CN115334320A - Cloud computing type uploaded data analysis system - Google Patents
Cloud computing type uploaded data analysis system Download PDFInfo
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- CN115334320A CN115334320A CN202210777690.6A CN202210777690A CN115334320A CN 115334320 A CN115334320 A CN 115334320A CN 202210777690 A CN202210777690 A CN 202210777690A CN 115334320 A CN115334320 A CN 115334320A
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- 238000007405 data analysis Methods 0.000 title claims abstract description 32
- 230000007246 mechanism Effects 0.000 claims abstract description 25
- 238000004458 analytical method Methods 0.000 claims abstract description 13
- 238000003062 neural network model Methods 0.000 claims description 34
- 238000000034 method Methods 0.000 claims description 12
- 230000009471 action Effects 0.000 claims description 10
- 238000012549 training Methods 0.000 claims description 10
- 238000001514 detection method Methods 0.000 claims description 8
- 238000005259 measurement Methods 0.000 claims description 3
- 238000012163 sequencing technique Methods 0.000 claims description 3
- 230000001360 synchronised effect Effects 0.000 claims description 2
- 238000012517 data analytics Methods 0.000 claims 3
- 238000004891 communication Methods 0.000 abstract description 8
- 238000004519 manufacturing process Methods 0.000 abstract description 2
- 230000000875 corresponding effect Effects 0.000 description 7
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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
- H04N21/2181—Source of audio or video content, e.g. local disk arrays comprising remotely distributed storage units, e.g. when movies are replicated over a plurality of video servers
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N21/00—Selective content distribution, e.g. interactive television or video on demand [VOD]
- H04N21/20—Servers specifically adapted for the distribution of content, e.g. VOD servers; Operations thereof
- H04N21/23—Processing of content or additional data; Elementary server operations; Server middleware
- H04N21/234—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs
- H04N21/23418—Processing of video elementary streams, e.g. splicing of video streams or manipulating encoded video stream scene graphs involving operations for analysing video streams, e.g. detecting features or characteristics
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Abstract
The invention relates to a cloud computing type uploaded data analysis platform, which comprises: the node storage mechanism is arranged in a server for executing short video storage and management, and comprises a plurality of cloud computing nodes, wherein the cloud computing nodes are physically isolated and cooperate to realize the storage of short video data of each client connected to the server; and the intelligent analysis equipment is used for intelligently analyzing the uploading duration of the current short video to be uploaded to the node storage mechanism based on the real-time uploading speed, the video length of the current short video to be uploaded and the reference operation times. The cloud computing type uploaded data analysis platform is compact in structure and stable in operation. The actual uploading duration of the short video to be uploaded can be intelligently analyzed based on the real-time network communication performance, the uploading equipment transportation capacity and the short video length to be uploaded, so that reliable reference data is provided for the manufacturing, editing, compressing and uploading of short video users.
Description
Technical Field
The invention relates to the field of cloud computing, in particular to a cloud computing type uploading data analysis platform.
Background
The implementation of computer cloud computing requires the creation of certain environments and conditions, and particularly, the architecture must have the following key features. Firstly, the system is required to be intelligent and autonomous, and the intelligent response requirement of an automatic processing platform is realized on the premise of reducing manual operation, so that an automation technology is embedded in the cloud system; secondly, the cloud system has agile response capability in the face of change signals or demand signals, so that certain agile requirements are required for the architecture of cloud computing. Meanwhile, with the rapid change of service level and growth speed, cloud computing also faces huge challenges, and embedded clustering technology and virtualization technology can cope with the change.
In the prior art, when a client side needs to upload an edited short video to a short video server after editing the short video, due to the discontinuity of network communication performance, the influence of equipment performance and the influence of short video length, the uploading time length fluctuates, the uploading time length cannot be accurately estimated, so that the subsequent editing time cannot be accurately mastered, and the multi-process management of network communication is lack of control.
Disclosure of Invention
In order to solve the technical problems in the prior art, the invention provides a cloud computing type uploading data analysis platform which can intelligently analyze the actual uploading duration of a short video to be uploaded based on the real-time network communication performance, the uploading equipment transportation capacity and the short video length to be uploaded, so that valuable reference data can be provided for accurate mastering of subsequent editing time and multi-process management of network communication.
According to an aspect of the present invention, there is provided a cloud computing upload data analysis platform, the platform comprising:
the node storage mechanism is arranged in a server for executing short video storage and management and comprises a plurality of cloud computing nodes, and the cloud computing nodes are physically isolated and cooperate to realize the storage of short video data of each client connected to the server;
the target measuring mechanism is arranged in a client executing the short video uploading operation and used for measuring the current network uploading speed from the client to each cloud computing node connected with the client and analyzing each current network uploading speed corresponding to a plurality of cloud computing nodes respectively to obtain a real-time uploading speed;
the length detection equipment is arranged in the client and used for detecting the video length of the short video to be uploaded currently and determining the video length of the short video to be uploaded currently based on the video frame number of the short video to be uploaded currently;
the operation measuring equipment is arranged in the client and used for measuring the operation times per second of the CPU chip of the client to be used as reference operation times to be output;
the intelligent analysis equipment is respectively connected with the target determination mechanism, the length detection equipment and the operation measurement equipment and is used for intelligently analyzing the uploading duration of the short video to be uploaded currently to the node storage mechanism based on the real-time uploading speed, the video length of the short video to be uploaded currently and the reference operation times;
wherein, the time length of uploading the currently to-be-uploaded short video to the node storage mechanism is intelligently analyzed based on the real-time uploading speed, the video length of the currently to-be-uploaded short video and the reference operation times, and the time length of uploading the currently to-be-uploaded short video to the node storage mechanism comprises: taking the real-time uploading speed, the video length of the short video to be uploaded at present and the reference operation times as a plurality of inputs of a deep neural network model, and executing the deep neural network model to obtain the output of the deep neural network model, namely the uploading duration of the short video to be uploaded to the node storage mechanism at present;
wherein the deep neural network model comprises a plurality of hidden layers, and a total number of the plurality of hidden layers is proportional to a total number of the plurality of cloud computing nodes.
According to another aspect of the present invention, a cloud computing type upload data analysis method is further provided, where the method includes using a cloud computing type upload data analysis platform as described above, so as to intelligently analyze the upload duration consumed when the currently-to-be-uploaded short video is uploaded to a cloud computing server based on the real-time upload speed, the video length of the currently-to-be-uploaded short video, and the reference operation times of a client processor.
The cloud computing type uploading data analysis platform is compact in structure and stable in operation. The actual uploading duration of the short video to be uploaded can be intelligently analyzed based on the real-time network communication performance, the uploading equipment transportation capacity and the short video length to be uploaded, so that reliable reference data are provided for the manufacturing, editing, compressing and uploading of short video users.
Brief description of the drawings
The numerous advantages of the present invention may be better understood by those skilled in the art by reference to the accompanying drawings in which:
fig. 1 is an internal structural diagram of a cloud computing upload data analysis platform according to a first embodiment of the present invention.
Fig. 2 is an internal structural diagram of a cloud computing upload data analysis platform according to a second embodiment of the present invention.
Detailed Description
Embodiments of the cloud computing upload data analysis platform according to the present invention will be described in detail below with reference to the accompanying drawings.
Short video refers to high-frequency pushed video content played on various new media platforms, suitable for viewing in mobile and short-time leisure, varying from seconds to minutes. The contents integrate the topics of skill sharing, humorous work, fashion trend, social hotspots, street interviews, public education, advertising creativity, business customization and the like. Because the content is short, the content can be individually sliced or can be a series of columns. In the prior art, when a client side needs to upload an edited short video to a short video server after editing the short video, due to the discontinuity of network communication performance, the influence of equipment performance and the influence of short video length, the uploading time length fluctuates, the uploading time length cannot be accurately estimated, so that the subsequent editing time cannot be accurately mastered, and the multi-process management of network communication is lack of control.
In order to overcome the defects, the cloud computing type uploaded data analysis platform is built, and the corresponding technical problem can be effectively solved.
The invention has the following two remarkable technical effects: the method comprises the steps that firstly, the uploading duration required by uploading the short video to be uploaded to a cloud computing server is intelligently analyzed based on the real-time uploading speed, the video length of the short video to be uploaded currently and the reference operation times of a client processor, the intelligent analysis is based on a deep neural network, and the depth of the deep neural network is positively correlated with the number of storage nodes in the cloud computing server; and secondly, introducing a node storage mechanism arranged in a server for executing short video storage and management, wherein the node storage mechanism comprises a plurality of cloud computing nodes, and the cloud computing nodes are physically isolated and cooperate to realize the storage of the short video data of each client connected to the server.
Fig. 1 is an internal structural view of a cloud computing upload data analysis platform according to a first embodiment of the present invention, the platform including:
the node storage mechanism is arranged in a server for executing short video storage and management, and comprises a plurality of cloud computing nodes, wherein the cloud computing nodes are physically isolated and cooperate to realize the storage of short video data of each client connected to the server;
the target measuring mechanism is arranged in a client executing the short video uploading operation and is used for measuring the current network uploading speed from the client to each cloud computing node connected with the client and analyzing the current network uploading speed respectively corresponding to the cloud computing nodes to obtain a real-time uploading speed;
the length detection equipment is arranged in the client and used for detecting the video length of the short video to be uploaded currently and determining the video length of the short video to be uploaded currently based on the video frame number of the short video to be uploaded currently;
the operation measuring equipment is arranged in the client and used for measuring the operation times per second of the CPU chip of the client to be used as reference operation times to be output;
the intelligent analysis equipment is respectively connected with the target determination mechanism, the length detection equipment and the operation measurement equipment and is used for intelligently analyzing the uploading duration of the short video to be uploaded to the node storage mechanism based on the real-time uploading speed, the video length of the short video to be uploaded currently and the reference operation times;
wherein, the uploading duration of uploading the currently to-be-uploaded short video to the node storage mechanism is intelligently analyzed based on the real-time uploading speed, the video length of the currently to-be-uploaded short video and the reference operation times, and comprises: taking the real-time uploading speed, the video length of the short video to be uploaded at present and the reference operation times as a plurality of inputs of a deep neural network model, and executing the deep neural network model to obtain the output of the deep neural network model, namely the uploading duration of the short video to be uploaded to the node storage mechanism at present;
wherein the deep neural network model comprises a plurality of hidden layers, a total number of the plurality of hidden layers being proportional to a total number of the plurality of cloud computing nodes;
wherein taking the real-time uploading speed, the video length of the short video to be uploaded currently and the reference operation times as a plurality of inputs of a deep neural network model and executing the deep neural network model to obtain the output of the deep neural network model, i.e. the uploading duration of the short video to be uploaded to the node storage mechanism currently includes: before inputting the real-time uploading speed, the video length of the short video to be uploaded currently and the reference operation times into the deep neural network model, the real-time uploading speed, the video length of the short video to be uploaded currently and the reference operation times are respectively subjected to normalization processing so as to enable the encoding forms of the three items of data to be the same.
Next, a detailed structure of the cloud computing upload data analysis platform of the present invention will be further described.
Fig. 2 is an internal structural diagram of a cloud computing type upload data analysis platform according to a second embodiment of the present invention
Compared with the first embodiment of the present invention, the cloud computing upload data analysis platform according to the second embodiment of the present invention may further include:
the model establishing equipment is arranged in the client, is connected with the intelligent analysis equipment, and is used for realizing each training action of the deep neural network model based on historical data of each short video which is uploaded historically and sending the deep neural network model after each training action to the intelligent analysis equipment for use;
the method comprises the following steps of obtaining historical data of short videos uploaded based on a history, and sending the deep neural network model after the deep neural network model is subjected to the training actions to the intelligent analysis equipment for use, wherein the historical data of the short videos uploaded based on the history comprises the following steps: the real-time uploading speed of each historically uploaded short video before uploading, the video length of the short video and a CPU chip of a client side where the short video is located are used as multiple inputs of a deep neural network model, and the duration consumed by the short video uploading is used as the output of the deep neural network model so as to execute each training action on the deep neural network model.
In a cloud computing upload data analysis platform according to any embodiment of the present invention:
detecting the video length of the short video to be uploaded currently, and determining the video length of the short video to be uploaded currently based on the video frame number of the short video to be uploaded currently comprises the following steps: when the resolution of each frame of picture forming the short video is equal to the set resolution, directly taking the video frame number of the short video to be uploaded currently as the video length of the short video to be uploaded currently;
wherein, the video length of the short video that the detection is at present will be uploaded, the video length of the short video that the video frame number based on the short video that is at present will be uploaded confirms that is at present will be uploaded still includes: when the resolution of each frame of picture forming the short video is greater than the set resolution, acquiring a multiple obtained by dividing the resolution of each frame of picture by the set resolution, and multiplying the multiple by the number of video frames of the short video to be uploaded currently to serve as the video length of the short video to be uploaded currently;
wherein, the video length of the short video that the detection is at present will be uploaded, the video length of the short video that the video frame number based on the short video that is at present will be uploaded confirms that is at present will be uploaded still includes: when the resolution of each frame of picture forming the short video is smaller than the set resolution, acquiring the set resolution to obtain a multiple obtained by dividing the resolution of each frame of picture, and dividing the video frame number of the short video to be uploaded by the multiple to be used as the video length of the short video to be uploaded.
In a cloud computing upload data analysis platform according to any embodiment of the present invention:
analyzing the current network uploading speeds respectively corresponding to the cloud computing nodes to obtain a real-time uploading speed comprises: sequencing current network uploading speeds respectively corresponding to the cloud computing nodes in a sequence from the magnitude to obtain a speed sequence, and taking the current network uploading speed with the minimum sequence number as a real-time uploading speed;
wherein the physically isolated and collaborative storage of short video data of each client connected to the server by the plurality of cloud computing nodes comprises: and the storage capacities of the plurality of cloud computing nodes are equal.
In a cloud computing upload data analysis platform according to any embodiment of the present invention:
the intelligent analysis equipment is internally provided with a storage unit, a synchronization unit and an execution unit, wherein the storage unit is used for storing various model parameters of the deep neural network model, the execution unit is used for executing the deep neural network model, and the synchronization unit is respectively connected with the storage unit and the execution unit and is used for realizing the synchronous control between the storage unit and the execution unit.
Meanwhile, in order to overcome the defects, the invention also builds a cloud computing type uploading data analysis method, and the method comprises the step of using the cloud computing type uploading data analysis platform for intelligently analyzing the uploading duration required by uploading the currently to-be-uploaded short video to the cloud computing server based on the real-time uploading speed, the video length of the currently to-be-uploaded short video and the reference operation times of the client processor.
In addition, in the cloud computing type upload data analysis platform, alternatively, analyzing each current network upload speed respectively corresponding to the plurality of cloud computing nodes to obtain the real-time upload speed includes: and sequencing the current network uploading speeds respectively corresponding to the cloud computing nodes in a sequence from the magnitude to obtain a speed sequence, and taking the current network uploading speed with the middle sequence number as a real-time uploading speed.
The embodiments described above are merely set forth for a clear understanding of the principles of the disclosure. Many variations and modifications may be made without departing substantially from this disclosure. All such modifications and variations are intended to be included herein within the scope of this disclosure.
Claims (10)
1. A cloud computing upload data analysis platform, the platform comprising:
the node storage mechanism is arranged in a server for executing short video storage and management, and comprises a plurality of cloud computing nodes, wherein the cloud computing nodes are physically isolated and cooperate to realize the storage of short video data of each client connected to the server;
the target measuring mechanism is arranged in a client executing the short video uploading operation and used for measuring the current network uploading speed from the client to each cloud computing node connected with the client and analyzing each current network uploading speed corresponding to a plurality of cloud computing nodes respectively to obtain a real-time uploading speed;
the length detection equipment is arranged in the client and used for detecting the video length of the short video to be uploaded currently and determining the video length of the short video to be uploaded currently based on the video frame number of the short video to be uploaded currently;
the operation measuring equipment is arranged in the client and used for measuring the operation times per second of the CPU chip of the client to be used as reference operation times to be output;
the intelligent analysis equipment is respectively connected with the target determination mechanism, the length detection equipment and the operation measurement equipment and is used for intelligently analyzing the uploading duration of the short video to be uploaded to the node storage mechanism based on the real-time uploading speed, the video length of the short video to be uploaded currently and the reference operation times;
wherein, the time length of uploading the currently to-be-uploaded short video to the node storage mechanism is intelligently analyzed based on the real-time uploading speed, the video length of the currently to-be-uploaded short video and the reference operation times, and the time length of uploading the currently to-be-uploaded short video to the node storage mechanism comprises: taking the real-time uploading speed, the video length of the short video to be uploaded at present and the reference operation times as a plurality of inputs of a deep neural network model, and executing the deep neural network model to obtain the output of the deep neural network model, namely the uploading duration of the short video to be uploaded to the node storage mechanism at present;
wherein the deep neural network model comprises a plurality of hidden layers, and a total number of the plurality of hidden layers is proportional to a total number of the plurality of cloud computing nodes.
2. The cloud computing upload data analytics platform of claim 1, wherein the platform further comprises:
and the model establishing equipment is arranged in the client, is connected with the intelligent analysis equipment, and is used for realizing each training action of the deep neural network model based on historical data of each short video which is uploaded historically and sending the deep neural network model after each training action to the intelligent analysis equipment for use.
3. The cloud computing upload data analysis platform of claim 2, wherein:
the method comprises the following steps of realizing each training action of the deep neural network model based on historical data of each short video uploaded historically, and sending the deep neural network model after each training action is finished to the intelligent analysis equipment for use, wherein the training actions comprise the following steps: the real-time uploading speed of each historically uploaded short video before uploading, the video length of the short video and a CPU chip of a client side where the short video is located are used as multiple inputs of a deep neural network model, and the duration consumed by the short video uploading is used as the output of the deep neural network model so as to execute each training action on the deep neural network model.
4. A cloud computing upload data analysis platform according to any of claims 1 to 3, characterized by:
detecting the video length of the short video to be uploaded currently, and determining the video length of the short video to be uploaded currently based on the video frame number of the short video to be uploaded currently comprises the following steps: when the resolution of each frame of picture constituting the short video is equal to the set resolution, directly taking the video frame number of the short video to be uploaded currently as the video length of the short video to be uploaded currently.
5. The cloud computing upload data analytics platform of claim 4, wherein:
detecting the video length of the short video to be uploaded currently, and determining the video length of the short video to be uploaded currently based on the video frame number of the short video to be uploaded currently further comprises: when the resolution of each frame of picture forming the short video is larger than the set resolution, acquiring a multiple obtained by dividing the resolution of each frame of picture by the set resolution, and multiplying the multiple by the number of video frames of the short video to be uploaded currently to serve as the video length of the short video to be uploaded currently.
6. The cloud computing upload data analytics platform of claim 5, wherein:
detecting the video length of the short video to be uploaded currently, and determining the video length of the short video to be uploaded currently based on the video frame number of the short video to be uploaded currently further comprises: when the resolution of each frame of picture forming the short video is smaller than the set resolution, acquiring the set resolution to obtain a multiple obtained by dividing the resolution of each frame of picture, and dividing the video frame number of the short video to be uploaded by the multiple to obtain the video length of the short video to be uploaded.
7. A cloud computing upload data analysis platform according to any of claims 1 to 3, characterized by:
analyzing each current network uploading speed respectively corresponding to the plurality of cloud computing nodes to obtain a real-time uploading speed comprises: and sequencing the current network uploading speeds respectively corresponding to the cloud computing nodes in a sequence from the magnitude to obtain a speed sequence, and taking the current network uploading speed with the minimum sequence number as a real-time uploading speed.
8. The cloud computing upload data analysis platform of claim 7, wherein:
the physically isolated and cooperative storage of the short video data of the clients connected to the server by the cloud computing nodes comprises: and the storage capacities of the plurality of cloud computing nodes are equal.
9. A cloud computing upload data analysis platform according to any of claims 1 to 3, characterized by:
the intelligent analysis equipment is internally provided with a storage unit, a synchronization unit and an execution unit, wherein the storage unit is used for storing various model parameters of the deep neural network model, the execution unit is used for executing the deep neural network model, and the synchronization unit is respectively connected with the storage unit and the execution unit and is used for realizing the synchronous control between the storage unit and the execution unit.
10. A cloud computing upload data analysis method, the method comprising providing a cloud computing upload data analysis platform according to any one of claims 1 to 9, for intelligently analyzing that it takes an upload duration for uploading a currently to-be-uploaded short video to a cloud computing server based on a real-time upload speed, a video length of the currently to-be-uploaded short video, and a client processor reference operation number.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104902344A (en) * | 2015-06-17 | 2015-09-09 | 天津通信广播集团有限公司 | System and method of obtaining television program short videos and sharing through network |
| CN110213623A (en) * | 2019-06-03 | 2019-09-06 | 上海哔哩哔哩科技有限公司 | Video method for uploading, video upload device and computer readable storage medium |
| CN111382213A (en) * | 2020-04-02 | 2020-07-07 | 无锡蓝色云湾信息技术有限公司 | Data analysis system combining internet of things and cloud computing technology |
| CN112039713A (en) * | 2020-09-09 | 2020-12-04 | 深圳市雁云信息技术有限公司 | Data transmission method and system for cloud computing and meeting user requirements |
| CN112131198A (en) * | 2020-09-23 | 2020-12-25 | 北京奇艺世纪科技有限公司 | Log analysis method and device and electronic equipment |
| CN113242469A (en) * | 2021-04-21 | 2021-08-10 | 南京大学 | Self-adaptive video transmission configuration method and system |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114222186A (en) * | 2022-01-28 | 2022-03-22 | 普春玲 | Information pushing system and method based on big data deep mining |
-
2022
- 2022-07-04 CN CN202210777690.6A patent/CN115334320B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104902344A (en) * | 2015-06-17 | 2015-09-09 | 天津通信广播集团有限公司 | System and method of obtaining television program short videos and sharing through network |
| CN110213623A (en) * | 2019-06-03 | 2019-09-06 | 上海哔哩哔哩科技有限公司 | Video method for uploading, video upload device and computer readable storage medium |
| CN111382213A (en) * | 2020-04-02 | 2020-07-07 | 无锡蓝色云湾信息技术有限公司 | Data analysis system combining internet of things and cloud computing technology |
| CN112039713A (en) * | 2020-09-09 | 2020-12-04 | 深圳市雁云信息技术有限公司 | Data transmission method and system for cloud computing and meeting user requirements |
| CN112131198A (en) * | 2020-09-23 | 2020-12-25 | 北京奇艺世纪科技有限公司 | Log analysis method and device and electronic equipment |
| CN113242469A (en) * | 2021-04-21 | 2021-08-10 | 南京大学 | Self-adaptive video transmission configuration method and system |
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