache node and the back source server in real time based on the issuing result, and carrying out load balancing adjustment on the live video content in the distributed cache nodes and the back source server based on the state trend of the live video content.
In this embodiment, the live video access requests are sent by different users, and are used to characterize the type of live video that needs to be accessed, etc.
In this embodiment, the request content refers to the specific content of the live video to be accessed specifically and represented by the live video access request, and the type of the live video, for example, the request content may be live video with a product, and the live content may be snack, etc.
In this embodiment, the request heating value refers to the amount of users accessing the same live video stream, and the more the amount of users, the higher the request heating value is characterized.
In this embodiment, the live video stream refers to a real-time audio/video data stream, which is used to transmit real-time audio/video content to the viewer through a network.
In this embodiment, the preset threshold is set in advance, so as to represent the minimum condition for traversing the live content, that is, the minimum number of users accessing the same live video stream.
In this embodiment, the distributed cache nodes are set in advance, and are not unique, and are used for storing different types of live video.
In this embodiment, the source-returning server is set in advance, and is a unit of a higher level of the distributed cache node, and is used for storing live video existing in the distributed cache node and live video not existing in the distributed cache node, where the type and content of the stored live video are higher than those of the distributed cache node.
In this embodiment, the condition traversal refers to querying live video content in the distributed cache node and the back source server by adopting different traversal strategies according to different conditions, specifically may be querying live video content in the distributed cache node first, and traversing live video content in the back source server only when no live video content consistent with the user request content exists in the distributed cache node, and traversing live video content in the back source server only once.
In this embodiment, the differential distribution back source policy refers to that live video traversed from the distributed cache node and the back source server is distributed to the user terminal by adopting different distribution policies according to the condition traversal result, where the distribution steps in the differential distribution policies are different.
In this embodiment, the status trend of the live video content refers to the change condition of the live video content in each distributed cache node and the back source server under the access amount of the user, and the like.
In this embodiment, load balancing adjustment refers to when a distributed cache node or a back source server is more idle, scheduling live video content in the distributed cache node or the back source server with higher load to the more idle distributed cache node or back source server, so as to implement load balancing adjustment.
The beneficial effects of the technical scheme are as follows: the live video access requests sent by different users are identified and analyzed, the accurate and effective determination of specific live video contents required to be accessed by the different users is realized, secondly, the unified processing of the requests of the different users is realized by determining the request heat values of the same live video stream by the different users, the processing efficiency of the live video access requests of the users is improved, finally, when the request heat values reach a preset threshold value, the live video contents in the distributed cache nodes and the back source server are traversed according to the request contents of the different users, the accurate and effective issuing of the live video contents required by the different users to each user terminal by adopting a differential distribution back source strategy is realized, the video access efficiency and accuracy are improved, the bandwidth consumption is reduced, the load balancing adjustment of the live video contents in each distributed cache node and the back source server is ensured, the stable operation of the system is ensured, and the viewing experience of the users is greatly improved.
Example 2:
on the basis of embodiment 1, this embodiment provides a live video acceleration system of a resource distribution back source, and a data request module, including:
the request monitoring unit is used for acquiring the request proxy server, deploying the request proxy server at a preset program entrance, and monitoring live video access requests sent by different users at different time points in real time based on deployment results;
the request preprocessing unit is used for carrying out structural splitting on the monitored live video access request, extracting a request header in the live video access request, analyzing the request header and extracting a user terminal identifier and a user identifier;
the request caching unit is used for constructing a request index list based on the user terminal identification and the user identification, constructing index links of the live video access request, the user terminal identification and the user identification, and caching live video access requests sent by different users based on the index links.
In this embodiment, the request proxy server is set in advance, and is configured to receive live video access requests sent by different users at different times.
In this embodiment, the preset program entry is set in advance, and is a port for interfacing the request proxy server with the live video acceleration system of the resource distribution return source, so that the live video access request sent by the user can be effectively forwarded to the live video acceleration system of the resource distribution return source for analysis and processing through the request proxy server.
In this embodiment, the splitting of the structure refers to splitting the obtained live video access request into a request header and a request body, where the request header may be source information characterizing the live video access request, for example, may be user communication address information, etc., and the request body may be specific request content characterizing the live video access request, for example, may be a request type and live video content to be accessed.
In this embodiment, the user terminal identification refers to a marking symbol for marking a terminal type or distinguishing between different user terminals.
In this embodiment, the user identifiers are marking symbols for distinguishing different user identities, and each user corresponds to one user identifier.
In this embodiment, the request index list is constructed according to the user terminal identifier and the user identifier, and is used for recording terminal identity information and user identity information corresponding to different users.
In this embodiment, the index link refers to a link obtained by associating live video access requests sent by different users with corresponding user terminal identifiers and user identifiers, and when the live video access requests need to be processed, the live video access requests corresponding to different users can be quickly retrieved and processed according to the user terminal identifiers and the user identifiers.
The beneficial effects of the technical scheme are as follows: the live video access requests sent by different users at different time points are received through the request proxy server, the received live video access requests are analyzed and processed, the user terminal identification and the user identification are accurately and effectively determined, meanwhile, a request index list is built according to the user terminal identification and the user identification, the live video access requests, the user terminal identification and the user identification are subjected to index linking, and the live video access requests sent by different users are effectively managed and cached, so that unified processing is facilitated when the request heat value is achieved, and the processing efficiency is improved.
Example 3:
on the basis of embodiment 1, this embodiment provides a live video acceleration system for distributing resources back to a source, as shown in fig. 2, a data request module includes:
the request analysis unit is used for extracting request protocols of live video access requests sent by different users and verifying access services of the live video access requests based on protocol characteristics of the request protocols;
a request identification unit for:
when the verification is passed, extracting request bodies in different live video access requests, and performing format conversion on the request bodies to obtain live video access request messages;
Extracting key index parameters in the live video access request message, and determining context information of the live video access request message based on target semantics of the key index parameters;
and determining resource parameters of the live video access request based on the context information, determining a live platform, a live stream address and a live video type required by the user based on the resource parameters, obtaining request contents of different users, and completing identification of the live video access request.
In this embodiment, the request protocol refers to a protocol used by a user when sending a live video access request, and defines rules and formats of interaction between the user terminal and the request proxy server, and an access type of a current request, including a request method, a request header, a request body, and the like.
In this embodiment, the protocol feature refers to specific rule content defined by the request protocol and specific data content contained therein.
In this embodiment, the access service refers to an access item represented by a live video access request, and is a basis for determining whether a currently received live video access request is for accessing live video content.
In this embodiment, the request body refers to a specific live video type and content to be accessed defined in the live video access request.
In this embodiment, the live video access request message refers to data information, which is obtained after format conversion of the live video access request and is consistent with the content of the live video access request but different in format.
In this embodiment, the key index parameter refers to a data segment in the live video access request, which can characterize the access purpose of the user.
In this embodiment, the target semantics refer to specific core content corresponding to the key index parameters.
In this embodiment, the context information refers to the logical relationship of data in the live video access request message.
In this embodiment, the resource parameters include a live platform, a live stream address, and a live video type required by the user.
The beneficial effects of the technical scheme are as follows: the request protocols of the live video access requests submitted by different users are determined, the access service of the live video access requests is checked through the request protocols, the live video access requests of the obtained users are ensured to be accessed to live videos, then, when the verification is passed, the live video access requests are analyzed, the accurate and effective determination of the resource parameters expressed by the users through the live video access requests is realized, so that the accuracy of returning the request content of the users is ensured, and compared with the method for calling the corresponding live videos according to the request content of the users, the accuracy of video access is improved.
Example 4:
on the basis of embodiment 1, this embodiment provides a live video acceleration system of a resource distribution back source, and a data request module, including:
a statistics unit for:
extracting semantic characterizations of request contents of different users, and determining live video access types of the different users based on the semantic characterizations;
grouping different users in the same access time period based on the live video access type as a classification index, and marking a corresponding user group by taking the live video access type as a group identifier;
and the request heat value determining unit is used for determining the statistic of the users in each user group based on the marking result and determining the request heat value of different users for the corresponding live video stream based on the statistic of the users in each user group.
In this embodiment, the semantic token refers to the subject content corresponding to the requested content, i.e., the request destination of the requested content token.
In this embodiment, the group identifier is a tag for marking the type of live video access to which the current user group corresponds.
In this embodiment, the statistics refer to the number of users included in each user group, where the number of users is proportional to the requested heating value.
The beneficial effects of the technical scheme are as follows: the method has the advantages that the request content of different users is analyzed, the live video access types of the different users are accurately and effectively determined, the different users are grouped according to the index video access types, and the request heat values of the different live video access types are accurately and effectively judged, so that the system is convenient to uniformly process a plurality of users, the live video access request processing efficiency is improved, and the user watching experience is improved.
Example 5:
on the basis of embodiment 1, this embodiment provides a live video acceleration system of a resource distribution back source, where the resource distribution back source module includes:
the condition triggering unit is used for synchronously triggering a resource source returning mechanism when the request heat value reaches a preset threshold value, analyzing condition traversal based on a triggering result, and determining traversal priority and traversal termination conditions of the distributed cache nodes and the source returning server, wherein the priority of the distributed cache nodes is higher than that of the source returning server;
a traversing unit for:
performing first traversal on the distributed cache nodes based on the traversal priority, and selectively performing second traversal on the back source server based on a first traversal result;
When a first traversal is performed for a distributed cache node:
extracting tree structure characteristics of the distributed cache nodes, and determining traversing paths of each cache node in the distributed cache nodes based on the tree structure characteristics;
traversing the distributed cache nodes based on the traversing paths, matching the traversing result of each cache node with traversing termination conditions, and feeding back the request live video content corresponding to the traversing result to different user terminals when the traversing result is matched with the traversing termination conditions;
when the traversing of the distributed cache node is completed and no matching result exists with the traversing termination condition, synchronously triggering second traversing of the source returning server, and generating a data access index based on the request content;
a data query engine is called based on the data access index to query the live video resources in the back source server, and the request live video content is obtained based on the query result;
and after synchronously caching the requested live video content at the distributed caching nodes, feeding back the requested live video content corresponding to the traversing result to different user terminals, recording the query result in a source return server, constructing a resource query verification strategy based on the recording result, and rejecting the query request when repeated query exists after a preset time period.
In this embodiment, the resource source-returning mechanism refers to a program that queries live video content in the distributed cache node and the source-returning server.
In this embodiment, the traversal priority is used to characterize the sequence of traversal of the distributed cache nodes and the back-source server.
In this embodiment, the traversal termination condition is a measurement parameter for characterizing that the traversal of the live video content is stopped, for example, when the live video content required by the user is queried.
In this embodiment, the first traversal refers to traversing live video content in the distributed cache node according to a live video access request of a user.
In this embodiment, selectively performing the second traversal on the back source server based on the first traversal result refers to not performing the second traversal on the live video content in the back source server when the first traversal result obtains the live video content required by the user, but performing the second traversal on the back source server when the first traversal result does not obtain the live video content required by the user.
In this embodiment, the tree structure features are used to characterize the relative positional relationship between distributed cache nodes, so that it is convenient to perform an effective traversal query on each node once during traversal of the distributed cache nodes.
In this embodiment, the traversal path refers to a path for traversing each cache node in the distributed cache nodes, so as to ensure that all the cache nodes can be traversed, that is, the traversal efficiency is improved, and the comprehensiveness of the traversal is ensured, for example, the traversal may be performed in a preamble or a middle-order.
In this embodiment, the second traversal refers to traversing the live video content in the back source server when the first traversal result does not query the live video content required by the user.
In this embodiment, the data access index is generated according to the content requested by the user and is used to access the back source server.
In this embodiment, the data query engine is set in advance, and is a tool for performing traversal query on live video content in the back source server.
In this embodiment, the request live video content corresponding to the traversal result is fed back to different user terminals, and the same live video content is synchronously issued to each user terminal.
In this embodiment, the resource query verification policy refers to recording the queried live video content in the back source server, so that when the same live video content needs to be queried again, the corresponding traversal query can be directly performed in the distributed cache node without performing the traversal query in the back source server, so as to improve the efficiency of determining the live video content.
In this embodiment, the preset time period is set in advance.
The beneficial effects of the technical scheme are as follows: the method comprises the steps of triggering a resource source returning mechanism when a request heat value reaches a preset threshold value, analyzing condition traversal according to a triggering result, accurately and effectively determining traversal priorities and traversal termination conditions of a distributed cache node and a source returning server, secondly, traversing the distributed cache node and the source returning server under corresponding conditions according to the traversal priorities, matching each traversal result with the traversal termination conditions, stopping traversal in time when the traversal termination conditions are met, improving traversal efficiency and accuracy, and finally, recording traversal query results in the source returning server after traversing the source returning server, so that traversal query can be directly performed in the corresponding distributed cache node when a user requests again, the efficiency of traversal query is ensured, different types of live video contents are accurately and reliably issued to corresponding user terminals, and bandwidth consumption is reduced.
Example 6:
on the basis of embodiment 5, this embodiment provides a live video acceleration system for distributing resources back to a source, and a traversal unit, including:
The result acquisition subunit is used for acquiring the request live video content obtained from the source return server and the position attribute of the distributed cache node, and determining the coverage area of the distributed cache node based on the position attribute;
a resource cache subunit configured to:
determining actual geographic positions of different users based on communication terminal addresses of different user terminals, and determining target cache nodes based on the actual geographic positions and the relative position relation of coverage areas;
the central server corresponding to the target cache node is used as a data forwarding center to be in butt joint with the back source server, and the request live video content is distributed and issued to the target cache node for caching according to the central server based on the butt joint result;
and the data distribution subunit is used for converting the requested live video content into a real-time live video stream based on the caching result and transmitting the real-time live video stream to different user terminals based on a preset streaming transmission protocol.
In this embodiment, the location attribute refers to a specific location where different cache nodes are located in the entire distributed cache node system, and may be that a region corresponds to multiple cache nodes.
In this embodiment, the coverage area refers to an area range that can be covered by the distributed cache node, so that it is convenient to determine, among all the cache nodes, the cache node closest to the user terminal.
In this embodiment, the actual geographic location information refers to a specific geographic location corresponding to a different user terminal, so as to determine an optimal cache node corresponding to the different user terminal (i.e., a cache node closest to the user terminal) according to the actual geographic location information and a location attribute of a distributed cache node, thereby implementing caching of the product video content invoked from the back source server in the optimal cache node, where the target cache node is the determined optimal cache node.
In this embodiment, the live video streaming refers to format conversion of cached requested live video content, so as to facilitate transmission of the requested live video content, and ensure that content received by a user is real-time video data and voice data.
In this embodiment, the preset streaming protocol is set in advance, and is used to characterize a transmission mode, a transmission condition, and the like for the live video stream.
The beneficial effects of the technical scheme are as follows: the method has the advantages that through determining the position attribute of each cache node in the distributed cache nodes and the actual geographic position of different users, the target cache nodes corresponding to the different users are accurately and effectively determined according to the position attribute and the actual geographic position, secondly, the request live video content traversed from the source return server is cached in the target cache nodes, the different users can acquire the corresponding request live video content nearby, the efficiency and the reliability of resource distribution source return are improved, finally, the cached request live video content is subjected to format conversion, and the real-time live video stream is transmitted to different user terminals through a preset streaming protocol, so that the time delay is reduced, the video acquisition accuracy of the different users is guaranteed, and the viewing experience is improved.
Example 7:
on the basis of embodiment 1, this embodiment provides a live video acceleration system of a resource distribution back source, where the resource distribution back source module includes:
the link bandwidth acquisition unit is used for acquiring the link bandwidth of the corresponding communication link issued to each user terminal in real time when the live video content is synchronously issued to each user terminal;
an average bandwidth determining unit, configured to calculate an average bandwidth of the communication link based on the link bandwidth of the communication link corresponding to each user terminal;
a speed determining unit for:
determining an average speed required when the requested live video content is synchronously issued to each user terminal according to the average bandwidth;
acquiring a historical average speed when the historical request live video content is synchronously issued to each user terminal;
an optimization reminding unit for:
comparing the average speed required by synchronously issuing the current request live video content to each user terminal with the historical average speed;
and when the comparison result shows that the average speed required by the current request live video content to be synchronously issued to each user terminal is smaller than the historical average speed, generating a reminding instruction, and sending the reminding instruction to the management terminal for optimized reminding.
In this embodiment, the average speed required when synchronously delivering the requested live video content to each user terminal is determined according to the average bandwidth refers to the amount of live video content data transmitted per second by the communication link that is determined while not taking other influencing factors into account, where the other influencing factors may be network delay, network congestion, and the like.
In this embodiment, the historical average delivery is determined according to the transmission parameters sent by the historical request live video content to each user terminal, for example, the historical average delivery may be finally determined by combining the transmission bandwidth and the network delay.
The beneficial effects of the technical scheme are as follows: the transmission bandwidth of each communication link is determined when the live video content is required to be distributed, so that the average bandwidth of the communication links in the live video acceleration system is effectively determined, the average bandwidth is converted into the average speed and then is compared with the historical average speed, the issuing efficiency of the live video content is accurately and effectively judged according to the comparison result, and finally, when the average speed is smaller than the historical average speed, the management terminal is optimally reminded, so that the bandwidth consumption is effectively reduced, and the issuing efficiency of the live video content is improved.
Example 8:
on the basis of embodiment 1, this embodiment provides a live video acceleration system of a resource distribution back source, and a resource scheduling management module includes:
a historical data analysis unit for:
acquiring historical access data of each distributed cache node and each back source server, and splitting the historical access data based on an observation time period to respectively obtain parameter comparison groups of each distributed cache node and each back source server;
performing analogy analysis on the historical access data in each parameter comparison group to obtain the change trend of the data in each observation time period and the access behavior characteristics of the user, and determining the access mutation quantity of the user to the hot content based on the change trend of the data in each observation time period and the access behavior characteristics of the user;
the model construction unit is used for extracting configuration parameters of each distributed cache node and the back source server, determining auxiliary analysis indexes based on the configuration parameters, and constructing a load state prediction model based on the change trend of data in each observation time period, the access behavior characteristics of the user, the access mutation quantity of the user to the hot content and the auxiliary analysis indexes;
the state prediction unit is used for acquiring the operation parameters of the live video content in each distributed cache node and the back source server, inputting the operation parameters of the live video content into the load state prediction model for analysis, and obtaining the state trend of the live video content in each distributed cache node and the back source server.
In this embodiment, the historical access data refers to the frequency and access amount of the live video content in each distributed cache node and the back source server that was accessed in the past period of time, and the like.
In this embodiment, the observation period is set in advance, and may be, for example, one observation period every ten minutes.
In this embodiment, the parameter comparison group refers to a comparison group parameter obtained when the historical access data is split according to the observation time period and the split results corresponding to different observation time periods are compared.
In this embodiment, the change trend of the data refers to a change trend of the value of the history access data, a change trend of the access amount, and the like.
In this embodiment, the user access behavior feature refers to a sudden change of the user access amount or live video content or the like accessed by a large amount of users in each observation period.
In this embodiment, the access mutation amount refers to a steep change amount of the number of users accessing the current live video content in a certain time, and may be, for example, an increase of ten thousand access amounts in one minute.
In this embodiment, the configuration parameters refer to the maximum load capacity of the distributed cache node and the back source server for live video content and the maximum amount of access that can be received by the user.
In this embodiment, the auxiliary analysis index may be network traffic, server resource utilization, bandwidth usage, etc.
In this embodiment, the operation parameters refer to the data amount of the live video content in each of the distributed cache nodes and the back source server currently, the user amount of the video content currently accessed as an index, and the like.
The beneficial effects of the technical scheme are as follows: by splitting and analogically analyzing historical access data of each distributed cache node and the back source server, the change trend of the data under different conditions, the access behavior characteristics of the user, the access mutation quantity of the user to the hot content and the auxiliary analysis index are accurately and effectively confirmed, a load state prediction model is constructed according to the confirmation result, the operation parameters of live video content in each current distributed cache node and the back source server are analyzed through the load state prediction model, the accurate and effective acquisition of the state trend of the live video content in each distributed cache node and the back source server is realized, and reliable guarantee is provided for load balancing.
Example 9:
on the basis of embodiment 1, this embodiment provides a live video acceleration system of a resource distribution back source, and a resource scheduling management module includes:
The state analysis unit is used for acquiring the obtained state trend of the live video content in each distributed cache node and the live video content in the live video content server at the current moment, the access flow of different users to each distributed cache node and the live video content server, and determining theoretical load values of each distributed cache node and the live video content server based on the access flow and the state trend of the live video content;
the load balancing unit is used for carrying out self-adaptive capacity scaling on each distributed cache node and the back source server based on the theoretical load value and carrying out dynamic mobilization on the live video content based on the self-adaptive capacity scaling result;
and the dynamic monitoring unit is used for polling the loads of the distributed cache nodes and the back source server based on a preset time interval after dynamic mobilization, dynamically triggering a load balancing adjustment mechanism based on polling results, and completing the real-time dynamic load balancing adjustment of the live video content in the distributed cache nodes and the back source server.
In this embodiment, the theoretical load value refers to the number of live video contents that should be cached by each distributed cache node and the back source server under the current access amount, and the maximum access amount that each distributed cache node and the back source server can carry.
In this embodiment, the adaptive capacity scaling refers to properly expanding the bearer capacity when the currently required live video content and the user access amount in each of the distributed cache nodes and the back source server exceed the maximum load, and simultaneously, properly reducing the volumes of the cache nodes and the back source server with smaller access amount, so as to ensure stable operation.
In this embodiment, the preset time interval is set in advance.
In this embodiment, polling refers to dynamically checking the real-time load conditions of each cache node and the back source server, so that when overload occurs, dynamic deployment is performed in time.
The beneficial effects of the technical scheme are as follows: by determining theoretical load values of the distributed cache nodes and the back source server and carrying out self-adaptive capacity scaling on the distributed cache nodes and the back source server according to the theoretical load values and the state trend of the live video content in the distributed cache nodes and the back source server, dynamic mobilization of the live video content in the distributed cache nodes and the back source server is realized, stable operation of a system is ensured, and different users are ensured to accurately and effectively acquire corresponding live video content.
Example 10:
the embodiment provides a live video acceleration method of a resource distribution return source, as shown in fig. 3, including:
step 1: identifying live video access requests sent by different users, and determining request contents of the different users and request heat values of the same live video stream based on identification results;
step 2: when the request heat value reaches a preset threshold, performing conditional traversal on the live video content in the distributed cache node and the back source server based on the request content, and synchronously transmitting the request live video content to each user terminal by adopting a differential distribution back source strategy based on a conditional traversal result;
step 3: and monitoring the state trend of the live video content in each distributed cache node and the back source server in real time based on the issuing result, and carrying out load balancing adjustment on the live video content in the distributed cache nodes and the back source server based on the state trend of the live video content.
The beneficial effects of the technical scheme are as follows: the live video access requests sent by different users are identified and analyzed, the accurate and effective determination of specific live video contents required to be accessed by the different users is realized, secondly, the unified processing of the requests of the different users is realized by determining the request heat values of the same live video stream by the different users, the processing efficiency of the live video access requests of the users is improved, finally, when the request heat values reach a preset threshold value, the live video contents in the distributed cache nodes and the back source server are traversed according to the request contents of the different users, the accurate and effective issuing of the live video contents required by the different users to each user terminal by adopting a differential distribution back source strategy is realized, the video access efficiency and accuracy are improved, the bandwidth consumption is reduced, the load balancing adjustment of the live video contents in each distributed cache node and the back source server is ensured, the stable operation of the system is ensured, and the viewing experience of the users is greatly improved.
It will be apparent to those skilled in the art that various modifications and variations can be made to the present invention without departing from the spirit or scope of the invention. Thus, it is intended that the present invention also include such modifications and alterations insofar as they come within the scope of the appended claims or the equivalents thereof.
Claims (10)
1. A live video acceleration system for distributing resources back to a source, comprising:
the data request module is used for identifying live video access requests sent by different users and determining request contents of the different users and request heat values of the same live video stream based on the identification results;
the resource distribution back source module is used for performing condition traversal on the live video content in the distributed cache node and the back source server based on the request content when the request heat value reaches a preset threshold value, and synchronously distributing the request live video content to each user terminal by adopting a difference distribution back source strategy based on a condition traversal result;
and the resource scheduling management module is used for monitoring the state trend of the live video content in each distributed cache node and the back source server in real time based on the issuing result, and carrying out load balancing adjustment on the live video content in the distributed cache nodes and the back source server based on the state trend of the live video content.
2. The live video acceleration system of claim 1, wherein the data request module comprises:
the request monitoring unit is used for acquiring the request proxy server, deploying the request proxy server at a preset program entrance, and monitoring live video access requests sent by different users at different time points in real time based on deployment results;
the request preprocessing unit is used for carrying out structural splitting on the monitored live video access request, extracting a request header in the live video access request, analyzing the request header and extracting a user terminal identifier and a user identifier;
the request caching unit is used for constructing a request index list based on the user terminal identification and the user identification, constructing index links of the live video access request, the user terminal identification and the user identification, and caching live video access requests sent by different users based on the index links.
3. The live video acceleration system of claim 1, wherein the data request module comprises:
the request analysis unit is used for extracting request protocols of live video access requests sent by different users and verifying access services of the live video access requests based on protocol characteristics of the request protocols;
A request identification unit for:
when the verification is passed, extracting request bodies in different live video access requests, and performing format conversion on the request bodies to obtain live video access request messages;
extracting key index parameters in the live video access request message, and determining context information of the live video access request message based on target semantics of the key index parameters;
and determining resource parameters of the live video access request based on the context information, determining a live platform, a live stream address and a live video type required by the user based on the resource parameters, obtaining request contents of different users, and completing identification of the live video access request.
4. The live video acceleration system of claim 1, wherein the data request module comprises:
a statistics unit for:
extracting semantic characterizations of request contents of different users, and determining live video access types of the different users based on the semantic characterizations;
grouping different users in the same access time period based on the live video access type as a classification index, and marking a corresponding user group by taking the live video access type as a group identifier;
And the request heat value determining unit is used for determining the statistic of the users in each user group based on the marking result and determining the request heat value of different users for the corresponding live video stream based on the statistic of the users in each user group.
5. The live video acceleration system of claim 1, wherein the resource distribution back to the source module comprises:
the condition triggering unit is used for synchronously triggering a resource source returning mechanism when the request heat value reaches a preset threshold value, analyzing condition traversal based on a triggering result, and determining traversal priority and traversal termination conditions of the distributed cache nodes and the source returning server, wherein the priority of the distributed cache nodes is higher than that of the source returning server;
a traversing unit for:
performing first traversal on the distributed cache nodes based on the traversal priority, and selectively performing second traversal on the back source server based on a first traversal result;
when a first traversal is performed for a distributed cache node:
extracting tree structure characteristics of the distributed cache nodes, and determining traversing paths of each cache node in the distributed cache nodes based on the tree structure characteristics;
traversing the distributed cache nodes based on the traversing paths, matching the traversing result of each cache node with traversing termination conditions, and feeding back the request live video content corresponding to the traversing result to different user terminals when the traversing result is matched with the traversing termination conditions;
When the traversing of the distributed cache node is completed and no matching result exists with the traversing termination condition, synchronously triggering second traversing of the source returning server, and generating a data access index based on the request content;
a data query engine is called based on the data access index to query the live video resources in the back source server, and the request live video content is obtained based on the query result;
and after synchronously caching the requested live video content at the distributed caching nodes, feeding back the requested live video content corresponding to the traversing result to different user terminals, recording the query result in a source return server, constructing a resource query verification strategy based on the recording result, and rejecting the query request when repeated query exists after a preset time period.
6. The live video acceleration system of claim 5, wherein the traversing unit comprises:
the result acquisition subunit is used for acquiring the request live video content obtained from the source return server and the position attribute of the distributed cache node, and determining the coverage area of the distributed cache node based on the position attribute;
a resource cache subunit configured to:
Determining actual geographic positions of different users based on communication terminal addresses of different user terminals, and determining target cache nodes based on the actual geographic positions and the relative position relation of coverage areas;
the central server corresponding to the target cache node is used as a data forwarding center to be in butt joint with the back source server, and the request live video content is distributed and issued to the target cache node for caching according to the central server based on the butt joint result;
and the data distribution subunit is used for converting the requested live video content into a real-time live video stream based on the caching result and transmitting the real-time live video stream to different user terminals based on a preset streaming transmission protocol.
7. The live video acceleration system of claim 1, wherein the resource distribution back to the source module comprises:
the link bandwidth acquisition unit is used for acquiring the link bandwidth of the corresponding communication link issued to each user terminal in real time when the live video content is synchronously issued to each user terminal;
an average bandwidth determining unit, configured to calculate an average bandwidth of the communication link based on the link bandwidth of the communication link corresponding to each user terminal;
A speed determining unit for:
determining an average speed required when the requested live video content is synchronously issued to each user terminal according to the average bandwidth;
acquiring a historical average speed when the historical request live video content is synchronously issued to each user terminal;
an optimization reminding unit for:
comparing the average speed required by synchronously issuing the current request live video content to each user terminal with the historical average speed;
and when the comparison result shows that the average speed required by the current request live video content to be synchronously issued to each user terminal is smaller than the historical average speed, generating a reminding instruction, and sending the reminding instruction to the management terminal for optimized reminding.
8. The live video acceleration system of claim 1, wherein the resource scheduling management module comprises:
a historical data analysis unit for:
acquiring historical access data of each distributed cache node and each back source server, and splitting the historical access data based on an observation time period to respectively obtain parameter comparison groups of each distributed cache node and each back source server;
performing analogy analysis on the historical access data in each parameter comparison group to obtain the change trend of the data in each observation time period and the access behavior characteristics of the user, and determining the access mutation quantity of the user to the hot content based on the change trend of the data in each observation time period and the access behavior characteristics of the user;
The model construction unit is used for extracting configuration parameters of each distributed cache node and the back source server, determining auxiliary analysis indexes based on the configuration parameters, and constructing a load state prediction model based on the change trend of data in each observation time period, the access behavior characteristics of the user, the access mutation quantity of the user to the hot content and the auxiliary analysis indexes;
the state prediction unit is used for acquiring the operation parameters of the live video content in each distributed cache node and the back source server, inputting the operation parameters of the live video content into the load state prediction model for analysis, and obtaining the state trend of the live video content in each distributed cache node and the back source server.
9. The live video acceleration system of claim 1, wherein the resource scheduling management module comprises:
the state analysis unit is used for acquiring the obtained state trend of the live video content in each distributed cache node and the live video content in the live video content server at the current moment, the access flow of different users to each distributed cache node and the live video content server, and determining theoretical load values of each distributed cache node and the live video content server based on the access flow and the state trend of the live video content;
The load balancing unit is used for carrying out self-adaptive capacity scaling on each distributed cache node and the back source server based on the theoretical load value and carrying out dynamic mobilization on the live video content based on the self-adaptive capacity scaling result;
and the dynamic monitoring unit is used for polling the loads of the distributed cache nodes and the back source server based on a preset time interval after dynamic mobilization, dynamically triggering a load balancing adjustment mechanism based on polling results, and completing the real-time dynamic load balancing adjustment of the live video content in the distributed cache nodes and the back source server.
10. The method for accelerating the live video of the resource distribution back source is characterized by comprising the following steps of:
step 1: identifying live video access requests sent by different users, and determining request contents of the different users and request heat values of the same live video stream based on identification results;
step 2: when the request heat value reaches a preset threshold, performing conditional traversal on the live video content in the distributed cache node and the back source server based on the request content, and synchronously transmitting the request live video content to each user terminal by adopting a differential distribution back source strategy based on a conditional traversal result;
Step 3: and monitoring the state trend of the live video content in each distributed cache node and the back source server in real time based on the issuing result, and carrying out load balancing adjustment on the live video content in the distributed cache nodes and the back source server based on the state trend of the live video content.
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