CN104320795A - Evaluation method for health degree of multidimensional wireless network - Google Patents
Evaluation method for health degree of multidimensional wireless network Download PDFInfo
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- CN104320795A CN104320795A CN201410550458.4A CN201410550458A CN104320795A CN 104320795 A CN104320795 A CN 104320795A CN 201410550458 A CN201410550458 A CN 201410550458A CN 104320795 A CN104320795 A CN 104320795A
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- 238000004891 communication Methods 0.000 claims description 4
- 238000012545 processing Methods 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims 3
- 238000005259 measurement Methods 0.000 claims 2
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
- H04W24/02—Arrangements for optimising operational condition
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
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Abstract
The invention discloses an evaluation method for health degree of multidimensional wireless network, the method comprises the steps as follows: confirming the dimension impacting health degree of the current wireless network in each classified source data through Hadoop, and the index parameter being corresponding to each dimension, combining the dimension and index parameter of the dimension for building the evaluation algorithm model of multidimensional health degree, comparing the obtained synthesis score to obtain the health state of wireless network and storing the health state of wireless network in the result list of the vertica database. The administrator and optimization personnel can conveniently and effectively master the network health state meeting the development trend of the current wireless network.
Description
Technical field
The invention belongs to mobile communication network technology field, more specifically say, relate to a kind of wireless network health degree appraisal procedure of various dimensions.
Background technology
Along with the development of the communication technology and the aggravation of market competition, telecom operators enter a competition more fierce epoch, and for operator, the quality of network service, directly can have influence on user to the perception of service and evaluation.In order to increase customer satisfaction degree; operator usually can on the basis of day regular data; set up some Key Performance Indicators (Key Performance Indicators; be called for short KPI); be used for the quality of the quality of Sampling network performance, evaluating network quality, critic network service, to promote service better.
After wireless network puts into effect, how assessing network running quality, is the content that Virtual network operators are concerned about very much." will improve it, first will measure it, measure it, just first must quantize it ", therefore must have one group of wireless network performance index quantized, this is all very important to the assessment of network performance and the network optimization in the future.
The main KPI of tradition reflection wireless network situation, can be divided into following a few class: cover class, as coverage rate; Switch class, as handover success rate between RNC soft handover success rate, C/S system etc.; Capacity class, as CS territory telephone traffic, PS territory flow, cell carrier frequencies uplink load etc.; Resource utilization class, as Chao Mang community ratio, Chao Xian community ratio etc.; Quality of service class, as RRC link is created as power, wireless interface passband, wireless drop call rate etc.Wherein, each classification, each dimension are independently, calculate separately often, separately reflection network problem in a certain respect.This mode cannot the holistic health situation of awareness network, and administrative staff intuitively can not check network health situation from GIS.
Summary of the invention
The object of the invention is to overcome the deficiencies in the prior art, a kind of wireless network health degree appraisal procedure of various dimensions is provided, mathematical modeling and assessment is carried out from multiple dimensions such as covering, capacity, performance, parameter, customer complaints, thus obtain wireless network health degree score, be conducive to manager and optimization personnel convenient, efficient grasp network health situation like this.
For achieving the above object, the wireless network health degree appraisal procedure of a kind of various dimensions of the present invention, is characterized in that, comprise the following steps:
(1), Hadoop gathers source data from bottom data source;
(2), Hadoop classifies by dimension to source data, divides the source data of same dimension into a class;
(3), Hadoop determines the dimension affecting active wireless network health degree from each classification source data, and index parameter corresponding under each dimension;
(4), Hadoop calculates each index parameter value under each dimension respectively, find between default Index areas according to index parameter value, calculate the score between Index areas corresponding to index parameter value, then the score between the index parameter value calculated, corresponding Index areas and between corresponding Index areas is existed in vertica database together;
(5), according to the weight information preset in Hadoop, the weighted value of each index parameter under each dimension and this dimension is got;
(6), in Hadoop, set up the evaluation algorithms model of various dimensions health degree, utilize this model to assess wireless network health degree, then by assessment result stored in vertica database;
(7), the geographical processing server of ArcGis by vertica database stored in Area generation picture corresponding to wireless communication status, then picture is presented by the mode superposed by geographical position coordinates on map.
Goal of the invention of the present invention is achieved in that
The wireless network health degree appraisal procedure of various dimensions of the present invention, in each classification source data, the dimension affecting active wireless network health degree is determined by Hadoop, and corresponding index parameter under each dimension, the evaluation algorithms model of various dimensions health degree is set up again in conjunction with the parameter index of these dimensions and dimension, this model is utilized to assess wireless network health degree, obtain the integrate score of active wireless network health degree, finally, the integrate score obtained is compared, obtains the health status of wireless network and be deposited in the result table of vertica database.Be conducive to manager and optimization personnel convenient, efficient grasp network health situation like this, meet the trend of active wireless network development.
Meanwhile, the wireless network health degree appraisal procedure of various dimensions of the present invention also has following beneficial effect:
(1) value is divided by index parameter
By quantizing between Index areas, being given different score values between the Index areas that difference is quantized, the mark of index parameter can be calculated, and then obtain the mark of the whole network health degree, make manager grasp current network health condition more intuitively;
(2) the whole network health degree situation can be checked
Originally single network KPI index, by setting up suitable Mathematical Modeling, is carried out comprehensively, and then is obtained the whole network health degree situation by the present invention;
(3), have employed the system of Hadoop system and columnar database vertica technological incorporation
Hadoop system is adopted to carry out the process computing of mass data in the present invention, overcome traditional data operation mode based on database: require that data once load rear computing, cannot meet and requirement is gathered to real time mass data, and the shortcoming that operating cost is high, and the present invention will treat that the mass data real-time loading of computing enters Hadoop platform, big data quantity, computing requirement that real-time is high can be met; Secondly, adopt columnar database vertica to carry out storage and the inquiry of mass data, during such data query, Vertica only need obtain the row of needs, instead of is selected all data of row, its average behavior can improve 50x-1000x doubly; Meanwhile, columnar database itself supports complete SQL specification, is conducive to the development and maintenance of applying.
Accompanying drawing explanation
Fig. 1 is the flow chart of the wireless network health degree appraisal procedure of various dimensions of the present invention;
Fig. 2 is the integrate score statistical chart of wireless network health degree;
Fig. 3 is that the geographical processing server of ArcGis presents design sketch to the wireless network health degree in region;
Table 1 is source data classification chart;
Table 2 is desired value score statistical forms;
Table 3 is that weight information arranges table.
Embodiment
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described, so that those skilled in the art understands the present invention better.Requiring particular attention is that, in the following description, when perhaps the detailed description of known function and design can desalinate main contents of the present invention, these are described in and will be left in the basket here.
Embodiment
Fig. 1 is the flow chart of the wireless network health degree appraisal procedure of various dimensions of the present invention.
In the present embodiment, as shown in Figure 1, the wireless network health degree appraisal procedure of a kind of various dimensions of the present invention, is characterized in that, comprise the following steps:
T1), Hadoop gathers source data from bottom data source;
In the present embodiment, Hadoop is from base station controller (BSC, Base Station Controller), operation maintenance center (OMC, Operationand Maintenance Center), mobile switching centre (MSC, Mobile Switching Center), Call Detail Trace system (CDT, Call Detail Trace) etc. gathers source data in bottom data source;
T2), Hadoop classifies by dimension to source data, divides the source data of same dimension into a class;
The source data collected is classified according to dimensions such as covering, performance, parameter, capacity, complaints by Hadoop, as shown in table 1;
Table 1
T3), Hadoop determines the dimension affecting active wireless network health degree from each classification source data, and index parameter corresponding under each dimension; As shown in table 1, the dimension affecting active wireless network health degree has: covering, performance, parameter, capacity, complaint; To complain dimension, its index parameter has again: voice ten thousand people's the rate of complaints and data ten thousand people the rate of complaints;
T4), Hadoop calculates each index parameter value under each dimension respectively, find between default Index areas according to index parameter value, calculate the score between Index areas corresponding to index parameter value, then the score between the index parameter value calculated, corresponding Index areas and between corresponding Index areas is existed in vertica database together;
Table 2
In the present embodiment, to cover dimension, the desired value crossing covering grid ratio covered in dimension is 20%, finds " >=20%and<15% " between default Index areas, calculates the score 70 corresponding to index parameter value between Index areas;
T5), according to the weight information preset in Hadoop, the weighted value of each index parameter under each dimension and this dimension is got; In the present embodiment, the weight information preset in Hadoop is as shown in table 3, lists the weight information of partial dimensional and corresponding index parameter in this table;
Table 3
T6), in Hadoop, set up the evaluation algorithms model of various dimensions health degree, utilize this model to assess wireless network health degree;
T6.1) wireless network health degree scoring algorithm model, is set up
Y
j=Z; Z=Z
1, Z
2..., Z
k; (work as a
1≤ evaluation index≤b
1time, Z=Z
1; Work as a
2≤ evaluation index≤b
2time, Z=Z
2; Work as a
k≤ evaluation index≤b
ktime, Z=Z
k; )
Wherein, n represents the number of dimension; X
irepresent the score of i-th dimension, K
irepresent the weight coefficient of i-th dimension; M represents the index parameter number in single dimension; Y
jrepresent the score of a jth index, T
jrepresent the weight coefficient of a jth index; a
1~ a
k, b
1~ b
kbetween the Index areas that expression is preset;
T6.2), wireless network health degree is assessed
As shown in Figure 2, the indices parameter of collection is sent to various dimensions health degree evaluation algorithms model to calculate, obtain the network health degree integrate score δ of active wireless network, as δ >=C, the state of active wireless network is healthy, as δ <C, the state of active wireless network is fault, and wherein, C is constant, represent the healthy threshold values of wireless network, finally again by the scores of assessment and map network state stored in vertica database;
In the present embodiment, threshold values C is set to 80 points, and the wireless network health degree calculating a certain area is 90 points, then illustrate that the wireless communication status of this area is for healthy
T7), ArcGis geography process service by vertica database stored in the Area generation picture corresponding without network state, mark out the latitude and longitude coordinates of picture, picture is presented by the mode superposed by geographical position coordinates on map again, as shown in Figure 3, the panel board in the upper right corner, illustrates the score calculated by method of the present invention, wherein, " comprehensively " panel board, display be the network health degree integrate score calculated by various dimensions; And " capacity ", " quality ", " complaint " panel board are each subitem score.What block diagram was shown is the score of regional, and the selection in region can be undertaken by the GIS map on the left side.Score trend line graph in the lower right corner of GIS map, the actual score of wireless network in viewable regions, as the average of 7 days, the average of the average of 15 days and 30 days; The upper left corner of GIS map, can select 1X networking, DO network or network synthesis situation.
Although be described the illustrative embodiment of the present invention above; so that those skilled in the art understand the present invention; but should be clear; the invention is not restricted to the scope of embodiment; to those skilled in the art; as long as various change to limit and in the spirit and scope of the present invention determined, these changes are apparent, and all innovation and creation utilizing the present invention to conceive are all at the row of protection in appended claim.
Claims (4)
1. a wireless network health degree appraisal procedure for various dimensions, is characterized in that, comprise the following steps:
(1), Hadoop gathers source data from bottom data source;
(2), Hadoop classifies by dimension to source data, divides the source data of same dimension into a class;
(3), Hadoop determines the dimension affecting active wireless network health degree from each classification source data, and index parameter corresponding under each dimension;
(4), Hadoop calculates each index parameter value under each dimension respectively, find between default Index areas according to index parameter value, calculate the score between Index areas corresponding to index parameter value, then the score between the index parameter value calculated, corresponding Index areas and between corresponding Index areas is existed in vertica database together;
(5), according to the weight information preset in Hadoop, the weighted value of each index parameter under each dimension and this dimension is got;
(6), in Hadoop, set up the evaluation algorithms model of various dimensions health degree, utilize this model to assess wireless network health degree, then by assessment result stored in vertica database;
(7), the geographical processing server of ArcGis by vertica database stored in Area generation picture corresponding to wireless communication status, then picture is presented by the mode superposed by geographical position coordinates on map.
2. the wireless network health degree appraisal procedure of various dimensions according to claim 1, it is characterized in that, described bottom data source comprises: base station controller (BSC, Base Station Controller), operation maintenance center (OMC, Operationand Maintenance Center), mobile switching centre (MSC, Mobile Switching Center), Call Detail Trace system (CDT, Call Detail Trace), driver test system (DT, Drive Test), point examining system (CQT, CALL QUALITY TEST), LTE measurement report (LTE MR, LET Measurement Report) etc.
3. the wireless network health degree appraisal procedure of various dimensions according to claim 1, it is characterized in that, described dimension comprises: covering, performance, parameter, capacity, complaint etc.
4. the wireless network health degree appraisal procedure of various dimensions according to claim 1, is characterized in that, the evaluation algorithms model of described various dimensions health degree to the method that wireless network health degree is assessed is:
S1) wireless network health degree scoring algorithm model, is set up
Y
j=Z; Z=Z
1, Z
2..., Z
k; (work as a
1≤ evaluation index≤b
1time, Z=Z
1; Work as a
2≤ evaluation index≤b
2time, Z=Z
2; Work as a
k≤ evaluation index≤b
ktime, Z=Z
k; )
Wherein, n represents the number of dimension; X
irepresent the score of i-th dimension, K
irepresent the weight coefficient of i-th dimension; M represents the index parameter number in single dimension; Y
jrepresent the score of a jth index, T
jrepresent the weight coefficient of a jth index; a
1~ a
k, b
1~ b
kbetween the Index areas that expression is preset;
S2), wireless network health degree is assessed
The indices parameter of collection is sent to various dimensions health degree evaluation algorithms model to calculate, obtain the network health degree integrate score δ of active wireless network, as δ >=C, the state of active wireless network is healthy, as δ <C, the state of active wireless network is fault, wherein, C is constant, represents the healthy threshold values of wireless network.
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| CN105959965A (en) * | 2016-07-16 | 2016-09-21 | 王晓刚 | Wireless mobile network analysis method and apparatus |
| WO2016206241A1 (en) * | 2015-06-25 | 2016-12-29 | 中兴通讯股份有限公司 | Data analysis method and apparatus |
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| CN112203166B (en) * | 2020-09-09 | 2023-03-14 | 中盈优创资讯科技有限公司 | Multi-model user health record scoring method and device |
| CN111901814A (en) * | 2020-09-11 | 2020-11-06 | 中国联合网络通信集团有限公司 | Wireless network health assessment method and device, electronic equipment and storage medium |
| CN111901814B (en) * | 2020-09-11 | 2022-07-26 | 中国联合网络通信集团有限公司 | Wireless network health assessment method and device, electronic equipment and storage medium |
| CN112565007A (en) * | 2020-11-27 | 2021-03-26 | 中盈优创资讯科技有限公司 | System health degree evaluation method and device |
| CN112601245A (en) * | 2020-12-03 | 2021-04-02 | ***通信集团内蒙古有限公司 | Method and device for evaluating utilization condition of capacity resources in long-term evolution area |
| CN112601245B (en) * | 2020-12-03 | 2023-04-07 | ***通信集团内蒙古有限公司 | Method and device for evaluating utilization condition of capacity resources in long-term evolution area |
| CN113904956A (en) * | 2021-10-29 | 2022-01-07 | 新华三大数据技术有限公司 | Network health degree detection method and device, electronic equipment and storage medium |
| CN113904956B (en) * | 2021-10-29 | 2023-04-25 | 新华三大数据技术有限公司 | Network health degree detection method and device, electronic equipment and storage medium |
| CN114911683A (en) * | 2022-06-21 | 2022-08-16 | 北京同创永益科技发展有限公司 | Evaluation method for health degree of Kubernetes platform |
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