CN112269801B - Asset information acquisition method, device, equipment and readable storage medium - Google Patents
Asset information acquisition method, device, equipment and readable storage medium Download PDFInfo
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/24569—Query processing with adaptation to specific hardware, e.g. adapted for using GPUs or SSDs
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/22—Detection or location of defective computer hardware by testing during standby operation or during idle time, e.g. start-up testing
- G06F11/2247—Verification or detection of system hardware configuration
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2458—Special types of queries, e.g. statistical queries, fuzzy queries or distributed queries
- G06F16/2471—Distributed queries
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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
- H04L41/02—Standardisation; Integration
- H04L41/0213—Standardised network management protocols, e.g. simple network management protocol [SNMP]
Abstract
The invention discloses an asset information acquisition method, which considers that the adaptive plug-ins for carrying out data communication with a server among some approximate models can be universal, so that in the application, after a model library is determined and the similarity with the target model information of a target server is highest, the model library can be used as the approximate model of the target server, then the adaptive plug-ins of the approximate model can be utilized to directly acquire the asset information of the target server, and as the application is applied to a processor, a worker does not need to manually acquire the asset information, the acquisition of the asset information can be rapidly carried out on brand-new models, and the working efficiency is greatly improved. The invention also discloses an asset information acquisition device, equipment and a computer readable storage medium, which have the same beneficial effects as the asset information acquisition method.
Description
Technical Field
The present invention relates to the field of server management technologies, and in particular, to an asset information acquisition method, and an asset information acquisition device, apparatus, and computer readable storage medium.
Background
In order to better manage the servers in the local area network, the server management platform can acquire asset information of the servers newly accessed to the local area network, but when the model of the newly accessed servers is a brand new model, the asset information of the servers cannot be acquired rapidly and efficiently in the prior art, even a worker is required to acquire the asset information manually, and the working efficiency is low.
Therefore, how to provide a solution to the above technical problem is a problem that a person skilled in the art needs to solve at present.
Disclosure of Invention
The invention aims to provide an asset information acquisition method, which does not need staff to manually acquire asset information, can rapidly acquire asset information of brand new models, and greatly improves the working efficiency; another object of the present invention is to provide an asset information acquiring apparatus, device, and computer readable storage medium, which can quickly acquire asset information of a brand new model without manually acquiring asset information by a worker, thereby greatly improving work efficiency.
In order to solve the above technical problems, the present invention provides an asset information acquisition method, applied to a processor, including:
acquiring target model characteristic information of a target server;
determining the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library by adopting a preset similarity algorithm;
taking the model of the server in the model base corresponding to the highest similarity as the approximate model of the target server;
and acquiring asset information of the target server by using the adapting plug-in of the approximate model.
Preferably, after the obtaining the target model feature information of the target server, before the adopting a preset similarity algorithm to determine the similarity between the target model feature information and model feature information of various servers pre-stored in a model base, the asset information obtaining method further includes:
judging whether the model of the target server is an existing model in a model library according to the target model characteristic information;
if yes, acquiring an adaptive plug-in corresponding to the actual model of the target server;
acquiring asset information of the target server by utilizing an adaptation plug-in corresponding to the actual model of the target server;
if not, executing the step of determining the similarity between the target model characteristic information and the model characteristic information of various servers prestored in the model library by adopting a preset similarity algorithm.
Preferably, the obtaining the target model feature information of the target server specifically includes:
scanning based on a scanning protocol of a preset type to obtain target model characteristic information of a target server;
the preset type of scanning protocol is specifically any one of simple network management protocol SNMP, intelligent platform management interface IPMI, storage management plan specification SMIS and secure shell protocol SSH.
Preferably, the determining, by using a preset similarity algorithm, the similarity between the target model feature information and model feature information of various servers pre-stored in a model library specifically includes:
and taking the ratio of the number of the same parameters to the total number of all the parameters as the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library.
Preferably, the target model feature information and the model feature information are the same and each include a manufacturer, a model, and a version.
Preferably, the adapting plug-in unit is specifically an adapting interface of a data communication interface and a data communication protocol of a server encapsulated with a corresponding model.
Preferably, the obtaining the target model feature information of the target server specifically includes:
responding to a server scanning instruction, scanning a newly accessed server in the local area network and taking the newly accessed server as a target server;
acquiring target model characteristic information of a target server;
the server scanning instruction is a server scanning instruction received through a man-machine interaction device or a periodically generated server scanning instruction.
In order to solve the technical problem, the present invention further provides an asset information acquisition device, which is applied to a processor and includes:
the first acquisition module is used for acquiring the characteristic information of the target machine type of the target server;
the determining module is used for determining the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library by adopting a preset similarity algorithm;
the mapping module is used for taking the model of the server in the model library corresponding to the highest similarity as the approximate model of the target server;
and the second acquisition module is used for acquiring the asset information of the target server by utilizing the adapting plug-in of the similar machine type.
In order to solve the above technical problem, the present invention further provides an asset information acquisition device, including:
a memory for storing a computer program;
a processor for implementing the steps of the asset information acquisition method as claimed in any one of the preceding claims when executing the computer program.
To solve the above technical problem, the present invention further provides a computer readable storage medium, on which a computer program is stored, which when executed by a processor, implements the steps of the asset information obtaining method according to any one of the above.
The invention provides an asset information acquisition method, which considers that the adaptive plug-ins for carrying out data communication with a server among some approximate models can be universal, so that in the application, after a model library is determined and the similarity with the target model information of a target server is highest, the model library can be used as the approximate model of the target server, then the adaptive plug-ins of the approximate model can be utilized to directly acquire the asset information of the target server, and as the application is applied to a processor, a worker does not need to manually acquire the asset information, the acquisition of the asset information can be rapidly carried out on brand-new models, and the working efficiency is greatly improved.
The invention also provides an asset information acquisition device, equipment and a computer readable storage medium, which have the same beneficial effects as the asset information acquisition method.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required in the prior art and the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present invention, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic flow chart of an asset information acquisition method provided by the invention;
FIG. 2 is a schematic diagram of an asset information obtaining apparatus according to the present invention;
fig. 3 is a schematic structural diagram of an asset information obtaining apparatus according to the present invention.
Detailed Description
The core of the invention is to provide an asset information acquisition method, which does not need staff to manually acquire asset information, can rapidly acquire asset information of brand new models, and greatly improves the working efficiency; another core of the present invention is to provide an asset information acquiring apparatus, device and computer readable storage medium, which can quickly acquire asset information of a brand new model without manually acquiring asset information by a worker, thereby greatly improving work efficiency.
For the purpose of making the objects, technical solutions and advantages of the embodiments of the present invention more apparent, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1, fig. 1 is a flow chart of an asset information obtaining method provided by the present invention, where the asset information obtaining method includes:
step S1: acquiring target model characteristic information of a target server;
specifically, in view of the technical problems in the background art and in view of the fact that the adapter plug-ins for performing data communication with the server between some similar models can be commonly used, in the embodiment of the present invention, asset information acquisition on the target server can be attempted by using the adapter plug-ins of similar models to the target server, and in order to acquire a model similar to the target server, model feature information of the target server needs to be analyzed first, so that in the embodiment of the present invention, the model feature information of the target server can be acquired first, so that the similar model matched to the target server can be used in the subsequent step.
The target server in the embodiment of the present invention may refer to a server of an unknown model, which may be of a plurality of types, and the embodiment of the present invention is not limited herein.
Specifically, the model feature information may be used to characterize the model of the target server, and has a close relationship with the adapter plug-in, for example, all servers of a manufacturer may use the same adapter plug-in to acquire asset information, which is not limited herein.
Step S2: determining the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library by adopting a preset similarity algorithm;
specifically, model characteristic information of various servers of the existing model is pre-stored in a model library, and in order to accurately find the approximate model of the target server, the similarity between the model characteristic information of the target server and model characteristic information of various servers pre-stored in the model library can be determined by using a preset similarity algorithm in the embodiment of the invention, so that the similarity can be compared and the approximate model of the target server can be found.
Step S3: taking the model of the server in the model library corresponding to the highest similarity as the approximate model of the target server;
specifically, the characteristic matching degree of the model of the server in the model base corresponding to the highest similarity and the model of the target server is highest, so that the probability that the corresponding adapting plug-in unit can be applied to the target server is also highest.
Of course, although the probability that the adaptation plug-in corresponding to the model of the server in the model library corresponding to the highest similarity can be applied to the target server is highest, there is also a possibility that the adaptation plug-in is not applied to the target server, so that a preset threshold may be set, firstly, the similarity with the value higher than the preset threshold is reserved, then, the operator additionally combines with the manual experience to analyze and judge the approximate model from the reserved similarity, so that the asset information of the target server can be acquired according to the adaptation plug-in of the approximate model later.
Step S4: and acquiring asset information of the target server by using an adapting plug-in of the similar model.
Specifically, in the embodiment of the invention, the determined adapting plug-in of the similar model can be utilized to acquire the asset information of the target server, so that the asset information of the target server can be successfully acquired with high probability.
The invention provides an asset information acquisition method, which considers that the adaptive plug-ins for carrying out data communication with a server among some approximate models can be universal, so that in the application, after a model library is determined and the similarity with the target model information of a target server is highest, the model library can be used as the approximate model of the target server, then the adaptive plug-ins of the approximate model can be utilized to directly acquire the asset information of the target server, and as the application is applied to a processor, a worker does not need to manually acquire the asset information, the acquisition of the asset information can be rapidly carried out on brand-new models, and the working efficiency is greatly improved.
Based on the above embodiments:
as a preferred embodiment, after obtaining the target model feature information of the target server, before determining the similarity between the target model feature information and model feature information of various types of servers pre-stored in the model base by using a preset similarity algorithm, the asset information obtaining method further includes:
judging whether the model of the target server is an existing model in the model library according to the characteristic information of the target model;
if yes, acquiring an adaptive plug-in corresponding to the actual model of the target server;
acquiring asset information of a target server by utilizing an adaptation plug-in corresponding to an actual model of the target server;
if not, executing the step of determining the similarity between the target model characteristic information and the model characteristic information of various servers prestored in the model library by adopting a preset similarity algorithm.
Specifically, in order to enable the method in the embodiment of the invention to be applicable to all target servers newly accessed to the local area network, namely, the method is not limited to acquiring asset information of the target servers with brand-new unknown model, the embodiment of the invention can judge whether the model of the target server is an existing model in the model base according to the characteristic information of the target model, if the model is the existing model, things become very simple, and only the asset information of the target server is required to be acquired according to an adapter model corresponding to the actual model of the target server, thereby further improving the working efficiency.
Specifically, the process of judging whether the model of the target server is the existing model in the model base according to the target model characteristic information may also be to compare the model characteristic information, if the model is the existing model, the model base must have a model with 100% similarity with the target model characteristic information.
As a preferred embodiment, the obtaining the characteristic information of the target model of the target server specifically includes:
scanning based on a scanning protocol of a preset type to obtain target model characteristic information of a target server;
among them, the preset type of scanning protocol is specifically any one of SNMP (Simple Network Management Protocol ), IPMI (Intelligent Platform Management Interface, intelligent platform management interface), SMIS (SMI Specification, storage management plan specification), and SSH (Secure Shell protocol).
Specifically, in order to smoothly scan and obtain the target model feature information of the target server, a scanning protocol is required to scan the target model feature information, and the above protocols have the advantages of strong stability, high processing speed and the like.
Of course, in addition to the above protocols, other scanning protocols of various types may be used to scan the characteristic information of the target model of the target server, which is not limited herein.
As a preferred embodiment, the similarity between the target model feature information and the model feature information of various servers pre-stored in the model library is determined by adopting a preset similarity algorithm, and specifically is:
and taking the ratio of the number of the same parameters to the total number of all the parameters as the similarity between the target model characteristic information and the model characteristic information of various servers prestored in the model library.
Specifically, since the model feature information has a plurality of parameters, the ratio of the number of the same parameters to the total number of all parameters can be used as the similarity between the model feature information of the target model and the model feature information of various servers pre-stored in the model library, and the similarity can be calculated simply and quickly, for example, the model feature information includes three parameters ABC in total, and if the model feature information of a certain model is the same as the AB parameter of the target model feature information, and the C parameters are different, the similarity between the model feature information and the target model feature information is 2/3.
In consideration of different association degrees with the adapter plug-in, different weights can be allocated to different parameters, and, taking the ABC three parameters as an example, 50% weights can be allocated to the a parameter, and 25% weights can be allocated to the B and the C, respectively, then assuming that the model characteristic information of a certain model is the same as the AB parameter of the target model characteristic information, and the C parameter is different, then the similarity between the model characteristic information and the target model characteristic information is 75%.
Of course, the method for calculating the similarity may be of various types other than the above-listed method for calculating the similarity, and the embodiment of the present invention is not limited thereto.
As a preferred embodiment, the target model feature information and the model feature information are the same and each include a manufacturer, a model, and a version.
In particular, the manufacturer, the model and the version are closely related to the model and the adapter plug-in, so that the manufacturer, the model and the version are used as model characteristic information in the embodiment of the invention.
Of course, the target model feature information and the model feature information may be other specific types besides the above listed parameters, and the embodiment of the present invention is not limited herein.
As a preferred embodiment, the adapter plug-in is in particular an adapter interface for a data communication protocol and a data communication interface encapsulating a server of the corresponding model.
Specifically, the data communication interface and the data communication protocol can be convenient for smoothly communicating with the target server so as to acquire the asset information thereof, so that the adapting plug-in unit in the embodiment of the invention is specifically an adapting interface of the data communication interface and the data communication protocol of the server packaged with the corresponding model.
Of course, the adaptor insert may be of various other types, and embodiments of the present invention are not limited herein.
As a preferred embodiment, the obtaining the characteristic information of the target model of the target server specifically includes:
responding to a server scanning instruction, scanning a newly accessed server in the local area network and taking the newly accessed server as a target server;
acquiring target model characteristic information of a target server;
the server scanning instruction is a server scanning instruction received through the man-machine interaction device or a periodically generated server scanning instruction.
Specifically, the local area network can be connected to new server equipment at random, so that in order to facilitate management of asset information of servers in the local area network, the servers in the local area network are required to be scanned so as to scan the newly connected servers and acquire the asset information, the server scanning instructions can be periodically and automatically generated instructions or instructions sent by a worker in real time through a man-machine interaction device, the periodically and automatically generated instructions can reduce workload of the worker, and the instructions sent by the worker in real time through the man-machine interaction device can ensure that the asset information of the servers newly connected to the local area network is acquired at the first time.
Of course, other specific types of obtaining the target model feature information of the target server may be used besides the above manner, and the embodiment of the present invention is not limited herein.
Referring to fig. 2, fig. 2 is a schematic structural diagram of an asset information obtaining apparatus according to the present invention, where the asset information obtaining apparatus is applied to a processor, and includes:
the first acquisition module 1 is used for acquiring the characteristic information of the target machine type of the target server;
the determining module 2 is used for determining the similarity between the target model characteristic information and the model characteristic information of various servers prestored in the model library by adopting a preset similarity algorithm;
the mapping module 3 is used for taking the model of the server in the model base corresponding to the highest similarity as the approximate model of the target server;
and the second acquisition module 4 is used for acquiring the asset information of the target server by using the adapting plug-in of the similar model.
For the description of the asset information obtaining apparatus provided by the embodiment of the present invention, reference is made to the foregoing embodiment of the asset information obtaining method, and the embodiment of the present invention is not repeated herein.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an asset information obtaining apparatus according to the present invention, the asset information obtaining apparatus includes:
a memory 5 for storing a computer program;
a processor 6 for implementing the steps of the asset information acquisition method of any of the preceding embodiments when executing a computer program.
For the description of the asset information obtaining device provided by the embodiment of the present invention, reference is made to the foregoing embodiment of the asset information obtaining method, and the embodiment of the present invention is not repeated herein.
The present invention also provides a computer readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the asset information acquisition method as in any of the preceding embodiments.
For the description of the computer readable storage medium provided in the embodiment of the present invention, please refer to the foregoing embodiment of the asset information obtaining method, and the embodiment of the present invention is not repeated here.
In the present specification, each embodiment is described in a progressive manner, and each embodiment is mainly described in a different point from other embodiments, and identical and similar parts between the embodiments are all enough to refer to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant points refer to the description of the method section.
It should also be noted that in this specification, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (7)
1. An asset information acquisition method, applied to a processor, comprising:
acquiring target model characteristic information of a target server;
determining the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library by adopting a preset similarity algorithm;
taking the model of the server in the model base corresponding to the highest similarity as the approximate model of the target server;
acquiring asset information of the target server by utilizing the adapting plug-in of the similar model;
the obtaining the target model characteristic information of the target server specifically comprises the following steps:
scanning based on a scanning protocol of a preset type to obtain target model characteristic information of a target server;
the preset type of scanning protocol is specifically any one of simple network management protocol SNMP, intelligent platform management interface IPMI, storage management plan specification SMIS and secure shell protocol SSH;
the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library is determined by adopting a preset similarity algorithm, and the similarity is specifically as follows:
taking the ratio of the number of the same parameters to the total number of all the parameters as the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library;
the adapting plug-in unit is specifically an adapting interface of a data communication protocol and a data communication interface of a server packaged with a corresponding model.
2. The method for acquiring asset information according to claim 1, wherein after the acquiring the target model feature information of the target server, before the adopting the preset similarity algorithm to determine the similarity between the target model feature information and model feature information of various types of servers pre-stored in a model base, the method for acquiring asset information further comprises:
judging whether the model of the target server is an existing model in a model library according to the target model characteristic information;
if yes, acquiring an adaptive plug-in corresponding to the actual model of the target server;
acquiring asset information of the target server by utilizing an adaptation plug-in corresponding to the actual model of the target server;
if not, executing the step of determining the similarity between the target model characteristic information and the model characteristic information of various servers prestored in the model library by adopting a preset similarity algorithm.
3. The asset information acquisition method according to claim 2, wherein the target model characteristic information and the model characteristic information are the same and each include a manufacturer, a model, and a version.
4. The asset information acquisition method according to any one of claims 1 to 3, wherein the acquisition of the target model characteristic information of the target server specifically includes:
responding to a server scanning instruction, scanning a newly accessed server in the local area network and taking the newly accessed server as a target server;
acquiring target model characteristic information of a target server;
the server scanning instruction is a server scanning instruction received through a man-machine interaction device or a periodically generated server scanning instruction.
5. An asset information acquisition device, for use with a processor, comprising:
the first acquisition module is used for acquiring the characteristic information of the target machine type of the target server;
the determining module is used for determining the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library by adopting a preset similarity algorithm;
the mapping module is used for taking the model of the server in the model library corresponding to the highest similarity as the approximate model of the target server;
the second acquisition module is used for acquiring asset information of the target server by utilizing the adapting plug-in of the similar machine type;
the obtaining the target model characteristic information of the target server specifically comprises the following steps:
scanning based on a scanning protocol of a preset type to obtain target model characteristic information of a target server;
the preset type of scanning protocol is specifically any one of simple network management protocol SNMP, intelligent platform management interface IPMI, storage management plan specification SMIS and secure shell protocol SSH;
the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library is determined by adopting a preset similarity algorithm, and the similarity is specifically as follows:
taking the ratio of the number of the same parameters to the total number of all the parameters as the similarity between the target model characteristic information and model characteristic information of various servers prestored in a model library;
the adapting plug-in unit is specifically an adapting interface of a data communication protocol and a data communication interface of a server packaged with a corresponding model.
6. An asset information acquisition device, characterized by comprising:
a memory for storing a computer program;
processor for implementing the steps of the asset information acquisition method according to any one of claims 1 to 4 when executing said computer program.
7. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the asset information acquisition method according to any one of claims 1 to 4.
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| Title |
|---|
| 基于RFID物联网技术的信息化资产管理应用研究;郑晓丽;杨常勇;;内燃机与配件(第10期);全文 * |
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| Publication number | Publication date |
|---|---|
| CN112269801A (en) | 2021-01-26 |
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