CN104105121A - Network quality segmented quantification evaluation method and system - Google Patents
Network quality segmented quantification evaluation method and system Download PDFInfo
- Publication number
- CN104105121A CN104105121A CN201310125528.7A CN201310125528A CN104105121A CN 104105121 A CN104105121 A CN 104105121A CN 201310125528 A CN201310125528 A CN 201310125528A CN 104105121 A CN104105121 A CN 104105121A
- Authority
- CN
- China
- Prior art keywords
- time delay
- target information
- measured
- network quality
- service
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Abstract
The invention provides a network quality segmented quantification evaluation method and system. The method includes: selecting APs to be evaluated and five sources of target information; accessing the five sources of target information through the APs to be evaluated, performing a service test, and recording related parameters; calculating service perception scores according to a formula WLAN-MOS=5-(alpha*Id-DNS+beta*Id-TCP+gamma*Id-mp-HTTp+delta*Id-object+eta*IJitter+lambda*Ie)+delta; and comparing the service perception scores corresponding to the five sources of target information, and performing segmented quantification of network quality. Compared with the prior art, the network quality segmented quantification evaluation method in the invention can directly, comprehensively, and accurately discover network quality and perception condition of a WLAN, define specific range of short boards that affect network quality of the WLAN, and locate the positions of the short boards.
Description
Technical field
The present invention relates to quality of wireless network evaluation and test technical field, relate in particular to a kind of network quality segment quantization evaluating method and system.
Background technology
Along with the development of wireless communication technology, WLAN (Wireless Local Area Networks, WLAN) technology is widely used.But wlan network exists and uses that common frequency band, available frequency are few, user behavior is to problems such as network quality affects are large, meanwhile, equipment, certification, route topological, the problem such as interconnect also all can directly affect customer service perception.Above factor interaction, causes the difficult assessment of wlan network ubiquity quality, index is good but customer complaint continuous, do not know that network quality problem occurs in the situations such as which network element.
At present, WLAN maintenance optimization personnel also need often to face following practical problem:
Be all the WLAN environment that signal is good, the customer service why having is used finely, is it very poor that do some users but feel?
User's reason is the key factor of WLAN client perception, and how that could reject this factor, allows WLAN O&M personnel really know wlan network quality
How by objective WLAN AP(Access Point, the wireless access node effectively evaluated of overall target of wlan network) health degree?
Is mobile wlan network quality or not than rival's difference on earth? where poor?
How to set up a strong operability, across manufacturer, fair WLAN AP quality evaluation standard?
Wlan network quality assessment scheme adopts manual testing and two kinds of means of network management monitoring at present conventionally:
Manual testing, refer to the on-the-spot WLAN testing software that uses of maintenance optimization personnel, AP to be measured is carried out to CQT(Call Quality Test, call quality test calls) operational trials or DT(DRIVER TEST, drive to test) cover jamming test, test event generally includes the projects such as field intensity, association, certification, Ping, FTP, e-mail, and output be associated to the indexs such as power, authentication success rate, ping time delay, carry out evaluating network quality by test index value.
Network management monitoring, refers to be moved back the rate of clothes, be associated to the network performance index after some parties such as power, associated congestion ratio by the collection of WLAN webmaster output equipment alarm, AP, carrys out evaluating network quality by network performance index.
Realizing in process of the present invention, inventor finds that existing scheme exists following shortcoming:
The factors such as user under AP to be measured is how many, customer service kind are very big to wlan network quality influence, and existing two class technical schemes all can not effectively be rejected user's factor;
Prior art scheme be all by performance index to recently evaluating and testing wlan network quality, this evaluation result does not directly reflect network quality, can not alignment quality short slab.
Prior art scheme can not realize rationally, multi-operator network quality contrast intuitively.
Therefore, how by wlan network performance standard, characterizing network quality with minority numerical value, and realize short slab location and many nets quality contrasts, is a problem demanding prompt solution.
Summary of the invention
The object of the invention is to overcome the shortcoming and defect of prior art, a kind of network quality segment quantization evaluating method and system are provided.
A kind of network quality segment quantization evaluating method, described method comprises:
Selected AP to be measured and the five class sources of target information;
Access the described five class sources of target information by AP to be measured respectively, carry out operational trials, and record DNS time delay, Web server connection time delay, Web homepage download time delay, the embedded file download of Web page time delay, message arrival jitter factor and TCP message packet loss;
According to formula W LAN-MOS=5 – (α * Id-DNS+ β * Id-TCP+ γ * Id-mp-HTTP+ δ * Id-object+ η * IJitter+ λ * Ie)+Δ; Computing service perception scoring; Wherein, WLAN-MOS is service-aware scoring, I
d-DNSfor DNS time delay, I
d-TCPfor Web server connects time delay, I
d-mpfor Web homepage is downloaded time delay, I
d-objectfor the embedded file of the Web page is downloaded time delay, Ijitter is that message arrives jitter factor, and Ie is TCP message packet loss, and α, β, γ, λ, η, δ are respectively weights coefficient, and Δ is algorithm modifying factor;
Service-aware scoring corresponding to more described five class sources of target information difference, segment quantization network quality.
Described method also comprises:
Other AP outside selected AP to be measured, accesses the described five class sources of target information by described other AP, carries out operational trials, obtains corresponding service-aware scoring;
The service-aware scoring that more described AP to be measured is corresponding with other AP, segment quantization network quality.
Before described method, also comprise:
AP to be measured is carried out to wireless environment test, the wireless environment of described AP is carried out to classification;
If it is unavailable that the wireless environment of described AP to be measured is classified as, export the disabled evaluation result of wireless environment, test finishes; Otherwise, proceed subsequent step.
Described method also comprises:
According to the wireless environment classification of described AP to be measured and other AP, the service-aware scoring of multiple AP in the classification of same wireless environment is analyzed to segment quantization network quality.
Described method also comprises:
Described AP to be measured is authenticated to link contrast evaluation and test, user log-in authentication stage difference in perception is evaluated, if certification can not be passed through, the disabled evaluation result of authentication output, tests and finishes; Otherwise, proceed subsequent step.
The described five class sources of target information, comprise local access, inter-provincial backbone network, interconnect, interconnect+inter-provincial backbone network, the source of target information corresponding to communication among nations five class network.
A kind of network quality segment quantization evaluating system, described system comprises that the source of target information selectes unit, operational trials unit, computing unit and segment quantization unit, wherein,
The described source of target information is selected unit, for selected AP to be measured and the five class sources of target information;
Described operational trials unit, for accessing the described five class sources of target information by AP to be measured respectively, carry out operational trials, and record DNS time delay, Web server connection time delay, Web homepage download time delay, the embedded file download of Web page time delay, message arrival jitter factor and TCP message packet loss;
Described computing unit, for according to formula W LAN-MOS=5 – (α * Id-DNS+ β * Id-TCP+ γ * Id-mp-HTTP+ δ * Id-object+ η * IJitter+ λ * Ie)+Δ; Computing service perception scoring; Wherein, WLAN-MOS is service-aware scoring, I
d-DNSfor DNS time delay, I
d-TCPfor Web server connects time delay, I
d-mpfor Web homepage is downloaded time delay, I
d-objectfor the embedded file of the Web page is downloaded time delay, Ijitter is that message arrives jitter factor, and Ie is TCP message packet loss, and α, β, γ, λ, η, δ are respectively weights coefficient, and Δ is algorithm modifying factor;
Described segment quantization unit, for service-aware scoring corresponding to more described five class sources of target information difference, segment quantization network quality.
Described system also comprises wireless environment test cell, for AP to be measured is carried out to wireless environment test, the wireless environment of described AP is carried out to classification, according to wireless environment classification results output evaluation result.
Described system also comprises certification link evaluation and test unit, for described AP to be measured being authenticated to link contrast evaluation and test, user log-in authentication stage difference in perception is evaluated to authentication output link evaluation result.
The described source of target information is selected unit, also, for other AP outside selected AP to be measured, accesses the described five class sources of target information by described other AP, carries out operational trials, obtains corresponding service-aware scoring;
Described segment quantization unit, also for the more described AP to be measured service-aware scoring corresponding with other AP, segment quantization network quality.
The present invention is by selecting the five class sources of target information of AP to be measured and needs test, access respectively the five class sources of target information by AP to be measured, carry out operational trials, record test index, and calculate respectively corresponding service-aware scoring according to these indexs by formula, then relatively service-aware scoring corresponding to five class sources of target information difference, find the wherein obvious abnormal source of target information, locate thus network corresponding to such source of target information and have quality problems, also realized thus segment quantization network quality.Compared with prior art, the present invention is based on point wlan network quality quantification and a bottleneck localization method for network segment multipath target service quality difference contrast, can find intuitively, comprehensively, exactly wlan network quality and perception situation, and define and affect the concrete scope of the short slab of wlan network quality, locate its position.And, can effectively reject the impact of user's factor on network quality, realization is simultaneously rationally, multi-operator network quality contrasts intuitively.Compare traditional WLAN service-aware subjective assessment means, the present invention can significantly improve the analysis efficiency of staff to wlan network quality problems, reduces the requirement of O&M technical staff in technical ability simultaneously.
Brief description of the drawings
The network quality segment quantization evaluating method principle flow chart that Fig. 1 provides for the embodiment of the present invention 1;
The five class source of target information schematic diagrames that Fig. 2 provides for the embodiment of the present invention 1;
The test result contrast schematic diagram that Fig. 3 provides for the embodiment of the present invention 1;
The network quality segment quantization evaluating system structural representation that Fig. 4 provides for the embodiment of the present invention 2.
Embodiment
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in detail.But embodiments of the present invention are not limited to this.
In prior art, wlan network, as one of traditional data network, has carried multi-traffic on it, and embodiment of the present invention application WEB browse service carries out wlan network and quantizes evaluation and test.Give on the basis of classification in AP time availability that WLAN is eated dishes without rice or wine, application WLAN-MOS Rating Model algorithm, associated by realizing function between operational trials performance index KPI, quality of service index KQI and user awareness index KEI, obtain WLAN-MOS appraisal result, complete network index is refine to service feature index, realize network quality figure of merit; And utilizing business evaluation result difference contrast between five class.path targets, point network segment that completes wlan network quality and teleservice perception quantizes, bottleneck is located and perception expectation gap quantizes.
In the embodiment of the present invention, give on the basis of classification in AP time availability that WLAN is eated dishes without rice or wine, WLAN-MOS appraisal result contrast based on user awareness index KEI between point network segment multipath information source target, point network segment that completes wlan network quality and teleservice perception quantizes, bottleneck is located and perception expectation gap quantizes.Give on the basis of classification in AP time availability that WLAN is eated dishes without rice or wine, utilize business contrast between five class.path targets to evaluate and test algorithm energy intuitively, accurately, find wlan network quality and difference in perception and deterioration problem comprehensively, and the acquisition algorithm of this wlan network quality and difference in perception has general applicability in the time of analyzing and positioning wlan network quality bottleneck problem, not only can in portable set, use, also can in fixed point WLAN probe mode formula network, apply, in addition, this algorithm is at diverse network standard (GPRS, TD-SCDMA, WCDMA, CDMA2000, TD-LTE etc.) under all applicable.WLAN-MOS scoring algorithm has completed network index has been refine to service feature index, and the subjective and objective index result association between KPI, KQI and KEI, has efficiently realized the work of network quality figure of merit.This algorithm is all applicable under diverse network standard (fixed network broadband, GPRS, TD-SCDMA, WCDMA, CDMA2000, TD-LTE etc.).
As shown in Figure 1, be the network quality segment quantization evaluating method principle flow chart that the embodiment of the present invention 1 provides, specific as follows:
Step 10, selected AP to be measured and the five class sources of target information.
AP to be measured is exactly the AP that needs test network quality, the AP that normally user specifies.The five class sources of target information, are with reference to the whole end-to-end flow process of WLAN business, and selected representational five kinds of paths arrive information source, specifically as shown in Figure 2, wherein, are accessed and are economized backbone network by AP from terminal, afterwards can be by the source of target information of different Path Connections.Terminal to the path difference in this five category informations source and measure of the quality of service result difference respectively corresponding local access, inter-provincial backbone network, interconnect, interconnect+impact of inter-provincial backbone network and communication among nations factor.This five classes source of target information, has represented the quality problems that five conventional class.paths may occur substantially.
In addition, before this step, can also there is a process of the wireless environment of AP to be measured being carried out to classification.AP to be measured is carried out to wireless environment test, the wireless environment of AP is carried out to classification; If it is unavailable that the wireless environment of AP to be measured is classified as, export the disabled evaluation result of wireless environment, test finishes; Otherwise, proceed subsequent step.
Due to the self-interference characteristic of WLAN, along with increasing of user terminal, the corresponding increase of AP utilance of channel, wlan network quality constantly worsens thereupon.Show according to actual measurement empirical data, WLAN wireless environment grade mainly can be divided into free time, busy, super busy and four grade intervals of overload by three grades of AP utilance thresholdings; Under ad eundem WLAN wireless environment, carry out again the comparative analysis of wlan network quality score.The wireless environment classification is here unavailable, is commonly referred to as the wireless environment that is classified as super busy and when overload.By monitoring WLAN AP to be measured place wireless channel environment, according to monitoring result, wireless channel environment is realized to grading and classification, user's factor is quantized the impact of network, make the network quality between ad eundem more objective effectively.
Specify AP and survey the relevant parameters such as this AP place wireless channel CCA in association, completing WLAN wireless environment grading and classification (three grades of above-mentioned fourth class), user's factor is quantized the impact of network.If wireless environment is good, carry out next step; Otherwise for example, if wireless environment severe (CCA is too high, and signal strength signal intensity is too low) provides WLAN wireless environment and need adjust the conclusion of optimization, test process stops.
Further, before or after this step, can also comprise Portal certification link contrast evaluation and test, consumer positioning login authentication stage difference in perception place.If portal authentication success, carries out next step, have problem otherwise provide conclusion Verification System, authenticate unavailable, simultaneously problem analysis place (pushing away failure/authentification failure under the associated failure/dhcp failure/page), and stop test process.
For the evaluation and test of wireless environment classification and Portal certification link, object is that the link that possible occur network quality problem gets rid of in advance, in fact be equivalent to first to carry out the network quality evaluation and test of wireless environment, two links of user log-in authentication, if can confirm that network quality problem occurs in this two links, do not need to carry out follow-up step, directly Output rusults.
Step 20, accesses the described five class sources of target information by AP to be measured respectively, carries out operational trials, and records index of correlation.
The index of correlation here at least comprises: DNS time delay, Web server connect time delay, Web homepage is downloaded time delay, the embedded file download of Web page time delay, message arrival jitter factor and TCP message packet loss.Conventionally, the URL of mirror image website to be tested is set, carries out web operational trials, record each element in webpage DOM and download delay, jitter factor and packet loss, and capture network data message.
Step 30, according to formula W LAN-MOS=5 – (α * Id-DNS+ β * Id-TCP+ γ * Id-mp-HTTP+ δ * Id-object+ η * IJitter+ λ * Ie)+Δ; Computing service perception scoring.
Here, use for reference voice MOS theoretical system, the wlan network subjective perception evaluation that the present embodiment has proposed web business divides.Concrete division as shown in table 1, to divide for subjective perception evaluation.
Table 1
WLAN-MOS Rating Model is the cubic fitting model of a network performance KPI, network quality objective indicator KQI and subjective WLAN service-aware result KEI.This model adopts WEB service time delay, message to arrive jitter factor, TCP message packet loss, page DOM structure and TCP stream content as the input of WLAN-MOS Rating Model function, finally obtains the WLAN-MOS value that WEB service network quality is evaluated.
Its basic calculating formula is as follows:
WLAN-MOS=5–(α*Id-DNS+β*Id-TCP+γ*Id-mp-HTTP+δ*Id-object+η*IJitter+λ*Ie)+Δ。
Wherein, I
d-DNS: DNS time delay; I
d-TCP: Web server connects time delay; I
d-mp: Web homepage is downloaded time delay; I
d-object: the embedded file of the Web page is downloaded time delay; Ijitter: message arrives jitter factor; Ie:TCP message packet loss.α, β, γ, λ, η, δ are weights coefficient, and Δ is algorithm modifying factor.I
d-DNS, I
d-TCP, I
d-mpand I
d-objectform Web business always consuming time.
The weights coefficient here and algorithm modifying factor, initial weight adopts Delphi method to obtain, and is trained and is given tuning by sample value.
In wlan network environment to be measured, access corresponding information Source Site, the index test results such as aforementioned KPI are carried out to filtering and noise reduction, then according to WLAN-MOS Rating Model function, user awareness is marked, and criterion score in basis of reference wlan network web service-aware the five-grade marking system demarcation system, evaluate quality and the gap of WLAN user awareness.
The fitting correction of WLAN-MOS Rating Model function is realized and is adopted classical neural network model and multitiered network error back propagation learning algorithm (BP algorithm).Utilize in advance a large amount of test sample books and customer service sensing results to be trained calibration to relevant weights coefficient in WLAN-MOS Rating Model, thereby reach the weights coefficient adjustment and optimization object of expection, obtain minimum convergency value.WLAN Rating Model function is solidified loading by this convergence result, directly uses output mos appraisal result in follow-up test.
After score function curve completes, it is relatively fixing that its function model and weights keep in follow-up test.The defect error of curve-fitting results just can be made up by suitable analytical expression.In addition, the systematic error of WLAN-MOS scoring algorithm can be offset in the appraisal result comparison procedure of multipath information source target, reaches and exceed the evaluation and test required precision of expection.
Step 40, relatively service-aware scoring corresponding to five class sources of target information difference, segment quantization network quality.
By the comparative analysis to difference between own wlan network 5 category information source MOS evaluation results and rival's wlan network 5 category information source MOS evaluation results, realize the comparative analysis of different operators wlan network quality and similar network segment quality contribution ratio.
The comparative analysis here, not only comprise that service-aware scoring corresponding to the five class sources of target information is analyzed, can also comprise other AP outside AP to be measured, for example, with operator other AP or the AP of different operators, access the five class sources of target information by other AP, carry out operational trials, obtain corresponding service-aware scoring; The service-aware scoring that AP more to be measured is corresponding with other AP, segment quantization network quality.
The process of contrast, is the WLAN-MOS value difference of application between different aforementioned sources, characterizes inter-provincial backbone network, interconnect, interconnect+impact on network quality of inter-provincial backbone network and communication among nations factor, realizes network quality bottleneck location.
Specifically, apply above-mentioned WLAN-MOS algorithm detecting information source respectively, contrast the WLAN-MOS value of five paths, for example, taking information source 1 as benchmark, just can be for AP & AC, the dry network of state, interconnect, international gateways everywhere, orient network quality bottleneck place, realize " qualitative data section ".Application WLAN-MOS test of heuristics information source 1,2,3,4,5, comparative information source 1 and 3, can highlight the difference of local rete mirabile quality, realization " network contrast visualize ".
For example,, if WLAN-MOS score when WLAN-MOS score (respective user perception) is obviously better than access path 3 information source server site when access path 1 information source server site illustrates and obviously has network bottleneck in backbone network.Similarly evaluation method can expand to interconnection gateway and international gateways outlet.
Especially, contrast can be carried out between the AP in same classification at wireless environment, the difference between the scoring of the relevant service-aware of more effective like this contrast.
As shown in Figure 3, for the service-aware scoring contrast situation producing after concrete application of the present embodiment, therefrom can find out intuitively the difference between network quality.Based on the method, can be comprehensively, directly perceived, quantize evaluation and test wlan network quality and perception situation, the short slab place of location wlan network quality deterioration, significantly improves the analysis efficiency of O&M technical staff to wlan network quality.
As shown in Figure 4, be a kind of network quality segment quantization evaluating system that the embodiment of the present invention 2 provides, this system comprises that the source of target information selectes unit 100, operational trials unit 200, computing unit 300 and segment quantization unit 400, specific as follows:
The source of target information is selected unit 100, for selected AP to be measured and the five class sources of target information;
Operational trials unit 200, for accessing the five class sources of target information by AP to be measured respectively, carry out operational trials, and record DNS time delay, Web server connection time delay, Web homepage download time delay, the embedded file download of Web page time delay, message arrival jitter factor and TCP message packet loss;
Computing unit 300, for according to formula W LAN-MOS=5 – (α * Id-DNS+ β * Id-TCP+ γ * Id-mp-HTTP+ δ * Id-object+ η * IJitter+ λ * Ie)+Δ; Computing service perception scoring;
Wherein, I
d-DNSfor DNS time delay, I
d-TCPfor Web server connects time delay, I
d-mpfor Web homepage is downloaded time delay, I
d-objectfor the embedded file of the Web page is downloaded time delay, Ijitter is that message arrives jitter factor, and Ie is TCP message packet loss, and α, β, γ, λ, η, δ are respectively weights coefficient, and Δ is algorithm modifying factor;
Segment quantization unit 400, for relatively service-aware scoring corresponding to five class sources of target information difference, segment quantization network quality.
Further, this system also comprises wireless environment test cell 500, for AP to be measured is carried out to wireless environment test, the wireless environment of AP is carried out to classification, according to wireless environment classification results output evaluation result.
Further, this system also comprises certification link evaluation and test unit 600, for AP to be measured being authenticated to link contrast evaluation and test, user log-in authentication stage difference in perception is evaluated to authentication output link evaluation result.
Further, the selected unit 100 of the above-mentioned source of target information, also, for other AP outside selected AP to be measured, accesses the five class sources of target information by other AP, carries out operational trials, obtains corresponding service-aware scoring;
Segment quantization unit 400, also for the AP more to be measured service-aware scoring corresponding with other AP, segment quantization network quality.
It should be noted that: the network quality segment quantization evaluating system that above-described embodiment provides is in the time that network quality segment quantization is evaluated and tested, only be illustrated with the division of above-mentioned each functional module, in practical application, can above-mentioned functions be distributed and completed by different functional modules as required, be divided into different functional modules by the internal structure of system, to complete all or part of function described above.In addition, the network quality segment quantization evaluating method that above-described embodiment provides and network quality segment quantization evaluating system embodiment belong to same design, and its specific implementation process refers to embodiment of the method, repeats no more here.
To sum up, the present invention is by selecting the five class sources of target information of AP to be measured and needs test, access respectively the five class sources of target information by AP to be measured, carry out operational trials, record test index, and calculate respectively corresponding service-aware scoring according to these indexs by formula, then relatively service-aware scoring corresponding to five class sources of target information difference, find the wherein obvious abnormal source of target information, locate thus network corresponding to such source of target information and have quality problems, also realized thus segment quantization network quality.Compared with prior art, the present invention is based on point wlan network quality quantification and a bottleneck localization method for network segment multipath target service quality difference contrast, can find intuitively, comprehensively, exactly wlan network quality and perception situation, and define and affect the concrete scope of the short slab of wlan network quality, locate its position.And, can effectively reject the impact of user's factor on network quality, realization is simultaneously rationally, multi-operator network quality contrasts intuitively.Compare traditional WLAN service-aware subjective assessment means, the present invention can significantly improve the analysis efficiency of staff to wlan network quality problems, reduces the requirement of O&M technical staff in technical ability simultaneously.
The invention described above embodiment sequence number, just to describing, does not represent the quality of embodiment.
Above-described embodiment is preferably execution mode 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 Spirit Essence of the present invention and principle, substitutes, combination, simplify; all should be equivalent substitute mode, within being included in protection scope of the present invention.
Claims (10)
1. a network quality segment quantization evaluating method, is characterized in that, described method comprises:
Selected wireless access node AP to be measured and the five class sources of target information;
Access the described five class sources of target information by AP to be measured respectively, carry out operational trials, and record DNS time delay, Web server connection time delay, Web homepage download time delay, the embedded file download of Web page time delay, message arrival jitter factor and TCP message packet loss;
According to formula W LAN-MOS=5 – (α * Id-DNS+ β * Id-TCP+ γ * Id-mp-HTTP+ δ * Id-object+ η * IJitter+ λ * Ie)+Δ; Computing service perception scoring; Wherein, WLAN-MOS is service-aware scoring, I
d-DNSfor DNS time delay, I
d-TCPfor Web server connects time delay, I
d-mpfor Web homepage is downloaded time delay, I
d-objectfor the embedded file of the Web page is downloaded time delay, Ijitter is that message arrives jitter factor, and Ie is TCP message packet loss, and α, β, γ, λ, η, δ are respectively weights coefficient, and Δ is algorithm modifying factor;
Service-aware scoring corresponding to more described five class sources of target information difference, segment quantization network quality.
2. the method for claim 1, is characterized in that, described method also comprises:
Other AP outside selected AP to be measured, accesses the described five class sources of target information by described other AP, carries out operational trials, obtains corresponding service-aware scoring;
The service-aware scoring that more described AP to be measured is corresponding with other AP, segment quantization network quality.
3. method as claimed in claim 1 or 2, is characterized in that, before described method, also comprises:
AP to be measured is carried out to wireless environment test, the wireless environment of described AP is carried out to classification;
If it is unavailable that the wireless environment of described AP to be measured is classified as, export the disabled evaluation result of wireless environment, test finishes; Otherwise, proceed subsequent step.
4. method as claimed in claim 3, is characterized in that, described method also comprises:
According to the wireless environment classification of described AP to be measured and other AP, the service-aware scoring of multiple AP in the classification of same wireless environment is analyzed to segment quantization network quality.
5. the method for claim 1, is characterized in that, described method also comprises:
Described AP to be measured is authenticated to link contrast evaluation and test, user log-in authentication stage difference in perception is evaluated, if certification can not be passed through, the disabled evaluation result of authentication output, tests and finishes; Otherwise, proceed subsequent step.
6. the method for claim 1, is characterized in that, the described five class sources of target information comprise local access, inter-provincial backbone network, interconnect, interconnect+inter-provincial backbone network, the source of target information corresponding to communication among nations five class network.
7. a network quality segment quantization evaluating system, is characterized in that, described system comprises that the source of target information selectes unit, operational trials unit, computing unit and segment quantization unit, wherein,
The described source of target information is selected unit, for selected AP to be measured and the five class sources of target information;
Described operational trials unit, for accessing the described five class sources of target information by AP to be measured respectively, carry out operational trials, and record DNS time delay, Web server connection time delay, Web homepage download time delay, the embedded file download of Web page time delay, message arrival jitter factor and TCP message packet loss;
Described computing unit, for according to formula W LAN-MOS=5 – (α * Id-DNS+ β * Id-TCP+ γ * Id-mp-HTTP+ δ * Id-object+ η * IJitter+ λ * Ie)+Δ; Computing service perception scoring; Wherein, WLAN-MOS is service-aware scoring, I
d-DNSfor DNS time delay, I
d-TCPfor Web server connects time delay, I
d-mpfor Web homepage is downloaded time delay, I
d-objectfor the embedded file of the Web page is downloaded time delay, Ijitter is that message arrives jitter factor, and Ie is TCP message packet loss, and α, β, γ, λ, η, δ are respectively weights coefficient, and Δ is algorithm modifying factor;
Described segment quantization unit, for service-aware scoring corresponding to more described five class sources of target information difference, segment quantization network quality.
8. system as claimed in claim 7, is characterized in that, described system also comprises wireless environment test cell, for AP to be measured is carried out to wireless environment test, the wireless environment of described AP is carried out to classification, according to wireless environment classification results output evaluation result.
9. system as claimed in claim 7, it is characterized in that, described system also comprises certification link evaluation and test unit, for described AP to be measured being authenticated to link contrast evaluation and test, user log-in authentication stage difference in perception is evaluated to authentication output link evaluation result.
10. system as claimed in claim 7, is characterized in that, the described source of target information is selected unit, also for other AP outside selected AP to be measured, access the described five class sources of target information by described other AP, carry out operational trials, obtain corresponding service-aware scoring;
Described segment quantization unit, also for the more described AP to be measured service-aware scoring corresponding with other AP, segment quantization network quality.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310125528.7A CN104105121A (en) | 2013-04-11 | 2013-04-11 | Network quality segmented quantification evaluation method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201310125528.7A CN104105121A (en) | 2013-04-11 | 2013-04-11 | Network quality segmented quantification evaluation method and system |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104105121A true CN104105121A (en) | 2014-10-15 |
Family
ID=51672853
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201310125528.7A Pending CN104105121A (en) | 2013-04-11 | 2013-04-11 | Network quality segmented quantification evaluation method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104105121A (en) |
Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107708130A (en) * | 2017-10-31 | 2018-02-16 | 下代互联网重大应用技术（北京）工程研究中心有限公司 | Wireless network test evaluation method |
| CN108632762A (en) * | 2017-03-15 | 2018-10-09 | 上海掌门科技有限公司 | Method and apparatus for generating and presenting the wireless access locus of points |
| CN108668302A (en) * | 2018-04-19 | 2018-10-16 | 维沃移动通信有限公司 | A kind of network recommendation method and mobile terminal |
| CN108934026A (en) * | 2018-06-30 | 2018-12-04 | 江苏有线数据网络有限责任公司 | A kind of mobile terminal Wi-Fi quality determining method |
| CN109474940A (en) * | 2017-09-08 | 2019-03-15 | 中兴通讯股份有限公司 | Quality of service detection method and device |
| CN111181862A (en) * | 2019-12-18 | 2020-05-19 | 广州市柏特科技有限公司 | Router capable of automatically diagnosing network quality |
| CN111369091A (en) * | 2018-12-26 | 2020-07-03 | 中国移动通信集团四川有限公司 | Method, apparatus, device and medium for user perceptual portrait analysis |
| WO2022134616A1 (en) * | 2020-12-21 | 2022-06-30 | 华为技术有限公司 | Wireless network delay processing method and system and access server |
| CN115473871A (en) * | 2022-09-19 | 2022-12-13 | 广州市百果园网络科技有限公司 | Domain name local resolution method and device, equipment, medium and product thereof |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007000633A1 (en) * | 2005-06-29 | 2007-01-04 | Nokia Corporation | Quality assessment for telecommunications network |
| CN101505237A (en) * | 2009-03-11 | 2009-08-12 | 华为技术有限公司 | Network quality determination method, apparatus and communication system |
| CN101951663A (en) * | 2010-08-26 | 2011-01-19 | 湘潭大学 | User-based multi-access network selection method being used under wireless heterogeneous network environment |
| CN102044247A (en) * | 2009-10-10 | 2011-05-04 | 北京理工大学 | Objective evaluation method for VoIP speech |
| WO2012113436A1 (en) * | 2011-02-21 | 2012-08-30 | Telefonaktiebolaget L M Ericsson (Publ) | Service problem diagnosis for mobile wireless networks |
| CN102664767A (en) * | 2012-04-18 | 2012-09-12 | 郑州三友软件科技有限公司 | IP-based WLAN network data QOS analysis method |
| CN102811465A (en) * | 2012-07-11 | 2012-12-05 | 北京邮电大学 | Service shunting system and method based on feedback information under heterogeneous network |
-
2013
- 2013-04-11 CN CN201310125528.7A patent/CN104105121A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007000633A1 (en) * | 2005-06-29 | 2007-01-04 | Nokia Corporation | Quality assessment for telecommunications network |
| CN101505237A (en) * | 2009-03-11 | 2009-08-12 | 华为技术有限公司 | Network quality determination method, apparatus and communication system |
| CN102044247A (en) * | 2009-10-10 | 2011-05-04 | 北京理工大学 | Objective evaluation method for VoIP speech |
| CN101951663A (en) * | 2010-08-26 | 2011-01-19 | 湘潭大学 | User-based multi-access network selection method being used under wireless heterogeneous network environment |
| WO2012113436A1 (en) * | 2011-02-21 | 2012-08-30 | Telefonaktiebolaget L M Ericsson (Publ) | Service problem diagnosis for mobile wireless networks |
| CN102664767A (en) * | 2012-04-18 | 2012-09-12 | 郑州三友软件科技有限公司 | IP-based WLAN network data QOS analysis method |
| CN102811465A (en) * | 2012-07-11 | 2012-12-05 | 北京邮电大学 | Service shunting system and method based on feedback information under heterogeneous network |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108632762A (en) * | 2017-03-15 | 2018-10-09 | 上海掌门科技有限公司 | Method and apparatus for generating and presenting the wireless access locus of points |
| CN109474940A (en) * | 2017-09-08 | 2019-03-15 | 中兴通讯股份有限公司 | Quality of service detection method and device |
| CN109474940B (en) * | 2017-09-08 | 2021-11-02 | 中兴通讯股份有限公司 | Service quality detection method and device |
| CN107708130A (en) * | 2017-10-31 | 2018-02-16 | 下代互联网重大应用技术（北京）工程研究中心有限公司 | Wireless network test evaluation method |
| CN108668302A (en) * | 2018-04-19 | 2018-10-16 | 维沃移动通信有限公司 | A kind of network recommendation method and mobile terminal |
| CN108934026A (en) * | 2018-06-30 | 2018-12-04 | 江苏有线数据网络有限责任公司 | A kind of mobile terminal Wi-Fi quality determining method |
| CN111369091A (en) * | 2018-12-26 | 2020-07-03 | 中国移动通信集团四川有限公司 | Method, apparatus, device and medium for user perceptual portrait analysis |
| CN111181862A (en) * | 2019-12-18 | 2020-05-19 | 广州市柏特科技有限公司 | Router capable of automatically diagnosing network quality |
| WO2022134616A1 (en) * | 2020-12-21 | 2022-06-30 | 华为技术有限公司 | Wireless network delay processing method and system and access server |
| CN115473871A (en) * | 2022-09-19 | 2022-12-13 | 广州市百果园网络科技有限公司 | Domain name local resolution method and device, equipment, medium and product thereof |
| CN115473871B (en) * | 2022-09-19 | 2023-08-04 | 广州市百果园网络科技有限公司 | Domain name local resolution method and device, equipment, medium and product thereof |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104105121A (en) | Network quality segmented quantification evaluation method and system | |
| Fiedler et al. | A generic quantitative relationship between quality of experience and quality of service | |
| CN104640125B (en) | A kind of method and apparatus of the quality of assessment WLAN business | |
| CN106092959B (en) | A kind of near-infrared food quality monitoring system based on cloud platform | |
| CN104683182B (en) | IDC network of computer room service quality detection method and device | |
| CN105610993B (en) | A kind of domain name analytic method, apparatus and system | |
| Alay et al. | MONROE: Measuring mobile broadband networks in Europe | |
| CN105679335B (en) | Speech quality assessment method and system based on no line analysis | |
| KADIOĞLU et al. | Quality of service assessment: a case study on performance benchmarking of cellular network operators in Turkey | |
| CN113678494A (en) | Method and device for providing network experience testing | |
| US20070081467A1 (en) | Method and apparatus for testing a telecommunications network | |
| US20190215716A1 (en) | Determining whether a flow is to be added to a network | |
| US20180352451A1 (en) | Method and system for testing telecommunications infrastructure | |
| CN106130791A (en) | Quality-of-service based buffer memory device service ability traversal test system and method | |
| CN102300238A (en) | Client perception system and method for broadband network | |
| JP2007036839A (en) | Apparatus, system, and method for dividing quality deterioration in packet exchange network | |
| CN104363130A (en) | System and method for analyzing, positioning and controlling network quality problems in communication networks | |
| Bagnulo et al. | Standardizing large-scale measurement platforms | |
| EP1447940A2 (en) | Method for measuring a user perception score | |
| Hoßfeld et al. | White Paper on Crowdsourced Network and QoE Measurements--Definitions, Use Cases and Challenges | |
| Nguyen-Ngoc et al. | Performance evaluation mechanisms for flowmod message processing in openflow switches | |
| Bermudez et al. | Statistical validation of an LTE emulation tool using live video streaming over reliable transport protocols | |
| Kokkinos et al. | Wireless crowdsourced performance monitoring and verification: Wifi performance measurement using end-user mobile device feedback | |
| Mandalari et al. | Measuring roaming in Europe: Infrastructure and implications on users’ QoE | |
| Stojanovic et al. | Approaches to Quality of Experience management in the future Internet |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20141015 |