CN110647587A - Heterogeneous resource mapping method based on two-stage model - Google Patents
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Abstract
The invention discloses a heterogeneous resource mapping method based on a two-stage model, which comprises the following steps: a. calling and loading cloud resource data; b. analyzing the cloud resource data and establishing a cloud resource model; c. calling and loading local resource data; d. analyzing the local resource data and establishing a local entity resource model; e. establishing a corresponding relation between cloud resource model data and body entity model data; f. mapping the cloud resource model data with the corresponding relation established into local entity model data; g. instantiating the mapped resource data and classifying the resource data; h. and respectively establishing a resource management database for the classified resource data. The invention solves the problem of difficult integration of heterogeneous data of different sources across platforms through the established two-stage model.
Description
Technical Field
The invention belongs to the field of network resource management, and particularly relates to a heterogeneous resource mapping method based on a two-stage model.
Background
With the arrival of the big data era, data information is scattered in various places, states are different, structures are different, and data integration is an important factor before decision making of various big companies. The traditional data integration mode is far from being adapted to the requirement of people for acquiring data. The data integration difficulty lies in the problems of heterogeneity of a data source, a limited access mechanism, modeling, data sharing and the like, and the integration of heterogeneous data of different sources across platforms is more difficult, so that the data sharing approaches are few, and the data value cannot be embodied to the maximum extent. The existing heterogeneous data integration mode mainly comprises an xml model, a data interface, middleware, an object proxy, a single model and the like, and the modes have the following defects when processing heterogeneous data: the data processing automation and intellectualization is insufficient, the cross-platform heterogeneous complex data processing capacity is insufficient, the data semantic integrity is high, and the like.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a heterogeneous resource mapping method based on a two-stage model aiming at the defects of the prior art, and the problem of difficult integration of heterogeneous data of a cross-platform heterogeneous system is solved through the established two-stage model.
The technical scheme adopted by the invention is as follows: a heterogeneous resource mapping method based on a two-level model is characterized by comprising the following steps:
a. calling and loading cloud resource data;
b. analyzing the cloud resource data and establishing a cloud resource model;
c. calling and loading local resource data;
d. analyzing the local resource data and establishing a local entity resource model;
e. establishing a corresponding relation between cloud resource model data and body entity model data;
f. mapping the cloud resource model data with the corresponding relation established into local entity model data;
g. instantiating the mapped resource data and classifying the resource data;
h. and respectively establishing a resource management database for the classified resource data.
In one embodiment, the step d or the step e further includes a selection control step, specifically as follows:
and selecting cloud resource model data or body entity model data, adjusting the selected cloud resource model data or body entity model data or mapping the selected cloud resource model data into local entity model data.
In one embodiment, in step b, a cloud resource model is established, which specifically includes the following steps:
and respectively establishing a tag name and an element name for each item of cloud resource data information according to the called cloud resource data information, and storing the tag name and the element name.
In one embodiment, the tag names are RPName, RPKwords, RPDesc, RPSize, and RPType, and the element names are cloud resource names, resource keywords, description information, resource import size, and resource types corresponding to RPName, RPKwords, RPDesc, RPSize, and RPType, respectively.
In one embodiment, in step d, a local entity resource model is established, which specifically includes the following steps:
and respectively establishing a label name and an element name for each item of local resource data information according to the called local resource data information and storing the label name and the element name.
In one embodiment, the tag names are ResName, ResKwords, ResDesc, ResSize, and ResType, and the element names are resource names, resource keywords, resource descriptions, resource sizes, and resource types corresponding to ResName, ResKwords, ResDesc, ResSize, and ResType, respectively.
In one embodiment, in step e, a corresponding relationship between the cloud resource model data and the body entity model data is established, specifically as follows:
and comparing the cloud resource data information and the body entity resource data information in the cloud resource model and the body entity resource model, and establishing a corresponding relation between the cloud resource data information and the body entity resource data information according to the label names and the element names of the cloud resource data information and the body entity resource data information.
In one embodiment, in step h, the resource management database established includes a relational database and a NoSQL database.
The invention has the beneficial effects that:
1. the method mainly solves the problem of difficult integration of cross-platform heterogeneous data through the established two-stage model;
2. the two-stage resource model of the method is composed of a cloud resource model and a local entity resource model, the two-stage model formulates a data model through metadata, source data achieve uniformity and normalization of data formats in a model mapping mode, and the resource data are stored in storage equipment corresponding to resource categories, so that the problem of heterogeneous data integration is solved.
Detailed Description
The present invention will be described in further detail with reference to specific examples.
The invention discloses a heterogeneous resource mapping method based on a two-stage model, which is characterized by comprising the following steps of:
the method comprises the following steps of firstly, calling cloud resource data and loading;
step two, analyzing the cloud resource data and establishing a cloud resource model;
step three, calling and loading local resource data;
analyzing the local resource data and establishing a local entity resource model;
establishing a corresponding relation between cloud resource model data and body entity model data;
mapping the cloud resource model data with the corresponding relationship established into local entity model data;
step seven, instantiating the mapped resource data and classifying the resource data;
and step eight, respectively establishing a resource management database for the classified resource data.
In this embodiment, the step four or the step five further includes a selection control step, which is specifically as follows:
and selecting cloud resource model data or body entity model data, adjusting the selected cloud resource model data or body entity model data or mapping the selected cloud resource model data into local entity model data.
In this embodiment, in step two, the cloud resource model is established as follows:
and respectively establishing a tag name and an element name for each item of cloud resource data information according to the called cloud resource data information, and storing the tag name and the element name.
In this embodiment, the tag names are RPName, RPKwords, RPDesc, RPSize, and RPType, and the element names are cloud resource names, resource keywords, description information, resource introduction sizes, and resource types corresponding to RPName, RPKwords, RPDesc, RPSize, and RPType, respectively.
In this embodiment, in step four, a local entity resource model is established, which specifically includes:
and respectively establishing a label name and an element name for each item of local resource data information according to the called local resource data information and storing the label name and the element name.
In this embodiment, the tag names are ResName, reskwards, ResDesc, ResSize, and ResType, and the element names are resource names, resource keywords, resource descriptions, resource sizes, and resource types corresponding to ResName, reskwards, ResDesc, ResSize, and ResType, respectively.
In this embodiment, in step five, a corresponding relationship between the cloud resource model data and the body entity model data is established, which is specifically as follows:
and comparing the cloud resource data information and the body entity resource data information in the cloud resource model and the body entity resource model, and establishing a corresponding relation between the cloud resource data information and the body entity resource data information according to the label names and the element names of the cloud resource data information and the body entity resource data information.
In this embodiment, in step eight, the established resource management database includes a relational database and a NoSQL database.
In the method, the cloud-end resource model mainly describes resource related information from the aspects of resource category, use method, service quality and the like. The cloud resource model is formalized as follows: CRPM = < RPID, RPProvider, RPService, RPMapping >. Wherein: the RPID is a unique mark generated by registering the resources provided by the cloud resource platform on the platform, is used for positioning and retrieving the resources provided by the cloud resource platform, and is not allowed to be changed once being applied. The method has the advantages that the unique RPID is provided for both the local resource and the cloud resource, and the logical relationship mapping between the local resource pool and the cloud resource is realized through the RPID.
The RPProvider representation provides basic properties, formally described as: RPProvider = { RPCID, RPName, RPKwords, RPDesc, RPType, RPSize, submitta }, which are respectively used for representing the ID of the cloud resource platform, the name of the resource on the cloud resource platform, the resource keyword, the resource description, the resource type, the resource size, and the submission date.
The RPService represents a service attribute for describing the resource and the related information of the provided service, and can be formatted as: RPService = { ResState, ResQos, ResRights, ResTrade,
ResAvgTime, …, ResSerForm, which respectively represents the status attribute of the resource, the comprehensive evaluation of the service quality, the service authority, the transaction mode, the average time of the resource service, the resource service form, and the like.
RPMapping represents a mapping description of a resource, which can be formalized as: RPMapping = { RPMID, RPMBasePro, RPMRBasePro, Constraint }, where RPMID is a model flag; RPMBasaPro is a description of the mapping (e.g., a relationship of resource mapping, etc.), RPMRBasePro is a specific description of the physical resource, and Constraint is a description of the Constraint in the mapping.
The local entity resource model in the method is used for storing relevant information of entity resources, providing a target template for cloud resource data mapping, and describing resource data mainly from multiple aspects such as basic attributes, service attributes and evaluation attributes. Formalized description of local entity resource model: LERM = < ResID, RPID, ResBaseInfo, ServicePro, AssessPro, OtherPro >, where: ResID represents a resource identifier that, once generated, does not change any more, and is used to uniquely represent a particular resource of the platform for use in enabling the location and retrieval of the resource. The RPID is the unique identifier of the resource in the cloud resource pool, and the mapping logic relationship between the cloud resource pool and the local resource pool is realized through the attribute.
ResBaseInfo is a basic attribute set of entity resources (including local resources and resources provided by a cloud resource platform), and the formalization expression of ResBaseInfo is as follows: resbaselnfo = < ResName, ResType,
ResInfo, ProviderID and ServiceInfo, wherein ResName is the name of the resource; ResType is a resource type; ResInfo is resource description information, provided by the resource provider, formalized as: restinfo = < ResKwords, ResDesc, ResSize, …, ResLimit >, which respectively represent resource key, resource description, resource size, resource limit, etc., ProviderID is a unique identifier of the resource provider for authenticating the identity of the resource provider.
The ServiceInfo is resource service related information, and can be described in a formalized manner as follows: ServiceInfo = < SerType, time, ETime, Qua, Cost, Enviro, AssessPro >, which respectively represent information of service type, resource service start time, resource service end time, service quality, price, service environment, and the like.
AssessPro represents the comprehensive evaluation information of the resource, and can be formally described as: AssessPro = < QAss, servas, inclreditas, Average >, where: qass is quality evaluation; servAss is service evaluation; IncreditAss is reputation evaluation; average is the Average value of all indexes of the current task of the resource.
OtherPro represents other related attribute information, and the related information can be added by a local resource manager and a cloud resource platform provider.
The data mapping is to map the cloud resource model data into local entity model data. And establishing a corresponding relation by using the model label name and the element name, realizing the mapping conversion from the source metadata to the target metadata, and ensuring the format uniformity of the data stored in the resource pool. The two-level model mapping correspondence is shown in table 1.
TABLE 1 two-level model mapping correspondence table
However, the tag names and element names of the two-level resource model are not limited to the above table, and can be added and deleted according to actual situations to meet the requirements of different situations.
The method mainly solves the problem of difficult integration of cross-platform heterogeneous data through the established two-stage model; the two-stage resource model of the method is composed of a cloud resource model and a local entity resource model, the two-stage model formulates a data model through metadata, source data achieve uniformity and normalization of data formats in a model mapping mode, and the resource data are stored in storage equipment corresponding to resource categories, so that the problem of heterogeneous data integration is solved.
The above-mentioned embodiments only express the specific embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention.
Claims (8)
1. A heterogeneous resource mapping method based on a two-level model is characterized by comprising the following steps:
a. calling and loading cloud resource data;
b. analyzing the cloud resource data and establishing a cloud resource model;
c. calling and loading local resource data;
d. analyzing the local resource data and establishing a local entity resource model;
e. establishing a corresponding relation between cloud resource model data and body entity model data;
f. mapping the cloud resource model data with the corresponding relation established into local entity model data;
g. instantiating the mapped resource data and classifying the resource data;
h. and respectively establishing a resource management database for the classified resource data.
2. The heterogeneous resource mapping method based on the two-stage model according to claim 1, wherein: a selection control step is further included between the step d or the step e, and the selection control step specifically comprises the following steps:
and selecting cloud resource model data or body entity model data, adjusting the selected cloud resource model data or body entity model data or mapping the selected cloud resource model data into local entity model data.
3. The heterogeneous resource mapping method based on the two-stage model according to claim 1, wherein: in the step b, a cloud resource model is established, which specifically comprises the following steps:
and respectively establishing a tag name and an element name for each item of cloud resource data information according to the called cloud resource data information, and storing the tag name and the element name.
4. The heterogeneous resource mapping method based on the two-stage model according to claim 1, wherein: the tag names are RPName, RPKwords, RPDesc, RPSize and RPType, and the element names are cloud resource names, resource keywords, description information, resource transmission sizes and resource types corresponding to the RPName, the RPKwords, the RPDesc, the RPSize and the RPType respectively.
5. The heterogeneous resource mapping method based on the two-stage model according to claim 1, wherein: in step d, a local entity resource model is established, specifically as follows:
and respectively establishing a label name and an element name for each item of local resource data information according to the called local resource data information and storing the label name and the element name.
6. The two-level model-based heterogeneous resource mapping method according to claim 5, wherein: the tag names are ResName, ResKwords, ResDesc, ResSize and ResType, and the element names are resource names, resource keywords, resource descriptions, resource sizes and resource types corresponding to ResName, ResKwords, ResDesc, ResSize and ResType respectively.
7. The heterogeneous resource mapping method based on the two-stage model according to claim 1, wherein: in step e, establishing a corresponding relation between the cloud resource model data and the body entity model data, specifically as follows:
and comparing the cloud resource data information and the body entity resource data information in the cloud resource model and the body entity resource model, and establishing a corresponding relation between the cloud resource data information and the body entity resource data information according to the label names and the element names of the cloud resource data information and the body entity resource data information.
8. The two-level model-based heterogeneous resource mapping method according to claim 7, wherein: in step h, the established resource management database comprises a relational database and a NoSQL database.
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CA2460717A1 (en) * | 2001-09-28 | 2003-04-10 | British Telecommunications Public Limited Company | Database management system |
| CN106534306A (en) * | 2016-11-14 | 2017-03-22 | 北京大学（天津滨海）新代信息技术研究院 | Extensible heterogeneous cloud platform adaptation method and system |
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Application publication date: 20200103 |