CN104639388B - A kind of dns server method for detecting availability perceived based on user - Google Patents
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Abstract
The invention discloses a kind of dns server method for detecting availability perceived based on user.This method is:1) monitoring point is set respectively on the node server of setting;2) M measurement data index is chosen;Dispatch server periodically sends order to specified monitoring point and carries out data acquisition;3) the benchmark QoS parameter Um of each index is calculated according to Base DN S authoritative server sample sets D, obtains a set X ';4) the QoS parameter U of each index is calculated according to the measurement data of collectionm', obtain a set Y ';5) contribution degree of each index relative datum QoS parameter is determined according to set Y ' and set X ' statistic correlation;6) according to the contribution degree of each index relative datum QoS parameter, the service quality of every DNS recursion servers is calculated, obtains the availability of target DNS authority server.The present invention provides data supporting from external view, so that decision-making judges.
Description
Technical field
The present invention relates to a kind of dns server method for detecting availability perceived based on user, belong to network technique field.
Background technology
The rapid development of internet, bring life and handle official business efficient and convenient.But network security accident in recent years
Take place frequently, also manifest the fragility of internet.One of the important infrastructure of domain name system (DNS) as internet, is being protected
Indispensable effect is played in terms of the normal operation for demonstrate,proving internet, DNS security also contributes to the safety of whole internet
With efficiency, therefore analysis to DNS security and research are just particularly important.DNS Protocol is when initial design to peace
Total factor is just short of consideration, and existing fragility causes dns server to be faced with full spectrum of threats often to agreement in itself.
The problem of DNS authority server availability failure, finds mainly to pass through the monitoring and flow analysis of inside, but this
Kind of mode can only pinpoint the problems from the angle of O&M, can not accurately be weighed from user perspective whether faulty and failure shadow
The degree of sound and coverage.Because 1) DNS authority server much provides service (such as root, com and cn using mirror-image fashion
Deng), even if a mirror image breaks down, bgp+anycast scheme can automatically switch to other mirror images, be mitigated or eliminated
Influence to user;2) what user directly accessed is DNS recursion servers, and recurrence can cache authoritative solution with TTL time
Data are analysed, can also alleviate the failure that user perceives authoritative server to a certain extent.
The content of the invention
Relative to the DNS authority server failure problem that target domain name is monitored, found from interior angle, present invention design is simultaneously
A kind of distributed DNS data acquisition and method for detecting availability are realized, data supporting is provided from external view, so that decision-making is sentenced
It is disconnected;It is an object of the invention to:1) easy task scheduling strategy, with adaptive network environmental change;2) reliable DNS is used
Acquisition strategies, to reduce the fluctuating error that UDP packet losses are brought;3) analysing whether to have DNS in real time based on active probe data can
With property failure, influence degree and coverage;4) analysis result is exported, as the foundation of system operation maintenance personnel handling failure,
And judge to provide support for decision-making.
The technical scheme is that:
A kind of dns server method for detecting availability perceived based on user, its step are:
1) monitoring point is set respectively on the node server of setting;
2) M measurement data index is chosen;Dispatch server periodically sends to specified monitoring point and ordered, and monitoring point receives life
Data acquisition is carried out to target DNS authority server after order;
3) the benchmark QoS parameter Um of each index is calculated according to Base DN S authoritative server sample sets D, is obtained
One set X ';
4) measurement data gathered according to step 2) calculates the QoS parameter U of each indexm', obtain a set Y ';
5) tribute of each index relative datum QoS parameter is determined according to set Y ' and set X ' statistic correlation
Degree of offering;
6) data of step 2) collection are divided according to DNS recursion servers, each index calculated according to step 5)
The contribution degree of relative datum QoS parameter, calculate the service quality of every DNS recursion servers;
7) service quality being calculated according to step 6) obtains the availability of target DNS authority server.
Further, formula is utilizedCalculate the benchmark QoS parameter Um of m class indexs;
Wherein, set D includes M subset, and m-th of subset dm preserves the sample data of m class indexs;Q (i, m) represents dns server
I-th of sampled data values of m class indexs, C (D) are the total sample number in set D.
Further, formula is utilizedIt is relative to calculate each index
The contribution degree Z of benchmark QoS parameter;Wherein, Z={ am}。
Further, M selected measurement data index is:The path round-trip time delay of target DNS authority server, lose
Bag rate and domain name mapping correctness.
Further, in the step 6), each index measurement data are normalized first, then calculated every
The service quality of one DNS recursion servers;Wherein, the service quality of n-th of DNS recursion server
TnFor the path round-trip time delay of n-th of DNS recursion server, G (Tn) be normalized after path round-trip time delay;EnFor n-th
The packet loss of individual DNS recursion servers, G (En) be normalized after packet loss;FnFor the domain of n-th of DNS recursion server
Name parsing correctness, G (Fn) be normalized after domain name mapping correctness;β is the contribution degree of path round-trip time delay, and ρ is
The contribution degree of packet loss, ω are the contribution degree of domain name mapping correctness.
Further, if TTL is less than 5 minutes, the transmission cycle of the order rounds up for p=(ttl/60);
If TTL is more than or equal to 5 minutes, the transmission period p of the order is 5 minutes;One is sent within the same transmission cycle
Or a plurality of order;Each order repeats to send repeatedly within the same transmission cycle, and each order returns at least one and adopted
Collection record, then the target DNS authority server is normal, and it is time-out otherwise to judge the target DNS authority server.
Further, the measurement data for the different indexs that the dispatch server returns to monitoring point is stored to corresponding index
In measurement data subset.
Further, in the step 7), formula is utilizedCalculate target DNS authority
The service quality QoE of server, wherein, KmFor the weights of m-th of index, N is DNS recursion servers sum.
Further, the scheduler establishes each metric history measurement data set of a dns server;And the history is surveyed
Amount data set carries out cluster sampling and establishes a proper network baseline;Then current each index measurement data of dns server with
Proper network baseline is compared, and fault warning is then carried out if the deviation from more than setting value.
Further, target DNS authority server service quality is detected using based on the statistical model of variance, its
Method is:QoS parameter U based on variance statistic to each indexm' calculate a confidential interval;In the setting time cycle
It is interior, if when the QoS parameter of previous index is in corresponding confidential interval, then it is assumed that it is normal, otherwise it is assumed that there is event
Barrier.
Compared with prior art, advantages of the present invention:
1) data supporting is provided from external view, so that decision-making judges availability, while simplifies the task of DNS data collection
Configuration, user only need to provide target domain name, and system realizes the complicated DNS tasks configuration found based on problem automatically;
2) collection is improved by 3 kinds of modes (retry, repeatedly detect, according to the configuration of result of detection filtration duty three times)
The reliability of DNS data;
3) use based on the method for variance statistic to realize DNS availability fault warnings.
Brief description of the drawings
Fig. 1 is the data acquisition flow figure of scene 1;
Fig. 2 is the data acquisition flow figure of scene 2;
Fig. 3 is the inventive method building-block of logic.
Embodiment
The present invention is explained in further detail below in conjunction with the accompanying drawings.
The key technical problem that the present invention solves is the availability failure for finding " the DNS authority server of target domain name ".
Dns resolution relates generally to two paths:User is to recursion server, recursion server to authoritative server;Therefore two kinds are considered
Scene, 1) simulation " DNS recursion servers ", access DNS authority server, such as Fig. 1;2) " user " is simulated, passes through ISP
The DNS recursion servers of (Internet Service Provider), access DNS authority server, such as Fig. 2.
The present invention sets monitoring point on each important network node or ISP server first, such as just domestic next
Say, selected server needs to cover each province's major carrier as far as possible.Because:1) the DNS authority service meeting of crucial domain name
There is provided High Availabitity service (such as root/com/cn etc.) by more mirror nodes, the broadcast strategies of each mirror nodes have global and
Local point, for local node, can only can have access in broadcasting area;2) user has Regional Property, only covers
The main line that user accesses, it could truly react the situation of DNS authority service;3) each ISP DNS recursion services also have
There is local attribute, in general only provide service to the user of this area, this operator.
The solution of the present invention mainly from considering following aspects:Task scheduling, data snooping, data analysis, alarm are defeated
Go out.Module's logic structure figure is as shown in Figure 3.
(1) task scheduling
It is directed to finding DNS availability failure, it is necessary to initiate to detect to target DNS authority server incessantly, adopts
Collect data;For doing the mainly response time data of fault detect, dispatch server timing is sent to monitoring point orders, monitoring
Point performs acquisition tasks after receiving order, issues which monitoring point can configure, and acquiescence is intended for all monitoring points.According to
The ageing requirement pinpointed the problems, there is different settings to the frequency of data acquisition.Frequency is too high, can inject larger stream to network
Amount, makes the load of objective network higher;Underfrequency, the time delay pinpointed the problems is higher, is unfavorable for failure disposal, or even delay is determined
Plan judges.In view of DNS caching mechanism, in our scheme of the invention, detection cycle is arranged to:
{ (ttl/60's p=) rounds up (min) ifttl<300;5min ifttl>=300 }
Why so take:1) be within 5 minutes one can be according to the business demand customized fault discovery time;TTL is small
In 5 minutes, it is necessary to be pinpointed the problems in or so TTL times;TTL is more than or equal to 5 minutes, and the fault discovery time is no more than
5 minutes;2) granularity in cycle is accurate to minute, in order to which technology is realized.
Scene 2) analog subscriber when, it is necessary to by DNS recursion server access target DNS authority servers, because DNS is passed
Return server that there is ISP attributes, the DNS recursion servers of corresponding province and operator should be selected on each monitoring point, and make
Continuity testing.
Scene 1, the order that dispatch server is sent include following information:
Monitoring objective domain name, monitoring item (response time, correctness etc.), monitoring point, detection times;
Scene 2, the order that dispatch server is sent include following information:;
Monitoring objective domain name, monitoring item (response time, correctness etc.), monitoring point, recursion server IP, detection times.
(2) data acquisition
1) DNS mainly provides service by udp protocol, and due to the unreliability of udp protocol, packet loss can be frequently present of;
In order to avoid UDP packet losses give the influence that brings of subsequently pinpointing the problems, in the following way, detection three times, three times within have response,
Then it is considered normal, returns to a result of detection, be otherwise time-out.
If 2) need a plurality of acquisition and recording in a detection cycle, further to improve the degree of accuracy of data, can adopt
With the mode of multi collect.
(3) data analysis and alarm
3.1 performance index definitions and evaluation method
For DNS service, when from the experience of the intuitive service of user perspective being exactly the response that DNS authority server parses
Between and its success rate (being determined based on the response time), accuracy (be mainly used to detect whether domain name kidnaps, pass through dig domains
Whether NS and the A of name are recorded, unanimously obtained then in conjunction with the contrast of existing list) whether in tolerance etc., so these property
Can index be that user can be with DNS service quality that direct feeling arrives.Estimate therefore, primarily to formulate reference performance index to characterize
The DNS service quality standard that user perceives, as sign QoS parameter.
If Base DN S authoritative servers sample set is D, set D includes M subclass d, wherein m-th of subclass dm
The sample data of m class measurement indexes is preserved, Q (i, m) represents the ith measurement of the measurement performance index of dns server m classes
Data target value, C (D) are the total sample number in set D, then the benchmark QoS parameter Um of m classes performance indications is formula
(1-1):
The contribution degree for the benchmark QoS parameter that indices by calculating end to end network performance perceive to user
The weighted calculation of network performance index is carried out, so as to draw the service quality evaluation quantitative model of unified dns server.
For the target DNS authority server performance index by actively measuring, by unified formula (1-2) to it
Carry out statistical analysis:
It is the data set by measuring obtained DNS performance metric results, wherein
Represent the measurement result collection of m class DNS performance metrics, ym,jFor m class DNS performances
The measurement result of the jth kind state of Measure Indexes.
Rm=(ym1,ym2...ymj...,ymJ) the measurement result state sets of m class DNS performance metrics is represented, state is total in J
Number.
V=1 ..., m ..., M } represent performance set of metrics.Shared M kinds performance participates in measurement.Comprehensive performance evaluation is exactly
A kind of m members carried out on XOperation and the n members carried out on YThe synthesis of operation,For xor operation.
Assuming that TiRepresent the path round-trip time delay that ith measurement obtains, EiRepresent the packet loss that ith measurement obtains, FiTable
Show the domain name mapping correctness that ith measurement obtains, if set Z={ amRepresent that each network performance index takes to DNS benchmark
The contribution degree for mass parameter of being engaged in, the statistics phase closed by the set of calculating network performance indications with DNS benchmark QoS parameter set
Closing property determines the value of corresponding contribution degree.Contribution degree formula is shown in formula (1-3):
In formula
The DNS benchmark QoS parameter set of X ' --- measurement closes list, i.e., utilizes formula (1-1) institute according to sample data
The M Um set of calculating;
The corresponding network performance index parameter sets list of Y ' --- measurement, i.e., utilize formula according to active measurement data
The M Um set that (1-1) is calculated.
N ' is measurement data sum.
X in formula --- certain measurement data of a kind of index once;
Min (x) --- the minimum value of all x measurement data;
Max (x) --- the greatest measure of all x measurement data.
Function is uniformly processed based on formula (1-3) and data normalization and sees formula (1-4), can by network performance index and
Its contribution degree to DNS service quality calculates DNS service quality evaluation result, sees formula (1-5):
In formula
Tn--- the path round-trip time delay of measurement;
En--- the packet loss of measurement;
Fn--- the domain name mapping correctness of measurement;
β --- the contribution degree of path round-trip time delay;
The contribution degree of ρ --- packet loss;
ω --- the contribution degree of domain name mapping correctness;
QoSnThe service quality evaluation result of n-th of DNS recursion server is represented, function representation is directed to network performance index
Unified normalization computational methods.
Relation is contributed by the transmission of the stratification of network element, extracts corresponding critical network performance indications parameter,
Its contribution degree for DNS benchmark QoS parameters is calculated by statistic correlation, can finally be calculated by this model
With the overall quality of service of one DNS authority server of evaluation.
The QoS that user's subjective feeling arrives is QoE (Quality ofExperience), and both main distinctions are that QoS is
Objectively, and QoE is subjective.In order to further illustrate the relation between QoS and QoE, quality of service index is introduced herein
Concept.
Quality of service index (KQI, Key Quality Indicator) is to reflect user-perceptive quality in service layer
Key index, is one group of qos parameter that can be measured, and service feature index focuses on the service layer of user's concern.Industry
Business quality index customer-centric, reflect user and perceive in a certain respect, the combination of several quality of service indexs is
User is perceived, and user's perception level can be determined by the measurement to quality of service index.
User perceives QoE and quality of service index KQI quantitative relationship, sees formula (1-6):
QoE represents user's perception of certain business, weights of the Km between m-th of KQI and user's perception, QoS in formulanFor
The service quality evaluation result of n DNS recursion server, wherein L=3 represent that user perceives and are divided into three dimensions:The road of measurement
The domain name mapping correctness of footpath round-trip delay, the packet loss of measurement and measurement.
Shown for QoE is general using 5 points of tabulations, it is corresponding excellent, it is good, in, it is secondary, it is bad.Table 1 represents score value, quality of service, user
Corresponding relation between satisfaction and the business extent of damage.
Relation between table 1QoE score values, quality of service, user satisfaction and the business extent of damage
QoE score values | Quality of service | User satisfaction | The business extent of damage |
5 | It is excellent | It is very satisfied | It is impacted DNS service can not to be perceived |
4 | It is good | It is satisfied | It is impacted that DNS service can be perceived, but |
It is negligible | |||
3 | In | Certain customers are unsatisfied with | Part NS or ISP service is impacted |
2 | It is secondary | Many users are unsatisfied with | Most of NS or ISP service is impacted |
1 | It is bad | Most of users are unsatisfied with | Overall access is obstructed |
3.2 data analyses and alarm
Carry out the alarm detection perceived based on user, it is necessary to initially set up normal network measure model, then contrast
Normal model can identify exception.Use herein based on the method for variance statistic to realize availability fault warning, with maturation
Probability Statistics Theory detects current abnormal failure as theoretical foundation using the historical behavior of DATA REASONING.
After it have accumulated a number of user's perception and estimate statistics, the serial history row of different scenes is formed
For collection can be estimated.Using these metric history measurement data, the proper network baseline in time in the past cycle is established in cluster sampling.
Current measurement behavior is compared with normal network baseline, if currently measurement behavior occurs significantly with proper network baseline
During deviation, that is, think different degrees of fault warning occurred, and can further analyse in depth;If two kinds of behaviors are not obvious
Deviation, then it is assumed that normal and update proper network measurement model.
It is varied due to measurement data, it is impossible to be compared using all historical measurement datas with current measurement data
Compared with, herein using the nearest cycle measurement data and periodic samples data as collection can be estimated, and use sliding window is surveyed
Data renewal is measured, ensures that problem detection is more accurate.
Fault detect is carried out using the statistical model based on variance herein, by the variance of calculating parameter, sets its confidence
Section, show to there may be failure or exception when scope of the measured value beyond confidential interval.
According to central-limit theorem, if the stochastic variable X studied can be expressed as independent stochastic variable X1,
X2,...,XnSum, if Xi(i=1,2 ..., n) is relatively independent to X, it is believed that X Normal Distributions.Due to being felt based on user
The measurement known all is independent variable, therefore the theorem can be used to carry out measurement evaluation.
The definition of sample standard deviation is:
It can be seen from the distribution situation of Normal Mean, sample averageStandard deviation be
Population mean confidence level is that the confidential interval of (1- α) is
Wherein, α is referred to as the level of signifiance, Za/2For the bilateral critical value of standardized normal distribution, Za/2Can be from gaussian distribution table
Check in, in conjunction with sample number n, sample quadratic sumAnd square of sample averageSample standard deviation can be calculated
The standard deviation of value and the confidential interval of population mean.If estimating in this confidential interval in some time cycle, then it is assumed that
Normally, otherwise it is assumed that different degrees of failure occur and carrying out abnormality processing.
Judge exception only according to the statistics number for calculating confidence space, not enough fully, these numerical value may be because certain
The reason for a little non-faulting (such as System Expansion), causes instantaneous not normal, and we will can tolerate that these instantaneous statistical values are not normal.
It is further noted that different stage DNS Statistic features are different, confidence spatial statisticses result gap
It is larger, to be treated respectively in alarming processing.Due to being difficult to provide a quantitative calculation formula, given here according to its importance
Go out importance factor hierarchical table, as shown in table 2.
The importance factor hierarchical table of table 2
Next alarm statistics respectively are also carried out for different scenes, such as
1) scene 1:For NS, for operator, entirety;
2) scene 2:For operator, entirety;
To the different business under each scene, different quality of service index and parameter are formulated respectively, do not done herein specific
Description.
Cycle for alerting herein is general shorter, generally 5 minutes or so, when typically continuing longer for DNS exception
Between, and the statistical value fallen into above outside confidential interval does not have continuation for instantaneous exception, in order to reduce rate of false alarm, introduces herein
Alarm queue, abnormal behaviour wouldn't be judged as.The number for simply counting abnormal numerical value is N, and N can dynamically increase in alarm queue
Subtract, pass through a time slip-window every time, N is reduced according to the fixed attenuation value γ in the importance factor hierarchical table of table 2, if N<0
Represent without exception and removed from alarm queue, and it is really abnormal typically can be continuously in multiple analysis (recently repeatedly with same period ratio)
Statistical value exception can be detected, repeatedly finds to exceed our the abnormal threat value thresholds that pre-set after increase and decrease, then is transformed into pair
In the QoE answered, carry out corresponding alarming processing and point out which link goes wrong, for example simply one of NS delays machine, accuses
Police repairs problem, if overall access is obstructed, high severity alarm is, it is necessary to notify all departments' Coordination Treatment to operation maintenance personnel.
Claims (10)
1. a kind of dns server method for detecting availability perceived based on user, its step are:
1) monitoring point is set respectively on the node server of setting;
2) M measurement data index is chosen;Dispatch server periodically sends to specified monitoring point and ordered, after monitoring point receives order
Data acquisition is carried out to target DNS authority server;
3) the benchmark QoS parameter U of each index is calculated according to Base DN S authoritative server sample sets Dm, obtain a collection
Close X ';
4) measurement data gathered according to step 2) calculates the QoS parameter U of each indexm', obtain a set Y ';
5) contribution degree of each index relative datum QoS parameter is determined according to set Y ' and set X ' statistic correlation;
6) data of step 2) collection are divided according to DNS recursion servers, it is relative according to each index that step 5) calculates
The contribution degree of benchmark QoS parameter, calculate the service quality of every DNS recursion servers;
7) service quality being calculated according to step 6) obtains the availability of target DNS authority server.
2. the method as described in claim 1, it is characterised in that utilize formulaCalculate m class indexs
Benchmark QoS parameter Um;Wherein, set D includes M subset, and m-th of subset dm preserves the sample number of m class indexs
According to;Q (i, m) represents i-th of sampled data values of dns server m class indexs, and C (D) is the total sample number in set D.
3. method as claimed in claim 2, it is characterised in that utilize formula
Calculate the contribution degree Z of each index relative datum QoS parameter;Wherein, Z={ am, N ' is measurement data sum.
4. the method as described in claim 1 or 2 or 3, it is characterised in that M selected measurement data index be:Target
Path round-trip time delay, packet loss and the domain name mapping correctness of DNS authority server.
5. method as claimed in claim 4, it is characterised in that in the step 6), each index measurement data are entered first
Row normalized, then calculate the service quality of every DNS recursion servers;Wherein, the clothes of n-th of DNS recursion server
Business qualityTnFor the path round-trip time delay of n-th of DNS recursion server, G (Tn) it is normalizing
Path round-trip time delay after change processing;EnFor the packet loss of n-th of DNS recursion server, G (En) be normalized after losing
Bag rate;FnFor the domain name mapping correctness of n-th of DNS recursion server, G (Fn) be normalized after domain name mapping it is correct
Property;β is the contribution degree of path round-trip time delay, and ρ is the contribution degree of packet loss, and ω is the contribution degree of domain name mapping correctness.
6. the method as described in claim 1, it is characterised in that if TTL is less than 5 minutes, the transmission cycle of the order
Rounded up for p=(TTL/60);If TTL is more than or equal to 5 minutes, the transmission period p of the order is 5 minutes;
One or more order is sent in the same transmission cycle;Each order repeats to send repeatedly, often within the same transmission cycle
One order returns at least one acquisition and recording, then the target DNS authority server is normal, otherwise judges that target DNS is weighed
Prestige server is time-out.
7. the method as described in claim 1, it is characterised in that the different indexs that the dispatch server returns to monitoring point
Measurement data is stored in the measurement data subset of corresponding index.
8. the method as described in claim 1, it is characterised in that in the step 7), utilize formulaMeter
The service quality QoE of target DNS authority server is calculated, wherein, KmFor the weights of m-th of index, N is that DNS recursion servers are total
Number.
9. the method as described in claim 1, it is characterised in that the dispatch server establishes each index of a dns server
Historical measurement data collection;And cluster sampling is carried out to the historical measurement data collection and establishes a proper network baseline;Then current
Each index measurement data of dns server compared with proper network baseline, then carry out failure announcement if the deviation from more than setting value
It is alert.
10. the method as described in claim 1 or 9, it is characterised in that weighed using based on the statistical model of variance to target DNS
Prestige server service quality is detected, and its method is:QoS parameter U based on variance statistic to each indexm'Calculate
One confidential interval;Within the setting time cycle, if when the QoS parameter of previous index is in corresponding confidential interval,
Think normal, otherwise it is assumed that breaking down.
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CN101841435A (en) * | 2010-01-18 | 2010-09-22 | 中国科学院计算机网络信息中心 | Method, apparatus and system for detecting abnormality of DNS (domain name system) query flow |
CN102123052A (en) * | 2011-03-30 | 2011-07-13 | 北京星网锐捷网络技术有限公司 | Method and system for estimating service system availability |
CN103491202A (en) * | 2013-09-09 | 2014-01-01 | 中国科学院计算机网络信息中心 | DNS node address selection method based on internet measurement |
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