CN109005223A - Internet of Things resource regulating method and system, computer readable storage medium and terminal - Google Patents
Internet of Things resource regulating method and system, computer readable storage medium and terminal Download PDFInfo
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- CN109005223A CN109005223A CN201810840200.6A CN201810840200A CN109005223A CN 109005223 A CN109005223 A CN 109005223A CN 201810840200 A CN201810840200 A CN 201810840200A CN 109005223 A CN109005223 A CN 109005223A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/50—Network services
- H04L67/60—Scheduling or organising the servicing of application requests, e.g. requests for application data transmissions using the analysis and optimisation of the required network resources
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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Abstract
A kind of Internet of Things resource regulating method and system, computer readable storage medium and terminal, the described method includes: cloud control centre generates cloud resources model using the training of history Internet of Things resource scheduling information, and the cloud resources model is optimized using the corresponding calculated performance of fringe node and storage performance, the corresponding edge node resources prediction model of each fringe node is generated, and is sent to corresponding fringe node step by step；Multiple fringe nodes receive itself corresponding edge node resources prediction model respectively；The information of the resource service condition of the current period of user is obtained, and predicts to obtain the resources requirement in next period using the edge node resources prediction model of itself；The information of resources requirement based on the next period for predicting to obtain distributes the resource in next period for the user.The speed and efficiency of Internet of Things scheduling of resource can be improved in above-mentioned scheme.
Description
Technical field
The present invention relates to internet of things field, more particularly to a kind of Internet of Things resource regulating method and system, calculating
Machine readable storage medium storing program for executing and terminal.
Background technique
Internet of Things (Internet of Things, IoT) is to develop to come on the basis of computer and Internet technology,
It can accomplish the information sharing and data exchange between object object, realize perception, monitoring, acquisition to information, there is intelligent, essence
The features such as standardization, real time implementation.
Currently, both at home and abroad mainly using cloud computing technology be core realize Internet of Things in scheduling of resource, there is speed with
The problem of inefficiency.
Summary of the invention
Present invention solves the technical problem that being how to improve the speed and efficiency of Internet of Things scheduling of resource.
In order to solve the above technical problems, the embodiment of the invention provides a kind of Internet of Things resource regulating method, the method
Include:
Cloud control centre generates cloud resources model using the training of history Internet of Things resource scheduling information, and uses side
The corresponding calculated performance of edge node and storage performance optimize the cloud resources model, generate each fringe node
Corresponding edge node resources prediction model, and it is sent to corresponding fringe node step by step；
Multiple fringe nodes receive itself corresponding edge node resources prediction model respectively；Obtain the current period of user
Resource service condition information, and needed using the resource that itself edge node resources prediction model predicts to obtain next period
The amount of asking；The information of resources requirement based on the next period for predicting to obtain distributes the resource in next period for the user.
Optionally, the resources requirement for predicting to obtain next period using itself edge node resources prediction model it
Before, the method also includes:
Whether the flange node judges itself have the computing capability for handling the resources request；
When determining that itself does not have the computing capability for handling the resource request, it is pre- that resource is sent to neighboring edge node
Request is surveyed, so that the resource that the neighboring edge node with idle computing resources predicts to obtain next period of the user needs
The amount of asking simultaneously is sent to the fringe node.
Optionally, reach preset frequency threshold value in the interaction times with neighboring edge node, and there is no have the free time
When the neighboring edge node of computing resource, the method also includes:
The fringe node sends resources request to the cloud control centre, so that the cloud control centre predicts
It obtains the resources requirement in next period of the user and is sent to the fringe node.
Optionally, the method also includes:
The fringe node receives the information of the real resource usage amount in next period of the user, and is based on measuring in advance
The resources requirement in next period of the user arrived and the information of real resource usage amount, using intensive training model to institute
It states edge node resources prediction model to be adjusted, and described to distributing to using edge node resources prediction model adjusted
The resource of user is adjusted, until the resource that the real resource usage amount of the user feedback and prediction obtain the user needs
The amount of asking is suitable.
The embodiment of the invention also provides a kind of Internet of Things resource scheduling system, the system comprises cloud control centres and more
A fringe node；The cloud control centre is coupled with the multiple fringe node respectively, and phase between the multiple fringe node
Mutually coupling；
Cloud control centre is suitable for generating cloud resources model using the training of history Internet of Things resource scheduling information, and
The cloud resources model is optimized using the corresponding calculated performance of fringe node and storage performance, generates each side
The corresponding edge node resources prediction model of edge node, and it is sent to corresponding fringe node step by step；
The fringe node is suitable for receiving itself corresponding edge node resources prediction model；Obtain the current week of user
The information of the resource service condition of phase, and predict to obtain the resource in next period using the edge node resources prediction model of itself
Demand；The information of resources requirement based on the next period for predicting to obtain distributes the resource in next period for the user.
Optionally, the fringe node is further adapted in the case where the edge node resources prediction model using itself is predicted to obtain
Before the resources requirement in one period, judge whether itself there is the computing capability for handling the resources request；Work as determination
When itself does not have the computing capability for handling the resource request, resources request is sent to neighboring edge node, so that
Neighboring edge node with idle computing resources is predicted to obtain the resources requirement in next period of the user and is sent to
The fringe node.
Optionally, the fringe node is to being further adapted for when reaching preset number with the interaction times of neighboring edge node
Threshold value, and there is no when the neighboring edge node with idle computing resources, resources, which are sent, to the cloud control centre asks
It asks, so that the cloud control centre predicts to obtain the resources requirement in next period of the user and is sent to the edge
Node.
Optionally, the fringe node is further adapted for receiving the letter of the real resource usage amount in next period of the user
Breath, and the information of the resources requirement in next period based on the user for predicting to obtain and real resource usage amount, use
Intensive training model is adjusted the edge node resources prediction model, and is predicted using edge node resources adjusted
Model is adjusted the resource for distributing to the user, until the real resource usage amount of the user feedback is obtained with prediction
The resources requirement of the user is suitable.
The embodiment of the invention also provides a kind of computer readable storage mediums, are stored thereon with computer instruction, described
The step of computer instruction executes Internet of Things resource regulating method described in any of the above embodiments when running.
The embodiment of the invention also provides a kind of terminal, including memory and processor, energy is stored on the memory
Enough computer instructions run on the processor, the processor execute any of the above-described when running the computer instruction
The step of described Internet of Things resource regulating method.
Compared with prior art, the technical solution of the embodiment of the present invention has the advantages that
Above-mentioned scheme, it is pre- using history Internet of Things resource scheduling information training generation cloud resource by cloud control centre
Model is surveyed, and the cloud resources model is optimized using the corresponding calculated performance of fringe node and storage performance,
The corresponding edge node resources prediction model of each fringe node is generated, and is sent to corresponding fringe node step by step；Multiple sides
Edge node receives itself corresponding edge node resources prediction model respectively；Obtain the resource service condition of the current period of user
Information, and predict to obtain the resources requirement in next period using itself edge node resources prediction model；Based on prediction
The information of the resources requirement in obtained next period distributes the resource in next period for the user, can use edge meter
Calculation technology further increases Internet of things system to the processing capability in real time of data, reduces Time Delay of Systems.
Further, the resources requirement and reality in the next period for the user that the fringe node is obtained based on prediction
The information of border resource usage amount is adjusted the edge node resources prediction model using intensive training model, and uses
Edge node resources prediction model adjusted is adjusted the resource for distributing to the user, until the user feedback
Real resource usage amount obtains that the resources requirement of the user is suitable with prediction, and the accuracy of resource allocation can be improved, into
And the utilization rate of resource can be improved.
Detailed description of the invention
Fig. 1 is the structural schematic diagram of one of embodiment of the present invention Internet of Things resource scheduling system；
Fig. 2 is the flow diagram of one of embodiment of the present invention Internet of Things resource regulating method.
Specific embodiment
Technical solution in the embodiment of the present invention is by cloud control centre using the training of history Internet of Things resource scheduling information
Cloud resources model is generated, and using the corresponding calculated performance of fringe node and storage performance to the cloud resources
Model optimizes, and generates the corresponding edge node resources prediction model of each fringe node, and be sent to corresponding side step by step
Edge node；Multiple fringe nodes receive itself corresponding edge node resources prediction model respectively；Obtain the current period of user
Resource service condition information, and needed using the resource that itself edge node resources prediction model predicts to obtain next period
The amount of asking；The information of resources requirement based on the next period for predicting to obtain distributes the resource in next period for the user, can
To further increase Internet of things system to the processing capability in real time of data using edge calculations technology, Time Delay of Systems is reduced.
It is understandable to enable above-mentioned purpose of the invention, feature and beneficial effect to become apparent, with reference to the accompanying drawing to this
The specific embodiment of invention is described in detail.
In order to make it easy to understand, being briefly described first below to one of embodiment of the present invention.
Fig. 1 is a kind of structural schematic diagram of Internet of Things resource scheduling system of the embodiment of the present invention.Referring to Fig. 1, the present invention
One of embodiment Internet of Things resource scheduling system may include cloud control centre 101 and multiple fringe nodes 102.Wherein,
Multiple fringe nodes 102 are coupled with the cloud control centre 101 respectively, are mutually coupled between the multiple fringe node 102.
It is described in detail below in conjunction with working principle of the Fig. 2 to Internet of Things resource scheduling system shown in FIG. 1.
Fig. 1 is a kind of flow diagram of Internet of Things resource regulating method of the embodiment of the present invention.Referring to Fig. 1, the present invention
One of embodiment Internet of Things resource regulating method, suitable for the drug Quick delivery in the electronics prescription by patient to patient
Place, can specifically include following step:
Step S201: the training of cloud control centre generates the corresponding edge node resources prediction model of each fringe node and sends
To each fringe node.
In specific implementation, cloud control centre utilizes the vast resources prediction data of collection and going through for the user that is stored
History resource usage record selects a movement to execute, and is adjusted by feedback, generates cloud prediction model, and basis respectively
The calculating of each fringe node can carry out model optimization to generated cloud prediction model with storage capacity, to obtain each
The edge node resources prediction model of fringe node, and it is issued to corresponding fringe node respectively.
Step S202: fringe node receives itself corresponding edge node resources prediction model and is stored.
In specific implementation, each fringe node is in the edge node resources prediction model for receiving cloud control centre and issuing
When, itself corresponding fringe node prediction model can be stored, subsequent pre- using itself corresponding fringe node
Model is surveyed to predict the resources requirement in each period of user.
Step S203: the fringe node receives the resource scheduling request of user, and judges itself whether there is processing institute
State the computing capability of resources request；When the judgment result is yes, step S204 can be executed；Conversely, can then execute step
Rapid S205.
Step S204: the fringe node is predicted to obtain next period using the edge node resources prediction model of itself
Resources requirement.
In specific implementation, when determining itself has the computing capability for handling the resources request, the edge
User can be obtained first in the information of the resource service condition of current period, and by acquired user current period money
The money in next period of the user is calculated in the edge node resources prediction model of the information input of source service condition itself
Source demand, and will be calculated the user next period the corresponding resource allocation of resources requirement to the user.
Step S205: the fringe node sends resources request to neighboring edge node, and judges the neighbouring side
Edge node handles the resources request with the presence or absence of idle computing resources.
In specific implementation, when fringe node determines the computing capability deficiency of itself, the fringe node can be called
The neighboring edge node that communication unit is located at its periphery with position interacts, to complete the money of user using neighboring edge node
Source predicted operation.
Step S206: the neighboring edge node receives the resources request, and is provided using the fringe node of itself
The resources requirement that source prediction model predicts to obtain next period is sent to the fringe node.
In specific implementation, when the neighboring edge node for receiving the resources request that the fringe node is sent has
When corresponding idle computing resources are enough to handle resources request, the neighboring edge node can be used and be used
The resources requirement that the edge node resources prediction model of itself predicts to obtain next period is sent to the fringe node.
Step S207: the flange node judges send whether the number that resources are requested reaches to neighboring edge node
Preset frequency threshold value；When the judgment result is yes, can continue to execute since step S205；Conversely, can then execute step
Rapid S208.
In specific implementation, the frequency threshold value of fringe node, when being the waiting that cloud control centre is requested based on user
Between TwThe ratio calculation of interaction time T obtains between fringe node, it may be assumed that
Dmax=Tw/T (1)
In specific implementation, it is not up to when fringe node sends the number that the resources are requested to neighboring edge node
When the frequency threshold value, the fringe node can continue to send the resources request to other neighboring edge nodes,
To which the idle neighboring edge node for handling the resources request can be searched out by constantly attempting.
Step S208: the fringe node sends the resources request to the cloud control centre.
In specific implementation, reach institute when fringe node sends the number that the resources are requested to neighboring edge node
State frequency threshold value DmaxWhen, the fringe node will stop sending resources request to other neighboring edge nodes, then will
The resources request is sent to the cloud control centre and is handled.
Step S209: the cloud control centre receives the resources request, and predicts to obtain the next of the user
The information of the demand in period is simultaneously sent to the fringe node.
In specific implementation, the cloud control centre, can be in the resources request for receiving fringe node
Using the fringe node fringe node prediction model according to from described in parsing obtains in received resources request
The data of the resource service condition of the current period of user predict that the resources requirement in the next period for obtaining the user is concurrent
It send to the fringe node.
Step S210: the fringe node obtains the demand in next period of the user according to prediction, is the use
The resource in next period is distributed at family.
In specific implementation, when fringe node itself prediction obtains the demand in next period of the user, Huo Zhecong
When neighboring edge node or cloud control centre receive the demand in next period of the user, prediction can be obtained
The user next period resource allocation give the user.
In specific implementation, in order to further increase the utilization rate of resource, the Internet of Things resource regulating method can be with
Include:
Step S211: the information of the real resource usage amount in next period of the user is received, and is obtained based on prediction
The user next period resources requirement and real resource usage amount information, using intensive training model to described
Edge node resources prediction model is adjusted.
In specific implementation, the result of the resources requirement in next period of the user predicted and the user
Real resource demand between there are certain errors, therefore in order to improve scheduling of resource accuracy rate, the fringe node can will
The real resource service condition Real-time Feedback in next period gives the fringe node, so that the fringe node can be using strong
The real resource service condition in change next period of the training pattern based on user's Real-time Feedback is to the user in next period
In resources requirement be adjusted, until the user feedback real resource usage amount and prediction obtain the money of the user
Source demand is suitable, to improve the utilization rate of Internet of Things resource by the accuracy for improving scheduling of resource.
Meanwhile fringe node can store the information of the prediction result of final resources requirement, under again
The prediction of the stock number of user described in one period provides reference.
The embodiment of the invention also provides a kind of computer readable storage mediums, are stored thereon with computer instruction, described
The step of Internet of Things resource regulating method is executed when computer instruction is run.Wherein, the Internet of Things scheduling of resource
Method refers to being discussed in detail for preceding sections, repeats no more.
The embodiment of the invention also provides a kind of terminal, including memory and processor, energy is stored on the memory
Enough computer instructions run on the processor, the processor execute the Internet of Things when running the computer instruction
The step of net resource regulating method.Wherein, the Internet of Things resource regulating method refers to being discussed in detail for preceding sections, no
It repeats again.
Using the above scheme in the embodiment of the present invention, history Internet of Things resource scheduling information is used by cloud control centre
Training generates cloud resources model, and using the corresponding calculated performance of fringe node and storage performance to the cloud resource
Prediction model optimizes, and generates the corresponding edge node resources prediction model of each fringe node, and be sent to correspondence step by step
Fringe node；Multiple fringe nodes receive itself corresponding edge node resources prediction model respectively；Obtain the current of user
The information of the resource service condition in period, and predict to obtain the money in next period using the edge node resources prediction model of itself
Source demand；The information of resources requirement based on the next period for predicting to obtain distributes the money in next period for the user
Source can use the processing capability in real time that edge calculations technology further increases Internet of things system to data, reduce Time Delay of Systems.
Further, the resources requirement and reality in the next period for the user that the fringe node is obtained based on prediction
The information of border resource usage amount is adjusted the edge node resources prediction model using intensive training model, and uses
Edge node resources prediction model adjusted is adjusted the resource for distributing to the user, until the user feedback
Real resource usage amount obtains that the resources requirement of the user is suitable with prediction, and the accuracy of resource allocation can be improved, into
And the utilization rate of resource can be improved.
Field those of ordinary skill is understood that all or part of the steps in the various methods of above-described embodiment is can be with
Relevant hardware is instructed to complete by program, which can store in computer readable storage medium, storage medium
It may include: ROM, RAM, disk or CD etc..
Although present disclosure is as above, present invention is not limited to this.Anyone skilled in the art are not departing from this
It in the spirit and scope of invention, can make various changes or modifications, therefore protection scope of the present invention should be with claim institute
Subject to the range of restriction.
Claims (10)
1. a kind of Internet of Things resource regulating method characterized by comprising
Cloud control centre generates cloud resources model using the training of history Internet of Things resource scheduling information, and uses edge section
The corresponding calculated performance of point and storage performance optimize the cloud resources model, and it is corresponding to generate each fringe node
Edge node resources prediction model, and be sent to corresponding fringe node step by step；
Multiple fringe nodes receive itself corresponding edge node resources prediction model respectively；Obtain the money of the current period of user
The information of source service condition, and predict to obtain the resource requirement in next period using the edge node resources prediction model of itself
Amount；The information of resources requirement based on the next period for predicting to obtain distributes the resource in next period for the user.
2. Internet of Things resource regulating method according to claim 1, which is characterized in that provided using the fringe node of itself
Source prediction model is predicted to obtain before the resources requirement in next period, further includes:
Whether the flange node judges itself have the computing capability for handling the resources request；
When determining that itself does not have the computing capability for handling the resource request, resources are sent to neighboring edge node and are asked
It asks, so that the neighboring edge node with idle computing resources is predicted to obtain the resources requirement in next period of the user
And it is sent to the fringe node.
3. Internet of Things resource regulating method according to claim 2, which is characterized in that the interaction time with neighboring edge node
Number reaches preset frequency threshold value, and there is no when the neighboring edge node with idle computing resources, further includes:
The fringe node sends resources request to the cloud control centre, so that the cloud control centre predicts to obtain
The resources requirement in next period of the user is simultaneously sent to the fringe node.
4. Internet of Things resource regulating method according to any one of claims 1 to 3, which is characterized in that further include:
The fringe node receives the information of the real resource usage amount in next period of the user, and obtained based on prediction
The resources requirement in next period of the user and the information of real resource usage amount, using intensive training model to the side
Edge node resource prediction model is adjusted, and using edge node resources prediction model adjusted to distributing to the user
Resource be adjusted, until the user feedback real resource usage amount and prediction obtain the resources requirement of the user
Quite.
5. a kind of Internet of Things resource scheduling system, which is characterized in that including cloud control centre and multiple fringe nodes；
The cloud control centre is coupled with the multiple fringe node respectively, and is mutually coupled between the multiple fringe node；
Cloud control centre is suitable for generating cloud resources model using the training of history Internet of Things resource scheduling information, and uses
The corresponding calculated performance of fringe node and storage performance optimize the cloud resources model, generate each edge section
The corresponding edge node resources prediction model of point, and it is sent to corresponding fringe node step by step；
The fringe node is suitable for receiving itself corresponding edge node resources prediction model；Obtain the current period of user
The information of resource service condition, and predict to obtain the resource requirement in next period using the edge node resources prediction model of itself
Amount；The information of resources requirement based on the next period for predicting to obtain distributes the resource in next period for the user.
6. Internet of Things resource scheduling system according to claim 5, which is characterized in that the fringe node is further adapted for
Before predicting to obtain the resources requirement in next period using the edge node resources prediction model of itself, judge whether itself has
There is the computing capability for handling the resources request；Itself do not have the computing capability for handling the resource request when determining
When, resources request is sent to neighboring edge node, so that the neighboring edge node with idle computing resources measures in advance
To next period of the user resources requirement and be sent to the fringe node.
7. Internet of Things resource scheduling system according to claim 6, which is characterized in that the fringe node is to being further adapted for
When the interaction times with neighboring edge node reach preset frequency threshold value, and there is no the neighbouring sides with idle computing resources
When edge node, resources request is sent to the cloud control centre, so that the cloud control centre predicts to obtain the use
The resources requirement in next period at family is simultaneously sent to the fringe node.
8. according to the described in any item Internet of Things resource scheduling systems of claim 5 to 7, which is characterized in that the fringe node,
It is further adapted for receiving the information of the real resource usage amount in next period of the user, and based on the user's for predicting to obtain
The resources requirement in next period and the information of real resource usage amount, using intensive training model to the edge node resources
Prediction model is adjusted, and is carried out using edge node resources prediction model adjusted to the resource for distributing to the user
Adjustment, until the real resource usage amount of the user feedback with predict that obtain the resources requirement of the user suitable.
9. a kind of computer readable storage medium, is stored thereon with computer instruction, which is characterized in that the computer instruction fortune
Perform claim requires the step of 1 to 4 described in any item Internet of Things resource regulating methods when row.
10. a kind of terminal, which is characterized in that including memory and processor, storing on the memory can be at the place
The computer instruction run on reason device, perform claim requires any one of 1 to 4 institute when the processor runs the computer instruction
The step of Internet of Things resource regulating method stated.
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| CN112465554A (en) * | 2020-12-03 | 2021-03-09 | 广东工业大学 | Block chain-based computing resource pricing method |
| CN113259359A (en) * | 2021-05-21 | 2021-08-13 | 重庆紫光华山智安科技有限公司 | Edge node capability supplementing method, system, medium and electronic terminal |
| CN113783716A (en) * | 2021-07-27 | 2021-12-10 | 国网冀北电力有限公司信息通信分公司 | Flow prediction method and device based on cloud edge collaborative framework |
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