CN103236957A - Network quality monitoring method based on self-similarity model - Google Patents
Network quality monitoring method based on self-similarity model Download PDFInfo
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Abstract
The invention discloses a network quality monitoring method based on a self-similarity model. The method comprises the following steps that S1, data of network access behavior and service quality information of a client is packaged into the current network access behavior and service quality information of the client; S2, a corresponding client business behavior model is established for raw data; S3, whether customer service is normal or not is judged; S4, a Servlet program is used for resolving and executing workflow operation; S5, when a network is abnormal, a network management part takes remote intervention measures; and S6, workflows are preset, and intelligent intervention is implemented to solve network abnormities. Compared with an original network management system, the method has the advantage that the network abnormities can be efficiently and accurately discovered and can be intelligently solved. Additionally, deep essential reaction to internet behavioral habits of the client, quick and accurate positioning and intelligent remediation of the network abnormities and diversity and convenience of alarms and manual intervention are fully embodied in a commissioning process of a large network operator.
Description
Technical field
The present invention relates to the technical field of computer network, particularly a kind of network quality monitoring method based on the self similarity model.
Background technology
Traditional Network Quality Management is generally only on the static data analysis foundation, and more prior setup parameter perhaps contrasts the diagnostic result that draws after the intrinsic Mathematical Modeling network quality.In recent years, along with the continuous development, particularly network traffics of network traffics analysis theories meets the proposition of the self similarity model with long correlation characteristic, more can not adapt to analysis, management expectancy when lower network based on the Network Quality Management system of old theory.
In addition, old Network Quality Management waits to realize though can play the effect of Network Quality Management to a certain extent, limitation is arranged all usually by fire compartment wall, Access Control List (ACL), QOS.Can not implement dynamic, real-time, intelligent management to particular user types.
Access Control List (ACL) can effectively be managed specific process by protocol number, port numbers, but inconvenience effectively arranges one by one to all types of users, and Access Control List (ACL) is once setting, can not adaptive change network environment, lack necessary intelligence.
QOS is by dividing different service class to satisfy different service types to the requirement of the packet loss of the time delay of transfer bandwidth, transmission, data and delay variation etc.The same with Access Control List (ACL), QOS has equally and can not change along with network change, lacks the defective of necessary intelligence.
Summary of the invention
The shortcoming that the objective of the invention is to overcome prior art provides a kind of network quality monitoring method based on the self similarity model with not enough.
Purpose of the present invention is achieved through the following technical solutions:
The present invention is based on the network quality monitoring method of self similarity model, comprise the steps:
S1, the data encapsulation that adopts the Hibernate method customer network to be visited behavior and service quality information are the visit behavior of client's current network and service quality information;
S2, with initial data by flow, URL visit, online number in time variation characteristic set up corresponding client's business conduct model;
S3, according to user's real-time traffic and visit URL factor, contrast this client's business conduct model, and whether customer service normally judged;
S4, resolve the execution work flow operation by the Servlet program, the operating function point is translated as the executable order of various access layer equipments, and the trace command execution result, the return command execution result is as the foundation of function point operation success or not, operating result judgement;
S5, occur when unusual when network, timely informing network management end, network management side takes the remote intervention measure.
S6, preestablish workflow, occur carrying out intelligence fast and effectively and intervening to solve the network abnormal conditions when unusual at network;
Preferably, among the step S1, when the user was online, corresponding user quality was monitored in real time, and when user's off-line, database is used for the business conduct model analysis, does not participate in quality and monitors in real time.
Preferably, among the step S2, described client's business conduct model is used for distinguishing interest and the behavioural habits that different user groups is used the Internet, forms the user behavior feature database by website URL and service application classification, carries out the model management and control by the mode that threshold values is set.
Preferably, by client's business conduct model analysis, obtain the traffic characteristic of typical customers, if certain type of user real-time traffic much larger than the type client characteristics, the quality of service dynamic monitoring offers warning device with information and reports to the police.
Preferably, among the step S3, adopt the mode of the corresponding thread of each client to carry out the real-time analysis monitoring, if the client is online, host process will start a thread to be come client's real time business quality is monitored, and when user offline, thread will be recovered, put in the middle of the thread pool, wait for calling next time.
Preferably, also comprise the setting of URL blacklist, by the URL blacklist is set, when the URL of client access belonged on the blacklist, the quality of service dynamic monitoring offered alarm module with information.
Preferably, among the step S4, in server S ervlet program, the operational order of submitting to by the user at the equipment situation, whether can it be legal to prejudge order, carry out at designated equipment, reduces the misoperation order to the influence of server and network quality.
Preferably, among the step S5, described remote intervention measure is handled for the mode that adopts note or mail.
Preferably, among the step S6, start according to the monitored results of quality of service dynamic monitoring module to the client, if monitoring module is judged as service exception then starts, the user selects the network control instruction of the required execution of workflow by Web interface mode; In the input instruction, can realize the intelligent executive mode of workflow by inserting the mode of intervention command.
The present invention has following advantage and effect with respect to prior art:
1, method of the present invention can rely on the data on flows of collecting on the long time scale and carries out modeling, thereby sets up the data traffic model that really meets the user network behavioural habits.The old system that compares analyzes, manages with unified model whole network, this system can set up separately self similarity model respectively at different user, thereby can treat different user with a certain discrimination, and then discovery network more rapidly and efficiently is unusual and the effective intelligence of enforcement is intervened.
2, method of the present invention gets based on comparatively advanced Self-similarity Theory design, exploitation, can better adapt to analysis and the monitoring of real network, the old network management of comparing, it can find unusual in the network more efficiently, accurately, and unusual in the more intelligentized solution network.Its discharge model is to this qualitative response of profound level of client's internet behavior custom, to unusual fast, accurately the locating and the intelligence reparation of network, diversity, the convenience of warning and manual intervention all are fully reflected in the trial run process of certain catenet operator.
Description of drawings
Fig. 1 is the flow chart that the present invention is based on the network quality monitoring method of self similarity model.
Embodiment
The present invention is described in further detail below in conjunction with embodiment and accompanying drawing, but embodiments of the present invention are not limited thereto.
Embodiment
The present invention is based on the network quality monitoring method of self similarity model on FBM self similarity model based, actual conditions according to institute of operator carrying client type of service, add the parameter that other can manually be set, thereby finally set up in order to the unusual self similarity model of decision network.Whether after obtaining real time data from data source, as long as the self similarity model that contrast has been set up, judge the similarity degree of real time data and model, it is unusual to get final product decision network.
Service traffics Mean Speed m, coefficient of variation a and three parameters of Hurst are calculated by historical data by system, just can intactly portray whole FBM model then, but the self similarity model of Jian Liing has its limitation like this, particularly when coefficient of variation a is less than normal, even enough big its self-similarity neither be clearly for the Hurst value.At this moment, the just effective actual conditions of reaction network service traffics of FBM model.Therefore, we have added some parameters that can manually set, thereby make the better truth of reaction network flow of final self similarity model.
As shown in Figure 1, the present invention is based on the network quality monitoring method of self similarity model, comprise the steps:
S1, the data encapsulation that adopts the Hibernate method customer network to be visited behavior and service quality information are the visit behavior of client's current network and service quality information;
S2, with initial data by flow, URL visit, online number in time variation characteristic set up corresponding client's business conduct model;
S3, according to user's real-time traffic and visit URL factor, contrast this client's business conduct model, and whether customer service normally judged;
S4, resolve the execution work flow operation by the Servlet program, the operating function point is translated as the executable order of various access layer equipments, and the trace command execution result, the return command execution result is as the foundation of function point operation success or not, operating result judgement;
S5, occur when unusual when network, timely informing network management end, network management side takes the remote intervention measure;
S6, preestablish workflow, occur carrying out intelligence fast and effectively and intervening to solve the network abnormal conditions when unusual at network.
Step S1 is specially: analyzing client's behavior and implementing in the process of quality of service monitoring, system needs a large amount of real time datas to carry out model analysis and quality monitoring, by the Hibernate mode customer network behavior of visiting is encapsulated as the visit behavior of client's current network and service quality information with service quality information related data, realizing real-time and the persistence of data analysis, for client's behavior model analysis module and client's real time business quality monitoring module provide data to support.
When the user was online, corresponding user quality was monitored in real time.When user's off-line, database data only is used for the behavior model analysis, does not participate in quality and monitors in real time, to save grid and server resource.
Among the step S2, described client's business conduct model is used for distinguishing interest and the behavioural habits that different user groups is used the Internet, forms the user behavior feature database by website URL and service application classification, carries out the model management and control by the mode that threshold values is set.
By client's business conduct model analysis, obtain the traffic characteristic of typical customers, if certain type of user real-time traffic much larger than the type client characteristics, the quality of service dynamic monitoring offers warning device with information and reports to the police.
Among the step S3, adopt the mode of the corresponding thread of each client to carry out the real-time analysis monitoring, if the client is online, host process will start a thread to be come client's real time business quality is monitored, and when user offline, thread will be recovered, put in the middle of the thread pool, wait for calling next time.
Also comprise the setting of URL blacklist, by the URL blacklist is set, when the URL of client access belonged on the blacklist, the quality of service dynamic monitoring offered alarm module with information.
Among the step S4, resolve the execution work flow operation by the Servlet program in the automatic intervention module, the various operating function points of intervening module automatically, be translated as the executable order of various access layer equipments, and trace command execution result, the return command execution result is as the foundation of function point operation success or not, operating result judgement.Support Huawei, Cisco, Alcatel, in main flow equipment such as emerging.
Owing to only supporting general-purpose network operations orders such as ping, tracert automatically intervening in the module, realizing on the access layer equipment operational module, we need the user import at network equipment model and corresponding operational order.In server S ervlet program, the operational order that we submit to by the user at the equipment situation, whether can it be legal to prejudge order, carry out etc. at designated equipment, reduces the misoperation order to the influence of server and network quality.
The regular expression example of operational order: ping*, end (all).* represent the operating parameter of artificial input, the coupling character in () is option.
Among the step S5, described remote intervention measure is handled for the mode that adopts note or mail, reports to the police and supports feedback function, and the mode by mobile Web ServiceAPI+Java realizes that note sends.Support short message interface (SMPP, CMPP2.0), after note sends, judge to report to the police whether confirm according to the short message content that returns (returning Y or N, if the user imports other characters and is considered as invalid affirmation).Be set with acquiescence stand-by period, default action (confirm to report to the police or do not confirm and report to the police).
Mail is supported feedback function, adopts the JavaMail technology, realizes that based on the smtp server of 139 mailboxes Email sends.After mail sends, judge to report to the police whether confirm according to the Mail Contents that returns.Be set with acquiescence stand-by period, default action (confirm to report to the police or do not confirm and report to the police).
System possesses the warning message query interface, is not limited to key message inquiries such as date, alert levels, warning recipient.System possesses warning and presents the interface, and the affirmation that can be not limited at the interface report to the police waits operation, and all operations is carried out user authority management and daily record record.。
Among the step S6, start according to the monitored results of quality of service dynamic monitoring module to the client, if monitoring module is judged as service exception then starts, the user selects the network control instruction of the required execution of workflow by Web interface mode; In the input instruction, can realize the intelligent executive mode of workflow by inserting the mode of intervention command, for example after inserting the if intervention command, when satisfying the if condition criterion, just can carry out the submodule that the if statement comprises, otherwise will skip the execution of this submodule.
The self-similarity of system refers to that the feature of certain structure or process all is similar from different space scales or time scale, perhaps the local character of certain system or structure or Local Structure and whole similar.In addition, between integral body and the integral body or between part and the part, also can there be self-similarity.Self-similarity has the form of expression of more complicated generally speaking, rather than local amplification certain multiple overlaps with integral body later on simply fully.But, characterize quantitative property such as the fractal dimension of self--similar systems or structure, can't change (this point is called as flexible symmetry) because of operation such as amplifying or dwindle, just its outside form of expression that changes, self-similarity is only relevant with the dynamic characteristic of complicated nonlinear system usually.
For this sudden not countershaft unit change and the characteristic that changes is called self similarity shape or fractal at any time that exists in the real network business, the system that means has self similarity character under different scales.Refer to that a random process has identical statistical property in each time scale.Self-similarity in the network service shows in longer a period of time, the not variation of scale in time and changing of the statistical property of network traffics (representing with byte number, packet count) in the unit interval.Intuitively, self-similar network traffic and time scale are irrelevant, and suitably under the yardstick, business looks " equally ".
Present embodiment is analyzed with the such client of colleges and universities' network, just there is notable difference in it certainly in the service traffics situation in these specific months of winter and summer vacation and service traffics situation At All Other Times, also have such as the such example of passenger traffic group, their network traffics some festivals or holidays the peak period of going on a journey also have significantly unusual.To the target service type of this system monitoring and by historical data calculate the parameter analysis after, some amendment schemes have been proposed targetedly.But add the artificial selection input flow threshold values bound parameter, with association in time to the FBM model carry out the amplitude correction the fluctuation factor parameter, generate the time interval parameter of the used historical data of self similarity model.
For example for the user of colleges and universities, at the self similarity model that can generate more realistic network traffic conditions between winter and summer vacations by following three means: 1, arrange the self similarity model generate used historical data be between winter and summer vacations in former years data 2, add initial stage vacation and with finishing latter stage model flow amplitude enlarged the fluctuation factor 3 of dwindling at convection current in mid-term in summer vacation discharge amplitude simultaneously, flow threshold values bound is set, it is unusual directly to be considered as network in case certain service traffics surpasses threshold values.
Above-described embodiment is preferred implementation of the present invention; but embodiments of the present invention are not restricted to the described embodiments; other any do not deviate from change, the modification done under spiritual essence of the present invention and the principle, substitutes, combination, simplify; all should be the substitute mode of equivalence, be included within protection scope of the present invention.
Claims (9)
1. based on the network quality monitoring method of self similarity model, it is characterized in that, comprise the steps:
S1, the data encapsulation that adopts the Hibernate method customer network to be visited behavior and service quality information are the visit behavior of client's current network and service quality information;
S2, with initial data by flow, URL visit, online number in time variation characteristic set up corresponding client's business conduct model;
S3, according to user's real-time traffic and visit URL factor, contrast this client's business conduct model, and whether customer service normally judged;
S4, resolve the execution work flow operation by the Servlet program, the operating function point is translated as the executable order of various access layer equipments, and the trace command execution result, the return command execution result is as the foundation of function point operation success or not, operating result judgement;
S5, occur when unusual when network, timely informing network management end, network management side takes the remote intervention measure;
S6, preestablish workflow, occur carrying out intelligence fast and effectively and intervening to solve the network abnormal conditions when unusual at network.
2. the network quality monitoring method based on the self similarity model according to claim 1 is characterized in that, among the step S1, when the user was online, corresponding user quality was monitored in real time, when user's off-line, database is used for the business conduct model analysis, does not participate in quality and monitors in real time.
3. the network quality monitoring method based on the self similarity model according to claim 1, it is characterized in that, among the step S2, described client's business conduct model is used for distinguishing interest and the behavioural habits that different user groups is used the Internet, form the user behavior feature database by website URL and service application classification, carry out the model management and control by the mode that threshold values is set.
4. the network quality monitoring method based on the self similarity model according to claim 3, it is characterized in that, by client's business conduct model analysis, obtain the traffic characteristic of typical customers, if certain type of user real-time traffic is much larger than the type client characteristics, the quality of service dynamic monitoring offers warning device with information and reports to the police.
5. the network quality monitoring method based on the self similarity model according to claim 1, it is characterized in that, among the step S3, adopt the mode of the corresponding thread of each client to carry out the real-time analysis monitoring, if the client is online, host process will start a thread and come client's real time business quality is monitored, when user offline, thread will be recovered, and put in the middle of the thread pool, wait for calling next time.
6. the network quality monitoring method based on the self similarity model according to claim 5, it is characterized in that, also comprise the setting of URL blacklist, by the URL blacklist is set, when the URL of client access belonged on the blacklist, the quality of service dynamic monitoring offered alarm module with information.
7. the network quality monitoring method based on the self similarity model according to claim 1, it is characterized in that, among the step S4, in server S ervlet program, the operational order of submitting to by the user at the equipment situation, whether can it be legal to prejudge order, carry out at designated equipment, reduces the misoperation order to the influence of server and network quality.
8. the network quality monitoring method based on the self similarity model according to claim 1 is characterized in that, among the step S5, described remote intervention measure is handled for the mode that adopts note or mail.
9. the network quality monitoring method based on the self similarity model according to claim 1, it is characterized in that, among the step S6, start according to the monitored results of quality of service dynamic monitoring module to the client, if monitoring module is judged as service exception then starts, the user selects the network control instruction of the required execution of workflow by Web interface mode; In the input instruction, can realize the intelligent executive mode of workflow by inserting the mode of intervention command.
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Application publication date: 20130807 |