CN1677934A - Method and system for monitoring network service performance - Google Patents

Method and system for monitoring network service performance Download PDF

Info

Publication number
CN1677934A
CN1677934A CN 200410032079 CN200410032079A CN1677934A CN 1677934 A CN1677934 A CN 1677934A CN 200410032079 CN200410032079 CN 200410032079 CN 200410032079 A CN200410032079 A CN 200410032079A CN 1677934 A CN1677934 A CN 1677934A
Authority
CN
China
Prior art keywords
baseline
data
network
performance
analysis
Prior art date
Application number
CN 200410032079
Other languages
Chinese (zh)
Other versions
CN100356729C (en
Inventor
胡旻
Original Assignee
华为技术有限公司
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to CNB2004100320792A priority Critical patent/CN100356729C/en
Publication of CN1677934A publication Critical patent/CN1677934A/en
Application granted granted Critical
Publication of CN100356729C publication Critical patent/CN100356729C/en

Links

Abstract

Through base line configured by network management system, the disclosed method analyses parameters in order to determine range of service data and type of base line. The method includes following steps: based on configuration, the network management system samples service data; obtaining mean value, maximum and / or minimum of service data so as to form one or more base lines of reflecting service performance; obtaining current service data from network; based on comparison between service data of current sampled points and base line, if values of service data of continuous multiple sampled points are deviated from base line and located at same side of base line, then it is determined that fixed change trend is existed in network performance of the network.

Description

The method and system of monitor network service feature
Technical field
The present invention relates to communication network technology, relate in particular to a kind of method and system of monitor network service feature.
Background technology
In communication network, operator need hold network ruuning situation in each in period, judge by analyzing the performance data of gathering whether operation degenerates or anomaly trend, as the foundation that the network optimization, plan of operation, failure diagnosis, viral source are found, black Internet bar is followed the trail of.
At present in the network performance analysis, particularly in the flow analysis, operator only obtains the performance data of being correlated with, and adds up according to time shaft and management object collection, certain statistical information constantly can only be obtained, the long-time running trend or the cycling service trend of network can't be obtained.
Summary of the invention
The object of the present invention is to provide a kind of method and system of monitor network service feature, exist in the prior art can't be for a long time or the problem of periodicity monitor network service feature variation tendency to solve.
Realize technical method of the present invention:
A kind of method of monitor network service feature, but described network has the network management system of collection network business datum, and the method comprising the steps of:
By network management system configuration baseline analysis parameter, to determine the scope and the baseline type of business datum;
According to disposing the business datum of from network, sampling;
From described business datum, obtain mean value, maximum and/or the minimum value of business datum, and be datum mark, form one or more baseline of reflection service feature with the corresponding relation of business datum value and time with this value;
With described baseline is reference, from network, obtain the current business data value and the value corresponding with current time point on the baseline compares, when the business datum value that continuous a plurality of sampled points occur all was greater than or less than the value of corresponding sampled point on the baseline, then there was fixing variation tendency in the service feature of decision network.
When there is fixing variation tendency in the service feature of decision network, produces warning information or/and carry out pre-configured control strategy network is carried out optimal control in dynamic.
Described baseline is for existing the simple baseline of relatively stable characteristic in the expression traffic data is during a time period, this baseline analysis parameter comprises baseline type, historical data point data, the superseded mode of abnormal data and confidential interval.
There is the period of performance baseline of cyclic variation trend in described baseline within a certain period of time for representing business datum, and this baseline analysis parameter comprises cycle, historical data periodicity, distributional analysis point base unit, the superseded mode of abnormal data and confidential interval.
A kind of Network performance monitoring system comprises:
The performance data library module is used to store History Performance Data;
The base-line data library module is used to store baseline configuration data and base-line data;
The service data acquisition module is used for collecting from communication network the real data of relevant performance operational indicator, and stores described performance data library module into;
The baseline analysis configuration module is used to receive the baseline analysis configuration parameter of customization, stores configuration data into the base-line data library module;
The base-line data analysis module reads History Performance Data and baseline analysis configuration parameter formation baseline from described performance data library module and base-line data library module respectively, and is saved in the baseline database;
Network optimization analysis module is used for judging the network performance quality according to the business configuration of base-line data, the network equipment and the current performance data that collects, and network is carried out corresponding Optimizing operation.
The present invention has following beneficial effect:
1, can monitor abnormal flow in the communication network, automatically unusual port be positioned and isolated controlling, be particularly useful in the black Internet bar of control virus and control.
2, the basic data by providing service feature to change is convenient to the O﹠M personnel and is carried out the network optimization, the network planning, failure diagnosis, viral source discovery, the tracking of black Internet bar.
3, by confidential interval rejecting abnormalities data, when avoiding carrying out the baseline analysis prediction because sample point seldom causes a deviation bigger situation.
4, by the baseline interval mode, provide an acceptable service feature of user constant interval.
5, the trend that the baseline by continuous consistent variation tendency relatively can early detection performance change (degenerating/improve).
Description of drawings
Fig. 1 is a telecommunications metropolitan area network schematic diagram;
Fig. 2 is a network optimization baseline analysis system configuration schematic diagram of the present invention;
Fig. 3 A is the simple baseline schematic diagrames of two district office uplink ports;
Fig. 3 B is the simple baseline schematic diagrames of eight district office uplink ports;
Fig. 4 A is two district office current business data and baseline comparison diagrams;
Fig. 4 B is eight district office current business data and baseline comparison diagrams;
Fig. 5 is two district office uplink port date periodicity baseline schematic diagrames;
Fig. 6 is that two district office uplink port actual traffic data and date periodicity baseline compare schematic diagram.
Embodiment
Embodiment one
Present embodiment describes performance simple radical line analysis of the present invention.Consult the network of telecommunications metropolitan area network shown in Figure 1, in metropolitan area, the broadband Access Network that such classification is converged, be divided into two areas, He Ba district, two districts, all adopt MA5100 that ADSL is provided service access, all traffic aggregations enter the metropolitan area network transmission behind ISN8850.Working procedure carries out the collection of data on flows on webmaster.The scope of gathering is the per day speed of all ISN8850 uplink ports.
Consult shown in Figure 2ly, the Network performance monitoring system comprises:
Performance database: preserve History Performance Data.
Baseline database: preserve baseline configuration data and base-line data.
Service data acquisition module: be responsible for collecting the real data of relevant performance operational indicator, and be saved in the performance database from communication network.
Baseline analysis configuration template: be responsible for receiving the baseline analysis configuration parameter of customization, configuration data is saved in database, be used for baseline analysis.
Base-line data analysis module: read History Performance Data and baseline analysis configuration parameter from described performance data library module and base-line data library module respectively, form the required baseline of user based on the baseline analysis method, and be saved in the baseline database.
Network optimization analysis module: be responsible for according to base-line data, in conjunction with the business configuration of the network equipment and the current performance data that collects, carry out baseline relatively, judge the network performance quality, output network is optimized analysis report, and carries out the automatic or manual Optimizing operation of network configuration.
Performance simple radical line analysis comprises: the configuration of simple radical line analysis, abnormal data rejecting, simple baseline data analysis, baseline are relatively.
1, simple radical line analysis configuration: baseline historical data scope is set up in definition, needs the following relevant parameter of configuration:
Baseline type: day baseline, all baselines, month baseline, year baseline.
Historical data is counted: carry out the required historical data of simple baseline data analysis and count out.Count many more long-term trend that reflect more, the nearest variation tendency of the fine reflection of less energy of counting are set.
Abnormal data is eliminated mode: eliminate abnormal data; Do not eliminate abnormal data.Do not eliminate the mode of abnormal data, all data will be used for baseline analysis.
Confidential interval: eliminate abnormal data and adopt [mean value-mean value * n%, mean value+mean value * n%], wherein n% is a confidence level, and the n value is 30, and the control of n can be by being provided with realization.
The scope and the baseline type of initial data determined in the configuration of simple radical line analysis.Eliminate the abnormal data mode for adopting, just need carry out the preliminary treatment of data.Entered for the 3rd step on the contrary: simple base-line data distributional analysis.Setting up the order baseline below is that example illustrates.
For example: set up simple day baseline with reference to the historical data in past 7 days altogether, the confidence level of employing 30% is eliminated abnormal data, and parameter is:
Baseline type: day baseline
Historical data is counted: 7
Abnormal data is eliminated mode: eliminate abnormal data
Confidential interval: [mean value-mean value * 30%, mean value+mean value * 30%]
The initial data of analyzing following (seven days):
The ISN 8850 uplink port actual speed rate (Gb/s) in two districts
1 2 3 4 5 6 7
0.7 0.45 0.65 0.5 0.60 0.55 0.85
The ISN 8850 uplink port actual speed rate (Gb/s) in eight districts
1 2 3 4 5 6 7
0.8 0.69 0.9 0.76 0.42 0.85 0.94
2, abnormal data is rejected
The data that abnormal data is meant and all initial data mean deviations are too big.Because the data of sample point are few, the calculating of inapplicable normal distribution adopts simple confidential interval [mean value-mean value * n%, mean value+mean value * n%] mode to come the rejecting abnormalities data.This initial average output value is different from follow-up baseline average.We are calculated as follows to the data in the example:
The ISN 8850 uplink port actual speed rate (Gb/s) in two districts
Mean value=(0.7+0.45+0.65+0.5+0.60+0.55+0.85)/7=0.614
Confidential interval: [0.614 * 0.7,0.614*1.3]=[0.43,0.80]
The 7th data 0.85 are disallowable.
The ISN 8850 uplink port actual speed rate (Gb/s) in eight districts
Mean value=(0.8+0.69+0.9+0.76+0.42+0.85+0.94)/7=0.766
Confidential interval: [0.766 * 0.7,0.766*1.3]=[0.54,0.99]
The 5th data 0.42 are disallowable.
3, simple baseline data analysis
Simple baseline data analysis is that historical data sampled point valid data are calculated its mean value, maximum, minimum value, so just forms three points, extends along x direction of principal axis horizontal-extending horizontal direction and has just formed baseline.To the data in the example, calculated data is as follows, extends and has just formed a day baseline.
The ISN 8850 uplink port actual speed rate (Gb/s) in two districts:
Maximum=MAX[0.7,0.45,0.65,0.5,0.60,0.55]=0.7
Minimum value=MIN[0.7,0.45,0.65,0.5,0.60,0.55]=0.45
Mean value=AVG[0.7,0.45,0.65,0.5,0.60,0.55]=0.575
The simple baseline of the performance in two districts is consulted shown in Fig. 3 A.
The ISN 8850 uplink port actual speed rate (Gb/s) in eight districts:
Maximum=MAX[0.8,0.69,0.9,0.76,0.85,0.94]=0.94
Minimum value=MIN[0.8,0.69,0.9,0.76,0.85,0.94]=0.69
Mean value=AVG[0.8,0.69,0.9,0.76,0.85,0.94]=0.82
The simple baseline of the performance in eight districts is consulted shown in Fig. 3 B.
4, baseline relatively
Network optimization analysis module, the current performance data from network obtains compares these performance datas and base-line data, relatively adopts baseline interval graph mode.Exceed the baseline interval according to current sampling point and do understanding current business performance change.
The speed data of the current collection of two district ISN8850 uplink ports:
0.6?0.58?0.65?0.49?0.52?0.56?0.65
Two district's current datas and base-line data are relatively shown in Fig. 4 A.
The speed data of the current collection of eight district ISN8850 uplink ports:
0.96?0.98?0.95?0.92?0.89?0.88?0.98
Eight district's current datas and base-line data are relatively shown in Fig. 4 B.
In relatively judging, use for reference the quality sampling analysis method in the quality management system, the general employing has continuous 7 times to surpass the deviation that is in identical direction, can decision-making system have fixing variation tendency.Native system exceeds a certain baseline interval according to continuous several times in same direction and judges whether network performance the performance change on certain trend has taken place.Its number of times is by the decision of different business field, and communication network generally adopts the 4-7 point to calculate, and also availablely adjusts (zooming in or out) according to the current business actual conditions.
5, when there is fixing variation tendency in the service feature of decision network, carries out pre-configured control strategy network is carried out optimal control in dynamic.
Judge performance change trend when getting 3 as quality sampling bias number of times.By last two figure as can be seen, the current uplink port actual flow of the convergence device in two districts is in the baseline scope, temporarily big variation can not appear, the demand that does not also have dilatation, and continuous three baseline intervals above baseline maximum and minimum value have appearred in the current uplink port actual flow of the convergence device in eight districts, represent that this Local Area Network traffic carrying capacity is excessive, be badly in need of carrying out the dilatation measure.In actual implementation process, the access point in eight intervals is cut to the ISN 8850 times in two intervals, realize the network optimization that no dilatation is invested like this.
Embodiment two:
Present embodiment describes period of performance baseline analysis of the present invention.Equally with the ISN8850 uplink port of network Zhong Er shown in Figure 1 district office every day 8:00-9:00AM the port actual speed rate be example.The Network performance monitoring system as shown in Figure 2.
The period of performance baseline analysis comprises: periodically baseline analysis configuration, abnormal data rejecting, periodicity base-line data analysis and baseline are relatively.
1, periodically the baseline analysis configuration comprises:
Cycle: according to service feature, the general cycle comprises diurnal periodicity, cycle, month cycle and annual period.
The historical data periodicity: the initial data of carrying out baseline analysis is the historical data in a plurality of cycles, historical data is many more to reflect general trend more, but increase/subtract the business of trend for having for a long time, the baseline that is comprehensively formed by too much historical data can not reflect nearest service feature well.Very few historical data causes data deviation bigger again easily, and individual influence is bigger, can not be as effective performance baseline.The number of cycles of suitable historical data is 3-8 cycle.
Distributional analysis point base unit: be exactly in the cycle, carry out the unit of the time point of distributional analysis.Generally in diurnal periodicity, adopt hour as distributional analysis point base unit; Adopt day as distributional analysis point base unit in the cycle; Adopt day as distributional analysis point base unit in the cycle moon; Adopt the moon as distributional analysis point base unit in annual period.
Abnormal data is eliminated mode: eliminate abnormal data; Do not eliminate abnormal data.Do not eliminate the mode of abnormal data, all data will be used for baseline analysis.
Confidential interval: eliminate abnormal data and adopt [mean value-mean value * n%, mean value+mean value * n%], wherein n% is a confidence level, and n gets 30, and the control of n can be by being provided with realization.
Periodically the scope and the baseline type of initial data determined in the baseline analysis configuration.Eliminate the abnormal data mode for adopting, just need carry out the preliminary treatment of data.Entered for the 3rd step on the contrary: periodically base-line data distributional analysis.Setting up a day baseline below is that example illustrates:
For example: set up a day baseline with reference to the port actual speed rate historical data in past 7 days altogether, distributional analysis in 24 hours point is arranged every day.The confidence level of employing 30% is eliminated abnormal data, and parameter is:
Cycle: diurnal periodicity
Historical data periodicity: 7
Distributed points as analysed basis our unit: hour
Abnormal data is eliminated mode: eliminate abnormal data
Confidential interval: [mean value-mean value * 30%, mean value+mean value * 30%]
Get 7 days simulation initial data of one of them distributional analysis point 8:00-9:00AM, as follows:
Unit: Gb/s
1 2 3 4 5 6 7
0.66?0.68?0.72?0.61?0.70?0.79?0.64
In order to set up periodically day baseline, need carry out following processing to each distributional analysis point.To situation in the example, need carry out following steps 2-3 respectively to 24 hours sections and handle.
2, abnormal data is rejected
The data that abnormal data is meant and all initial data mean deviations are too big.Because the sample data of distributional analysis point is few, the calculating of inapplicable normal distribution adopts simple confidential interval [mean value-mean value * n%, mean value+mean value * n%] mode (n=30) to come the rejecting abnormalities data.This initial average output value is different from follow-up baseline average.As follows to the data computation in the example:
Mean value=(0.66+0.68+0.95+0.61+0.70+0.79+0.64)/7=0.72
Confidential interval: [0.72 * 0.7,0.72*1.3]=[0.50,0.94]
The 3rd data 0.95 are disallowable.
3, periodically base-line data analysis
Periodically the base-line data analysis is to adopt valid data to calculate its mean value, maximum, minimum value to each distributional analysis point in the cycle, and a plurality of distributional analysis points in the cycle just form three lines like this, as the periodicity baseline.
Data to above-mentioned distributional analysis point are calculated as follows:
Maximum=MAX[0.66,0.68,0.61,0.70,0.79,0.64]=0.79
Minimum value=MIN[0.66,0.68,0.61,0.70,0.79,0.64]=0.61
Mean value=AVG[0.66,0.68,0.61,0.70,0.79,0.64]=0.68
24 hours sections are carried out following steps 2-3 respectively handle, three baselines of totally 24 distributional analysis point formation as shown in Figure 5.
4, baseline relatively
The performance data of the current period that obtains from network compares these data and current base-line data.Relatively adopt curve interval graph mode, as shown in Figure 6.Exceed the service feature variation that the specific distribution analysis site is understood in the curve interval according to certain distributional analysis point.
Use for reference the quality sampling analysis method in the quality management system, the general employing has continuous 7 times to surpass the deviation that is in equidirectional, can decision-making system have fixing variation tendency.Native system exceeds the baseline interval according to the continuous several times in the cycle in same direction and judges whether network performance the performance change on certain trend has taken place.Described continuous several times adopts the 15%-30% of distributed points number to calculate by the decision of the distributed points in the cycle.
For the data that adopt the output of performance simple radical line analysis and period of performance baseline analysis, can carry out the network optimization, ensure the telecommunications network service quality.For example: have the fixing big trend that becomes for the network interface flow, system-computed goes out according to current rate of change, and what will reach the heap(ed) capacity of the current configuration of network in the future.When the network interface flow reach heap(ed) capacity 60% the time, system sends alarm, when the network interface flow reach heap(ed) capacity 80% the time, system provides high severity alarm, and whether need to increase the band width configuration of PVC, and record is carried out in user's operation by modal dialog mandatory requirement user decision.If the user need increase the PVC band width configuration, the network interface PVC flow configuration template that then provides the user to select required configuration.
Use this baseline analysis method early warning degradation or the busy situation of Internet resources effectively, thereby control is to the optimization of network configuration.If the user has disposed strategic server, can (for example: the network optimization control strategy top network interface flow of mentioning etc.) customize some key network performance index based on strategic server, among the SLA that network performance index limits and the user signs with key, thereby realize automatic optimal control in dynamic to network.
Adopt the dateout of this baseline analysis method to can be used as the reference data that the network service efficiency improves in operator.For example: to the data in the example, 24 hours distributed points adopt 4 continuous distribution point deviations to change as serious trend and judge sign.Can see that port flow was on the low side, is lower than baseline value since 0 o'clock to 4 o'clock, operator can provide some preferential policies at this period like this, makes the user use in this period and obtains certain discount, makes full use of network.
Adopt the network management system of this baseline analysis method and telecommunications OSS system to set up interface and transmit some utilization rate performance index, can be to the utilization rate that baseline analysis comes out the low time period, adopts different rate sections to divide, the expenses ajustment strategy of formation science.
Adopt periodically baseline analysis method, can be used for monitoring the abnormal flow in the communication network, unusual port is positioned, be even more important aspect control virus and the black Internet bar of control.For example: will adopt the network management system of baseline analysis and virus monitoring software to set up interface, can pass through the flow baseline analysis, find out the port of abnormal flow, further analyze it then and transmit message or other the viral forwarding servers that bag can find whether to carry out the dos attack request, thereby carry out port isolation control, prevent that it from jeopardizing the operation of whole network.

Claims (11)

1, a kind of method of monitor network service feature, but described network has the network management system of collection network business datum, it is characterized in that comprising step:
By network management system configuration baseline analysis parameter, to determine the scope and the baseline type of business datum;
According to disposing the business datum of from network, sampling;
From described business datum, obtain mean value, maximum and/or the minimum value of business datum, and be datum mark, form one or more baseline of reflection service feature with the corresponding relation of business datum value and time with this value;
With described baseline is reference, from network, obtain the current business data value and the value corresponding with current time point on the baseline compares, when the business datum value that continuous a plurality of sampled points occur all was greater than or less than the value of corresponding sampled point on the baseline, then there was fixing variation tendency in the service feature of decision network.
2, the method for claim 1 is characterized in that, when there is fixing variation tendency in the service feature of decision network, produces warning information or/and carry out pre-configured control strategy network is carried out optimal control in dynamic.
3, the method for claim 1 is characterized in that, before the maximum and/or minimum value of determining business datum, rejects the abnormal data bigger with the mean deviation of all business datums in the business datum.
4, method as claimed in claim 3 is characterized in that, adopts [mean value-mean value * n%, mean value+mean value * n%] confidential interval come the rejecting abnormalities data, promptly be not regarded as abnormal data in this interval business datum and reject, wherein n% is a confidence level, n=20~30.
5, method as claimed in claim 3 is characterized in that, adopts the mean value of method of weighting computing service data, gives weights near sampled point of current time and is higher than weights from current time sampled point far away.
6, as the arbitrary described method of claim 1 to 5, it is characterized in that, described baseline is for existing the simple baseline of relatively stable characteristic in the expression traffic data is during a time period, this baseline analysis parameter comprises baseline type, historical data point data, the superseded mode of abnormal data and confidential interval.
7, method as claimed in claim 6 is characterized in that, is that datum mark extends with mean value, maximum and/or the minimum value that obtains, and forms the simple baseline of performance perpendicular to the axis of representing the business datum value.
8, as the arbitrary described method of claim 1 to 5, it is characterized in that, there is the period of performance baseline of cyclic variation trend in described baseline within a certain period of time for representing business datum, and this baseline analysis parameter comprises cycle, historical data periodicity, distributional analysis point base unit, the superseded mode of abnormal data and confidential interval.
9, method as claimed in claim 8 is characterized in that, mean value, maximum and/or the minimum value of a plurality of analysis sites is connected to form the period of performance baseline respectively.
10, a kind of Network performance monitoring system is characterized in that comprising:
The performance data library module is used to store History Performance Data;
The base-line data library module is used to store baseline configuration data and base-line data;
The service data acquisition module is used for collecting from communication network the real data of relevant performance operational indicator, and stores described performance data library module into;
The baseline analysis configuration module is used to receive the baseline analysis configuration parameter of customization, stores configuration data into the base-line data library module;
The base-line data analysis module reads History Performance Data and baseline analysis configuration parameter formation baseline from described performance data library module and base-line data library module respectively, and is saved in the baseline database;
Network optimization analysis module is used for judging the network performance quality according to the business configuration of base-line data, the network equipment and the current performance data that collects, and network is carried out corresponding Optimizing operation.
11, system as claimed in claim 10 is characterized in that, the base-line data analysis module forms one or more simple baseline or period of performance baseline.
CNB2004100320792A 2004-03-31 2004-03-31 Method and system for monitoring network service performance CN100356729C (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CNB2004100320792A CN100356729C (en) 2004-03-31 2004-03-31 Method and system for monitoring network service performance

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CNB2004100320792A CN100356729C (en) 2004-03-31 2004-03-31 Method and system for monitoring network service performance

Publications (2)

Publication Number Publication Date
CN1677934A true CN1677934A (en) 2005-10-05
CN100356729C CN100356729C (en) 2007-12-19

Family

ID=35050250

Family Applications (1)

Application Number Title Priority Date Filing Date
CNB2004100320792A CN100356729C (en) 2004-03-31 2004-03-31 Method and system for monitoring network service performance

Country Status (1)

Country Link
CN (1) CN100356729C (en)

Cited By (21)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN100384153C (en) * 2005-12-26 2008-04-23 北京交通大学 Network performance analysis report system based on IPv6 and its implementing method
CN101141759B (en) * 2007-02-12 2010-12-29 中兴通讯股份有限公司 Call behavior statistical and analytical method and device
CN102026230A (en) * 2010-12-20 2011-04-20 中兴通讯股份有限公司 Method and device for monitoring data service quality of code division multiple access (CDMA) network
CN102035666A (en) * 2009-09-24 2011-04-27 中兴通讯股份有限公司 Method of administration of networks for business single plate and network administration system
CN102111307A (en) * 2009-12-29 2011-06-29 亿阳信通股份有限公司 Method and device for monitoring and controlling network risks
CN101291177B (en) * 2008-06-16 2012-05-23 中兴通讯股份有限公司 Diagnosis method and device for historical performance data of network management
CN102480381A (en) * 2010-11-29 2012-05-30 腾讯科技(深圳)有限公司 Method and device for checking network service operational data
CN102495808A (en) * 2011-11-24 2012-06-13 深圳市亚特尔科技有限公司 Method for saving memory space
CN101770419B (en) * 2008-12-31 2013-03-20 中国银联股份有限公司 System robustness analyzer and analysis method
CN103036741A (en) * 2012-12-19 2013-04-10 北京神州绿盟信息安全科技股份有限公司 Determination method and determination device of flow monitoring base line
CN103139007A (en) * 2011-12-05 2013-06-05 阿里巴巴集团控股有限公司 Method and system for detecting application server performance
CN103793309A (en) * 2012-10-29 2014-05-14 中国移动通信集团浙江有限公司 Method and device for early warning of batch services
CN103856965A (en) * 2014-03-24 2014-06-11 宁夏信友通信监理咨询有限责任公司 WLAN (Wireless Local Area Network) comprehensive analysis system and method
CN103905227A (en) * 2012-12-26 2014-07-02 中国移动通信集团辽宁有限公司 Server energy consumption control method and system
CN104767651A (en) * 2014-01-07 2015-07-08 中国移动通信集团黑龙江有限公司 Multi-service merging and processing method, system and device
CN105406991A (en) * 2015-10-26 2016-03-16 上海华讯网络系统有限公司 Method and system for generating service threshold by historical data based on network monitoring indexes
CN106357474A (en) * 2016-08-30 2017-01-25 成都科来软件有限公司 Data flow baseline acquisition method and device based on link
CN106951351A (en) * 2017-01-16 2017-07-14 上海新炬网络信息技术有限公司 A kind of database loads tendency monitoring method
CN108732313A (en) * 2018-05-31 2018-11-02 深圳市创艺工业技术有限公司 Urban air pollution object concentration intelligence observation system
CN108965039A (en) * 2017-05-19 2018-12-07 腾讯科技(深圳)有限公司 A kind of alarm method and electronic equipment based on traffic monitoring
WO2020103735A1 (en) * 2018-11-23 2020-05-28 华为技术有限公司 Network quality monitoring method and device

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP0990349A1 (en) * 1997-06-16 2000-04-05 Telefonaktiebolaget Lm Ericsson A telecommunications performance management system

Cited By (27)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN100384153C (en) * 2005-12-26 2008-04-23 北京交通大学 Network performance analysis report system based on IPv6 and its implementing method
CN101141759B (en) * 2007-02-12 2010-12-29 中兴通讯股份有限公司 Call behavior statistical and analytical method and device
CN101291177B (en) * 2008-06-16 2012-05-23 中兴通讯股份有限公司 Diagnosis method and device for historical performance data of network management
CN101770419B (en) * 2008-12-31 2013-03-20 中国银联股份有限公司 System robustness analyzer and analysis method
CN102035666A (en) * 2009-09-24 2011-04-27 中兴通讯股份有限公司 Method of administration of networks for business single plate and network administration system
CN102111307B (en) * 2009-12-29 2013-09-04 亿阳信通股份有限公司 Method and device for monitoring and controlling network risks
CN102111307A (en) * 2009-12-29 2011-06-29 亿阳信通股份有限公司 Method and device for monitoring and controlling network risks
CN102480381A (en) * 2010-11-29 2012-05-30 腾讯科技(深圳)有限公司 Method and device for checking network service operational data
CN102480381B (en) * 2010-11-29 2015-04-15 腾讯科技(深圳)有限公司 Method and device for checking network service operational data
CN102026230A (en) * 2010-12-20 2011-04-20 中兴通讯股份有限公司 Method and device for monitoring data service quality of code division multiple access (CDMA) network
CN102495808A (en) * 2011-11-24 2012-06-13 深圳市亚特尔科技有限公司 Method for saving memory space
CN102495808B (en) * 2011-11-24 2014-12-17 深圳市亚特尔科技有限公司 Method for saving memory space
CN103139007A (en) * 2011-12-05 2013-06-05 阿里巴巴集团控股有限公司 Method and system for detecting application server performance
CN103793309A (en) * 2012-10-29 2014-05-14 中国移动通信集团浙江有限公司 Method and device for early warning of batch services
CN103793309B (en) * 2012-10-29 2017-11-21 中国移动通信集团浙江有限公司 A kind of batch service method for early warning and device
CN103036741A (en) * 2012-12-19 2013-04-10 北京神州绿盟信息安全科技股份有限公司 Determination method and determination device of flow monitoring base line
CN103036741B (en) * 2012-12-19 2016-02-03 北京神州绿盟信息安全科技股份有限公司 The defining method of flow monitoring baseline and device
CN103905227A (en) * 2012-12-26 2014-07-02 中国移动通信集团辽宁有限公司 Server energy consumption control method and system
CN103905227B (en) * 2012-12-26 2018-05-22 中国移动通信集团辽宁有限公司 A kind of server energy consumption control method and system
CN104767651A (en) * 2014-01-07 2015-07-08 中国移动通信集团黑龙江有限公司 Multi-service merging and processing method, system and device
CN103856965A (en) * 2014-03-24 2014-06-11 宁夏信友通信监理咨询有限责任公司 WLAN (Wireless Local Area Network) comprehensive analysis system and method
CN105406991A (en) * 2015-10-26 2016-03-16 上海华讯网络系统有限公司 Method and system for generating service threshold by historical data based on network monitoring indexes
CN106357474A (en) * 2016-08-30 2017-01-25 成都科来软件有限公司 Data flow baseline acquisition method and device based on link
CN106951351A (en) * 2017-01-16 2017-07-14 上海新炬网络信息技术有限公司 A kind of database loads tendency monitoring method
CN108965039A (en) * 2017-05-19 2018-12-07 腾讯科技(深圳)有限公司 A kind of alarm method and electronic equipment based on traffic monitoring
CN108732313A (en) * 2018-05-31 2018-11-02 深圳市创艺工业技术有限公司 Urban air pollution object concentration intelligence observation system
WO2020103735A1 (en) * 2018-11-23 2020-05-28 华为技术有限公司 Network quality monitoring method and device

Also Published As

Publication number Publication date
CN100356729C (en) 2007-12-19

Similar Documents

Publication Publication Date Title
JP5111719B2 (en) Method and system for collecting and retrieving time-series real-time and non-real-time data
CN1132377C (en) Communications network management
US20160080965A1 (en) Distributed RAN Information Collection, Consolidation And RAN-Analytics
EP3046289B1 (en) Techniques for dynamic network optimization using geolocation and network modeling
US10333724B2 (en) Method and system for low-overhead latency profiling
EP2183570B1 (en) Network review in clinical hematology
CN101176305B (en) Distributed communication service system and method for analyzing communication service flow
CN105183609A (en) Real-time monitoring system and method applied to software system
US7904080B2 (en) Mobile communications network monitoring systems
CN101197621B (en) Method and system for remote diagnosing and locating failure of network management system
US20110191138A1 (en) Risk scorecard
CN1300693C (en) Device for adjusting used of system resource and its method
US7809817B2 (en) Method and system for determining compatibility of computer systems
CN103685150B (en) The method and apparatus of upload file
CN1296848C (en) Alarm management method and equipment thereof
CN101964985B (en) Coverage and capacity self-optimization device of self-organization network in LTE/LTE-A and method thereof
EP2487860A1 (en) Method and system for improving security threats detection in communication networks
CN102291264B (en) Broadband service guarantee support system
RU2425470C2 (en) Base station system performance measurement system in gsm radio communication network
EP2200362A1 (en) Dynamic mobile network traffic control
CN1309214C (en) Cooperative intrusion detection based large-scale network security defense system
CN1826514A (en) Vehicular diagnostic method, vehicular diagnostic system, vehicle and center
JP4261389B2 (en) Unauthorized access detection device and unauthorized access detection program
CN103544093A (en) Monitoring and alarm control method and system
WO2006132756A2 (en) Automated reporting of computer system metrics

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
C14 Grant of patent or utility model
GR01 Patent grant
EXPY Termination of patent right or utility model
CF01 Termination of patent right due to non-payment of annual fee

Granted publication date: 20071219

Termination date: 20150331