CN103856789A - System and method for achieving OTT service quality guarantee based on user behavior analysis - Google Patents
System and method for achieving OTT service quality guarantee based on user behavior analysis Download PDFInfo
- Publication number
- CN103856789A CN103856789A CN201410092349.2A CN201410092349A CN103856789A CN 103856789 A CN103856789 A CN 103856789A CN 201410092349 A CN201410092349 A CN 201410092349A CN 103856789 A CN103856789 A CN 103856789A
- Authority
- CN
- China
- Prior art keywords
- user
- fault
- module
- monitoring module
- quality
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Landscapes
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The invention relates to a system and method for achieving OTT service quality guarantee based on user behavior analysis. The system comprises a film source quality monitoring module, a content distribution network node monitoring module, a terminal monitoring module and a failure positioning and analysis module, wherein the content distribution network node monitoring module is used for carrying out dial testing on an electronic program list and programs of a platform through a simulation terminal at each content distribution network node, and the failure positioning and analysis module is used for positioning a failure according to the monitored states of the film source quality monitoring module and the content distribution network node monitoring module when the terminal monitoring module gives an alarm. The system and method for achieving OTT service quality guarantee based on user behavior analysis monitor the operation conditions of all links of an OTT service from film source production, broadcasting control and dispatching of CDN content to user terminals in real time, rapidly find out and position a problem, improve user experience comprehensively, guarantee long-term development of the OTT core service, provide a powerful support method for achieving the enterprise operation goal, and have a wide application range.
Description
Technical field
The present invention relates to video service quality safeguards technique field, relate in particular to OTT video service quality safeguards technique field, specifically refer to a kind of system and method for realizing the guarantee of OTT quality of service based on user behavior analysis.
Background technology
OTT(Over The Top, refers to various videos and data service business based on open the Internet) TV is that one integrates the multiple technologies such as the Internet, multimedia, communication, and the brand-new business of multiple interactive services is provided to domestic consumer.As a kind of digital service, OTT television services will certainly be with traditional cable TV and IPTV competition.Because people have been accustomed to lower expenses standard and the unbroken service availability of cable TV, therefore how to guarantee that OTT user experience quality can arrive or exceed cable TV and just become one of successful key element of OTT TV.
At present, be mainly to complain while encountering problems by user for the business safeguard work of OTT TV, O&M personnel carry out malfunction elimination and realize.Terminal use's rating is experienced and lacked effective survey tool, OTT video quality problem is lacked to preventative administering and maintaining, OTT video traffic is increased to the network pressure problem brought cannot anticipation etc., is all the problems that run in current OTT business safeguard work process.
OTT video traffic adopts standard http protocol delivery of media data between Web server and client, and HTTP is carried on TCP, the feature of TCP is reliable connection, harmless transmission, after packet loss, can retransmit, shake and time delay meeting are digested by the download of client buffering, and generally client can perception.Only have when the video playback of buffering area is complete does not download to new video segment again in time, just there will be picture to wait for and cushion.At present, there is no international norm OTT quality of service is carried out to complete definition, ITU(International Telecommunication Union, International Telecommunications Union) etc. the existing measurement standard of normal structure mainly for be the application scenarios that damages transmission, also, not for HTTP ABR(Adaptive Bit Rate, be applicable to transmission speed) the issue standard of this OTT Internet business.
Summary of the invention
The object of the invention is to overcome the shortcoming of above-mentioned prior art, provide a kind of and can realize the operation conditions of Real-Time Monitoring OTT business from film source production, Broadcast Control, CDN contents distribution to links such as user terminal sights, found and range of application is widely experienced, had to orientation problem, General Promotion user realizes based on user behavior analysis the system and method that OTT quality of service ensures fast.
To achieve these goals, of the present invention based on user behavior analysis realize OTT quality of service ensure system and method there is following formation:
Should realize the system that OTT quality of service ensures based on user behavior analysis, its main feature is that described system comprises:
Film source quality-monitoring module, in order to detect the sheet source file before reaching the standard grade in product platform side;
Content delivery network node monitoring modular, in order to carry out testing by pseudo-terminal to platform electric program menu and program at each content delivery network node;
Terminal monitoring module, in order to gather user using the rating parameter in OTT business procedure and experience video quality scoring according to described rating calculation of parameter user;
Fault locating analysis module, in order in the time that described terminal monitoring module is reported to the police, positions fault according to the monitoring state of described film source quality-monitoring module and content delivery network node monitoring modular.
Preferably, described system also comprises:
Expertise library module, in order to according to the described warning message analysis of failure type of film source quality-monitoring module, terminal monitoring module and fault locating analysis module and user's rating experience information and notify O&M personnel in the time that the fault order of severity exceedes systemic presupposition value.
More preferably, described expertise library module comprises:
Expertise rule parsing device, in order to according to the warning message analysis of failure type of described film source quality-monitoring module, terminal monitoring module and fault locating analysis module;
User awareness analyzer, in order to according to the rating experience information of the warning message analysis user of described film source quality-monitoring module, terminal monitoring module and fault locating analysis module;
Failure severity evaluator, in order to analyze failure severity and to work as and notify O&M personnel when the fault order of severity exceedes systemic presupposition value.
The invention still further relates to a kind of method that realizes the guarantee of OTT quality of service by described system based on user behavior analysis, it is characterized in that, described method comprises the following steps:
(1) described film source quality-monitoring module detects the sheet source file before reaching the standard grade in product platform side;
(2) described content delivery network node monitoring modular carries out testing by pseudo-terminal to platform electric program menu and program at each content delivery network node;
(3) described terminal monitoring module gathers user using the rating parameter in OTT business procedure and experience video quality scoring according to described rating calculation of parameter user;
(4) in the time that described terminal monitoring module is reported to the police, described fault locating analysis module positions fault according to the monitoring state of described film source quality-monitoring module and content delivery network node monitoring modular.
Preferably, the described rating calculation of parameter user according to described experiences video quality scoring, is specially:
During playing according to program initial buffer duration, program, cushioning the ratio of duration and playing duration and program again cushions the frequency and calculates user and experience video quality and mark.
Preferably, described fault locating analysis module positions fault according to the monitoring state of described film source quality-monitoring module and content delivery network node monitoring modular, comprises the following steps:
(41) whether normally described fault locating analysis module detects the operation of described Set Top Box, if so, continues step (42), otherwise determines that abort situation is in described Set Top Box;
(42) described fault locating analysis module judgement is reported to the police moment front and back within the scope of Preset Time, and whether the monitoring state of described content delivery network node monitoring modular has fault, if so, continues step (43), otherwise continues step (44);
(43) described fault locating analysis module is experienced video quality scoring according to the monitoring state of described content delivery network node monitoring modular and user described content delivery network node service ability is carried out to the comprehensive analysis of regionality;
(44) whether normally described fault locating analysis module judges the operation of Broadcast Control platform, if not, continues step (45);
(45) described fault locating analysis module is analyzed the failsafe link of playing platform according to the interactive information of customer service request.
Preferably, described system also comprises expertise library module, between described step (3) and (4), further comprising the steps of:
(31) the expertise library module described in is according to the described warning message analysis of failure type of film source quality-monitoring module, terminal monitoring module and fault locating analysis module and user's rating experience information and in the time that the fault order of severity exceedes systemic presupposition value, notify O&M personnel.
More preferably, described expert knowledge library comprises expertise rule parsing device, user awareness analyzer and failure severity evaluator, described expertise library module is according to the described warning message analysis of failure type of film source quality-monitoring module, terminal monitoring module and fault locating analysis module and user's rating experience information and in the time that the fault order of severity exceedes systemic presupposition value, notify O&M personnel, comprises the following steps:
(311) described expertise rule parsing device receives warning message and judge fault type corresponding to warning message described in whether existing in described expert knowledge library by cluster analysis, if, continue step (312), otherwise, step (313) continued;
(312) described expertise rule parsing device carries out definite described fault type corresponding to warning message of fuzzy matching based on knowledge base rule of similarity, then continues step (314);
(313) described expertise rule parsing device creates new fault type according to described warning message, then continues step (314);
(314) described user awareness analyzer tidies up according to described fault type and user the impact that this fault of parameter evaluation causes user;
(315) described failure severity evaluator is analyzed failure severity and is worked as and when the fault order of severity exceedes systemic presupposition value, notify O&M personnel.
Adopted in this invention based on user behavior analysis realize OTT quality of service ensure system and method, there is following beneficial effect:
OTT quality of service based on user behavior analysis ensures that invention helps the operation conditions of OTT business O&M personnel Real-Time Monitoring OTT business from film source production, Broadcast Control, CDN contents distribution to links such as user terminal sights, find fast and orientation problem, General Promotion user experiences, ensure the long-run development of OTT core business, for realizing the enterprise operation target means that provide strong support, there is range of application widely.
Its advantage is mainly reflected in the following aspects:
1, active O&M, finds and handling failure prior to user, promotes user and experiences;
2, Real-time Alarm, helps O&M personnel to respond fast emphasis fault;
3, the service ability of CDN node is carried out to Efficient Evaluation, be convenient to the planning of overall content propelling movement network;
4, terminal monitoring reflection OTT user's actual experience;
5, full process and full network, realizes integrated management; Accurately intelligence, realizes operation excellent.
Accompanying drawing explanation
Fig. 1 is the structural representation of realizing the system of OTT quality of service guarantee based on user behavior analysis of the present invention.
Fig. 2 is OTT quality of service measurement model schematic diagram of the present invention.
Fig. 3 is the parameter model of video flowing QoE of the present invention.
Fig. 4 is the flow chart of expertise library module intellectual analysis of the present invention.
Fig. 5 is the end-to-end monitoring schematic diagram of source of the present invention to terminal.
Embodiment
In order more clearly to describe technology contents of the present invention, conduct further description below in conjunction with specific embodiment.
The present invention is based on the testing standard that damages transmission, business scenario under harmless transmission is expanded, according to the transmission feature of OTT video traffic, based on user behavior, by the soft probe technique of terminal, on the real subject matter that affects OTT user's experience, as buffering stand-by period, wait number of times, video code rate reduction etc., comprehensively analyze, evaluate.
The present invention sets up a set of OTT video service quality guarantee system, comprise OTT quality of service (QoS, Quality of Service, service quality) and user's experience (QoE, Quality Of Experience, Quality of experience) measuring technique, monitoring index system, OTT method for diagnosing faults opinion, OTT testing tool and end-to-end QoS monitoring system etc., utilize soft probe technique to gather OTT terminal use viewing-data, analyze, utilize testing technology to CDN(Content DistributionNetwork, content distributing network) node monitors, thereby help user directly effectively to understand terminal use's rating quality, location affects the problem that user experiences fast, thereby improve terminal use's business satisfaction.
The present invention sets up a set of OTT video service quality guarantee system, comprise that OTT Quality of Service and user experience (QoE) measuring technique, monitoring index system, OTT method for diagnosing faults opinion, OTT testing tool and end-to-end QoS monitoring system etc., comprise following several key content.
One, OTT quality of service measurement model as shown in Figure 2.
Analyze by network layer packet capturing, and in conjunction with indexs such as buffering situations in user watched process, calculate MOS(Mean Opinion Score, mean opinion score according to model generalization) score, embodies terminal use's rating and experiences.MOS score is as following table:
Two, OTT quality of service is measured basic index
One) basic index
1, QoS detects index:
--program cushions duration first;
--the buffering ratio in program buffering number of times, the program buffering frequency, program playing process;
--EPG(Electronic Program Guide, electric program menu) request number of times, the frequency of failure;
--EPG request response average delay, maximum delay;
--program ID;
--program is downloaded time started and lasting duration;
--the total duration of program;
--program download progress;
--the CDN node of request;
--program speed of download (average, maximum, minimum);
--request program fragment total degree and the frequency of failure;
--program code check, code check switch;
2, network index:
--time, TCP re-transmission, TCP that TCP connects are out of order;
3, user behavior index:
--user's open and close machine time;
--user's online hours;
--user watches programme information (program code, request time, watch duration, coding parameter, code check etc.)
4, terminal equipment operating index:
--CPU usage;
--memory usage;
--disk space utilization rate;
Two) user experiences video quality scoring
It is the MOS scoring that the subjective assessment of reflection human eye is measured that user experiences video quality scoring (MOS, Mean Opinion Score, mean opinion score).
Narrowly, MOS calculates, in OTT video monitoring main and below three relating to parameters:
1) program initial buffer duration
2) program cushions the ratio of duration and playing duration during playing
3) program cushions the frequency again
Broad sense in fact, in order correctly to simulate the situation of program buffering, we splice according to catching packet, put into local buffering, operation to buffering area when simulation normal video is play, draws three parameters of above-mentioned calculating MOS with the producer-consumer's model.
A few class parameters below carrying out needing in packet capturing, flow-mergence, data splicing, simulated cushioned process:
1) network index class: comprise average bandwidth, maximum bandwidth, packet loss number of times, number of retransmissions etc., network delay
2) Resource Properties class: comprise resource name, code check, code check rise and fall number of times of request etc.
3) user behavior class: the time shift, F.F., the pausing operation that comprise user.
Therefore MOS calculates the above parameter of main basis, draws by certain data model and algorithm.
Three, CDN(Content Delivery Network, i.e. content distributing network) monitoring
By video analysis equipment, CDN node is carried out to initiatively testing of periodicity.The interface that video analysis equipment can provide by Broadcast Control platform obtains the Token of authentication use.Contents for Monitoring comprises EPG service and the order program service that POP point provides.
Testing strategy, testing task are configurable.
Four, intelligent expert storehouse
Expertise library module is mainly according to knowledge base, the warning message of terminal/CDN/ Broadcast Control platform to be gathered and generates fault intellectual analysis and go out the true perception of user, not only draw failure cause, phenomenon of the failure, and determine whether to notify attendant etc. according to severity.
In the warning message input expertise rule parsing device that OTT terminal/CDN/ Broadcast Control platform is reported, tentatively warning message is carried out after cluster analysis, utilize knowledge base rule of similarity to carry out fuzzy matching, thereby obtain reporting to the police affiliated fault type.
Import this fault type and warning message into user awareness analyzer, the video parameter enter video information analyzer of this analyzer by fault and in reporting to the police, thus obtain this alarm failure to the user watched experience impression causing.
User awareness analyzer is experienced result by fault and user and is imported the impact that in the evaluation mechanism of intelligent trouble severity, this fault of Intelligent Evaluation causes user into, and determines whether to notify O&M personnel.
O&M personnel confirm after fault and menace level notice and process this fault receiving.
Five, efficient fault location algorithm
Failure effect analysis (FEA) is to be based upon on the comprehensive basis of warning information, resource information and customer information, fault is carried out to the analysis of temporal correlation, resource dependencies, client's correlation.
Fault location strategy mainly carries out accident analysis location from 3 levels: OTT end side, CDN network side, Broadcast Control platform side.
The control door limit value parameter that fault location arranges according to operating personnel, in the time of OTT terminal monitoring report and alarm, first detect set-top-box system situation, as CPU, internal memories etc., if there is no problem, inquire about in warning t moment surrounding time section, the CDN node that this terminal connects and alarm, the performance data of Broadcast Control platform, further determine whether it is the problem that CDN node or Broadcast Control platform cause.
If CDN node problems,, in this period of association analysis, the viewership of accessing the relevant OTT terminal use of this node, to carry out the comprehensive analysis of regionality to CDN node service ability.
If the problem of Broadcast Control platform, the interactive information of this customer service request of recording by Broadcast Control platform, further analysis is which link in Broadcast Control platform goes wrong.
Fault location result can intuitively embody on OTT terminal use's service link, helps O&M personnel to find fast root problem.
The parameter model of video flowing QoE
For the quality evaluation of video flowing, be according to objective indicator, and give different weights, the QoE index obtaining in conjunction with the actual experience of people's observation.The parameter model of video flowing QoE has covered all levels of OSI seven layer model, as shown in Figure 3.
Under OTT video service quality guarantee system, the monitoring of OTT business is mainly considered to the end-to-end monitoring from source to terminal, schematic diagram is as Fig. 5.
One, film source quality-monitoring
Build film source skill in product platform side and examine system, the sheet source file before reaching the standard grade is detected.
Two, CDN node monitoring
The platform side guarantee video file of reaching the standard grade meets content standard requirement, and the service ability of content distributing network experiences to terminal use's rating the key effect that also plays.At CDN node deployment video analysis equipment, by pseudo-terminal, platform EPG and program are carried out to testing, reflect service availability and the service promptness of CDN node.
Three, terminal monitoring
Gather and report relevant parameter by terminal monitoring module, reflect that user is in the rating experience using in OTT video traffic process.Terminal monitoring emphasis is experienced and quality of service for user.
Four, fault locating analysis
The Real-time Alarm reporting by terminal monitoring module, the result that can detect by inquiry same period CDN testing and platform film source, helps user to carry out fault location.
Five, statistical analysis
The data that report for film source, CDN platform, terminal monitoring module, system is carried out comprehensive statistical analysis.
As shown in Figure 1, of the present invention based on user behavior analysis realize OTT quality of service ensure system comprise:
Film source quality-monitoring module, in order to detect the sheet source file before reaching the standard grade in product platform side;
Content delivery network node monitoring modular, in order to carry out testing by pseudo-terminal to platform electric program menu and program at each content delivery network node;
Terminal monitoring module, in order to gather user using the rating parameter in OTT business procedure and experience video quality scoring according to described rating calculation of parameter user;
Fault locating analysis module, in order in the time that described terminal monitoring module is reported to the police, positions fault according to the monitoring state of described film source quality-monitoring module and content delivery network node monitoring modular;
Expertise library module, in order to according to the described warning message analysis of failure type of film source quality-monitoring module, terminal monitoring module and fault locating analysis module and user's rating experience information and notify O&M personnel in the time that the fault order of severity exceedes systemic presupposition value;
Described expertise library module comprises:
Expertise rule parsing device, in order to according to the warning message analysis of failure type of described film source quality-monitoring module, terminal monitoring module and fault locating analysis module;
User awareness analyzer, in order to according to the rating experience information of the warning message analysis user of described film source quality-monitoring module, terminal monitoring module and fault locating analysis module;
Failure severity evaluator, in order to analyze failure severity and to work as and notify O&M personnel when the fault order of severity exceedes systemic presupposition value.
Of the present invention based on user behavior analysis realize OTT quality of service ensure method comprise the following steps:
(1) described film source quality-monitoring module detects the sheet source file before reaching the standard grade in product platform side;
(2) described content delivery network node monitoring modular carries out testing by pseudo-terminal to platform electric program menu and program at each content delivery network node;
(3) described terminal monitoring module gathers user using rating parameter in OTT business procedure and cushion the ratio of duration and playing duration and program during playing according to program initial buffer duration, program and again cushion the frequency and calculate user and experience video quality and mark;
(31) the expertise library module described in is according to the described warning message analysis of failure type of film source quality-monitoring module, terminal monitoring module and fault locating analysis module and user's rating experience information and in the time that the fault order of severity exceedes systemic presupposition value, notify O&M personnel;
(4) in the time that described terminal monitoring module is reported to the police, described fault locating analysis module positions fault according to the monitoring state of described film source quality-monitoring module and content delivery network node monitoring modular; Specifically comprise following five sub-steps:
(41) whether normally described fault locating analysis module detects the operation of described Set Top Box, if so, continues step (42), otherwise determines that abort situation is in described Set Top Box;
(42) described fault locating analysis module judgement is reported to the police moment front and back within the scope of Preset Time, and whether the monitoring state of described content delivery network node monitoring modular has fault, if so, continues step (43), otherwise continues step (44);
(43) described fault locating analysis module is experienced video quality scoring according to the monitoring state of described content delivery network node monitoring modular and user described content delivery network node service ability is carried out to the comprehensive analysis of regionality;
(44) whether normally described fault locating analysis module judges the operation of Broadcast Control platform, if not, continues step (45);
(45) described fault locating analysis module is analyzed the failsafe link of playing platform according to the interactive information of customer service request.
As shown in Figure 4, described expertise library module is according to the described warning message analysis of failure type of film source quality-monitoring module, terminal monitoring module and fault locating analysis module and user's rating experience information and in the time that the fault order of severity exceedes systemic presupposition value, notify O&M personnel, comprises the following steps:
(311) described expertise rule parsing device receives warning message and judge fault type corresponding to warning message described in whether existing in described expert knowledge library by cluster analysis, if, continue step (312), otherwise, step (313) continued;
(312) described expertise rule parsing device carries out definite described fault type corresponding to warning message of fuzzy matching based on knowledge base rule of similarity, then continues step (314);
(313) described expertise rule parsing device creates new fault type according to described warning message, then continues step (314);
(314) described user awareness analyzer tidies up according to described fault type and user the impact that this fault of parameter evaluation causes user;
(315) described failure severity evaluator is analyzed failure severity and is worked as and when the fault order of severity exceedes systemic presupposition value, notify O&M personnel.
Adopted in this invention based on user behavior analysis realize OTT quality of service ensure system and method, there is following beneficial effect:
OTT quality of service based on user behavior analysis ensures that invention helps the operation conditions of OTT business O&M personnel Real-Time Monitoring OTT business from film source production, Broadcast Control, CDN contents distribution to links such as user terminal sights, find fast and orientation problem, General Promotion user experiences, ensure the long-run development of OTT core business, for realizing the enterprise operation target means that provide strong support, there is range of application widely.
Its advantage is mainly reflected in the following aspects:
1, active O&M, finds and handling failure prior to user, promotes user and experiences;
2, Real-time Alarm, helps O&M personnel to respond fast emphasis fault;
3, the service ability of CDN node is carried out to Efficient Evaluation, be convenient to the planning of overall content propelling movement network;
4, terminal monitoring reflection OTT user's actual experience;
5, full process and full network, realizes integrated management; Accurately intelligence, realizes operation excellent.
In this specification, the present invention is described with reference to its specific embodiment.But, still can make various modifications and conversion obviously and not deviate from the spirit and scope of the present invention.Therefore, specification and accompanying drawing are regarded in an illustrative, rather than a restrictive.
Claims (8)
1. realize based on user behavior analysis the system that OTT quality of service ensures, it is characterized in that, described system comprises:
Film source quality-monitoring module, in order to detect the sheet source file before reaching the standard grade in product platform side;
Content delivery network node monitoring modular, in order to carry out testing by pseudo-terminal to platform electric program menu and program at each content delivery network node;
Terminal monitoring module, in order to gather user using the rating parameter in OTT business procedure and experience video quality scoring according to described rating calculation of parameter user;
Fault locating analysis module, in order in the time that described terminal monitoring module is reported to the police, positions fault according to the monitoring state of described film source quality-monitoring module and content delivery network node monitoring modular.
2. the system that realizes the guarantee of OTT quality of service based on user behavior analysis according to claim 1, is characterized in that, described system also comprises:
Expertise library module, in order to according to the described warning message analysis of failure type of film source quality-monitoring module, terminal monitoring module and fault locating analysis module and user's rating experience information and notify O&M personnel in the time that the fault order of severity exceedes systemic presupposition value.
3. the system that realizes the guarantee of OTT quality of service based on user behavior analysis according to claim 2, is characterized in that, described expertise library module comprises:
Expertise rule parsing device, in order to according to the warning message analysis of failure type of described film source quality-monitoring module, terminal monitoring module and fault locating analysis module;
User awareness analyzer, in order to according to the rating experience information of the warning message analysis user of described film source quality-monitoring module, terminal monitoring module and fault locating analysis module;
Failure severity evaluator, in order to analyze failure severity and to work as and notify O&M personnel when the fault order of severity exceedes systemic presupposition value.
4. realize based on user behavior analysis the method that OTT quality of service ensures by the system described in any one in claims 1 to 3, it is characterized in that, described method comprises the following steps:
(1) described film source quality-monitoring module detects the sheet source file before reaching the standard grade in product platform side;
(2) described content delivery network node monitoring modular carries out testing by pseudo-terminal to platform electric program menu and program at each content delivery network node;
(3) described terminal monitoring module gathers user using the rating parameter in OTT business procedure and experience video quality scoring according to described rating calculation of parameter user;
(4) in the time that described terminal monitoring module is reported to the police, described fault locating analysis module positions fault according to the monitoring state of described film source quality-monitoring module and content delivery network node monitoring modular.
5. the method that realizes the guarantee of OTT quality of service based on user behavior analysis according to claim 4, is characterized in that, the described rating calculation of parameter user according to described experiences video quality scoring, is specially:
During playing according to program initial buffer duration, program, cushioning the ratio of duration and playing duration and program again cushions the frequency and calculates user and experience video quality and mark.
6. the method that realizes the guarantee of OTT quality of service based on user behavior analysis according to claim 4, it is characterized in that, described fault locating analysis module positions fault according to the monitoring state of described film source quality-monitoring module and content delivery network node monitoring modular, comprises the following steps:
(41) whether normally described fault locating analysis module detects the operation of described Set Top Box, if so, continues step (42), otherwise determines that abort situation is in described Set Top Box;
(42) described fault locating analysis module judgement is reported to the police moment front and back within the scope of Preset Time, and whether the monitoring state of described content delivery network node monitoring modular has fault, if so, continues step (43), otherwise continues step (44);
(43) described fault locating analysis module is experienced video quality scoring according to the monitoring state of described content delivery network node monitoring modular and user described content delivery network node service ability is carried out to the comprehensive analysis of regionality;
(44) whether normally described fault locating analysis module judges the operation of Broadcast Control platform, if not, continues step (45);
(45) described fault locating analysis module is analyzed the failsafe link of playing platform according to the interactive information of customer service request.
7. the method that realizes the guarantee of OTT quality of service based on user behavior analysis according to claim 4, is characterized in that, described system also comprises expertise library module, between described step (3) and (4), further comprising the steps of:
(31) the expertise library module described in is according to the described warning message analysis of failure type of film source quality-monitoring module, terminal monitoring module and fault locating analysis module and user's rating experience information and in the time that the fault order of severity exceedes systemic presupposition value, notify O&M personnel.
8. the method that realizes the guarantee of OTT quality of service based on user behavior analysis according to claim 7, it is characterized in that, described expert knowledge library comprises expertise rule parsing device, user awareness analyzer and failure severity evaluator, described expertise library module is according to the described warning message analysis of failure type of film source quality-monitoring module, terminal monitoring module and fault locating analysis module and user's rating experience information and in the time that the fault order of severity exceedes systemic presupposition value, notify O&M personnel, comprises the following steps:
(311) described expertise rule parsing device receives warning message and judge fault type corresponding to warning message described in whether existing in described expert knowledge library by cluster analysis, if, continue step (312), otherwise, step (313) continued;
(312) described expertise rule parsing device carries out definite described fault type corresponding to warning message of fuzzy matching based on knowledge base rule of similarity, then continues step (314);
(313) described expertise rule parsing device creates new fault type according to described warning message, then continues step (314);
(314) described user awareness analyzer tidies up according to described fault type and user the impact that this fault of parameter evaluation causes user;
(315) described failure severity evaluator is analyzed failure severity and is worked as and when the fault order of severity exceedes systemic presupposition value, notify O&M personnel.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410092349.2A CN103856789B (en) | 2014-03-13 | 2014-03-13 | The system and method that OTT quality of services are ensured is realized based on user behavior analysis |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410092349.2A CN103856789B (en) | 2014-03-13 | 2014-03-13 | The system and method that OTT quality of services are ensured is realized based on user behavior analysis |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN103856789A true CN103856789A (en) | 2014-06-11 |
| CN103856789B CN103856789B (en) | 2017-07-14 |
Family
ID=50863929
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410092349.2A Active CN103856789B (en) | 2014-03-13 | 2014-03-13 | The system and method that OTT quality of services are ensured is realized based on user behavior analysis |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN103856789B (en) |
Cited By (26)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105827447A (en) * | 2016-03-31 | 2016-08-03 | 乐视控股（北京）有限公司 | Service alarm method and apparatus |
| CN105848174A (en) * | 2015-01-16 | 2016-08-10 | 中国移动通信集团浙江有限公司 | Method and apparatus for detecting internet access perception of user |
| CN105898427A (en) * | 2016-03-29 | 2016-08-24 | 天脉聚源(北京)传媒科技有限公司 | Method and apparatus for positioning abnormal log-in of set top box |
| CN105978910A (en) * | 2016-07-14 | 2016-09-28 | 中国联合网络通信集团有限公司 | Video service quality index generating method, device and system |
| CN106603340A (en) * | 2016-12-28 | 2017-04-26 | 成都网丁科技有限公司 | Active dial testing method and system of CDN quality |
| CN107087159A (en) * | 2017-04-18 | 2017-08-22 | 天津市德力电子仪器有限公司 | The apparatus for evaluating and appraisal procedure of IPTV and OTT video qualities |
| CN107231552A (en) * | 2017-05-09 | 2017-10-03 | 复旦大学 | A kind of mass monitoring system towards ultra high-definition video request program |
| CN107509121A (en) * | 2016-06-14 | 2017-12-22 | 华为技术有限公司 | Determine method and apparatus, the method and apparatus of locating network fault of video quality |
| TWI625623B (en) * | 2016-09-30 | 2018-06-01 | Chunghwa Telecom Co Ltd | Digital service component quality information assembly and correlation analysis method |
| CN108174286A (en) * | 2017-12-27 | 2018-06-15 | 北京奇艺世纪科技有限公司 | A kind of processing method and processing device of video code flow |
| CN108243446A (en) * | 2016-12-27 | 2018-07-03 | 中国移动通信集团浙江有限公司 | A kind of network communication problem determination processing method and device |
| CN108876098A (en) * | 2018-04-28 | 2018-11-23 | 北京奇艺世纪科技有限公司 | Determine the method and device of user quality |
| CN108933694A (en) * | 2018-06-09 | 2018-12-04 | 西安电子科技大学 | Data center network Fault Node Diagnosis method and system based on testing data |
| CN110087101A (en) * | 2018-01-25 | 2019-08-02 | 北京市博汇科技股份有限公司 | A kind of interactive video quality monitoring method, device |
| CN110213572A (en) * | 2019-06-13 | 2019-09-06 | 上海佰贝科技发展股份有限公司 | A kind of filtering false alarm method in broadcast link |
| CN110896544A (en) * | 2018-09-13 | 2020-03-20 | 中国移动通信集团山东有限公司 | Fault delimiting method and device |
| CN110944232A (en) * | 2018-09-21 | 2020-03-31 | 中国移动通信有限公司研究院 | Method and device for monitoring cognitive behaviors and set top box |
| CN111586475A (en) * | 2020-05-27 | 2020-08-25 | 飞思达技术（北京）有限公司 | IPTV and OTT live broadcast audio and video quality and perception evaluation system |
| CN111918103A (en) * | 2019-05-08 | 2020-11-10 | 中国移动通信集团福建有限公司 | Internet television service fault determination method and equipment and internet television service architecture |
| CN112104470A (en) * | 2019-06-18 | 2020-12-18 | 中国移动通信有限公司研究院 | Network equipment fault positioning method and digital home service analysis platform |
| CN112995648A (en) * | 2019-12-13 | 2021-06-18 | 中国移动通信集团辽宁有限公司 | Internet television full-flow fault diagnosis method and device and computing equipment |
| CN113630285A (en) * | 2020-11-11 | 2021-11-09 | 中国移动通信有限公司研究院 | Broadband network quality diagnosis method, device and system |
| CN114244691A (en) * | 2020-09-09 | 2022-03-25 | 中国移动通信有限公司研究院 | Video service fault positioning method and device and electronic equipment |
| CN114584760A (en) * | 2022-03-01 | 2022-06-03 | 湖南快乐阳光互动娱乐传媒有限公司 | Media asset dial testing method and related equipment |
| CN115002518A (en) * | 2022-05-30 | 2022-09-02 | 咪咕视讯科技有限公司 | Data monitoring method and device and computer readable storage medium |
| CN115834940A (en) * | 2022-11-14 | 2023-03-21 | 浪潮通信信息系统有限公司 | IPTV/OTT end-to-end data reverse acquisition analysis method and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102143389A (en) * | 2011-04-22 | 2011-08-03 | 赛特斯网络科技(南京)有限责任公司 | Quality assurance (QA) system and method of internet protocol television (IPTV) services |
| CN103036707A (en) * | 2012-11-27 | 2013-04-10 | 赛特斯网络科技(南京)有限责任公司 | Portable diagnostic device of internet protocol television (IPTV) business service quality and diagnostic method of IPTV business service quality |
| CN103236948A (en) * | 2013-04-24 | 2013-08-07 | 中国电信股份有限公司重庆分公司 | Telecommunication network alarm method and system |
| US20130326551A1 (en) * | 2012-05-30 | 2013-12-05 | Debdeep CHATTERJEE | Wireless multimedia quality of experience reporting |
-
2014
- 2014-03-13 CN CN201410092349.2A patent/CN103856789B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102143389A (en) * | 2011-04-22 | 2011-08-03 | 赛特斯网络科技(南京)有限责任公司 | Quality assurance (QA) system and method of internet protocol television (IPTV) services |
| US20130326551A1 (en) * | 2012-05-30 | 2013-12-05 | Debdeep CHATTERJEE | Wireless multimedia quality of experience reporting |
| CN103036707A (en) * | 2012-11-27 | 2013-04-10 | 赛特斯网络科技(南京)有限责任公司 | Portable diagnostic device of internet protocol television (IPTV) business service quality and diagnostic method of IPTV business service quality |
| CN103236948A (en) * | 2013-04-24 | 2013-08-07 | 中国电信股份有限公司重庆分公司 | Telecommunication network alarm method and system |
Cited By (38)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105848174A (en) * | 2015-01-16 | 2016-08-10 | 中国移动通信集团浙江有限公司 | Method and apparatus for detecting internet access perception of user |
| CN105848174B (en) * | 2015-01-16 | 2019-10-29 | 中国移动通信集团浙江有限公司 | A kind of method and apparatus of detection user online perception |
| CN105898427B (en) * | 2016-03-29 | 2019-07-26 | 天脉聚源(北京)传媒科技有限公司 | A kind of method and apparatus that set-top box login positions extremely |
| CN105898427A (en) * | 2016-03-29 | 2016-08-24 | 天脉聚源(北京)传媒科技有限公司 | Method and apparatus for positioning abnormal log-in of set top box |
| CN105827447A (en) * | 2016-03-31 | 2016-08-03 | 乐视控股（北京）有限公司 | Service alarm method and apparatus |
| CN107509121B (en) * | 2016-06-14 | 2020-06-02 | 华为技术有限公司 | Method and device for determining video quality and method and device for positioning network fault |
| CN107509121A (en) * | 2016-06-14 | 2017-12-22 | 华为技术有限公司 | Determine method and apparatus, the method and apparatus of locating network fault of video quality |
| CN105978910A (en) * | 2016-07-14 | 2016-09-28 | 中国联合网络通信集团有限公司 | Video service quality index generating method, device and system |
| TWI625623B (en) * | 2016-09-30 | 2018-06-01 | Chunghwa Telecom Co Ltd | Digital service component quality information assembly and correlation analysis method |
| CN108243446B (en) * | 2016-12-27 | 2021-07-13 | 中国移动通信集团浙江有限公司 | Network communication problem judgment processing method and device |
| CN108243446A (en) * | 2016-12-27 | 2018-07-03 | 中国移动通信集团浙江有限公司 | A kind of network communication problem determination processing method and device |
| CN106603340A (en) * | 2016-12-28 | 2017-04-26 | 成都网丁科技有限公司 | Active dial testing method and system of CDN quality |
| CN107087159A (en) * | 2017-04-18 | 2017-08-22 | 天津市德力电子仪器有限公司 | The apparatus for evaluating and appraisal procedure of IPTV and OTT video qualities |
| CN107087159B (en) * | 2017-04-18 | 2018-12-28 | 天津市德力电子仪器有限公司 | The assessment device and appraisal procedure of IPTV and OTT video quality |
| CN107231552A (en) * | 2017-05-09 | 2017-10-03 | 复旦大学 | A kind of mass monitoring system towards ultra high-definition video request program |
| CN108174286A (en) * | 2017-12-27 | 2018-06-15 | 北京奇艺世纪科技有限公司 | A kind of processing method and processing device of video code flow |
| CN108174286B (en) * | 2017-12-27 | 2021-02-09 | 北京奇艺世纪科技有限公司 | Video code stream processing method and device |
| CN110087101B (en) * | 2018-01-25 | 2022-01-21 | 北京市博汇科技股份有限公司 | Interactive video quality monitoring method and device |
| CN110087101A (en) * | 2018-01-25 | 2019-08-02 | 北京市博汇科技股份有限公司 | A kind of interactive video quality monitoring method, device |
| CN108876098A (en) * | 2018-04-28 | 2018-11-23 | 北京奇艺世纪科技有限公司 | Determine the method and device of user quality |
| CN108933694B (en) * | 2018-06-09 | 2021-11-09 | 西安电子科技大学 | Data center network fault node diagnosis method and system based on dial testing data |
| CN108933694A (en) * | 2018-06-09 | 2018-12-04 | 西安电子科技大学 | Data center network Fault Node Diagnosis method and system based on testing data |
| CN110896544A (en) * | 2018-09-13 | 2020-03-20 | 中国移动通信集团山东有限公司 | Fault delimiting method and device |
| CN110944232A (en) * | 2018-09-21 | 2020-03-31 | 中国移动通信有限公司研究院 | Method and device for monitoring cognitive behaviors and set top box |
| CN111918103B (en) * | 2019-05-08 | 2022-06-14 | 中国移动通信集团福建有限公司 | Internet television service fault determination method and equipment and internet television service system |
| CN111918103A (en) * | 2019-05-08 | 2020-11-10 | 中国移动通信集团福建有限公司 | Internet television service fault determination method and equipment and internet television service architecture |
| CN110213572A (en) * | 2019-06-13 | 2019-09-06 | 上海佰贝科技发展股份有限公司 | A kind of filtering false alarm method in broadcast link |
| CN112104470A (en) * | 2019-06-18 | 2020-12-18 | 中国移动通信有限公司研究院 | Network equipment fault positioning method and digital home service analysis platform |
| CN112995648A (en) * | 2019-12-13 | 2021-06-18 | 中国移动通信集团辽宁有限公司 | Internet television full-flow fault diagnosis method and device and computing equipment |
| CN112995648B (en) * | 2019-12-13 | 2023-10-27 | 中国移动通信集团辽宁有限公司 | Internet television full-flow fault diagnosis method and device and computing equipment |
| CN111586475A (en) * | 2020-05-27 | 2020-08-25 | 飞思达技术（北京）有限公司 | IPTV and OTT live broadcast audio and video quality and perception evaluation system |
| CN111586475B (en) * | 2020-05-27 | 2022-05-06 | 飞思达技术（北京）有限公司 | IPTV and OTT live broadcast audio and video quality and perception evaluation system |
| CN114244691A (en) * | 2020-09-09 | 2022-03-25 | 中国移动通信有限公司研究院 | Video service fault positioning method and device and electronic equipment |
| CN113630285A (en) * | 2020-11-11 | 2021-11-09 | 中国移动通信有限公司研究院 | Broadband network quality diagnosis method, device and system |
| CN114584760A (en) * | 2022-03-01 | 2022-06-03 | 湖南快乐阳光互动娱乐传媒有限公司 | Media asset dial testing method and related equipment |
| CN115002518A (en) * | 2022-05-30 | 2022-09-02 | 咪咕视讯科技有限公司 | Data monitoring method and device and computer readable storage medium |
| CN115002518B (en) * | 2022-05-30 | 2024-03-22 | 咪咕视讯科技有限公司 | Data monitoring method, device and computer readable storage medium |
| CN115834940A (en) * | 2022-11-14 | 2023-03-21 | 浪潮通信信息系统有限公司 | IPTV/OTT end-to-end data reverse acquisition analysis method and system |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103856789B (en) | 2017-07-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN103856789A (en) | System and method for achieving OTT service quality guarantee based on user behavior analysis | |
| US10841358B2 (en) | System and method for determining quality of a media stream | |
| Bronzino et al. | Inferring streaming video quality from encrypted traffic: Practical models and deployment experience | |
| CN107493509A (en) | Video quality monitoring method and device | |
| CN107277160A (en) | A kind of content delivery network node switching method and device | |
| CN102143389B (en) | Quality assurance (QA) system and method of internet protocol television (IPTV) services | |
| US20150319004A1 (en) | System and method of monitoring video data packet delivery | |
| US8537683B2 (en) | Method for estimating the quality of experience of a user in respect of audio and/or video contents distributed through telecommunications networks | |
| US8238258B2 (en) | System and method of managing network performance | |
| CN112584192B (en) | Network quality monitoring method and device and server | |
| CN107318046B (en) | Internet television service transmission quality monitoring method and system | |
| CN102291267A (en) | Failure positioning method and device | |
| CN106656629A (en) | Prediction method for stream media playing quality | |
| CN107231552A (en) | A kind of mass monitoring system towards ultra high-definition video request program | |
| US20230156068A1 (en) | System and method for managing video streaming quality of experience | |
| CN105335437A (en) | Data processing method and apparatus | |
| US20080101591A1 (en) | System and method for selecting a profile for a digital subscriber line | |
| Shaikh et al. | Modeling and analysis of web usage and experience based on link-level measurements | |
| CN103369403B (en) | Set Top Box program request packet analysis system and analysis method | |
| CN106549794A (en) | A kind of mass monitoring system of OTT business, apparatus and method | |
| Bartolec et al. | Impact of user playback interactions on in-network estimation of video streaming performance | |
| Karthikeyan et al. | Benchmarking video service quality: Quantifying the viewer impact of loss-related impairments | |
| Bhargava et al. | Comparative evaluation of user perceived quality assessment of design strategies for http-based adaptive streaming | |
| Qiao et al. | Understanding and improving user engagement in adaptive video streaming | |
| CN107317692B (en) | Fault reporting method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| ASS | Succession or assignment of patent right |
Owner name: BEIJING MEIQI HUAYUE COMMUNICATION TECHNOLOGY CO., Free format text: FORMER OWNER: CERTUS INFORMATION TECHNOLOGY CO., LTD. Effective date: 20140808 |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| COR | Change of bibliographic data |
Free format text: CORRECT: ADDRESS; FROM: 210042 NANJING, JIANGSU PROVINCE TO: 100052 XUANWU, BEIJING |
|
| TA01 | Transfer of patent application right |
Effective date of registration: 20140808 Address after: 100052, Beijing, Xuanwu, No. 10, 1015 square Avenue, central office building, north wing, room 10 Applicant after: BEIJING MEIQI HUAYUE COMMUNICATION TECHNOLOGY CO., LTD. Address before: 210042 Xuanwu District, Xuanwu District, Jiangsu, Nanjing, No. 699-22, building 18 Applicant before: CERTUSNET CORP. |
|
| C41 | Transfer of patent application or patent right or utility model | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20160314 Address after: 100086 Beijing city Haidian District Zhongguancun academy road section Information Center No. 2 B block 8 layer Applicant after: BEIJING CERTUSNET INFORMATION TECHNOLOGY CO., LTD. Address before: 100052, Beijing, Xuanwu, No. 10, 1015 square Avenue, central office building, north wing, room 10 Applicant before: BEIJING MEIQI HUAYUE COMMUNICATION TECHNOLOGY CO., LTD. |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant |