CN109246487A - A kind of intelligent dispatching system - Google Patents
A kind of intelligent dispatching system Download PDFInfo
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- CN109246487A CN109246487A CN201810937415.XA CN201810937415A CN109246487A CN 109246487 A CN109246487 A CN 109246487A CN 201810937415 A CN201810937415 A CN 201810937415A CN 109246487 A CN109246487 A CN 109246487A
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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]
- H04N21/80—Generation or processing of content or additional data by content creator independently of the distribution process; Content per se
- H04N21/83—Generation or processing of protective or descriptive data associated with content; Content structuring
- H04N21/845—Structuring of content, e.g. decomposing content into time segments
- H04N21/8456—Structuring of content, e.g. decomposing content into time segments by decomposing the content in the time domain, e.g. in time segments
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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
- H04N21/23103—Content storage operation, e.g. caching movies for short term storage, replicating data over plural servers, prioritizing data for deletion using load balancing strategies, e.g. by placing or distributing content on different disks, different memories or different servers
-
- 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
-
- 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
- H04N21/258—Client or end-user data management, e.g. managing client capabilities, user preferences or demographics, processing of multiple end-users preferences to derive collaborative data
- H04N21/25808—Management of client data
-
- 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
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- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Signal Processing (AREA)
- Databases & Information Systems (AREA)
- Computer Graphics (AREA)
- Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)
- Information Transfer Between Computers (AREA)
Abstract
The present invention relates to a kind of intelligent dispatching systems, including video server, management server, monitoring center, client, node administration module, cache module, scheduler module.Data are saved using Hadoop distributed file system, alleviate server stress.User data is acquired, then computation model intellectual analysis is used based on big data system, accomplishes to do optimal scheduling based on user link experience.
Description
Technical field
The present invention relates to artificial intelligence field more particularly to a kind of intelligent dispatching systems.
Background technique
At present in P2P stream media system, there is no so stringent differences for client and server-side, and a client is often
Also server-side is served as, provides data for other nodes.And in network the resources such as bandwidth, processing capacity, data of each node with
Time change all can be different, how to find suitable node as service node, this is an important problem.In addition,
The dynamic of each node in network, this is but also requesting node obtains the increasing of resource difficulty.Therefore, rationally effective stream matchmaker is formulated
Volume data scheduling mechanism is vital for stream media system.
At present in P2P stream media system data dispatch the problem is that: (1) when some node request resource when, by what
Kind sequentially requests resource；(2) when requesting a certain resource, multiple neighbor nodes can provide service simultaneously, how select rationally
Neighbor node receive resource, to reach the reasonable utilization of resource；(3) when requesting resource, how to be requested from other nodes
Data avoid sending to server and request, reduce the load of server.
Summary of the invention
In view of this, the present invention provides a kind of intelligent dispatching system solved or part solves the above problems.
To achieve the effect that above-mentioned technical proposal, the technical solution of the present invention is as follows: a kind of intelligent dispatching system, including video
Server, management server, monitoring center, client, node administration module, cache module, scheduler module；
Having multiple client, each client in intelligent dispatching system is exactly a node；Each client respectively and
Video server, management server, monitoring center are connected；Video server is connected with management server；Intelligent dispatching system benefit
Data are saved with Hadoop distributed file system, realize cloud computing using the Map Reduce in Hadoop；
Video server is for issuing and saving video file；Video file is divided into equal-sized by video server
Data block；Data block information is transferred to management server by video server；
Management server is used for managing customer client information；
Node administration module, cache module, scheduler module all integrate on the client；
Node administration module is used to manage the information of this node and partner node, registers to management server；Cache module
For caching data block, data block can also be forwarded for partner node, caching data block is real by Hadoop distributed file system
It is existing；Scheduler module sends request of data to corresponding partner node for formulating scheduling scheme, and according to scheduling scheme；
Intelligent dispatching system includes following work step:
1) user selects video distribution website in such a way that mouse is clicked or keyboard inputs in client, into intelligent tune
Degree system；
2) node administration module is registered on the management server, and the content of registration includes the IP address of node, port numbers, band
Video program that is wide and will watching；
3) management server returns to 20 partner nodes of node administration module, and partner node is to watch to watch
Video program node, the principle that partner node is selected is that the IP address of node is most close；
4) scheduler module reads other nodes viewing on the previous video-see behavior of user and network first and will see
The behavior for the video program seen constructs model using the Map Reduce in Hadoop, predicts user by hidden Markov chain
Next jump-point, next jump-point are exactly that user terminates data block being played on when the video program that viewing will be watched
The position at place, the data block before next jump-point need to cache；
5) scheduler module sends request of data, caching data block to corresponding partner node；
Monitoring center can modify scheduling scheme for evaluating scheduling scheme；Monitoring center utilizes the Map in Hadoop
Reduce calculates the system pressure of client in real time, and system pressure is calculated with formula one:
Formula one:
Wherein, ω is system pressure；A, b, c, d are proportionality coefficient, are the rationals between 0~1, by backstage personnel's root
According to needing to adjust, and meeting summation is 1；P is better upload bandwidth utilisation, be using upstream bandwidth and total bandwidth ratio；Q is
Server stress is the ratio of the sum and the sum of data block being played on of the data block that video server saves；R is to open
Dynamic delay is after user enters intelligent dispatching system, until obtain between all data blocks for playing video in initial 5s when
Between be spaced；T is play quality, is current time depending on the sum of the practical data block obtained of node and the data block that should be obtained
The ratio of sum；ω, P, Q, R, T are the rationals between 0~1；
When system pressure is less than 0.5, then monitoring center stops scheduling scheme immediately, modifies scheduling scheme by backstage personnel
And execute, until system pressure is not less than 0.5, restarts scheduler module and formulate new scheduling scheme and execution.
Beneficial achievement of the invention are as follows: the present invention provides a kind of intelligent dispatching systems, including video server, management clothes
Business device, monitoring center, client, node administration module, cache module, scheduler module.Utilize Hadoop distributed file system
Data are saved, server stress is alleviated.User data is acquired, then computation model intellectual analysis is used based on big data system,
Accomplish to do optimal scheduling based on user link experience.
Specific embodiment
In order to which technical problems, technical solutions and advantages to be solved are more clearly understood, tie below
Embodiment is closed, the present invention will be described in detail.It should be noted that specific embodiment described herein is only to explain
The present invention is not intended to limit the present invention, and the product for being able to achieve said function belongs to equivalent replacement and improvement, is all contained in this hair
Within bright protection scope.The specific method is as follows:
Embodiment 1: the present embodiment specifically introduces P2P stream media data dispatching mechanism, as follows:
Currently, data dispatch mechanism mainly has " pushing away ", " drawing ", " push-and-pull " combines and uses four kinds of modes of data encoding.
(1) data dispatch mechanism " is pushed away "
The thought of " pushing away " data dispatch technology results from multicasting technology, it is the scheduling mechanism used earliest." pushing away " mode
It is mainly used in Streaming Media tree structure, the form that each node is set with single or more organizes together.Source service node is made
For root node, data are from source node by the top-down distribution of hierarchical relationship of tree.Father node is always obtained prior to child nodes
Data, child nodes can only wait the data to be received from father node, once child nodes receive data, it can be downward immediately
Generation forwarding, forwards layer by layer in this way, and final all nodes all get the data from source service node.
(2) " drawing " data dispatch mechanism
Another data dispatch mechanism after mode that " drawing " mode is " pushing away ", in " pushing away " mode, data transmission, which has, to be determined
Direction, and in " drawing " mode, data transmission needs node to send request to other neighbor nodes to obtain without fixed-direction
It takes." drawing " mode is generally otherwise known as based on data-driven.Node in " drawing " mode is no longer as the node in " pushing away " mode
Passively receive the data that other nodes forward, but select neighbor node " drawing " access evidence, is actively to be saved to other
Point request data.In " drawing " mode data scheduling mechanism, node in network is random to be connect with other nodes, and is periodically handed over
Cache image is changed, when needing request data, request of data can be sent to neighbor node according to the cache information that exchange obtains.
In the scheduling of " drawing " mode data, node is needed data block from requesting to receiving through all previous communication, and which increases time delays.
(3) " push-and-pull " combined data scheduling mechanism
" push-and-pull " binding pattern has taken into account the advantages of both " pushing away " mode and " drawing " mode, drops while reducing control overhead
Low data reach delay, and the overall performance of system is made to be greatly improved.General " push-and-pull " modular system is by nerve of a covering
Two levels of tree structure and reticular structure are divided into, usually in tree structure, with " pushing away " mode to other node forwarding numbers
According to, and to obtain data from other nodes in reticular structure, and with " drawing " mode, pass through the phase interworking of both of which in this way
It closes, data needed for node can be allowed quickly and effectively to obtain.How to coordinate to be that " push-and-pull " mode needs to solve between " pushing away " and " drawing "
A major issue.If both of which carries out simultaneously, will cause asking for repeated downloads data in the transmitting of same data block
Topic.
(4) the data dispatch mechanism of data encoding is used
Coding techniques is applied in stream media system, can be provided and be adapted to the service quality of network bandwidth variation, enhance
The stability of system.Current multiple description coded MDC and network code NC extensive utilization are into P2P stream media system.
MDC (Mutiple Description Coding) is highly effective in terms of Fault recovery, usually a kind of more descriptions
Encoder generates multiple equal rates and description of equal importance, and each description need to only carry lower quality but acceptable is believed
Breath, such user can decode as long as receiving one of description and play media data, when the description received is more,
The stream medium data of acquisition also just increases, to improve the quality of media data, greatly improves service quality.
NC (Network Coding), which is applied in stream media system, is conducive to extensive content.Distribution, network gulps down
The amount of spitting improves, thus the improvement of promotion system performance.But node needs to play media data until enough data blocks
After reaching and decoding, therefore network code cannot be used directly in VOD system.
Embodiment 2: the present embodiment concrete example illustrates the structure of intelligent dispatching system, comprising:
Video server, management server, monitoring center, client, node administration module, cache module, scheduler module；
Having multiple client, each client in intelligent dispatching system is exactly a node；Each client respectively and
Video server, management server, monitoring center are connected；Video server is connected with management server；Intelligent dispatching system benefit
Data are saved with Hadoop distributed file system, realize cloud computing using the Map Reduce in Hadoop；
Video server is for issuing and saving video file；Video file is divided into equal-sized by video server
Data block；Data block information is transferred to management server by video server；
Management server is used for managing customer client information；
Node administration module, cache module, scheduler module all integrate on the client；
Node administration module is used to manage the information of this node and partner node, registers to management server；Cache module
For caching data block, data block can also be forwarded for partner node, caching data block is real by Hadoop distributed file system
It is existing；Scheduler module sends request of data to corresponding partner node for formulating scheduling scheme, and according to scheduling scheme；
Intelligent dispatching system includes following work step:
1) user selects video distribution website in such a way that mouse is clicked or keyboard inputs in client, into intelligent tune
Degree system；
2) node administration module is registered on the management server, and the content of registration includes the IP address of node, port numbers, band
Video program that is wide and will watching；
3) management server returns to 20 partner nodes of node administration module, and partner node is to watch to watch
Video program node, the principle that partner node is selected is that the IP address of node is most close；
4) scheduler module reads other nodes viewing on the previous video-see behavior of user and network first and will see
The behavior for the video program seen constructs model using the Map Reduce in Hadoop, predicts user by hidden Markov chain
Next jump-point, next jump-point are exactly that user terminates data block being played on when the video program that viewing will be watched
The position at place, the data block before next jump-point need to cache；
5) scheduler module sends request of data, caching data block to corresponding partner node；
Monitoring center can modify scheduling scheme for evaluating scheduling scheme；Monitoring center utilizes the Map in Hadoop
Reduce calculates the system pressure of client in real time, and system pressure is calculated with formula one:
Formula one:
Wherein, ω is system pressure；A, b, c, d are proportionality coefficient, are the rationals between 0~1, by backstage personnel's root
According to needing to adjust, and meeting summation is 1；P is better upload bandwidth utilisation, be using upstream bandwidth and total bandwidth ratio；Q is
Server stress is the ratio of the sum and the sum of data block being played on of the data block that video server saves；R is to open
Dynamic delay is after user enters intelligent dispatching system, until obtain between all data blocks for playing video in initial 5s when
Between be spaced；T is play quality, is current time depending on the sum of the practical data block obtained of node and the data block that should be obtained
The ratio of sum；ω, P, Q, R, T are the rationals between 0~1；
When system pressure is less than 0.5, then monitoring center stops scheduling scheme immediately, modifies scheduling scheme by backstage personnel
And execute, until system pressure is not less than 0.5, restarts scheduler module and formulate new scheduling scheme and execution.
Beneficial achievement of the invention are as follows: the present invention provides a kind of intelligent dispatching systems, including video server, management clothes
Business device, monitoring center, client, node administration module, cache module, scheduler module.Utilize Hadoop distributed file system
Data are saved, server stress is alleviated.User data is acquired, then computation model intellectual analysis is used based on big data system,
Accomplish to do optimal scheduling based on user link experience.
The foregoing is merely the preferred embodiments of the invention, the claims that are not intended to limit the invention.
Simultaneously it is described above, for those skilled in the technology concerned it would be appreciated that and implement, therefore other be based on institute of the present invention
The equivalent change that disclosure is completed, should be included in the covering scope of the claims.
Claims (1)
1. a kind of intelligent dispatching system characterized by comprising video server, management server, monitoring center, client,
Node administration module, cache module, scheduler module；
Having multiple clients, each client in intelligent dispatching system is exactly a node；Each client
All it is connected respectively with the video server, the management server, the monitoring center；The video server and the pipe
Server is managed to be connected；The intelligent dispatching system saves data using Hadoop distributed file system, using in Hadoop
Map Reduce realizes cloud computing；
The video server is for issuing and saving video file；The video file is divided into greatly by the video server
Small equal data block；The data block information is transferred to the management server by the video server；
The management server is used for managing customer client information；
The node administration module, the cache module, the scheduler module are all integrated in the client；
The node administration module is used to manage the information of this node and partner node, registers to the management server；It is described
Cache module is used for caching data block, the data block can also be forwarded for the partner node, caching data block passes through described
Hadoop distributed file system is realized；The scheduler module is for formulating scheduling scheme, and according to the scheduling scheme to right
The partner node answered sends request of data；
The intelligent dispatching system includes following work step:
1) user selects video distribution website in such a way that mouse is clicked or keyboard inputs in the client, into the intelligence
System can be dispatched；
2) the node administration module is registered in the management server, and the content of registration includes the IP address of node, port
Number, bandwidth and the video program that will be watched；
3) management server returns to 20 partner nodes of the node administration module, and the partner node is to watch
The node of the video program that will be watched, 20 partner nodes are 20 most similar with the IP address of the node
Node；
4) it is described i.e. to read other nodes viewing on the previous video-see behavior of user and network first for the scheduler module
By the behavior of the video program of viewing, model is constructed using the Map Reduce in the Hadoop, passes through hidden Markov chain
The next jump-point of user is predicted, when next jump-point is exactly that user terminates the video program that will be watched described in viewing
Position where data block being played on, the data block before next jump-point need to cache；
5) scheduler module sends request of data, caching data block to the corresponding partner node；
The monitoring center can modify the scheduling scheme for evaluating scheduling scheme；Described in the monitoring center utilizes
Map Reduce in Hadoop calculates the system pressure of client in real time, and the system pressure is calculated with formula one:
Formula one:
Wherein, ω is the system pressure；A, b, c, d are proportionality coefficient, are the rationals between 0~1, by backstage personnel's root
According to needing to adjust, and meeting summation is 1；P is better upload bandwidth utilisation, be using upstream bandwidth and total bandwidth ratio；Q is
Server stress is the ratio of the sum and the sum of data block being played on of the data block that the video server saves；R
It is to play all data blocks of video in initial 5s until obtaining after user enters the intelligent dispatching system for start delay
Between time interval；T is play quality, be described in current time depending on the practical data block obtained of node sum with should obtain
The ratio of the sum of the data block obtained；The ω, the P, the Q, the R, the T are the rationals between 0~1；
When the system pressure is less than 0.5, then the monitoring center stops the scheduling scheme immediately, and by backstage, personnel are modified
The scheduling scheme simultaneously executes, until the system pressure is not less than 0.5, restarts the scheduler module and formulates new dispatching party
Case simultaneously executes.
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| CN112583922A (en) * | 2020-12-16 | 2021-03-30 | 罗普特科技集团股份有限公司 | Intelligent scheduling system for video monitoring service |
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Denomination of invention: An intelligent scheduling system Effective date of registration: 20230701 Granted publication date: 20210903 Pledgee: Bank of Beijing Limited by Share Ltd. Shanghai branch Pledgor: SHANGHAI ULUCU ELECTRONIC TECHNOLOGY CO.,LTD. Registration number: Y2023980046838 |