CN110659832A - Method and equipment for detecting health degree of 5G network element - Google Patents
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Abstract
The application relates to a method and equipment for detecting health degree of a 5G network element. One embodiment of the present application describes a method for detecting health of a 5G network element, which includes: setting one or more dimensions and one or more corresponding dimension weights thereof, wherein each dimension of the one or more dimensions comprises one or more health indicators; setting one or more index weights corresponding to the one or more health indexes in each dimension; obtaining a score of each health degree index based on a preset score standard; respectively weighting the one or more health indicators in each dimension by using the corresponding one or more indicator weights, and setting the weighted sum of scores as the score of the corresponding dimension; weighting the scores of the corresponding dimensions respectively by using the corresponding one or more dimension weights, and setting the weighted sum of the scores as a health score; and determining the health degree of the 5G network element according to the health degree score.
Description
Technical Field
The present application relates to the field of communications technologies, and in particular, to a method and a device for detecting a health degree of a 5G network element.
Background
More network elements and interfaces are introduced into the 5G network, and correspondingly, more management objects (entities and interfaces), performance indexes, fault types, service flows, fault points and the like are introduced. In the face of more and more network elements, how to safely and effectively carry out intelligent operation and maintenance on the network elements becomes particularly important.
The traditional method is mainly limited to diagnosing a single index, such as the CPU utilization rate, and the push performance of a virtual machine or a physical machine is reported, and when the CPU utilization rate is detected to exceed a preset threshold rule, the push performance of an upper application is reported. In the prior art, only the health status of a single index of a network element is involved, and the overall conditions of the network element, such as the network performance of a virtual machine, the service perception capability and the like, cannot be reflected, and the health status of the network element is generally formed by freely combining and converting a plurality of indexes. That is, the prior art cannot flexibly set the index weight to observe the health of the network element under multiple dimensions.
Therefore, a new method and apparatus for detecting the health of a 5G network element is needed.
Disclosure of Invention
One embodiment of the present application discloses: a method of detecting health of a 5G network element, comprising: setting one or more dimensions and one or more corresponding dimension weights thereof, wherein each dimension of the one or more dimensions comprises one or more health indicators; setting one or more index weights corresponding to the one or more health indexes in each dimension; scoring each of the one or more health indicators in the each dimension based on a preset scoring criterion to obtain a score for the each health indicator; respectively weighting the one or more health indicators in each dimension by using the corresponding one or more indicator weights, and setting the weighted sum of scores as the score of the corresponding dimension; weighting scores of corresponding dimensions in the one or more dimensions respectively by using the corresponding one or more dimension weights, and setting the weighted sum of the scores as a health score; and determining the health degree of the 5G network element according to the health degree score.
Another embodiment of the present application discloses: an apparatus for detecting health of a 5G network element, comprising: a memory configured to store instructions; and a processor configured to execute instructions stored in the memory, the instructions causing the processor to: setting one or more dimensions and one or more corresponding dimension weights thereof, wherein each dimension of the one or more dimensions comprises one or more health indicators; setting one or more index weights corresponding to the one or more health indexes in each dimension; scoring each of the one or more health indicators in the each dimension based on a preset scoring criterion to obtain a score for the each health indicator; respectively weighting the one or more health indicators in each dimension by using the corresponding one or more indicator weights, and setting the weighted sum of scores as the score of the corresponding dimension; weighting scores of corresponding dimensions in the one or more dimensions respectively by using the corresponding one or more dimension weights, and setting the weighted sum of the scores as a health score; and determining the health degree of the 5G network element according to the health degree score.
Drawings
Fig. 1 illustrates a relational database model that may be used for all network element health assessments in some embodiments according to the present application.
Fig. 2 illustrates an all-network-element health assessment configuration management interface for displaying all network element configurations in some embodiments according to the present application.
Fig. 3 illustrates an index configuration included in a single dimension of a single network element health assessment for flexible configuration of indexes, weights, etc., in some embodiments according to the application.
Fig. 4 illustrates an overall configuration of a single network element health assessment for adjusting dimensions, weights, metrics, etc., in some embodiments according to the application.
Detailed Description
In order to solve the above technical problem, the present application provides a method and an apparatus for detecting the health degree of a 5G network element. The method mainly reflects the operation state of multi-maintenance of the network element indexes in real time through the health degree analysis result, and the auxiliary monitoring platform responds in time according to the result.
Fig. 1 illustrates a relational database model that may be used for all network element health assessments in some embodiments according to the present application, such as: oracle, mysql, etc.
According to the method of the application, a model is added, for example: and (5) a low-delay business health degree evaluation model. For the model, known index information needs to be input into the index model.
Fig. 2 illustrates an all-network-element health assessment configuration management interface for displaying all network element configurations in some embodiments according to the present application.
Evaluation dimensions included in the low-latency service health evaluation model and corresponding dimension weights thereof, such as service awareness, network quality, complaint handling, and failure handling, are shown in fig. 2. The present application does not limit the content and number of evaluation dimensions. That is, the low-latency traffic health assessment model may include one or more of the above assessment dimensions, as well as other assessment dimensions. For the evaluation dimensions, the weight a, the dimension score m, the health degree score formula and the health degree label formula of the dimensions are respectively set. These parameters can be modified according to actual requirements.
Fig. 3 illustrates an index configuration included in a single dimension of a single network element health assessment for flexible configuration of indexes, weights, etc., in some embodiments according to the application. In particular, fig. 3 relates to the health indicators included in the service awareness assessment dimension, which include one or more of end-to-end (E2E) delay, uplink rate, downlink rate, packet loss rate, number of connections, and delay jitter. For these health degree indexes, a management dimension, an index unit, an excellent value B1, a bid value B2, a score criterion N, and a weight are set. The content and number of the health indicators are not limited in the present application. That is, the business awareness assessment dimension may include one or more of the above health indicators, as well as other health indicators. The management dimension, index unit, excellent value B1, reach value B2, score standard N and weight of the health index can be modified according to actual requirements.
Fig. 4 illustrates an overall configuration of a single network element health assessment for adjusting dimensions, weights, metrics, etc., in some embodiments according to the application. Specifically, the setting and modification of parameters in the low-latency business health assessment model are shown in fig. 4.
According to the method of the application, firstly, based on the database model shown in fig. 1, a new model is added: for example: and (5) a low-delay business health degree evaluation model.
Next, based on fig. 4, add an evaluation dimension of the low-latency business health evaluation model: for example: and (4) service perception, and setting the weight of the evaluation dimension service perception to calculate a single evaluation dimension score.
Then, as shown in fig. three, indexes included in the evaluation dimension service awareness, such as indexes of uplink rate, connection number, and the like, are added, and an excellent value B1 and a standard value B2 are set. For example, the excellent value B1 of the delay of E2E is set to 10ms, and the standard value B2 is set to 15 ms.
Assuming that the actual delay is represented by B, the score criterion is:
if B ≧ B1, then N ≧ 100
-if B2< B ≦ B1, then N ═ 60+ (B-B2)/(B1-B2) × 40
-if B ≦ B2, then N ≦ B/B2 × 60
According to the weight of the E2E time delay index, 50%, obtaining the score of the health index E2E after time delay weighting
N＝N×50％
Obtaining a total score M of a single network element according to each dimension weight:
M＝30％×m1+30％×m2+20％×m3+20％×m4
where m1 is the traffic awareness dimension score, m2 is the network quality dimension score, m3 is the complaint handling dimension score, and m4 is the failure handling dimension score. m1, m2, m3, and m4 are each a sum of a plurality of health indicator scores N weighted.
In one embodiment, the present application describes a method for detecting health of a 5G network element, which includes:
four evaluation dimensions are set: service awareness, network quality, complaint handling, and failure handling, and their corresponding dimensional weights, the weights in this application are 30%, 20%, and 20%, respectively. Each of these four dimensions includes one or more health indicators.
Then, one or more index weights corresponding to the one or more health indexes in each dimension are set, for example, the health indexes in the service perception of the evaluation dimension and the weights thereof are set as disclosed in fig. 3.
Based on preset scoring criteria, for example: the score criterion M in fig. 3 scores each fitness indicator in the evaluation dimension business perception to obtain a score for said each fitness indicator.
The indexes of health are weighted respectively by using the index weights in the rightmost column of the table in fig. 3, and the sum of the weighted scores is set as a score m1 for evaluating the dimension business perception.
Weighting the scores of the corresponding dimensions respectively by using the dimension weights, and setting the sum of the weighted scores as a health degree score M; and determining the health degree of the 5G network element according to the health degree score M.
For example, the score M is greater than or equal to 90, the health degree is excellent, the score is greater than or equal to 80 and less than 90, the health degree is good, the score is greater than or equal to 70 and less than 80, the health degree is medium.
The method can self-define the multi-dimensional evaluation network element health degree, digitalizes the index score and the dimension score, and is more reasonable and comprehensive in judgment of the health degree compared with the method of only setting a single index threshold in the prior art. The user can set the index weight or the dimension weight which needs to pay special attention higher, thereby classifying the health degree of the network element by the grade of the Service-Level agent (SLA).
In some embodiments, an apparatus to detect 5G network element health may perform various operations based on computer-executable instructions provided via memory components, registers, and the like. The memory component or storage may be any suitable article of manufacture that may act as a medium for storing processor executable code, data, or the like. These articles of manufacture may represent computer-readable media (i.e., any suitable form of memory storage device) that may store processor-executable code for use by display control apparatuses and detection devices to perform the presently disclosed techniques. Memory and storage devices may also be used to store data, data analysis, and the like. The memory and storage may represent non-transitory computer-readable media (i.e., any suitable form of memory or storage) that may store processor-executable code used by the display and detection devices to perform the various techniques described herein. It should be noted that non-transitory merely indicates that the medium is tangible and not a signal.
While the embodiments described herein are susceptible to various modifications and alternative forms, specific embodiments have been shown by way of example in the drawings and have been described in detail herein. The invention is not intended to be limited to the particular forms disclosed. The intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. A method of detecting health of a 5G network element, comprising:
setting one or more dimensions and one or more corresponding dimension weights thereof, wherein each dimension of the one or more dimensions comprises one or more health indicators;
setting one or more index weights corresponding to the one or more health indexes in each dimension;
scoring each of the one or more health indicators in the each dimension based on a preset scoring criterion to obtain a score for the each health indicator;
respectively weighting the one or more health indicators in each dimension by using the corresponding one or more indicator weights, and setting the weighted sum of scores as the score of the corresponding dimension;
weighting scores of corresponding dimensions in the one or more dimensions respectively by using the corresponding one or more dimension weights, and setting the weighted sum of the scores as a health score; and
and determining the health degree of the 5G network element according to the health degree score.
2. The method of claim 1, wherein the one or more dimensions include one or more of traffic awareness, network quality, complaint handling, and failure handling.
3. The method of claim 2, wherein the traffic awareness comprises one or more of end-to-end (E2E) latency, uplink rate, downlink rate, packet loss rate, number of connections, and latency jitter.
4. An apparatus for detecting health of a 5G network element, comprising:
a memory configured to store instructions; and
a processor configured to execute instructions stored in the memory, the instructions causing the processor to:
setting one or more dimensions and one or more corresponding dimension weights thereof, wherein each dimension of the one or more dimensions comprises one or more health indicators;
setting one or more index weights corresponding to the one or more health indexes in each dimension;
scoring each of the one or more health indicators in the each dimension based on a preset scoring criterion to obtain a score for the each health indicator;
respectively weighting the one or more health indicators in each dimension by using the corresponding one or more indicator weights, and setting the weighted sum of scores as the score of the corresponding dimension;
weighting scores of corresponding dimensions in the one or more dimensions respectively by using the corresponding one or more dimension weights, and setting the weighted sum of the scores as a health score; and
and determining the health degree of the 5G network element according to the health degree score.
5. The method of claim 4, wherein the one or more dimensions include one or more of traffic awareness, network quality, complaint handling, and failure handling.
6. The method of claim 5, wherein traffic awareness comprises one or more of end-to-end (E2E) latency, uplink rate, downlink rate, packet loss rate, number of connections, and latency jitter.
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| CN113541982A (en) * | 2020-04-14 | 2021-10-22 | 中国移动通信集团浙江有限公司 | Network element health early warning method and device, computing equipment and computer storage medium |
| CN116132278A (en) * | 2022-10-08 | 2023-05-16 | 中电信数智科技有限公司 | Health evaluation method and device based on 5GC network element |
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