CN107483240A - Power communication network service health degree analysis method based on Internet resources incidence relation - Google Patents
Power communication network service health degree analysis method based on Internet resources incidence relation Download PDFInfo
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- CN107483240A CN107483240A CN201710666872.5A CN201710666872A CN107483240A CN 107483240 A CN107483240 A CN 107483240A CN 201710666872 A CN201710666872 A CN 201710666872A CN 107483240 A CN107483240 A CN 107483240A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
- H04L41/065—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis involving logical or physical relationship, e.g. grouping and hierarchies
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/04—Network management architectures or arrangements
- H04L41/044—Network management architectures or arrangements comprising hierarchical management structures
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/50—Network service management, e.g. ensuring proper service fulfilment according to agreements
- H04L41/5003—Managing SLA; Interaction between SLA and QoS
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Abstract
The invention discloses a kind of power communication network service health degree analysis method based on Internet resources incidence relation, including establish the whole network business health degree assessment indicator system；According to the whole network business health degree assessment indicator system, step analysis figure is established；Development of judgment matrix；It is associated key element optimization；Calculate weight vectors of the every layer of index relative to upper strata index；Calculate weight vectors of the every layer of index relative to first order index：Weight vectors are multiplied and are ranked up with judgment matrix, as health degree sorts.The present invention helps user to realize the optimization for power telecom network resource management mode, user can more accurately and rapidly check whole power communication Running State, solve different alarms and lack efficient association between each other, single alarm includes the problem of information is less, improves management of the administrative staff to whole network running status.
Description
Technical field
The present invention relates to a kind of power communication network service health degree analysis method based on Internet resources incidence relation, belong to
Power communication network service health analysis technical field.
Background technology
Power telecom network is to integrate transmission, exchange, the complication system for having multiple links to form of terminal, including SDH,
EPON, wavelength-division multiplex, data network, programme-controlled exchange, teleconference, video monitoring etc., various equipment carry respective webmaster,
It is independent mutually, it is incompatible.The main task that power telecom network undertakes is to transmit various power generations and management business information.
With the fast development of electricity market, it is logical that system has various substantial amounts of data, speech and graphic service information to need
Communication private network is crossed to transmit.This management such as safe and stable, quick to communication network it is also proposed higher requirement.
With the rapid development of computer technology, network technology, automatic technology and the communication technology, at this stage for network
The construction of bearer service health degree analysis system has deployed.But still there is：Communication network is huge, in daily management
It is big there is alarm quantity, it is difficult to effectively management and analysis.Difference alarm lacks efficient association between each other, and single alarm includes
Information is less, can not realize effective the whole network business impact analysis.Existing network bearer service health degree analysis technology is single, lacks
Weary the whole network business health degree analysis for mixed networking.
The content of the invention
The technical problems to be solved by the invention are the defects of overcoming prior art, there is provided one kind is associated based on Internet resources
The power communication network service health degree analysis method of relation, the power telecom network alarm resource in the case of realizing based on mixed networking
Incidence relation management between management, network resource management, running environment resource management and three, ensure that for power communication
The promptness and accuracy of network service health degree analysis.
In order to solve the above technical problems, the present invention provides a kind of power communication network service based on Internet resources incidence relation
Health degree analysis method, comprises the following steps：
1) the whole network business health degree assessment indicator system is established；
2) according to the whole network business health degree assessment indicator system, step analysis figure is established；
3) development of judgment matrix；
4) it is associated key element optimization；
5) weight vectors of the every layer of index relative to upper strata index are calculated；
6) weight vectors of the every layer of index relative to first order index are calculated：
7) weight vectors are multiplied and are ranked up with judgment matrix, as health degree sorts.
Foregoing the whole network business health degree assessment indicator system is divided into level Four, is respectively：First order index：Business health
Degree；Business health degree is divided into three kinds of second level indexs：Alert grade, type of service, bandwidth；Alarm grade is divided into the several 3rd
Level index, including：Critical alarm, main alarm, minor alarm；Type of service is divided into several third level index, including：It is administrative
Switching network, scheduling exchange network, relay protection net；Bandwidth is divided into several third level index, including：2.5G, 622M, 155M；Often
A kind of third level index is also divided into several fourth stage index.
Foregoing development of judgment matrix refers to, by way of expert estimation, rule of thumb and to certain extension
Subjective judgement, quantitatively by the chromatographic analysis figure of the step 2), factor compares two-by-two in same level, draws single finger
The significance level relative to each index of last layer is marked, so as to build positive and negative interactive judgment matrix A.
Foregoing positive and negative interactive judgment matrix A uses 1~9 scaling law.
The correlating factor optimization of foregoing step 4) is optimized using frequent item set and correlation rule.
Foregoing calculating weight vectors, refer to meet AC=A for positive and negative interactive judgment matrix A, calculatingmaxC characteristic root
AmaxWith characteristic vector C,
Wherein, C is normalized characteristic vector, and as the one of weight estimates.
Beneficial effects of the present invention are：
(1) business health degree analysis algorithm is based on existing power telecom network network management system platform, realizes on this basis
Health degree appraisement system, adds some distinctive Data Analysis Models, and to original power telecom network resource data
Associate management component has carried out function expansion, effectively improves the monitoring of power telecom network network bearer, health degree analysis and pre-
Alert promptness and accuracy.
(2) present invention helps user to realize the optimization for power telecom network resource management mode, and user can be more
Whole power communication Running State is accurately and rapidly checked, different alarms is solved and lacks efficient association between each other, it is single
Alarm includes the problem of information is less, improves management of the administrative staff to whole network running status.
(3) present invention completes the power communication network service based on power telecom network network and Internet resources incidence relation and is good for
Kang Du is analyzed, and has been taken into full account the incidence relations such as alarm resource, the communication resource and network protection, has been realized the whole network of mixed networking
Business health degree analysis, improve operation maintenance personnel and power telecom network failure and traffic affecting are integrated.
Brief description of the drawings
Fig. 1 the whole network business health degree step analysis figures；
The scale implication of Fig. 2 indexs；
Fig. 3 is item collection schematic diagram.
Embodiment
The invention will be further described below.Following examples are only used for the technical side for clearly illustrating the present invention
Case, and can not be limited the scope of the invention with this.
1st, the setting of health degree appraisement system
The key problem of health degree evaluation is carried out to system, is how to determine an assessment indicator system.Evaluation index body
The science of system, reasonability will directly influence the quality of final appraisal results.Therefore, the present invention is carried out from following angle
Analysis and judgement：
1) in face of the horizontal gap of business event and the particularity of concrete condition, select which type of index trueer
In fact, accurately, objectively reflect that health degree is horizontal.
2) evaluation of professional skill is faced, how how health degree assessment to be complemented each other with value assessment and combined
Health degree is assessed and mutually linked up with KPI and business development.
3) representative and succinct generalization dominant index should be screened by establishing the assessment indicator system of science, with standard
Really, delicately reflect that health degree is horizontal.
By carefully analyzing, according to the characteristics of full power communication network operation, the present invention establishes three two-level appraisement indexs
With its correlator level index, table 1 is referred to.Because index is a lot, part index number is only listed after the second level as example.
The whole network business health degree assessment indicator system of table 1
2nd, the foundation of hierarchical model
Research object is resolved into different compositing factors first, then by the membership between each factor, them
Arranged according to some levels from high to low, form a recursive hierarchy structure.And then two are carried out to each element of same level
Two compare, and give quantificational expression with regard to the relative importance of each level, and using mathematical method determine each level items because
The weights of element.
Basic step is as follows:
Step 1:By tectonic remnant basin analyze drawing method in challenge various factors division connect each other it is orderly
Level is allowed to methodization, stratification, establishes the structural model of step analysis.The characteristics of for power telecom network the whole network business, root
The index system set according to table 1, proposes step analysis figure as shown in Figure 1, for follow-up evaluation analysis.
Step 2:Development of judgment matrix
Hierarchical structure reflects the relation between factor, but the proportion that each criterion in rule layer is shared in target measurement
Might not be identical.Therefore, it is quantitative rule of thumb and to certain extension subjective judgement by way of expert estimation
The importance that factor compares two-by-two in same level is described on ground, draws the relative importance of single index, so as to build
Positive and negative interactive judgment matrix A.What each element in matrix reflected is this layer of element relative to the important of each index of last layer
Degree.
In order that compared the judgment matrix quantified between each element two-by-two, with reference to relevant psychologic research into
Fruit, we introduce scale index and implication, as shown in Figure 2.
Step 3:Correlating factor optimizes
In view of deficiency of the judgment matrix in key element correlation, therefore we will be closed before calculating weight is carried out
Join key element relevance optimization to calculate.
This step mainly realizes frequent item set and correlation rule.
(1) frequent item set
Assuming that we carry out having 4 kinds of key elements (key element 0, key element 1, key element 2 and key element 3) during health degree analysis, Fig. 3 is shown
All possibility combination between all key elements：
For the support of single item collection, can be recorded by traveling through every and check the record whether comprising the item collection come
Calculate.2 are shared for the data set comprising N kind key elementsN-1 kind of item collection combination, then using converse negative proposition, judge the whether non-frequency of item collection
It is numerous, i.e., if an item collection right and wrong frequently, then also right and wrong are frequently for its all supersets.
(2) correlation rule
Regular calculating is associated using Apriori algorithm, is comprised the following steps that：
1. single time scan database x excessively；The support of each 1 item collection is calculated, obtains the set of frequent 1 item collection.
2. being started the cycle over from 2 item collections, frequent k item collections are generated by frequent k-1 item collections.
2.1 connection steps：In order to generate, previously generate, (a k- is by 2 different frequency collection belonged to of an only item
2) JOIN computings obtain.
If connection step, which refers to, two k-1 item collections, each item collection is carried out according to the lexicographic order of " attribute-value " (typically according to value)
Sequence.If the preceding k-2 item of two k-1 item collections is identical, and last difference, then prove they be it is attachable, i.e.,
This k-1 item collection can be with marriage, you can connection generation k item collections.Make if any two 3 item collections：{ a, b, c } { a, b, d }, the two 3
Item collection is exactly attachable, and they can connect 4 item collections of generation { a, b, c, d }.And for example two 3 item collections { a, b, c } { a, d, e },
The two 3 item collections, which are shown, can not connect 3 item collections of generation.
2.2 beta prunings walk：Due to the superset for being, it is possible that some elements are not frequently.It is not frequent to give up to fall subset
The item collection i.e. not item collection in frequent k-1 item collections
If the subset that beta pruning step refers to an item collection is not frequent item set, the item collection is certainly nor frequent item set.Even
In the presence of 3 item collections { a, b, c }, if the support of its 2 subsets { a, b }, which is the number occurred, does not reach threshold value simultaneously, then a,
B, c } at the same occur number be obviously also do not reach threshold value.Therefore, if the subset in the presence of an item collection is not frequent item set,
So the item collection just should giving up by mercilessness.
2.3 scan databases, the support of the k item collections after being filtered in 2.2 steps is calculated, give up to fall support less than threshold value
Item collection, generate frequent k item collections.
3. only have circulation during an item collection to terminate in the frequent k item collections being currently generated.
Step 4:Calculate weight
For judgment matrix, calculating meets AC=AmaxC characteristic root AmaxWith characteristic vector C.C be corresponding to normalization
One estimation of characteristic vector, as rank order filtering (i.e. weight).A is understood by the Perron theorems of positive matricesmaxIn the presence of only
One, C component are also positive component.
Step 5:Always sorted
What previous step was calculated is one group of factor to the weight vectors of some element of its last layer, and we also need to count
Calculate weight order of each layer factor to overall goals relative importance.That is, by always sorting, draw each factor of bottom for total
The relative importance of body target.
Step 6：Health degree calculates
The computing of synthesis is exactly a multiplying in fact, by the multiplied by weight for all factors that will have dominance relation,
Can draws weight sequencing of each factor to overall goals (such as system health degree) of the bottom.Total sequence can instruct system
Key index is paid close attention to, limited resources are put into the project for maximum of producing effects.
Step 7:Sorted, taken measures according to health degree, promote business service is horizontal to improve
By the analysis to historical data, we can draw business health degree assessment order, and index is carried out laterally
Comparative analysis, realize that business support service ability short slab is analyzed, found a job emphasis and breakthrough for follow-up sustained improvement work
Mouthful.
Described above is only the preferred embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, without departing from the technical principles of the invention, some improvement and deformation can also be made, these are improved and deformation
Also it should be regarded as protection scope of the present invention.
Claims (6)
1. the power communication network service health degree analysis method based on Internet resources incidence relation, it is characterised in that including following
Step：
1）Establish the whole network business health degree assessment indicator system；
2）According to the whole network business health degree assessment indicator system, step analysis figure is established；
3）Development of judgment matrix；
4）It is associated key element optimization；
5）Calculate weight vectors of the every layer of index relative to upper strata index；
6）Calculate weight vectors of the every layer of index relative to first order index：
7）Weight vectors are multiplied and are ranked up with judgment matrix, as health degree sorts.
2. the power communication network service health degree analysis method according to claim 1 based on Internet resources incidence relation,
Characterized in that, the whole network business health degree assessment indicator system is divided into level Four, it is respectively：First order index：Business health
Degree；Business health degree is divided into three kinds of second level indexs：Alert grade, type of service, bandwidth；Alarm grade is divided into the several 3rd
Level index, including：Critical alarm, main alarm, minor alarm；Type of service is divided into several third level index, including：It is administrative
Switching network, scheduling exchange network, relay protection net；Bandwidth is divided into several third level index, including：2.5G, 622M, 155M；Often
A kind of third level index is also divided into several fourth stage index.
3. the power communication network service health degree analysis method according to claim 1 based on Internet resources incidence relation,
Characterized in that, the development of judgment matrix refers to, by way of expert estimation, rule of thumb and to certain extension
Subjective judgement, quantitatively by the step 2）Chromatographic analysis figure in, factor compares two-by-two in same level, draws single finger
The significance level relative to each index of last layer is marked, so as to build positive and negative interactive judgment matrix A.
4. the power communication network service health degree analysis method according to claim 3 based on Internet resources incidence relation,
Characterized in that, the positive and negative interactive judgment matrix A uses 1 ~ 9 scaling law.
5. the power communication network service health degree analysis method according to claim 1 based on Internet resources incidence relation,
Characterized in that, the step 4）Correlating factor optimization optimized using frequent item set and correlation rule.
6. the power communication network service health degree analysis method according to claim 3 based on Internet resources incidence relation,
Characterized in that, the calculating weight vectors, refer to meet AC=A for positive and negative interactive judgment matrix A, calculatingmaxC characteristic root
AmaxWith characteristic vector C,
Wherein, C is normalized characteristic vector, and as the one of weight estimates.
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Cited By (5)
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| CN111865689A (en) * | 2020-07-20 | 2020-10-30 | 南京信息职业技术学院 | Alarm voltage drop method based on index set tree |
| CN113139701A (en) * | 2021-05-19 | 2021-07-20 | 中能融合智慧科技有限公司 | Regional energy source health degree evaluation method based on hierarchical analysis method |
| CN113159638A (en) * | 2021-05-17 | 2021-07-23 | 国网山东省电力公司电力科学研究院 | Intelligent substation layered health degree index evaluation method and device |
| CN114418226A (en) * | 2022-01-21 | 2022-04-29 | 广东电网有限责任公司 | Fault analysis method and device of power communication system |
| CN116029604A (en) * | 2023-02-03 | 2023-04-28 | 华南农业大学 | Cage-raised meat duck breeding environment regulation and control method based on health comfort level |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111865689A (en) * | 2020-07-20 | 2020-10-30 | 南京信息职业技术学院 | Alarm voltage drop method based on index set tree |
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| CN113159638A (en) * | 2021-05-17 | 2021-07-23 | 国网山东省电力公司电力科学研究院 | Intelligent substation layered health degree index evaluation method and device |
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| CN116029604A (en) * | 2023-02-03 | 2023-04-28 | 华南农业大学 | Cage-raised meat duck breeding environment regulation and control method based on health comfort level |
| CN116029604B (en) * | 2023-02-03 | 2024-01-23 | 华南农业大学 | Cage-raised meat duck breeding environment regulation and control method based on health comfort level |
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