CN-121217772-B - Ext> 5ext> Gext> -ext> Aext> -ext> basedext> largeext> -ext> scaleext> Internetext> ofext> thingsext> equipmentext> connectionext> managementext> methodext> andext> systemext>

Abstract

The invention discloses a 5G-A-based large-scale Internet of things equipment connection management method and system, and relates to the technical field of Internet of things. The method comprises the following steps: acquiring equipment characteristics and coordinates of an equipment cluster to form a characteristic set and a coordinate set; obtaining a movement parameter set from the feature set by a device movement analyzer, and compensating a compensation coordinate set of coordinates in a direction away from the base station; combining the feature set, the mobile parameter set and the compensation coordinate set, and obtaining an optimized access parameter set through mobile signal quality analysis path evaluation and iterative optimization; and accessing the device cluster into the 5G-A internet of things according to the parameter set. The system comprises a data acquisition module, a mobile analysis module, a coordinate compensation module, an access parameter optimization module and an equipment access module. The invention realizes the full-dimensional adaptation of the static attribute, the dynamic movement and the space position of the equipment, improves the connection stability and the resource utilization rate, and adapts to the access requirements of the multi-scene large-scale equipment.

Inventors

• WANG WEIXIONG
• LIANG YOUCHENG
• LU XIANYU
• SU WENJUN

Assignees

• 广州民航职业技术学院

Dates

Publication Date

20260508

Application Date

20251024

Claims (6)

1. 1. Ext> theext> methodext> forext> managingext> theext> connectionext> ofext> theext> largeext> -ext> scaleext> Internetext> ofext> thingsext> equipmentext> basedext> onext> theext> 5ext> Gext> -ext> Aext> isext> characterizedext> byext> comprisingext> theext> followingext> stepsext>:ext> Acquiring equipment characteristics and equipment coordinates of an equipment cluster to be connected with the Internet of things, and acquiring an equipment characteristic set and an equipment coordinate set; According to the equipment characteristic set, carrying out equipment movement analysis to obtain an equipment movement parameter set, and compensating the equipment coordinate set to obtain a compensation equipment coordinate set, wherein each equipment movement parameter comprises movement speed and movement distance; Ext> performingext> 5ext> Gext> -ext> Aext> accessext> parameterext> optimizationext> accordingext> toext> theext> equipmentext> characteristicext> setext>,ext> theext> equipmentext> movementext> parameterext> setext> andext> theext> compensationext> equipmentext> coordinateext> setext> toext> obtainext> anext> optimizedext> accessext> parameterext> setext>;ext> Ext> accordingext> toext> theext> optimizedext> accessext> parameterext> setext>,ext> theext> equipmentext> clusterext> isext> accessedext> toext> theext> Internetext> ofext> thingsext> byext> adoptingext> 5ext> Gext> -ext> Aext>;ext> According to the device feature set, performing device movement analysis to obtain a device movement parameter set, compensating the device coordinate set to obtain a compensated device coordinate set, including: inputting each device feature in the device feature set into a device movement analyzer to obtain a device movement parameter set, wherein each device movement parameter comprises a movement speed and a movement distance; Ext> compensatingext> theext> equipmentext> coordinateext> setext> byext> adoptingext> theext> equipmentext> movingext> distanceext> setext> inext> theext> equipmentext> movingext> parameterext> setext> toext> obtainext> aext> compensatingext> equipmentext> coordinateext> setext>,ext> whereinext> coordinateext> compensationext> isext> carriedext> outext> inext> aext> directionext> awayext> fromext> theext> 5ext> Gext> -ext> Aext> baseext> stationext>;ext> Ext> performingext> 5ext> Gext> -ext> Aext> accessext> parameterext> optimizationext> accordingext> toext> theext> deviceext> featureext> setext>,ext> theext> deviceext> movementext> parameterext> setext> andext> theext> compensationext> deviceext> coordinateext> setext> toext> obtainext> anext> optimizedext> accessext> parameterext> setext>,ext> includingext>:ext> Randomly generating a first access parameter set of the device cluster; Inputting the first access parameters of each device into a mobile signal quality analysis path by combining the device characteristics and the device movement speed to obtain a first mobile access quality parameter set; Inputting the first access parameters of each device into a mobile signal quality analysis path by combining the device characteristics and the compensation device coordinates to obtain a first distance access quality parameter set; configuring a plurality of moving weights and a plurality of distance weights according to a plurality of moving speeds, carrying out weighted calculation on a first moving access quality parameter set and a first distance access quality parameter set to obtain a first access quality parameter set, and calculating a mean value to obtain a first cluster access quality parameter; And continuing to randomly generate an access parameter set for iterative optimization to obtain an optimized access parameter set with the maximum cluster access quality parameter.
2. 2. Ext> theext> 5ext> Gext> -ext> aext> basedext> largeext> -ext> scaleext> internetext> ofext> thingsext> deviceext> connectionext> managementext> methodext> ofext> claimext> 1ext>,ext> whereinext> obtainingext> deviceext> featuresext> andext> deviceext> coordinatesext> ofext> aext> deviceext> clusterext> toext> beext> connectedext> byext> theext> internetext> ofext> thingsext>,ext> obtainingext> aext> deviceext> featureext> setext> andext> aext> deviceext> coordinateext> setext>,ext> comprisesext>:ext> Acquiring equipment characteristics and equipment coordinates of an equipment cluster to be connected with the Internet of things; And integrating the equipment characteristics and the equipment coordinates of all the equipment to obtain an equipment characteristic set and an equipment coordinate set.
3. 3. Ext> theext> 5ext> Gext> -ext> aext> basedext> largeext> -ext> scaleext> internetext> ofext> thingsext> deviceext> connectionext> managementext> methodext> ofext> claimext> 1ext>,ext> whereinext> theext> trainingext> stepext> ofext> theext> deviceext> movementext> analyzerext> comprisesext>:ext> According to historical management data of the Internet of things equipment, collecting a sample equipment characteristic set, and collecting the maximum moving speed and the maximum moving distance of equipment with different sample equipment characteristics in the using process, and marking to obtain a sample moving speed set and a sample moving distance set; Building a device movement analyzer based on machine learning; And iteratively supervising and training the equipment movement analyzer until the loss converges by adopting the sample equipment characteristic set, the sample movement speed set and the sample movement distance set.
4. 4. Ext> theext> methodext> forext> managingext> connectionext> ofext> devicesext> ofext> theext> largeext> -ext> scaleext> internetext> ofext> thingsext> basedext> onext> 5ext> Gext> -ext> aext> accordingext> toext> claimext> 1ext>,ext> whereinext> theext> stepext> ofext> constructingext> theext> mobileext> signalext> qualityext> analysisext> pathext> comprisesext>:ext> Collecting a sample access parameter set, a sample equipment moving speed set and a sample moving access quality parameter set according to the equipment connection data in the historical time; Constructing a mobile signal quality analysis path based on machine learning; and adopting the sample access parameter set, the sample equipment moving speed set and the sample moving access quality parameter set to iterate supervision training on the moving signal quality analysis path until the loss converges.
5. 5. Ext> theext> 5ext> Gext> -ext> aext> basedext> largeext> -ext> scaleext> internetext> ofext> thingsext> deviceext> connectionext> managementext> methodext> ofext> claimext> 1ext>,ext> whereinext> configuringext> aext> pluralityext> ofext> movementext> weightsext> andext> aext> pluralityext> ofext> distanceext> weightsext> accordingext> toext> aext> pluralityext> ofext> movementext> speedsext>,ext> weightingext> andext> calculatingext> aext> firstext> mobileext> accessext> qualityext> parameterext> setext> andext> aext> firstext> distanceext> accessext> qualityext> parameterext> setext>,ext> obtainingext> aext> firstext> accessext> qualityext> parameterext> setext>,ext> comprisesext>:ext> Calculating the ratio of the moving speed of each device to the maximum moving speed as a moving weight; Subtracting the moving weight from 1 to obtain a distance weight; and adopting the moving weight and the distance weight of each device, carrying out weighted calculation on the first moving access quality parameter and the first distance access quality parameter of each device to obtain a first access quality parameter, and calculating to obtain a first access quality parameter set of the device cluster.
6. 6. Ext> aext> 5ext> Gext> -ext> aext> basedext> largeext> scaleext> internetext> ofext> thingsext> deviceext> connectionext> managementext> systemext> forext> performingext> theext> methodext> ofext> anyext> ofext> claimsext> 1ext> -ext> 5ext>,ext> comprisingext>:ext> The data acquisition module is configured to acquire equipment characteristics and equipment coordinates of an equipment cluster to be connected with the Internet of things, and acquire an equipment characteristic set and an equipment coordinate set; The movement analysis and coordinate compensation module is configured to perform equipment movement analysis according to the equipment characteristic set to obtain an equipment movement parameter set, and compensate the equipment coordinate set by adopting the equipment movement parameter set to obtain a compensation equipment coordinate set, wherein each equipment movement parameter comprises a movement speed and a movement distance; ext> theext> accessext> parameterext> optimizationext> moduleext> isext> configuredext> toext> performext> 5ext> Gext> -ext> Aext> accessext> parameterext> optimizationext> accordingext> toext> theext> equipmentext> characteristicext> setext>,ext> theext> equipmentext> movementext> parameterext> setext> andext> theext> compensationext> equipmentext> coordinateext> setext> toext> obtainext> anext> optimizedext> accessext> parameterext> setext>;ext> Ext> andext> theext> equipmentext> accessext> moduleext> isext> configuredext> toext> accessext> theext> equipmentext> clusterext> toext> theext> Internetext> ofext> thingsext> byext> adoptingext> aext> 5ext> Gext> -ext> Aext> technologyext> accordingext> toext> theext> optimizedext> accessext> parameterext> setext>.ext>

Description

Ext> 5ext> Gext> -ext> Aext> -ext> basedext> largeext> -ext> scaleext> Internetext> ofext> thingsext> equipmentext> connectionext> managementext> methodext> andext> systemext> Technical Field Ext> theext> inventionext> relatesext> toext> theext> technicalext> fieldext> ofext> theext> Internetext> ofext> thingsext>,ext> inext> particularext> toext> aext> 5ext> Gext> -ext> Aext> -ext> basedext> largeext> -ext> scaleext> Internetext> ofext> thingsext> equipmentext> connectionext> managementext> methodext> andext> systemext>.ext> Background The internet of things (Internet of Things, ioT) concept is a network concept that extends and extends its clients to any item-to-item information exchange and communication based on the "internet concept". The internet of things connects all articles with the internet through the information sensing equipment to exchange information, namely the articles are in information, so that intelligent identification and management are realized. Ext> theext> 5ext> Gext> -ext> Aext> technologyext> isext> usedext> asext> anext> enhancedext> evolutionext> versionext> ofext> 5ext> Gext>,ext> hasext> higherext> bandwidthext>,ext> lowerext> timeext> delayext> andext> strongerext> connectionext> capabilityext>,ext> andext> providesext> powerfulext> supportext> forext> largeext> -ext> scaleext> Internetext> ofext> thingsext> equipmentext> connectionext>.ext> However, in practical application, the internet of things device often has the characteristics of large mobility difference, wide distribution range and the like, and the traditional device connection management method does not consider the device characteristic difference, so that the dynamic movement characteristic of the device and the different position relations from the base station are difficult to adapt, and unstable device access quality and low network resource utilization rate are easy to cause. Disclosure of Invention Ext> theext> inventionext> providesext> aext> 5ext> Gext> -ext> Aext> -ext> basedext> largeext> -ext> scaleext> Internetext> ofext> thingsext> equipmentext> connectionext> managementext> methodext> andext> systemext>,ext> andext> aimsext> toext> solveext> theext> problemsext> ofext> unstableext> Internetext> ofext> thingsext> connectionext> qualityext>,ext> insufficientext> mobileext> equipmentext> supportext>,ext> largeext> -ext> scaleext> accessext> bottleneckext> andext> theext> likeext> causedext> byext> neglectingext> equipmentext> characteristicext> differenceext>,ext> lackext> ofext> dynamicext> adaptabilityext> andext> lowext> efficiencyext> ofext> resourceext> allocationext> inext> theext> priorext> artext>.ext> Ext> inext> aext> firstext> aspectext>,ext> theext> presentext> applicationext> providesext> aext> methodext> forext> managingext> largeext> -ext> scaleext> internetext> ofext> thingsext> deviceext> connectionext> basedext> onext> 5ext> Gext> -ext> aext>,ext> theext> methodext> comprisingext>:ext> Acquiring equipment characteristics and equipment coordinates of an equipment cluster to be connected with the Internet of things, and acquiring an equipment characteristic set and an equipment coordinate set; According to the equipment characteristic set, carrying out equipment movement analysis to obtain an equipment movement parameter set, and compensating the equipment coordinate set to obtain a compensation equipment coordinate set, wherein each equipment movement parameter comprises movement speed and movement distance; Ext> performingext> 5ext> Gext> -ext> Aext> accessext> parameterext> optimizationext> accordingext> toext> theext> equipmentext> characteristicext> setext>,ext> theext> equipmentext> movementext> parameterext> setext> andext> theext> compensationext> equipmentext> coordinateext> setext> toext> obtainext> anext> optimizedext> accessext> parameterext> setext>;ext> Ext> andext> accessingext> theext> equipmentext> clusterext> intoext> theext> Internetext> ofext> thingsext> byext> adoptingext> 5ext> Gext> -ext> Aext> accordingext> toext> theext> optimizedext> accessext> parameterext> setext>.ext> Ext> inext> aext> secondext> aspectext>,ext> theext> presentext> applicationext> providesext> aext> 5ext> Gext> -ext> aext> -ext> basedext> largeext> -ext> scaleext> internetext> ofext> thingsext> deviceext> connectionext> managementext> systemext>,ext> whichext> isext> characterizedext> byext> comprisingext>:ext> The data acquisition module is configured to acquire equipment characteristics and equipment coordinates of an equipment cluster to be connected with the Internet of things, and acquire an equipment characteristic set and an equipment coordinate set; The movement analysis and coordinate compensation module is configured to perform equipment movement analysis according to the equipment characteristic set to obtain an equipment movement parameter set, and compensate the equipment coordinate set by adopting the equipment movement parameter set to obtain a compensation equipment coordina