CN116095372B - Method and system for dispatching and distributing streaming media data - Google Patents

Method and system for dispatching and distributing streaming media data Download PDF

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CN116095372B
CN116095372B CN202310369969.5A CN202310369969A CN116095372B CN 116095372 B CN116095372 B CN 116095372B CN 202310369969 A CN202310369969 A CN 202310369969A CN 116095372 B CN116095372 B CN 116095372B
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CN116095372A (en
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刘树魁
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Big Expert Education Technology Beijing Co ltd
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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
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L65/00—Network arrangements, protocols or services for supporting real-time applications in data packet communication
    • H04L65/80—Responding to QoS
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/06—Protocols specially adapted for file transfer, e.g. file transfer protocol [FTP]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/104—Peer-to-peer [P2P] networks
    • H04L67/1074—Peer-to-peer [P2P] networks for supporting data block transmission mechanisms
    • H04L67/1078—Resource delivery mechanisms
    • H04L67/108—Resource delivery mechanisms characterised by resources being split in blocks or fragments
    • 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
    • H04N21/251—Learning process for intelligent management, e.g. learning user preferences for recommending movies
    • 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
    • H04N21/25866—Management of end-user data
    • H04N21/25883—Management of end-user data being end-user demographical data, e.g. age, family status or address
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
    • Y02D30/00—Reducing energy consumption in communication networks
    • Y02D30/50—Reducing energy consumption in communication networks in wire-line communication networks, e.g. low power modes or reduced link rate

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  • Engineering & Computer Science (AREA)
  • Signal Processing (AREA)
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  • Two-Way Televisions, Distribution Of Moving Picture Or The Like (AREA)

Abstract

The invention relates to a method and a system for dispatching and distributing stream media data, in particular to the technical field of dispatching and distributing stream media data, wherein the method comprises the following steps: the method comprises the steps of S1 capturing historical skip information, S2 calculating effective skip, S3 fusing to establish an effective skip frame set, S4 cluster analysis, S5 determining key skip frames, S6 determining estimated frame spacing, S7 sectionally scheduling and sending, and S8 caching; according to the invention, based on historical data, statistical analysis is carried out on streaming media data files to obtain the jump node with high confidence, so that the watching preference of a user can be accurately known, priority scheduling distribution is carried out on the key areas, and the smoothness of watching is ensured; the invention also adopts a proportion algorithm, improves the tolerance of prejudgement for statistical data which does not meet Gaussian distribution, and can better contain the proportion interval for users with deviation of watching habit and statistical mean, improves prejudgement precision and reduces the problems of team blocking and waiting when the users jump.

Description

Method and system for dispatching and distributing streaming media data
Technical Field
The present invention relates to the field of streaming media data scheduling and distributing technologies, and in particular, to a streaming media data scheduling and distributing method and system.
Background
Streaming media (streaming media) refers to a technology and a process of compressing a series of media data, transmitting the data through network segmentation, and transmitting video and audio on the network in real time for viewing, wherein the technology enables data packets to be transmitted like streaming; if this technique is not used, the entire media file must be downloaded before use. Streaming can transmit live video or movies pre-stored on a server, and when a viewer is watching these video files, the video data is played by specific playing software immediately after being transmitted to the viewer's computer.
The stream media distributing and transmitting is a new network constructing mode, which is a network covering layer specially optimized for releasing broadband rich media in the traditional IP network, and aims to release the program content to multiple stream servers distributed in various places by adding a new layer of network architecture in the existing network, so that the client can obtain the required content nearby in the mode closest to the user, and the response speed of the user access is improved. In a broad sense, streaming media distribution systems represent a network service model based on quality and order. In general, a streaming media distribution system is a strategically deployed overall system. However, the traditional stream distribution transmission is based on a more complex implementation architecture of distributed computation and centralized management, and comprises several elements of content access management, data distribution scheduling, network request redirection and disconnection reconnection, resource configuration management and the like;
the prior art is as disclosed in the publication No.: the invention discloses a stream media distributing and transmitting method of CN101753439A, which comprises the following steps: the content access module receives the coded program data and then transmits the coded program data to each scheduling module; each scheduling module end establishes a corresponding linear data storage queue, and the content access module directly and sequentially transmits the received program data to the storage queues of each scheduling module; and each scheduling module takes out the data from each queue according to a certain time segment and sends the data to the next-stage streaming transmission system.
The prior art can greatly improve the service quality of the streaming media service, lighten the load of a source server and a network, reduce the investment of system hardware equipment, increase the concurrent service capability of the system, ensure that the same system cost can serve more users, but the prior art also has the advantages that a certain time is required for transmitting audio, video or multimedia digital resources required by the users to a display terminal when the streaming media data is scheduled and distributed, and the use requirements and the use habits of the users are not well learned, so that the use effect is poor due to the fact that the time is longer in the media data scheduling and distributing process.
Aiming at the problems, the invention provides a method and a system for dispatching and distributing stream media data, which are realized by the following technical scheme: the method for dispatching and distributing the streaming media data is characterized by comprising the following steps:
s1, capturing historical jump information; transmitting end L of streaming media data S Based on bidirectional interconnection protocol, multiple receiving ends L of streaming media data are provided R The historical skip frames of the historical user when skipping the streaming media data are grabbed, wherein the historical skip frames comprise a skip in frame Pin and a skip out frame Pout, and a historical skip frame set { (Pin) is formed ij , Pout ij , L ij ) -a }; wherein i is a play frequency index, j is a skip frequency index; pin ij 、Pout ij 、L ij Respectively representing the skip in frame, the skip out frame and the frame spacing of the jth skip of the video or audio file played at the ith time;
s2, calculating effective skip; for one jump (Pin ij , Pout ij , L ij ) If either of the following conditions T1, T2 is satisfied, it is determined as a valid jump:
T1：
Figure SMS_1
wherein L is 0 A preset frame interval threshold value;
T2：
Figure SMS_2
wherein->
Figure SMS_3
The mean value of the frame spacing is as follows:
Figure SMS_4
Figure SMS_5
wherein n represents the total play frequency,m i representing the number of times of jumping played at the ith time, wherein c is the total number of times of jumping;
s3, establishing an effective jump frame set through fusion; merging all effective jumps, and arranging the jump frames in order from small to large to obtain an effective jump frame set { (Pin) k , Pout k , L k )| k=1,2,…,w -a }; wherein k is the valid jump sequence number,wpin for effective total number of hops k , Pout k , L k Respectively jumping-in frames, jumping-out frames and frame intervals of the kth effective jump;
s4, cluster analysis; performing cluster analysis on all the effectively skipped frames to obtain a plurality of cluster groups;
s5, determining a key jump-in frame Pkey x The method comprises the steps of carrying out a first treatment on the surface of the Carrying out any one of Gaussian distribution analysis and proportional analysis on each cluster group to obtain a key jump-in frame Pkey x Wherein, the method comprises the steps of, wherein,xis a cluster group subscript;
s6, determining the estimated frame spacing; carrying out any one of Gaussian distribution analysis and mean analysis on the inter-frame distances of each cluster group to obtain estimated inter-frame distances;
s7, carrying out sectional scheduling and sending; the key jump-in frame is taken as a distribution node, and stream media data is sent to a receiving end;
s8, caching; the receiving end caches the streaming media data.
Further, the step S5 specifically includes: extracting jump-in frames of each cluster group, and checking whether Gaussian distribution is met or not, wherein the checking method is any one of a histogram, a KDE diagram, a Q-Q diagram, a shape-Wilk check and a Kolmogorov-Smirnov check;
if a cluster group is jumped into the frame set { Pin } k |xIf the Gaussian distribution is satisfied, selecting the Gaussian mean value
Figure SMS_6
Triple standard deviation>
Figure SMS_7
The frame at the position is used as the key jump-in frame of the cluster group, and the following conditions are satisfied:
Figure SMS_8
if the Gaussian distribution is not satisfied, selecting a frame which is based on the minimum jump-in frame and is at an increment of 5% of the difference between the minimum jump-in frame and the maximum jump-in frame as a key jump-in frame, and satisfying the following conditions:
Figure SMS_9
。
further, the step S6 specifically includes:
extracting the frame spacing of each cluster group, and checking whether the Gaussian distribution is met, wherein the checking method is any one of a histogram, a KDE diagram, a Q-Q diagram, a Shapiro-Wilk check and a Kolmogorov-Smirnov check;
if the inter-frame distance set { L ] of one cluster group k |xIf the Gaussian distribution is satisfied, selecting the Gaussian mean value
Figure SMS_10
Add three times standard deviation->
Figure SMS_11
The frame at the position is used as the key jump-in frame of the cluster group, and the following conditions are satisfied:
Figure SMS_12
if the Gaussian distribution is not satisfied, selecting 95% of the difference between the minimum frame spacing and the maximum frame spacing as the estimated frame spacing, and satisfying the following conditions:
Figure SMS_13
。
a stream media data dispatching and distributing system for executing the method, which comprises a preprocessing module and a processing module; the preprocessing module is used for executing steps S1 to S6; the processing module is used for executing the steps S7 to S8.
Further, the preprocessing module comprises a pre-storage module and a calculation module; the pre-storage module is used for storing the grabbed historical jump information; the calculation module is used for completing cluster analysis, calculating effective skip, establishing an effective skip frame set in a fusion mode, carrying out cluster analysis and determining key skip frames and estimated frame spacing according to the historical skip information.
Further, the processing module comprises a network controller, a network protocol module, a first scheduling and distributing module, a second scheduling and distributing module and a plurality of streaming media servers; the first dispatching distribution module and the second dispatching distribution module are mutually backed up.
The beneficial effects of the invention are as follows:
(1) Aiming at the problems of blocking and waiting data when the conventional streaming media is jumped by a user, particularly relating to video playing, the invention adopts a segmented transmission mode, and can carry out segmented transmission on streaming media files, thereby avoiding the problems of crowded front-end data and insufficient rear-end data.
(2) Aiming at the technical scheme of fixed multi-node transmission in the existing streaming media, the invention adopts a statistical method, and based on historical data, each streaming media data file is subjected to statistical analysis to obtain the jump node with high confidence, namely the node which the user prefers to jump, so that the watching preference of the user can be accurately known, the priority scheduling distribution is carried out on the key areas, and the smoothness of watching is ensured.
(3) According to the invention, 5% and 95% proportion algorithm is adopted, so that the tolerance of pre-judgment is improved for statistical data which do not meet Gaussian distribution, namely, for users with deviation between watching habits and statistical mean values, the proportion interval of the method can be well contained, the pre-judgment precision is improved, and the problems of team blocking and waiting when the users jump are reduced.
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FIG. 1 is a schematic flow chart of the method of the present invention;
Detailed Description
The present invention will be further described in detail with reference to the following examples, which are only for the purpose of illustrating the invention and are not to be construed as limiting the scope of the invention.
Example 1
According to fig. 1, the present embodiment provides a method for scheduling and distributing streaming media data, which includes the following steps:
s1, capturing historical jump information; transmitting end L of streaming media data S Based on bidirectional interconnection protocol, multiple receiving ends L of streaming media data are provided R The historical skip frames of the historical user when skipping the streaming media data are grabbed, wherein the historical skip frames comprise a skip in frame Pin and a skip out frame Pout, and a historical skip frame set { (Pin) is formed ij , Pout ij , L ij ) -a }; wherein i is a play frequency index, j is a skip frequency index; pin ij 、Pout ij 、L ij Respectively representing the skip in frame, the skip out frame and the frame spacing of the jth skip of the video or audio file played at the ith time;
s2, calculating effective skip; for one jump (Pin ij , Pout ij , L ij ) If either of the following conditions T1, T2 is satisfied, it is determined as a valid jump:
T1：
Figure SMS_14
wherein L is 0 A preset frame interval threshold value;
T2：
Figure SMS_15
wherein->
Figure SMS_16
The mean value of the frame spacing is as follows: />
Figure SMS_17
；/>
Figure SMS_18
；
Wherein n represents the total play frequency,m i representing the number of times of jumping played at the ith time, wherein c is the total number of times of jumping;
s3, establishing an effective jump frame set through fusion; merging all effective jumps, and arranging the jump frames in order from small to large to obtain an effective jump frame set { (Pin) k , Pout k , L k )| k=1,2,…,w -a }; wherein k is the valid jump sequence number,wpin for effective total number of hops k , Pout k , L k Respectively jumping-in frames, jumping-out frames and frame intervals of the kth effective jump;
s4, cluster analysis; performing cluster analysis on all the effectively skipped frames to obtain a plurality of cluster groups;
s5, determining a key jump-in frame Pkey x The method comprises the steps of carrying out a first treatment on the surface of the Carrying out any one of Gaussian distribution analysis and proportional analysis on each cluster group to obtain a key jump-in frame Pkey x Wherein, the method comprises the steps of, wherein,xis a cluster group subscript; the method specifically comprises the following steps: extracting jump-in frames of each cluster group, and checking whether Gaussian distribution is met or not, wherein the checking method is any one of a histogram, a KDE diagram, a Q-Q diagram, a shape-Wilk check and a Kolmogorov-Smirnov check;
if a cluster group is jumped into the frame set { Pin } k |xIf the Gaussian distribution is satisfied, selecting the Gaussian mean value
Figure SMS_19
Triple standard deviation>
Figure SMS_20
The frame at the position is used as the key jump-in frame of the cluster group, and the following conditions are satisfied: />
Figure SMS_21
The method comprises the steps of carrying out a first treatment on the surface of the If the Gaussian distribution is not satisfied, selecting the frame based on the minimum jump-in frame, wherein the difference between the minimum jump-in frame and the maximum jump-in frame is 5% of the increment as the keyAnd jumping into a frame, and meeting the following conditions: />
Figure SMS_22
；
S6, determining the estimated frame spacing; carrying out any one of Gaussian distribution analysis and mean analysis on the inter-frame distances of each cluster group to obtain estimated inter-frame distances; the method specifically comprises the following steps:
extracting the frame spacing of each cluster group, and checking whether the Gaussian distribution is met, wherein the checking method is any one of a histogram, a KDE diagram, a Q-Q diagram, a Shapiro-Wilk check and a Kolmogorov-Smirnov check;
if the inter-frame distance set { L ] of one cluster group k |xIf the Gaussian distribution is satisfied, selecting the Gaussian mean value
Figure SMS_23
Add three times standard deviation->
Figure SMS_24
The frame at the position is used as the key jump-in frame of the cluster group, and the following conditions are satisfied:
Figure SMS_25
if the Gaussian distribution is not satisfied, selecting 95% of the difference between the minimum frame spacing and the maximum frame spacing as the estimated frame spacing, and satisfying the following conditions:
Figure SMS_26
；
s7, carrying out sectional scheduling and sending; the key jump-in frame is taken as a distribution node, and stream media data is sent to a receiving end;
s8, caching; the receiving end caches the streaming media data.
Example 2
A stream media data dispatching and distributing system for executing the method, which comprises a preprocessing module and a processing module; the preprocessing module is used for executing steps S1 to S6; the processing module is used for executing steps S7 to S8 and other processes related to the dispatching and distributing of the streaming media data. The preprocessing module comprises a pre-storage module and a calculation module; the pre-storage module is used for storing the grabbed historical jump information; the calculation module is used for completing cluster analysis, calculating effective skip, establishing an effective skip frame set in a fusion mode, carrying out cluster analysis and determining key skip frames and estimated frame spacing according to the historical skip information. The processing module comprises a network controller, a network protocol module, a first scheduling and distributing module, a second scheduling and distributing module and a plurality of streaming media servers; the first dispatching distribution module and the second dispatching distribution module are mutually backed up.
The foregoing has shown and described the basic principles, principal features and advantages of the invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, and that the above embodiments and descriptions are merely illustrative of the principles of the present invention, and various changes and modifications may be made without departing from the spirit and scope of the invention, which is defined in the appended claims. The scope of the invention is defined by the appended claims and equivalents thereof.

Claims (6)

1. The method for dispatching and distributing the streaming media data is characterized by comprising the following steps:
s1, capturing historical jump information; transmitting end L of streaming media data S Based on bidirectional interconnection protocol, multiple receiving ends L of streaming media data are provided R The historical skip frames of the historical user when skipping the streaming media data are grabbed, wherein the historical skip frames comprise a skip in frame Pin and a skip out frame Pout, and a historical skip frame set { (Pin) is formed ij , Pout ij , L ij ) -a }; wherein i is a play frequency index, j is a skip frequency index; pin ij 、Pout ij 、L ij Respectively representing a skip-in frame, a skip-out frame and a frame interval of the j-th skip of the streaming media data file played at the i-th time;
s2, calculating effective skip; for one jump (Pin ij , Pout ij , L ij ) If either of the following conditions T1, T2 is satisfied, it is determined as a valid jump:
T1：
Figure QLYQS_1
wherein L is 0 A preset frame interval threshold value;
T2：
Figure QLYQS_2
wherein->
Figure QLYQS_3
The mean value of the frame spacing is as follows: />
Figure QLYQS_4
；/>
Figure QLYQS_5
The method comprises the steps of carrying out a first treatment on the surface of the Wherein n represents the total play frequency,m i representing the number of times of jumping played at the ith time, wherein c is the total number of times of jumping;
s3, establishing an effective jump frame set through fusion; merging all effective jumps, and arranging the jump frames in order from small to large to obtain an effective jump frame set { (Pin) k , Pout k , L k )| k=1,2,…,w -a }; wherein k is the valid jump sequence number,wpin for effective total number of hops k , Pout k , L k Respectively jumping-in frames, jumping-out frames and frame intervals of the kth effective jump;
s4, cluster analysis; performing cluster analysis on all the effectively skipped frames to obtain a plurality of cluster groups;
s5, determining a key jump-in frame Pkey x The method comprises the steps of carrying out a first treatment on the surface of the Carrying out any one of Gaussian distribution analysis and proportional analysis on each cluster group to obtain a key jump-in frame Pkey x Wherein, the method comprises the steps of, wherein,xis a cluster group subscript;
s6, determining the estimated frame spacing; carrying out any one of Gaussian distribution analysis and mean analysis on the inter-frame distances of each cluster group to obtain estimated inter-frame distances;
s7, carrying out sectional scheduling and sending; the key jump-in frame is taken as a distribution node, and stream media data is sent to a receiving end;
s8, caching; the receiving end caches the streaming media data.
2. The method for scheduling and distributing streaming media data according to claim 1, wherein: the step S5 specifically includes: extracting jump-in frames of each cluster group, and checking whether Gaussian distribution is met or not, wherein the checking method is any one of a histogram, a KDE diagram, a Q-Q diagram, a shape-Wilk check and a Kolmogorov-Smirnov check;
if a cluster group is jumped into the frame set { Pin } k |xIf the Gaussian distribution is satisfied, selecting the Gaussian mean value
Figure QLYQS_6
Triple standard deviation>
Figure QLYQS_7
The frame at the position is used as the key jump-in frame of the cluster group, and the following conditions are satisfied: />
Figure QLYQS_8
The method comprises the steps of carrying out a first treatment on the surface of the If the Gaussian distribution is not satisfied, selecting a frame which is based on the minimum jump-in frame and is at an increment of 5% of the difference between the minimum jump-in frame and the maximum jump-in frame as a key jump-in frame, and satisfying the following conditions: />
Figure QLYQS_9
。
3. A method for scheduling and distributing streaming media data according to claim 1 or 2, wherein: the step S6 specifically includes:
extracting the frame spacing of each cluster group, and checking whether the Gaussian distribution is met, wherein the checking method is any one of a histogram, a KDE diagram, a Q-Q diagram, a Shapiro-Wilk check and a Kolmogorov-Smirnov check;
if the inter-frame distance set { L ] of one cluster group k |xIf the Gaussian distribution is satisfied, selecting the Gaussian mean value
Figure QLYQS_10
Adding three times of standard deviation
Figure QLYQS_11
The frame at the position is used as the key jump-in frame of the cluster group, and the following conditions are satisfied: />
Figure QLYQS_12
The method comprises the steps of carrying out a first treatment on the surface of the If the Gaussian distribution is not satisfied, selecting 95% of the difference between the minimum frame spacing and the maximum frame spacing as the estimated frame spacing, and satisfying the following conditions:
Figure QLYQS_13
。/>
4. a streaming media data scheduling distribution system for performing the method of any of claims 1-3, comprising a preprocessing module and a processing module; the preprocessing module is used for executing steps S1 to S6; the processing module is used for executing the steps S7 to S8.
5. The streaming media data scheduling and distributing system according to claim 4, wherein the preprocessing module comprises a pre-storage module and a calculation module; the pre-storage module is used for storing the grabbed historical jump information; the calculation module is used for completing cluster analysis, calculating effective skip, establishing an effective skip frame set in a fusion mode, carrying out cluster analysis and determining key skip frames and estimated frame spacing according to the historical skip information.
6. The system according to claim 5, wherein the processing module comprises a network controller, a network protocol module, a first scheduling and distributing module, a second scheduling and distributing module, and a plurality of streaming media servers; the first dispatching distribution module and the second dispatching distribution module are mutually backed up.
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Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101753439A (en) * 2009-12-18 2010-06-23 深圳市融创天下科技发展有限公司 Method for distributing and transmitting streaming media
CN105656774A (en) * 2016-01-12 2016-06-08 东北大学 Multipath hybrid redundant transmission method for real-time network video session media data
CN111526153A (en) * 2020-04-29 2020-08-11 高新兴科技集团股份有限公司 Streaming media scheduling method, computer storage medium and electronic device
CN111757144A (en) * 2020-04-13 2020-10-09 湖南化工职业技术学院（湖南工业高级技工学校） Network computer multimedia video playing method and system

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20170142177A1 (en) * 2015-11-13 2017-05-18 Le Holdings (Beijing) Co., Ltd. Method and system for network dispatching

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101753439A (en) * 2009-12-18 2010-06-23 深圳市融创天下科技发展有限公司 Method for distributing and transmitting streaming media
CN105656774A (en) * 2016-01-12 2016-06-08 东北大学 Multipath hybrid redundant transmission method for real-time network video session media data
CN111757144A (en) * 2020-04-13 2020-10-09 湖南化工职业技术学院（湖南工业高级技工学校） Network computer multimedia video playing method and system
CN111526153A (en) * 2020-04-29 2020-08-11 高新兴科技集团股份有限公司 Streaming media scheduling method, computer storage medium and electronic device

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
RMFS：一种支持用户交互的流媒体调度方案;智英建;《电 子 与 信 息 学 报》;第第31卷卷(第第6期期);全文 *
一种基于优化混合调度策略的P2P VoD 系统的研究与设计;陈江;《计算机应用与软件》;第第28卷卷(第第6期期);全文 *

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