CN107124321A - A kind of network operation condition predicting model based on big data - Google Patents
A kind of network operation condition predicting model based on big data Download PDFInfo
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- CN107124321A CN107124321A CN201710556812.8A CN201710556812A CN107124321A CN 107124321 A CN107124321 A CN 107124321A CN 201710556812 A CN201710556812 A CN 201710556812A CN 107124321 A CN107124321 A CN 107124321A
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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
- H04L41/14—Network analysis or design
- H04L41/147—Network analysis or design for predicting network behaviour
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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
- H04L41/14—Network analysis or design
- H04L41/145—Network analysis or design involving simulating, designing, planning or modelling of a network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/06—Testing, supervising or monitoring using simulated traffic
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Abstract
The present invention discloses a kind of network operation condition predicting model based on big data, it is related to the communications field, based on Network Management Equipment data, introduce subscriber signaling data, MR data, complaint data and the survey data of magnanimity, the network operation analysis forecast model architectural framework that two layers of three domains of the proposition based on big data, using the MPP distributed data processings of current main-stream, based on the regression forecasting algorithm in data mining technology, realize that network operation status analysis is predicted；From network O＆M domain, service application domain, three, network security domain dimensional analysis, each dimension is deployed from network, two aspects of user.The present invention improves the business depth and operational efficiency of forecast model；It can truly reflect that network quality perceives the gap of part with client traffic experience, embody security status, prediction can be estimated for single user, single business, be comprehensive, the efficient network synthesis appraisal procedure of operator's proposition under mobile Internet background.
Description
Technical field
The present invention relates to the communications field, specifically a kind of network operation condition predicting model based on big data.
Background technology
In telecommunications network operation, network operation condition predicting is most important.In time, rational neural network forecast result can be straight
Connect help manager make correct decisions and investment, instruct the dilatation and optimization of network, it is ensured that telecommunications network health, safely, effectively
Operation, with great society and economic implications.Early stage neural network forecast both domestic and external increases mainly around traffic, resource is used,
The network O＆M such as potential faults angle carries out scale-model investigation, and prediction algorithm is mainly with linear regression, index return, polynomial regression
Based on classical trend extropolation prediction algorithm, in recent years to ensure the accuracy predicted the outcome, Kalman filtering etc. is introduced again
Algorithm is optimized to predicting the outcome.
No matter which kind of algorithm is used, and the core of prediction will surrounding target modeling expansion.Current main-stream telecom operation commercial city
Attempting from NOC (Network Operation Center, Network Operation Centre) to SOC (Service Operating
Center, Service Operation center) transition, realize the end-to-end preventive operation management pattern of business that curstomer-oriented is perceived.Meanwhile,
Country should focus on information security pay attention to day by day corresponding in terms of network operation prediction there is provided the telecom operators of basic network
Transition.
In summary, operator is in the mobile Internet epoch, and network technology, O＆M pattern are faced with great change,
Currently the network operation forecast model based on O＆M can not meet the new work requirements of telecom operators, create and meet current
The network operation forecast model that work transition is required turns into the major issue that telecom operators need to consider.
The content of the invention
There is provided a kind of network operation shape based on big data for the demand and weak point that the present invention develops for current technology
Condition forecast model and method.
A kind of network operation condition predicting model based on big data of the present invention, solves what above-mentioned technical problem was used
Technical scheme is as follows：The network operation condition predicting model based on big data, based on Network Management Equipment data, introduces sea
Subscriber signaling data, MR data, complaint data and the survey data of amount, the network operation that two layers of three domains of the proposition based on big data
Forecast model architectural framework is analyzed, using the MPP distributed data processings of current main-stream, based in data mining technology
Regression forecasting algorithm, realizes that network operation status analysis is predicted；
The network operation analysis predicts mould from network O＆M domain, service application domain, three, network security domain dimensional analysis,
Each dimension is deployed from network, two aspects of user.
It is preferred that, the enabling capabilities of telecom operators' basic network are mainly assessed in the network O＆M domain, are referred to by one-level
Mark network O＆M score is evaluated.
It is preferred that, further decomposite that resource is reasonable, the network coverage is good, network quality is excellent, O＆M ability by first class index
Strong four two-level index；Good, the easily access two user class indexs strong with signal of the network coverage exist and associated；Network quality it is excellent with not
Go offline, noiseless two user class indexs have association.
It is preferred that, the own and value-added service clothes that telecom operators can provide the user mainly are assessed in the service application domain
Business ability, is evaluated by first class index service application score, supports single business to assess.
It is preferred that, further decomposited by first class index resource occupation rationally, using perceiving, without in violation of rules and regulations, be worth Gao Si
Item two-level index；Using perceive it is good with easily access, time delay is low, the reasonable three user class indexs of flow are in the presence of associating.
It is preferred that, the network security domain is used to evaluate the safety that telecom operators provide in itself for mobile subscriber, network
Protective capacities, is evaluated by first class index network security score.
It is preferred that, terminal security, network security, three two-level index of content safety are further decomposited by first class index；
Terminal security with without trojan horse, be as good as normal flow binomial user class index exist associate；Content safety is with information completely, without separated
Advise two user class indexs of content and there is association.
A kind of network operation condition predicting model and method based on big data of the present invention, have compared with prior art
Some beneficial effects are：On the basis of the present invention is based on Network Management Equipment data, mass users signaling data, MR data are introduced,
A series of problems present in legacy network assessment prediction method is solved, such as can not truly reflect network quality and client's industry
Gap between business experience perception, it is impossible to fully reflect security status, it is difficult to be estimated prediction from user class, single service level
Deng；
The present invention can overcome the network operation forecast model currently based on O＆M can not meet telecom operators' work
The defect of demand, model index system is extended it is perfect, create meet work at present transition require the network operation it is pre-
Survey model；Further lift the business depth and operational efficiency of forecast model；Network quality and client traffic can truly be reflected
The gap for perceiving part is experienced, security status is embodied, prediction can be estimated for single user, single business, it is mutual for movement
Operator proposes comprehensive, efficient network synthesis appraisal procedure under background of networking.
Brief description of the drawings
Accompanying drawing 1 is the schematic block diagram of the network operation condition predicting model.
Embodiment
For the object, technical solutions and advantages of the present invention are more clearly understood, below in conjunction with specific embodiment, to this hair
A kind of bright network operation condition predicting model based on big data is further described.
Network operation condition predicting model of the present invention based on big data, it is proposed that " three domains based on big data
Two layers " network operation analysis forecast model architectural framework, provide one group of index system and a set of assessment algorithm；The network operation shape
Condition forecast model introduces subscriber signaling, MR (the measurement result, measurement of magnanimity based on Network Management Equipment data
Report) and survey data, it can truly reflect that network quality experiences the gap for perceiving part with client traffic, embody network security shape
Condition, can be estimated prediction for single user, single business, be that operator proposes comprehensively, efficiently under mobile Internet background
Network synthesis appraisal procedure.
Embodiment：
The network operation condition predicting model based on big data, based on Network Management Equipment data, draws described in the present embodiment
Enter subscriber signaling data, MR data, complaint data and the survey data of magnanimity, the network that two layers of three domains of the proposition based on big data
Operating analysis forecast model architectural framework, using the MPP distributed data processings of current main-stream, based on data mining technology
In regression forecasting algorithm, model index system is extended it is perfect, realize network operation status analysis predict, improve pre-
Survey the business depth and operational efficiency of model.
As shown in Figure 1, the network operation analysis predicts mould from network O＆M domain, service application domain, network security domain
Three dimensional analysis, each dimension is deployed from network, two aspects of user.
The enabling capabilities of telecom operators' basic network are mainly assessed in the network O＆M domain, are transported by first class index network
Dimension score is evaluated.Further decomposite that resource is reasonable, the network coverage is good, network quality is excellent, O＆M ability by first class index
Strong four two-level index.Also, good, the easily access two user class indexs strong with signal of the network coverage exist and associated；Network quality
It is excellent with not going offline, noiseless two user class indexs exist associate.
The own and value-added service service ability that telecom operators can provide the user mainly is assessed in the service application domain,
Evaluated by first class index service application score, support single business to assess.Resource is further decomposited by first class index
Take rationally, using perceiving, without in violation of rules and regulations, high four two-level index of value.And using perceive it is good with easily access, time delay it is low,
There is association in the reasonable three user class indexs of flow.
The network security domain is used to evaluate the security protection energy that telecom operators provide in itself for mobile subscriber, network
Power, is evaluated by first class index network security score.Further decomposited by first class index terminal security, network security,
Three two-level index of content safety.Also, terminal security with without trojan horse, be as good as normal flow binomial user class index exist pass
Connection；Content safety is associated with information completely, without the two user class indexs presence of violation content.
In the network operation condition predicting model, the subscriber signaling data of introducing are to realize that Consumer's Experience quantifies and user
The significant data source of behavioural analysis, therefrom know user with who call, voice frequency how, present position, signal environment, business
Use time, which browsed webpage of user, applied using which kind of mobile Internet, using these service applications frequency such as
What, performance such as how many user class service datas.By subscriber signaling data combination Network Management Equipment data, can further it pass through
Depth data is excavated, and is perceived with user and is quantified to improve understanding of the operator to user, it will help expands shadow from more perspective
The correlative factor of the network operation is rung, so as to make more accurate analysis and evaluation to existing network situation.
When implementing the network operation condition predicting model, user class index is from subscriber signaling data, MR data, complaint number
According to and survey data, network level index collects from Network Management Equipment data, user-level data.The network operation condition predicting model
Detailed index system it is as shown in the table：
Wherein, in network O＆M score, resource is reasonable：Whether resource distribution, the resource utilization for evaluating network are reasonable；Net
Network is covered：Whether comprehensive evaluate the network coverage, if there is covering blind spot；Network quality is excellent：Whether just to evaluate network quality
Often, business can be met to require with user；O＆M ability is strong：Operator is evaluated for the treatment effeciency effect after Network Abnormal.
In service application score, resource occupation is reasonable：Whether evaluation assignment is reasonable for the occupancy of Internet resources；Use feeling
Know：How are the using effect and Consumer's Experience of evaluation assignment；Without in violation of rules and regulations：Evaluation assignment whether there is violation problem, such as steals and flows
Amount；Value is high：The situation of Profit that evaluation assignment is brought to operator.
In network security score, terminal security：Operator is evaluated to user terminal anti-Trojan, the enabling capabilities of anti-virus；
Network security：Evaluate the ability that carrier network puts monitoring, anti-hacker amounts to；Content safety：Operator is evaluated to user profile
Completely, the control ability of abnormal information.
A reference value is set for each KPI index (Key Performance Indicator, KPI Key Performance Indicator) and chosen
War value, divides less than a reference value, between a reference value and challenging value, higher than the class of challenging value three to give a mark, draws KPI index scores
f(x)：
(x is corresponding K PI desired values, the challenging value of max, min correspondence index, a reference value)
Evaluation index score f (z), by being drawn to each autocorrelative KPI indexs score weighted average calculation：
(in formula：F (x) is each KPI indexs score,For KPI index weight coefficients, n is correlation KPI indexs sum)
Each evaluates score f (m), by showing that specific algorithm is as follows to relevant evaluation index score weighted average calculation：
F (m)=∑ (f (z) i* β i)/n
(in formula：F (z) is each evaluation index score, and β i are evaluation index weight coefficient, and n is that relevant evaluation index is total
Number).
The information such as a reference value, challenging value, weight coefficient in above-mentioned formula are determined using expert judging method, expert evaluation
Method is to provide weighted value to each index importance by expert group.
Above-mentioned embodiment is only the specific case of the present invention, and scope of patent protection of the invention includes but is not limited to
Above-mentioned embodiment, any person of an ordinary skill in the technical field that meet claims of the present invention and any
The appropriate change or replacement done to it, should all fall into the scope of patent protection of the present invention.
Claims (10)
1. a kind of network operation condition predicting model based on big data, it is characterised in that based on Network Management Equipment data, draw
Enter subscriber signaling data, MR data, complaint data and the survey data of magnanimity, the network that two layers of three domains of the proposition based on big data
Operating analysis forecast model architectural framework, using the MPP distributed data processings of current main-stream, based on data mining technology
In regression forecasting algorithm, realize network operation status analysis predict；
Network operation analysis prediction mould is from network O＆M domain, service application domain, three, network security domain dimensional analysis, each
Dimension is deployed from network, two aspects of user.
2. a kind of network operation condition predicting model based on big data according to claim 1, it is characterised in that the net
The enabling capabilities of telecom operators' basic network are mainly assessed in network O＆M domain, are commented by first class index network O＆M score
Valency.
3. a kind of network operation condition predicting model based on big data according to claim 2, it is characterised in that by one-level
Index further decomposites that resource is reasonable, the network coverage is good, network quality is excellent, strong four two-level index of O＆M ability；Network covers
, easily access two user class indexs strong with signal are covered to exist and associate；Network quality it is excellent with do not go offline, noiseless two user classes
There is association in index.
4. a kind of network operation condition predicting model based on big data according to claim 1, it is characterised in that the industry
Business application domain mainly assesses the own and value-added service service ability that telecom operators can provide the user, by first class index industry
Business is evaluated using score, supports single business to assess.
5. a kind of network operation condition predicting model based on big data according to claim 4, it is characterised in that by one-level
Index further decomposite resource occupation rationally, using perceiving, without in violation of rules and regulations, high four two-level index of value；Using perceiving
With easily accessing, time delay is low, the reasonable three user class indexs presence of flow is associated.
6. a kind of network operation condition predicting model based on big data according to claim 1, it is characterised in that the net
Network security domain is used to evaluate the security protection ability that telecom operators provide in itself for mobile subscriber, network, by first class index
Network security score is evaluated.
7. a kind of network operation condition predicting model based on big data according to claim 6, it is characterised in that by one-level
Index further decomposites terminal security, network security, three two-level index of content safety；Terminal security with without trojan horse,
It is as good as normal flow binomial user class index and there is association；Content safety is with information completely, without two user class indexs of violation content
In the presence of association.
8. a kind of network operation condition predicting model based on big data according to claim 7, it is characterised in that for every
Item KPI setup measures a reference value and challenging value, divide less than a reference value, between a reference value and challenging value, higher than challenging value three
Class is given a mark, and draws KPI index score f (x)：
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X is corresponding K PI desired values, the challenging value of max, min correspondence index, a reference value.
9. a kind of network operation condition predicting model based on big data according to claim 8, it is characterised in that evaluation refers to
F (z) must be divided into by marking, by being drawn to each autocorrelative KPI indexs score weighted average calculation：
In formula：F (x) is each KPI indexs score,For KPI index weight coefficients, n is correlation KPI indexs sum.
10. a kind of network operation condition predicting model based on big data according to claim 9, it is characterised in that each
F (m) must be divided into by evaluating, by showing that specific algorithm is as follows to relevant evaluation index score weighted average calculation：
F (m)=∑ (f (z) i* β i)/n,
In formula：F (z) is each evaluation index score, and β i are evaluation index weight coefficient, and n is relevant evaluation index sum.
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Cited By (8)
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| CN107733693A (en) * | 2017-09-22 | 2018-02-23 | 中国人民解放军国防科技大学 | Network security operation and maintenance capability evaluation method and system based on security event statistics |
| CN107888418A (en) * | 2017-11-14 | 2018-04-06 | 国网河南省电力公司信息通信公司 | Electric power various dimensions distribution adapted telecommunication network-building method based on big data technology |
| CN109377252A (en) * | 2018-08-30 | 2019-02-22 | 广州崇业网络科技有限公司 | A kind of customer satisfaction prediction technique based on big data frame |
| CN111083710A (en) * | 2019-12-20 | 2020-04-28 | 大唐网络有限公司 | Intelligent networking method for 5G system |
| CN111242171A (en) * | 2019-12-31 | 2020-06-05 | 中移（杭州）信息技术有限公司 | Model training, diagnosis and prediction method and device for network fault and electronic equipment |
| CN112235035A (en) * | 2020-10-08 | 2021-01-15 | 军事科学院系统工程研究院网络信息研究所 | Spatial information network networking method based on distributed constellation |
| CN112996015A (en) * | 2019-12-18 | 2021-06-18 | 中国移动通信集团河南有限公司 | Index association relationship construction method and device |
| CN114599042A (en) * | 2022-03-04 | 2022-06-07 | 清华大学 | Network state sensing method and device, electronic equipment and storage medium |
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| CN107733693A (en) * | 2017-09-22 | 2018-02-23 | 中国人民解放军国防科技大学 | Network security operation and maintenance capability evaluation method and system based on security event statistics |
| CN107888418A (en) * | 2017-11-14 | 2018-04-06 | 国网河南省电力公司信息通信公司 | Electric power various dimensions distribution adapted telecommunication network-building method based on big data technology |
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| CN111242171A (en) * | 2019-12-31 | 2020-06-05 | 中移（杭州）信息技术有限公司 | Model training, diagnosis and prediction method and device for network fault and electronic equipment |
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| CN112235035A (en) * | 2020-10-08 | 2021-01-15 | 军事科学院系统工程研究院网络信息研究所 | Spatial information network networking method based on distributed constellation |
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