WO2015154549A1 - Procédé et dispositif de traitement de données - Google Patents
Procédé et dispositif de traitement de données Download PDFInfo
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- WO2015154549A1 WO2015154549A1 PCT/CN2015/070235 CN2015070235W WO2015154549A1 WO 2015154549 A1 WO2015154549 A1 WO 2015154549A1 CN 2015070235 W CN2015070235 W CN 2015070235W WO 2015154549 A1 WO2015154549 A1 WO 2015154549A1
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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]
- H04N21/60—Network structure or processes for video distribution between server and client or between remote clients; Control signalling between clients, server and network components; Transmission of management data between server and client, e.g. sending from server to client commands for recording incoming content stream; Communication details between server and client
- H04N21/63—Control signaling related to video distribution between client, server and network components; Network processes for video distribution between server and clients or between remote clients, e.g. transmitting basic layer and enhancement layers over different transmission paths, setting up a peer-to-peer communication via Internet between remote STB's; Communication protocols; Addressing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
Definitions
- the present invention relates to the field of communications, and in particular to a method and apparatus for processing data.
- OTT TV is an abbreviation of “Over The Top TV”, which refers to an open Internet-based video service.
- the terminal can be a TV, a computer, a set-top box, a PAD, a smart phone, etc., which provides services on the network, emphasizing service and physics. Network independence.
- OTT TV is an Internet TV that meets the needs of consumers and integrates full-featured Internet TV with interactive TV functions.
- OTT TV refers to the convergence of Internet Protocol (IP) video and Internet applications for television transmission over the public Internet.
- IP Internet Protocol
- the receiving terminal is an Internet TV integrated machine or a set top box + a television set.
- OTT TV refers to the controllable and manageable service of video content provided by state-owned broadcasters through the public Internet for television.
- the receiving terminal is generally a domestic Internet TV integrated machine.
- OTT TVs in the related art mainly have two implementation modes: HTTP Progressive Download (HPD) and HTTP Adaptive Streaming (HAS).
- HPD HTTP Progressive Download
- HAS HTTP Adaptive Streaming
- Traditional OTT TVs generally use HPD technology.
- the HPD-based client only needs to wait a short period of time to download and buffer the first part of the media file before starting playback, and then play it while downloading.
- HPD OTT TV has many limitations, such as: it is not suitable for the transmission of live programs with high real-time requirements; the waiting delay for initial playback is generally longer; when the network bandwidth is unstable, the card screen phenomenon is more likely to occur;
- the video file will continue to be downloaded, and when the user gives up the program to watch, it will cause a waste of downloaded files (consuming bandwidth).
- HAS-based OTT TV uses video segmentation and adaptive bit rate (ABR) technology.
- ABR adaptive bit rate
- the media stream splitter splits the video stream output by the encoder into a series of consecutive, equal-length small slice files and stores them in a web content distribution server.
- the HAS client device can automatically request the appropriate video quality (ie different resolution and bit rate) fragment files from the web server based on the available bandwidth, thus giving the user the best visual experience.
- HAS video In order to facilitate the HAS client to achieve fast, real-time switching between different code rate slices, HAS video generally uses a shorter slice length (for example: 10 seconds). Because the HAS system can be The same size screen terminal provides video fragmentation files suitable for resolution and smooth video playback under different network bandwidth conditions. Therefore, HAS is considered by the industry to be the core technology of multi-screen interactive video that is ubiquitous in the future.
- the embodiment of the invention provides a method and a device for processing data, so as to at least solve the problem of how to monitor and analyze the data reported by the OTT set-top box by using the big data technology in the related art.
- a method of processing data is provided.
- the data processing method includes: the data to be processed reported by the receiver top box, wherein the data to be processed is obtained by processing, by the set top box, the original data obtained from the third party application component, and the original data includes the following. At least one of: file download data, user triggered behavior data, file play data; analysis of processed data to obtain key performance indicator (KPI) data.
- KPI key performance indicator
- the data to be processed is analyzed, and obtaining the KPI data comprises: parsing the data to be processed by using a load balancing component, and sending the parsed data to the distributed message queue cluster; and utilizing the distributed message queue in the distributed message queue cluster
- the parsed data is backed up, and the parsed data is sent to the distributed real-time computing system; the parsed data is analyzed and counted by the distributed real-time computing system to obtain KPI data.
- the parsing of the data to be processed by the load balancing component comprises: parsing the message header and the message body from the data to be processed by using the load balancing component; and stripping the message header by using the load balancing component to reserve the message body.
- the data to be processed reported by the top box is received via the negotiated data interface according to the preset duration.
- the method further comprises: performing offline analysis mining on the KPI data.
- a data processing apparatus is provided.
- the data processing apparatus includes: a receiving module configured to report data to be processed reported by the receiver set top box, wherein the data to be processed is input by the set top box to the original data acquired from the third party application component.
- the original data includes at least one of the following: file download data, user trigger behavior data, file play data; processing module, set to analyze the data to be processed, and obtain KPI data.
- the processing module comprises: a parsing unit configured to parse the data to be processed by the load balancing component, and send the parsed data to the distributed message queue cluster; and the backup unit is configured to utilize the distribution in the distributed message queue cluster The message queue backs up the parsed data, and sends the parsed data to the distributed real-time computing system; the analysis unit is configured to analyze and collect the parsed data through the distributed real-time computing system to obtain KPI data.
- the parsing unit comprises: a parsing subunit, configured to parse the message header and the message body from the to-be-processed data by using the load balancing component; and the processing subunit is configured to perform stripping processing on the message header by using the load balancing component, and retain the message body .
- the receiving module is configured to process the data to be processed reported by the top box via the negotiated data interface according to the preset duration.
- the above apparatus further comprises: an analysis module, configured to perform offline analysis and mining on the KPI data.
- the to-be-processed data reported by the receiver set-top box is used, wherein the to-be-processed data is obtained by processing, by the set-top box, the original data obtained from the third-party application component, and the original data includes at least one of the following: Download data, user triggered behavior data, file playback data; analyze the data to be processed, obtain KPI data, and solve the problem of how to use the big data technology to monitor and analyze the data reported by the OTT set-top box in related technologies, and then it can be timely and timely
- the massive raw data reported by the OTT set-top box is statistically analyzed, and offline mining can be realized.
- FIG. 1 is a flow chart of a method of processing data according to an embodiment of the present invention
- FIG. 2 is a schematic diagram of an OTT set top box data collection model in accordance with a preferred embodiment of the present invention
- FIG. 3 is a flow chart of data processing based on the OTT set top box data collection model shown in FIG. 2, in accordance with a preferred embodiment of the present invention
- FIG. 4 is a block diagram showing the structure of a data processing apparatus according to an embodiment of the present invention.
- FIG. 5 is a block diagram showing the structure of a data processing apparatus in accordance with a preferred embodiment of the present invention.
- FIG. 1 is a flow chart of a method of processing data according to an embodiment of the present invention. As shown in FIG. 1, the method may include the following processing steps:
- Step S102 The data to be processed reported by the receiver top box, wherein the data to be processed is obtained by processing, by the set top box, the original data obtained from the third party application component, and the original data includes at least one of the following: file download data, user Trigger behavior data, file playback data;
- Step S104 analyzing the data to be processed, and acquiring KPI data.
- big data technology cannot be used to monitor and analyze the data reported by the OTT set-top box.
- the method shown in FIG. 1 is used to process the raw data obtained from the third-party application component by the set-top box, and then the data to be processed is obtained, and then the data to be processed reported by the set-top box is analyzed to obtain KPI data, thereby solving the problem.
- the data to be processed reported by the top box can be received via the negotiated data interface according to the preset duration.
- the third party application component collects file downloads, user triggered behavior, and plays back related raw data, and transmits the collected raw data to the set top box data collection interface in real time.
- the set-top box processes the collected raw data, and then reports the data to the specified address via the negotiated data interface according to the preset duration.
- step S104 the data to be processed is analyzed, and acquiring the KPI data may include the following operations:
- Step S1 parsing the data to be processed by using the load balancing component, and sending the parsed data to the distributed message queue cluster;
- Step S2 Backing up the parsed data by using a distributed message queue in the distributed message queue cluster, and sending the parsed data to the distributed real-time computing system;
- Step S3 Perform analysis and statistics on the parsed data through a distributed real-time computing system to obtain KPI data.
- a load balancing component can be employed to receive data reported by the set-top box.
- the data reported by the set top box is parsed, and at the same time, as a client of the distributed message queue, the message body is sent to the distributed message queue cluster.
- the distributed message queue backs up the received data and sends it to the distributed real-time computing system.
- the distributed real-time computing system uses streaming technology to perform real-time parsing and statistics on valid data, thereby obtaining statistical KPI data of the entire network.
- parsing the data to be processed by using the load balancing component may include the following steps:
- Step S11 using a load balancing component to parse the message header and the message body from the to-be-processed data;
- Step S12 The message header is stripped by the load balancing component, and the message body is reserved.
- the load balancing component can be used to parse the data reported by the set top box, stripping the message headers, leaving only the actual useful message body.
- step S104 the data to be processed is analyzed, and after the KPI data is acquired, the following operations may also be included:
- Step S4 Perform offline analysis and mining on the KPI data.
- the distributed real-time computing system can use the streaming technology to perform real-time parsing and statistics on the valid data, thereby obtaining the statistical KPI data of the entire network, and then permanently storing the KPI data to the distributed file system.
- the off-line analysis system can perform on-line analysis and mining of the massive data collected above at any time as needed.
- FIG. 2 is a schematic diagram of an OTT set top box data collection model in accordance with a preferred embodiment of the present invention.
- the set-top box is preset with a third-party application and a platform-side probe component, and the preset monitoring center reports the address.
- the third-party application component is mainly responsible for interacting with the player and the electronic program menu (EPG), collecting user trigger events, the most original playback data, and the like.
- EPG electronic program menu
- licensees have application components that have these functions.
- the probe component is part of the monitoring and analysis system, and the raw data collected by the licensee can be analyzed and processed, and can be upgraded separately.
- the technical solution provided by the embodiment of the present invention will be applied in a monitoring center.
- the operator can decide whether to remotely modify the reporting address of the monitoring center through the network management. Due to various reasons such as network planning, in some cases, operators need to change the allocation to monitoring. The relevant IP address of the center. At this point, you must modify the monitoring center address of the set-top box in time, otherwise the monitoring center may not collect the original data.
- the load balancing component of the monitoring center performs the detection of legitimate terminals and the parsing of network data message headers.
- the data reported by the illegal terminal will be discarded, and the basic information of the terminal will be recorded, which is convenient for troubleshooting.
- the distributed real-time computing system initiates separate threads for detailed data storage without affecting real-time monitoring and analysis.
- FIG. 3 is a flow diagram of data processing based on the OTT set top box data collection model shown in FIG. 2, in accordance with a preferred embodiment of the present invention. As shown in FIG. 3, the method may include the following steps:
- the third-party application component collects the file download, the user triggers the behavior, and plays the relevant original data, and transmits the collected original data to the set-top box data collection interface in real time, for example, if the user has clicked the pause or cancel the pause button, Record the time when the user clicks to pause or cancel the pause button; if buffering has already occurred during the playback of the video, the buffer start time and buffer time can be recorded.
- the set top box performs processing calculation on the collected original data, and reports the data to the specified address via the negotiated data interface according to a preset duration (1 minute, 30 seconds or even 10 seconds).
- the load balancing component is used to receive data reported by the top box. Parsing the data reported by the set-top box, stripping the message header, leaving only the actual useful message body, and sending the message body to the distributed message queue cluster as the client of the distributed message queue.
- the distributed message queue backs up the received data (preventing loss) and simultaneously sends it to the distributed real-time computing system that has registered to listen.
- the fifth step uses the streaming technology to analyze and count the effective data in real time, and basically obtains the statistical key performance indicator (KPI) data of the whole network in real time, and restores the viewing behavior of the user.
- KPI statistical key performance indicator
- massive amounts of raw data are also stored faster in distributed file systems.
- the sixth step is to perform on-line analysis and mining of the massive data collected above according to the needs. For example, the source of the film is classified into a finer classification, and the viewing behavior of each user is analyzed, and the interests and hobbies of the user are found, so that the newly released similar film source is pushed to the user; the program that the user last viewed and the viewing are recorded. Where to go, you can continue playing from that location the next time you need to continue watching.
- the processing device of the data may include: a receiving module 10 configured to process data to be processed reported by the receiver set-top box, wherein the data to be processed is processed by the set-top box for the original data acquired from the third-party application component.
- the start data includes at least one of the following: file download data, user trigger behavior data, file play data; the processing module 20 is configured to analyze the data to be processed, and obtain KPI data.
- the device shown in FIG. 4 is used to solve the problem of how to use the big data technology to monitor and analyze the data reported by the OTT set-top box in the related art, and then the statistical analysis of the massive raw data reported by the OTT set-top box can be performed in a timely manner, and Implement offline mining.
- the processing module 20 may include: a parsing unit 200 configured to parse the data to be processed by the load balancing component, and send the parsed data to the distributed message queue cluster; the backup unit 202, set The data is backed up by using the distributed message queue in the distributed message queue cluster, and the parsed data is sent to the distributed real-time computing system; the analyzing unit 204 is configured to parse through the distributed real-time computing system. The data is analyzed and statistically obtained to obtain KPI data.
- a parsing unit 200 configured to parse the data to be processed by the load balancing component, and send the parsed data to the distributed message queue cluster
- the backup unit 202 set The data is backed up by using the distributed message queue in the distributed message queue cluster, and the parsed data is sent to the distributed real-time computing system
- the analyzing unit 204 is configured to parse through the distributed real-time computing system. The data is analyzed and statistically obtained to obtain KPI data.
- the parsing unit 200 may include: a parsing subunit (not shown) configured to parse the message header and the message body from the to-be-processed data by using a load balancing component; Not shown), set to use the load balancing component to strip the message header and retain the message body.
- a parsing subunit (not shown) configured to parse the message header and the message body from the to-be-processed data by using a load balancing component; Not shown), set to use the load balancing component to strip the message header and retain the message body.
- the receiving module 10 is configured to process the data to be processed reported by the top box via the negotiated data interface according to the preset duration.
- the foregoing apparatus further includes: an analysis module 30 configured to perform offline analysis mining on the KPI data.
- the foregoing embodiment achieves the following technical effects (it is required that the effects are achievable by some preferred embodiments): the technical solution provided by the embodiment of the present invention is adopted by the operator, The Internet TV licensee and the set-top box manufacturer cooperated to realize the collection and quasi-real-time reporting of the user's viewing behavior data and effect data, and then monitor and analyze the massive data reported by the big data technology, thereby restoring the user's viewing behavior and discovering.
- the problems existing in the viewing and the analysis of the user's viewing interests and hobbies so that relevant parties can improve in time, improve the quality of service and conduct targeted marketing, and then statistically analyze the massive raw data reported by the OTT set-top box in a timely manner, and Offline mining is possible.
- the terminal data collection process is jointly participated by operators, domestic mainstream licensees, and mainstream set-top box manufacturers, it can be promoted as an industry standard.
- modules or steps of the present invention described above can be implemented by a general-purpose computing device that can be centralized on a single computing device or distributed across a network of multiple computing devices. Alternatively, they may be implemented by program code executable by the computing device such that they may be stored in the storage device by the computing device and, in some cases, may be different from The steps shown or described are performed sequentially, or they are separately fabricated into individual integrated circuit modules, or a plurality of modules or steps thereof are fabricated into a single integrated circuit module. Thus, the invention is not limited to any specific combination of hardware and software.
- the data processing method and apparatus have the following beneficial effects: through the cooperation of the operator, the Internet TV license party, and the set-top box manufacturer, the user's viewing behavior data and the effect data collection and quasi-realization are realized.
- Real-time reporting and then through the big data technology to monitor and analyze the massive data reported, which can restore the user's viewing behavior, discover the problems in the viewing and analyze the user's viewing interests, so that relevant parties can improve and improve the service in time.
- the quality is targeted and marketed, so that the massive raw data reported by the OTT set-top box can be statistically analyzed in a timely manner, and offline mining can be realized.
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Abstract
L'invention porte sur un procédé et un dispositif de traitement de données. Le procédé comprend : la réception de données à traiter rapportées par un boîtier décodeur, les données à traiter étant obtenues après que le boîtier décodeur conduit un calcul de traitement sur des données d'origine obtenues à partir d'un ensemble d'applications de tiers, les données d'origine comprenant au moins l'un parmi : des données de téléchargement de fichier, des données de comportement de déclenchement d'utilisateur et des données de lecture de fichier; et l'analyse des données à traiter pour obtenir des données KPI. Selon la solution technique fournie dans la présente invention, une analyse statistique peut être conduite sur des données d'origine en masse rapportées par un boîtier décodeur OTT relativement dans le temps.
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CN201410393213.5A CN105335437A (zh) | 2014-08-11 | 2014-08-11 | 数据的处理方法及装置 |
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Cited By (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10841645B1 (en) | 2019-12-09 | 2020-11-17 | Western Digital Technologies, Inc. | Storage system and method for video frame segregation to optimize storage |
US10897627B2 (en) | 2019-01-11 | 2021-01-19 | Western Digital Technologies, Inc. | Non-volatile memory system including a partial decoder and event detector for video streams |
US11064194B2 (en) | 2019-10-31 | 2021-07-13 | Western Digital Technologies, Inc. | Encoding digital videos using controllers of data storage devices |
US11328511B2 (en) | 2020-03-13 | 2022-05-10 | Western Digital Technologies, Inc. | Storage system and method for improved playback analysis |
US11562018B2 (en) | 2020-02-04 | 2023-01-24 | Western Digital Technologies, Inc. | Storage system and method for optimized surveillance search |
Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN106028091B (zh) * | 2016-05-23 | 2020-09-22 | 深圳Tcl数字技术有限公司 | 视频节目推送方法及装置 |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8027264B2 (en) * | 2007-06-01 | 2011-09-27 | Alcatel Lucent | Method and apparatus for measuring subjective assessment of digital video impairment |
CN102291617A (zh) * | 2011-09-03 | 2011-12-21 | 四川公用信息产业有限责任公司 | Iptv业务端到端故障诊断与定位平台 |
CN102457390A (zh) * | 2010-10-15 | 2012-05-16 | 中兴通讯股份有限公司 | 一种基于qoe的故障定位方法和系统 |
CN102547475A (zh) * | 2012-02-21 | 2012-07-04 | 德科仕通信(上海)有限公司 | 提高ip视频媒体流业务质量告警精准度的方法及系统 |
WO2012089708A1 (fr) * | 2010-12-28 | 2012-07-05 | Telefonica, S.A. | Dispositif et procédé de surveillance de trafic de bout en bout et de mesure de qualité délivrée à des consommateurs dans des réseaux optiques passifs |
Family Cites Families (4)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN101835027B (zh) * | 2010-04-16 | 2012-04-18 | 中山大学 | 一种基于双向机顶盒的视频收视率统计及内容推荐系统及方法 |
CN103888798A (zh) * | 2012-12-19 | 2014-06-25 | 中国移动通信集团公司 | 一种用户常用频道之间的切换方法及装置 |
CN103888810B (zh) * | 2014-03-19 | 2017-11-07 | 深圳市九洲电器有限公司 | 一种电视节目排布方法及系统 |
CN103945243A (zh) * | 2014-05-16 | 2014-07-23 | 无锡北斗星通信息科技有限公司 | 用于数字电视节目的收看统计设备 |
-
2014
- 2014-08-11 CN CN201410393213.5A patent/CN105335437A/zh active Pending
-
2015
- 2015-01-06 WO PCT/CN2015/070235 patent/WO2015154549A1/fr active Application Filing
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US8027264B2 (en) * | 2007-06-01 | 2011-09-27 | Alcatel Lucent | Method and apparatus for measuring subjective assessment of digital video impairment |
CN102457390A (zh) * | 2010-10-15 | 2012-05-16 | 中兴通讯股份有限公司 | 一种基于qoe的故障定位方法和系统 |
WO2012089708A1 (fr) * | 2010-12-28 | 2012-07-05 | Telefonica, S.A. | Dispositif et procédé de surveillance de trafic de bout en bout et de mesure de qualité délivrée à des consommateurs dans des réseaux optiques passifs |
CN102291617A (zh) * | 2011-09-03 | 2011-12-21 | 四川公用信息产业有限责任公司 | Iptv业务端到端故障诊断与定位平台 |
CN102547475A (zh) * | 2012-02-21 | 2012-07-04 | 德科仕通信(上海)有限公司 | 提高ip视频媒体流业务质量告警精准度的方法及系统 |
Cited By (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10897627B2 (en) | 2019-01-11 | 2021-01-19 | Western Digital Technologies, Inc. | Non-volatile memory system including a partial decoder and event detector for video streams |
US11064194B2 (en) | 2019-10-31 | 2021-07-13 | Western Digital Technologies, Inc. | Encoding digital videos using controllers of data storage devices |
US11503285B2 (en) | 2019-10-31 | 2022-11-15 | Western Digital Technologies, Inc. | Encoding digital videos using controllers of data storage devices |
US10841645B1 (en) | 2019-12-09 | 2020-11-17 | Western Digital Technologies, Inc. | Storage system and method for video frame segregation to optimize storage |
US11562018B2 (en) | 2020-02-04 | 2023-01-24 | Western Digital Technologies, Inc. | Storage system and method for optimized surveillance search |
US11328511B2 (en) | 2020-03-13 | 2022-05-10 | Western Digital Technologies, Inc. | Storage system and method for improved playback analysis |
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