CN106686136A - Cloud resource scheduling method and device - Google Patents
Cloud resource scheduling method and device Download PDFInfo
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- CN106686136A CN106686136A CN201710105788.6A CN201710105788A CN106686136A CN 106686136 A CN106686136 A CN 106686136A CN 201710105788 A CN201710105788 A CN 201710105788A CN 106686136 A CN106686136 A CN 106686136A
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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
- H04L67/1001—Protocols in which an application is distributed across nodes in the network for accessing one among a plurality of replicated servers
- H04L67/1004—Server selection for load balancing
- H04L67/1008—Server selection for load balancing based on parameters of servers, e.g. available memory or workload
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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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Abstract
The invention discloses a cloud resource scheduling method. The cloud resource scheduling method and device comprises the steps that a resource scheduling model is generated on the basis of an elastic stretching strategy and a dynamic migration strategy by combining the scale of a cloud platform; transverse and/or longitudinal multi-dimensional scheduling is conducted on virtual resources of which resource allocation exceeds a preset value through the elastic stretching strategy and the dynamic migration strategy in the resource scheduling model. According to the cloud resource scheduling method, by adopting the resource scheduling model which is generated on the basis of the elastic stretching strategy and the dynamic migration strategy by combing the scale of the cloud platform to conduct dynamic scheduling on the virtual resources in the platform, the migration and bad dynamic loading effect problems which are likely to be caused by an instant resource utilization rate peak value can be avoided, the resource using efficiency of the cloud platform is effectively improved, the stability of the cloud platform is improved, the cloud platform is safer and more reliable, and the user experience degree is increased. The invention further discloses a cloud resource scheduling device which also has the above-mentioned advantages.
Description
Technical field
The present invention relates to cloud computing virtualization field, the more particularly to a kind of dispatching method and device of cloud resource.
Background technology
With the development of modern society's Internet technology, cloud computing technology has also obtained more next as the IT patterns of a new generation
More it is widely applied.Cloud computing technology is developed from grid computing, parallel computation and Distributed Calculation, and user can utilize it
Easily to pass through the configurable computing resource of network access one on demand (such as calculating, network, storage, application and service etc.)
Shared pool, the management workload that need to only minimize or service provider intervene just can rapidly open or discharge resource.
Resource in current cloud environment is all to be virtualized the hardware resource of bottom by Intel Virtualization Technology, forms one
Individual huge virtualization pool, the deployment way of final dynamic retractility is supplied to user in the form of services.As cloud management is flat
The increase that user in platform persistently uses so that the scale of cloud data center is also constantly being increased, and how efficiently to utilize cloud
Virtual resource in management platform is simultaneously quickly supplied to user, is the subject matter that we face now.
In the prior art, cloud resource dynamic dispatching is distributed according to need according to the demand of user, added and release virtual resource, and
Non-load balanced case according to physical machine is dynamically migrated to virtual resource in real time so that existing cloud resource management platform
There are problems that transient resource utilization rate peak value easily triggers migration, dynamic load.Therefore, how cloud is effectively improved
The resource utilization of resource management platform system, lifting system stability improves user experience, is to be badly in need of solving now
Problem.
The content of the invention
It is an object of the invention to provide a kind of dispatching method and device of cloud resource, moved by elastic telescopic strategy and dynamic
Move strategy carries out dynamic dispatching to the resource in cloud platform, effectively improves the resource utilization of cloud platform, makes cloud platform more
It is safe and reliable, improve user experience.
In order to solve the above technical problems, the present invention provides a kind of dispatching method of cloud resource, including：
Scale based on elastic telescopic strategy and dynamic migration strategy combination cloud platform, generates resource dispatching model；
By elastic telescopic strategy and dynamic migration strategy in the resource dispatching model, resource allocation is exceeded predetermined
The virtual resource of value carries out the scheduling of laterally and/or longitudinally various dimensions.
Optionally, the scale based on elastic telescopic strategy and dynamic migration strategy combination cloud platform, generation resource is adjusted
Degree model, including：
Elastic telescopic parameter based on the elastic telescopic strategy setting virtual machine processor, internal memory and storage, virtual number
According to the excess distribution ratio of processor, internal memory and storage in the load balancing and cluster at center；Wherein, the elastic telescopic ginseng
Number includes raising threshold value, lowers threshold value, raise ratio, lower at least one in ratio and dilatation higher limit, the load balancing
Dilatation threshold value and the dilatation upper limit of the strategy including processor and internal memory；
The parameter of migration trigger condition and purpose migration information based on the dynamic migration strategy setting virtual resource；Its
In, the parameter includes the essential information and activation threshold value condition of the migration virtual resource.
Optionally, the tune that laterally and/or longitudinally various dimensions are carried out to the virtual resource that resource allocation exceedes predetermined value
Degree, including：
Successively to the virtual machine more than the predetermined value, the virtual data center where the virtual machine and the virtual number
Elastic telescopic is carried out according to the cluster where center；
Judge the virtual machine with the presence or absence of the resource allocation more than the predetermined value；
If so, then carrying out dynamic thermophoresis to the virtual machine.
Optionally, the elastic telescopic strategy and dynamic migration strategy by the resource dispatching model, to resource
Before being allocated more than the virtual resource of predetermined value and carrying out the laterally and/or longitudinally scheduling of various dimensions, also include：
Monitor the service condition of various virtual resources in the cloud platform；
Judge whether that resource allocation exceedes the virtual resource of the predetermined value；
If so, the elastic telescopic strategy and dynamic migration strategy by the resource dispatching model is then performed, it is right
The step of virtual resource that resource allocation exceedes predetermined value carries out the laterally and/or longitudinally scheduling of various dimensions.
Optionally, the service condition for monitoring various virtual resources in the cloud platform, including：
The service condition of various virtual resources in cloud platform described in monitor in real time；Or
At preset timed intervals in cloud platform described in Monito ping at intervals various virtual resources service condition.
Additionally, present invention also offers a kind of dispatching device of cloud resource, including：
Model generation module, for the scale based on elastic telescopic strategy and dynamic migration strategy combination cloud platform, generation
Resource dispatching model；
Scheduler module, for by the elastic telescopic strategy and dynamic migration strategy in the resource dispatching model, to money
The virtual resource that source is allocated more than predetermined value carries out the scheduling of laterally and/or longitudinally various dimensions.
Optionally, the model generation module, including：
Elastic telescopic strategy submodule, for based on the elastic telescopic strategy setting virtual machine processor, internal memory and depositing
The elastic telescopic parameter of storage, the load balancing of virtual data center and in cluster processor, internal memory and storage excess point
Proportioning；Wherein, the elastic telescopic parameter includes raising threshold value, lowers threshold value, raise ratio, lower ratio and dilatation higher limit
In at least one, the load balancing includes the dilatation threshold value and the dilatation upper limit of processor and internal memory；
Dynamic migration strategy submodule, for the migration trigger condition based on the dynamic migration strategy setting virtual resource
With the parameter of purpose migration information；Wherein, the parameter includes the essential information and activation threshold value bar of the migration virtual resource
Part.
Optionally, the scheduler module, including：
Elastic telescopic submodule, for successively to the virtual machine more than the predetermined value, virtual where the virtual machine
Cluster where data center and the virtual data center carries out elastic telescopic；
Dynamic thermophoresis submodule, for judging the virtual machine with the presence or absence of the resource allocation more than the predetermined value；
If so, then carrying out dynamic thermophoresis to the virtual machine.
Optionally, the device also includes：
Monitoring module, the service condition for monitoring various virtual resources in the cloud platform；
Judge module, for judging whether that resource allocation exceedes the virtual resource of the predetermined value；If so, to
The scheduler module sends enabling signal.
Optionally, the monitoring module, including：
Monito ping at intervals submodule, at preset timed intervals in cloud platform described in Monito ping at intervals various virtual resources service condition；
Or
Monitor in real time submodule, the service condition of various virtual resources in cloud platform described in monitor in real time.
A kind of dispatching method of cloud resource provided by the present invention, including：Based on elastic telescopic strategy and dynamic migration plan
Slightly with reference to the scale of cloud platform, resource dispatching model is generated；By the elastic telescopic strategy in the resource dispatching model and dynamic
State migration strategy, the scheduling of laterally and/or longitudinally various dimensions is carried out to the virtual resource that resource allocation exceedes predetermined value；
It can be seen that, the present invention is generated by using the scale based on elastic telescopic strategy and dynamic migration strategy combination cloud platform
Resource dispatching model, dynamic dispatching is carried out to the virtual resource in platform, transient resource utilization rate peak value can be avoided easily to draw
The generation of the problems such as migration, dynamic load effect on driving birds is not good of hair, and the resource utilization of cloud platform is effectively raised, carry
The stability of cloud platform high, makes cloud platform more safe and reliable, improves the Experience Degree of user.Additionally, the present invention is also provided
A kind of dispatching device of cloud resource, equally with above-mentioned beneficial effect.
Brief description of the drawings
In order to illustrate more clearly about the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
The accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, drawings in the following description are only this
Inventive embodiment, for those of ordinary skill in the art, on the premise of not paying creative work, can also basis
The accompanying drawing of offer obtains other accompanying drawings.
A kind of flow chart of the dispatching method of cloud resource that Fig. 1 is provided by the embodiment of the present invention；
The flow chart of the dispatching method of another cloud resource that Fig. 2 is provided by the embodiment of the present invention；
A kind of structure chart of the dispatching device of cloud resource that Fig. 3 is provided by the embodiment of the present invention.
Specific embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
A part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
Refer to Fig. 1, a kind of flow chart of the dispatching method of cloud resource that Fig. 1 is provided by the embodiment of the present invention.The party
Method can include：
Step 101：Scale based on elastic telescopic strategy and dynamic migration strategy combination cloud platform, generates scheduling of resource mould
Type.
Wherein, the resource dispatching model of generation can be by the various of elastic telescopic strategy and dynamic migration strategy setting
Parameter values, such as elastic telescopic parameter, virtual data based on elastic telescopic strategy setting virtual machine processor, internal memory and storage
The excess distribution ratio of processor, internal memory and storage in the load balancing and cluster at center, based on dynamic migration strategy setting
The migration trigger condition of virtual resource and the parameter of purpose migration information, the design parameter numerical value for resource dispatching model set
Put, can be automatically generated by cloud platform according to the practical scene of cloud platform or user's request or voluntarily be set by designer or user
Put, the present embodiment is unrestricted to this.
Step 102：By elastic telescopic strategy and dynamic migration strategy in the resource dispatching model, to resource allocation
Virtual resource more than predetermined value carries out the scheduling of laterally and/or longitudinally various dimensions.
Wherein, the virtual resource in cloud platform can be divided into by level：Virtual control center (center), cluster
(cluster), virtual data center (vdc) and virtual machine (vm).Virtual data center can be to include processor, internal memory and deposit
One group of virtualization pool of storage, virtual machine there may be the empty machine under a certain virtual data center, and cluster can be one group virtual
The set of resource pool.Predetermined value can be that designer or user pre-set according to the practical scene of cloud platform or user's request
Numerical value, the distribution condition for determining virtual resource in cloud platform.When resource allocation exceedes predetermined value, then the resource is illustrated
The index of distribution is too high, it is necessary to be scheduled.The present embodiment does not do any limitation for the specific setting of predetermined value.
It is understood that resource allocation can be the use feelings of the processor, internal memory or storage of virtual machine in cloud platform
Condition, such as utilization rate, apportionment ratio and its corresponding aggregate data.The virtual resource that resource allocation exceedes predetermined value can be cloud platform
In one of the processor of one or several virtual machines, internal memory or storage or several indexs exceed respective predetermined values.To resource point
The scheduling of laterally and/or longitudinally various dimensions is carried out with the virtual resource more than predetermined value, index can be exceeded for successively predetermined
The cluster where virtual data center and the virtual data center where the virtual machine of value, the virtual machine carries out elastic telescopic,
If after elastic shrinkage, the index of the virtual machine still exceedes predetermined value, then can carry out dynamic thermophoresis to the virtual machine.This reality
Example is applied for specific scheduling mode, such as the order of elastic shrinkage, any limitation is not done.
Preferably, can also be added before this step and the monitoring of the service condition of various virtual resources in cloud platform is walked
Suddenly, for the judgement of the convenient virtual resource for exceeding predetermined value to resource allocation, can in real time or at preset timed intervals Monito ping at intervals
The service condition of various virtual resources in cloud platform, the present embodiment is unrestricted to this.
As long as it should be noted that can determine that resource allocation exceedes the virtual resource of predetermined value, determining for specific
Whether mode, by monitoring the service condition of various virtual resources in cloud platform, and can enter to resource allocation more than predetermined value
The mode that row judges, it is also possible to which by other means, the present embodiment does not do any limitation to this.
In the present embodiment, the embodiment of the present invention is by using flat based on elastic telescopic strategy and dynamic migration strategy combination cloud
The resource dispatching model of the scale generation of platform, dynamic dispatching is carried out to the virtual resource in platform, can avoid transient resource profit
The generation of the problems such as migration, dynamic load effect on driving birds is not good for easily being triggered with rate peak value, and effectively raise the money of cloud platform
Source service efficiency, improves the stability of cloud platform, makes cloud platform more safe and reliable, improves the Experience Degree of user.
Refer to Fig. 2, the flow chart of the dispatching method of another cloud resource that Fig. 2 is provided by the embodiment of the present invention.Should
Method can include：
Step 201：The service condition of various virtual resources in monitor in real time cloud platform；
Wherein, the service condition of various virtual resources, can be Virtual control center (center), cluster in cloud platform
(cluster), the service condition of virtual data center (vdc) and virtual machine (vm), can include each virtual resource processor,
Internal memory and the utilization rate of storage, apportionment ratio and its corresponding aggregate data.
Step 202：Judge whether that resource allocation exceedes the virtual machine of predetermined value；If so, then entering step 203.
It is understood that the present embodiment is to judge it is predetermined whether the resource allocation of virtual machine in virtual resource exceedes
Carried out with the presence or absence of the judgment mode more than respective respective predetermined values in value, that is, the processor of virtual machine, internal memory and storage
Displaying, can also by judge virtual data center in virtual resource processor and dilatation whether exceed it is each self-corresponding pre-
The judgment mode of definite value, as long as can be corresponding with the resource dispatching model of generation, for specific judgment mode, the present embodiment
Any limitation is not done.
Step 203：Scale based on elastic telescopic strategy and dynamic migration strategy combination cloud platform, generates scheduling of resource mould
Type.
Wherein, generation resource dispatching model can be each seed ginseng by elastic telescopic strategy and dynamic migration strategy setting
In number numerical value, such as elastic telescopic parameter, virtual data based on elastic telescopic strategy setting virtual machine processor, internal memory and storage
The excess distribution ratio of processor, internal memory and storage in the load balancing and cluster of the heart, it is empty based on dynamic migration strategy setting
Intend the migration trigger condition of resource and the parameter of purpose migration information.
It should be noted that elastic telescopic parameter can include raising threshold value, lower threshold value, raise ratio, lower ratio
With dilatation higher limit, dilatation threshold value and the dilatation upper limit that load balancing can be including processor and internal memory, migration triggering bar
The parameter of part and purpose migration information can include the essential information (title/ip) and activation threshold value condition of migration virtual resource,
The trigger condition can include processor threshold value and memory threshold.
It is understood that for the generation time of resource dispatching model, can be deposited detecting as shown in this embodiment
Resource allocation exceed predetermined value virtual machine after, regenerate resource dispatching model, or start monitoring before or start
Do not detected after monitoring exist resource allocation more than predetermined value virtual machine when, generate resource dispatching model, as long as may insure
Detect after there is resource allocation more than the virtual machine of predetermined value, resource dispatching model can be used by following step, it is right
In the generation time of resource dispatching model, the present embodiment does not do any limitation.
Equally, resource dispatching model can be the model just automatically saved after being generated in detecting every time, or every time
Detect after there is resource allocation more than the virtual machine of predetermined value, the model for regenerating.The present embodiment is not received equally to this
Any limitation.
Step 204：Successively to the virtual machine more than predetermined value, in virtual data center and virtual data where virtual machine
Cluster where the heart carries out elastic telescopic.
Wherein, the method that the present embodiment is provided can exceed the void of predetermined value by elastic telescopic strategy to resource allocation
Plan machine carries out elastic telescopic, for the concrete mode of elastic telescopic, can be shown by such as the present embodiment successively to exceeding
Virtual data center where virtual machine, the virtual machine of predetermined value and the cluster where virtual data center carry out elastic telescopic
Mode, it is also possible to by other means, the present embodiment does not do any limitation to this.
It is understood that the elastic telescopic mode in this step be directed to the resource allocation that this implementation shown exceed it is pre-
The virtual machine of definite value, if it is not virtual machine but virtual data center that resource allocation exceedes predetermined value, can equally using this
Elastic telescopic mode or other corresponding elastic telescopic modes, the present embodiment do not do any limitation to this.
Step 205：Judge virtual machine with the presence or absence of the resource allocation more than predetermined value；If so, then entering step 206.
It is understood that the purpose of this step is to exceed the void of predetermined value to resource allocation by elastic telescopic strategy
After plan machine carries out elastic telescopic, judge the virtual machine resource allocation whether still exceed predetermined value, if so, then explanation need into
Row step 206, thermophoresis is carried out by dynamic migration strategy to the virtual machine.If it is not, can then terminate scheduling, continue to monitor empty
Intend the service condition of resource.
It should be noted that the predetermined value in this step, can be and identical predetermined value in above-mentioned steps, or
The activation threshold value condition of dynamic migration strategy the inside setting in resource dispatching model, that is, processor threshold value and memory threshold.
The present embodiment is unrestricted to this.
Step 206：Dynamic thermophoresis is carried out to virtual machine.
It is understood that the virtual machine to there is the resource allocation more than predetermined value carries out dynamic thermophoresis, Ke Yiwei
The essential information of the migration virtual machine by being set in dynamic migration strategy in resource dispatching model, Mobile state is entered to the virtual machine
Thermophoresis, can include migration main frame and storage.For specific migration pattern and the place for moving to, the present embodiment is not appointed
What is limited.
It should be noted that the method that the present embodiment is provided, is that the virtual machine that resource allocation exceedes predetermined value is first led to
The elastic telescopic strategy crossed in resource dispatching model carries out elastic telescopic, then by the dynamic migration strategy in resource dispatching model
Dynamic thermophoresis is carried out, redistributing and optimizing for resource is finally completed.Elastic telescopic is carried out to virtual resource and Dynamic Thermal is moved
Move, that is, the scheduling for carrying out horizontal and vertical various dimensions.
In the present embodiment, the service condition that the embodiment of the present invention passes through various virtual resources in monitor in real time cloud platform can
The situation that resource allocation exceedes the virtual machine of predetermined value is obtained with the very first time, and is quickly responded, by successively to super
Virtual data center where crossing virtual machine, the virtual machine of predetermined value and the cluster where virtual data center carry out elastic telescopic
Dynamic thermophoresis is carried out with to virtual machine, the scheduling to the horizontal and vertical various dimensions of virtual resource can be completed, it is final complete
Redistributing and optimize into resource, further improves the Experience Degree of user.
Refer to Fig. 3, a kind of structure chart of the dispatching device of cloud resource that Fig. 3 is provided by the embodiment of the present invention.The dress
Putting to include：
Model generation module 100, it is raw for the scale based on elastic telescopic strategy and dynamic migration strategy combination cloud platform
Into resource dispatching model；
Scheduler module 200 is right for by the elastic telescopic strategy and dynamic migration strategy in the resource dispatching model
Resource allocation carries out the scheduling of laterally and/or longitudinally various dimensions more than the virtual resource of predetermined value.
Optionally, the model generation module 100, can include：
Elastic telescopic strategy submodule, for based on the elastic telescopic strategy setting virtual machine processor, internal memory and depositing
The elastic telescopic parameter of storage, the load balancing of virtual data center and in cluster processor, internal memory and storage excess point
Proportioning；Wherein, the elastic telescopic parameter includes raising threshold value, lowers threshold value, raise ratio, lower ratio and dilatation higher limit
In at least one, the load balancing includes the dilatation threshold value and the dilatation upper limit of processor and internal memory；
Dynamic migration strategy submodule, for the migration trigger condition based on the dynamic migration strategy setting virtual resource
With the parameter of purpose migration information；Wherein, the parameter includes the essential information and activation threshold value bar of the migration virtual resource
Part.
Optionally, the scheduler module 200, can include：
Elastic telescopic submodule, for successively to the virtual machine more than the predetermined value, virtual where the virtual machine
Cluster where data center and the virtual data center carries out elastic telescopic；
Dynamic thermophoresis submodule, for judging the virtual machine with the presence or absence of the resource allocation more than the predetermined value；
If so, then carrying out dynamic thermophoresis to the virtual machine.
Optionally, the device can also include：
Monitoring module, the service condition for monitoring various virtual resources in the cloud platform；
Judge module, for judging whether that resource allocation exceedes the virtual resource of the predetermined value；If so, to
The scheduler module sends enabling signal.
Optionally, the monitoring module, can include：
Monito ping at intervals submodule, at preset timed intervals in cloud platform described in Monito ping at intervals various virtual resources service condition；
Or
Monitor in real time submodule, the service condition of various virtual resources in cloud platform described in monitor in real time.
In the present embodiment, the embodiment of the present invention is by model generation module 100 using based on elastic telescopic strategy and dynamic
The resource dispatching model of the scale generation of migration strategy combination cloud platform, by scheduler module 200 to the virtual resource in platform
Carry out dynamic dispatching, can avoid transient resource utilization rate peak value easily trigger migration, dynamic load effect on driving birds is not good the problems such as
Occur, and effectively raise the resource utilization of cloud platform, improve the stability of cloud platform, cloud platform is more pacified
It is complete reliable, improve the Experience Degree of user.
Each embodiment is described by the way of progressive in specification, and what each embodiment was stressed is and other realities
Apply the difference of example, between each embodiment identical similar portion mutually referring to.For device disclosed in embodiment
Speech, because it is corresponded to the method disclosed in Example, so description is fairly simple, related part is referring to method part illustration
.
Professional further appreciates that, with reference to the unit of each example of the embodiments described herein description
And algorithm steps, can be realized with electronic hardware, computer software or the combination of the two, in order to clearly demonstrate hardware and
The interchangeability of software, generally describes the composition and step of each example according to function in the above description.These
Function is performed with hardware or software mode actually, depending on the application-specific and design constraint of technical scheme.Specialty
Technical staff can realize described function to each specific application using distinct methods, but this realization should not
Think beyond the scope of this invention.
The step of method or algorithm for being described with reference to the embodiments described herein, directly can be held with hardware, processor
Capable software module, or the two combination is implemented.Software module can be placed in random access memory (RAM), internal memory, read-only deposit
Reservoir (ROM), electrically programmable ROM, electrically erasable ROM, register, hard disk, moveable magnetic disc, CD-ROM or technology
In field in known any other form of storage medium.
The dispatching method and device to cloud resource provided by the present invention are described in detail above.It is used herein
Specific case is set forth to principle of the invention and implementation method, and the explanation of above example is only intended to help and understands this
The method and its core concept of invention.It should be pointed out that for those skilled in the art, not departing from this hair
On the premise of bright principle, some improvement and modification can also be carried out to the present invention, these are improved and modification also falls into power of the present invention
In the protection domain that profit is required.
Claims (10)
1. a kind of dispatching method of cloud resource, it is characterised in that including：
Scale based on elastic telescopic strategy and dynamic migration strategy combination cloud platform, generates resource dispatching model；
By elastic telescopic strategy and dynamic migration strategy in the resource dispatching model, predetermined value is exceeded to resource allocation
Virtual resource carries out the scheduling of laterally and/or longitudinally various dimensions.
2. the dispatching method of cloud resource according to claim 1, it is characterised in that described based on elastic telescopic strategy and dynamic
The scale of state migration strategy combination cloud platform, generates resource dispatching model, including：
In elastic telescopic parameter, virtual data based on the elastic telescopic strategy setting virtual machine processor, internal memory and storage
The excess distribution ratio of processor, internal memory and storage in the load balancing and cluster of the heart；Wherein, the elastic telescopic parameter bag
Include rise threshold value, lower at least one in threshold value, rise ratio, downward ratio and dilatation higher limit, the load balancing
Dilatation threshold value and the dilatation upper limit including processor and internal memory；
The parameter of migration trigger condition and purpose migration information based on the dynamic migration strategy setting virtual resource；Wherein,
The parameter includes the essential information and activation threshold value condition of the migration virtual resource.
3. the dispatching method of cloud resource according to claim 2, it is characterised in that described that predetermined value is exceeded to resource allocation
Virtual resource carry out the scheduling of laterally and/or longitudinally various dimensions, including：
Successively to the virtual machine more than the predetermined value, in virtual data center and the virtual data where the virtual machine
Cluster where the heart carries out elastic telescopic；
Judge the virtual machine with the presence or absence of the resource allocation more than the predetermined value；
If so, then carrying out dynamic thermophoresis to the virtual machine.
4. the dispatching method of the cloud resource according to any one of claims 1 to 3, it is characterised in that described by the money
Elastic telescopic strategy and dynamic migration strategy in the scheduling model of source, horizontal stroke is carried out to the virtual resource that resource allocation exceedes predetermined value
To and/or the scheduling of longitudinal various dimensions before, also include：
Monitor the service condition of various virtual resources in the cloud platform；
Judge whether that resource allocation exceedes the virtual resource of the predetermined value；
If so, the elastic telescopic strategy and dynamic migration strategy by the resource dispatching model is then performed, to resource
The step of being allocated more than the virtual resource of predetermined value and carry out the laterally and/or longitudinally scheduling of various dimensions.
5. the dispatching method of cloud resource according to claim 4, it is characterised in that various in the monitoring cloud platform
The service condition of virtual resource, including：
The service condition of various virtual resources in cloud platform described in monitor in real time；Or
At preset timed intervals in cloud platform described in Monito ping at intervals various virtual resources service condition.
6. a kind of dispatching device of cloud resource, it is characterised in that including：
Model generation module, for the scale based on elastic telescopic strategy and dynamic migration strategy combination cloud platform, generates resource
Scheduling model；
Scheduler module, for by the elastic telescopic strategy and dynamic migration strategy in the resource dispatching model, to resource point
The scheduling of laterally and/or longitudinally various dimensions is carried out with the virtual resource more than predetermined value.
7. the dispatching device of cloud resource according to claim 6, it is characterised in that the model generation module, including：
Elastic telescopic strategy submodule, for based on the elastic telescopic strategy setting virtual machine processor, internal memory and storage
Elastic telescopic parameter, the load balancing of virtual data center and in cluster processor, internal memory and storage excess distribution ratio；
Wherein, during the elastic telescopic parameter is including raising threshold value, lowering threshold value, rise ratio, downward ratio and dilatation higher limit extremely
One item missing, the load balancing includes the dilatation threshold value and the dilatation upper limit of processor and internal memory；
Dynamic migration strategy submodule, for migration trigger condition and mesh based on the dynamic migration strategy setting virtual resource
Migration information parameter；Wherein, the parameter includes the essential information and activation threshold value condition of the migration virtual resource.
8. the dispatching device of cloud resource according to claim 7, it is characterised in that the scheduler module, including：
Elastic telescopic submodule, for successively to the virtual machine more than the predetermined value, the virtual data where the virtual machine
Cluster where center and the virtual data center carries out elastic telescopic；
Dynamic thermophoresis submodule, for judging the virtual machine with the presence or absence of the resource allocation more than the predetermined value；If so,
Dynamic thermophoresis then is carried out to the virtual machine.
9. the dispatching device of the cloud resource according to any one of claim 6 to 8, it is characterised in that also include：
Monitoring module, the service condition for monitoring various virtual resources in the cloud platform；
Judge module, for judging whether that resource allocation exceedes the virtual resource of the predetermined value；If so, to described
Scheduler module sends enabling signal.
10. the dispatching device of cloud resource according to claim 9, it is characterised in that the monitoring module, including：
Monito ping at intervals submodule, at preset timed intervals in cloud platform described in Monito ping at intervals various virtual resources service condition；Or
Monitor in real time submodule, the service condition of various virtual resources in cloud platform described in monitor in real time.
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| CN201710105788.6A CN106686136A (en) | 2017-02-24 | 2017-02-24 | Cloud resource scheduling method and device |
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| CN201710105788.6A CN106686136A (en) | 2017-02-24 | 2017-02-24 | Cloud resource scheduling method and device |
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Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107231264A (en) * | 2017-07-25 | 2017-10-03 | 北京百度网讯科技有限公司 | For the method and apparatus for the capacity for managing Cloud Server |
| CN107506241A (en) * | 2017-08-25 | 2017-12-22 | 郑州云海信息技术有限公司 | A kind of flexible method of cloud platform automatic elastic |
| CN109445931A (en) * | 2018-08-31 | 2019-03-08 | 安徽四创电子股份有限公司 | A kind of big data resource scheduling system and method |
| WO2019144788A1 (en) * | 2018-01-24 | 2019-08-01 | 中兴通讯股份有限公司 | Resource control method and device, equipment and computer readable storage medium |
| CN110809062A (en) * | 2019-11-14 | 2020-02-18 | 苏州思必驰信息科技有限公司 | Public cloud voice recognition resource calling control method and device |
| CN111708604A (en) * | 2020-05-28 | 2020-09-25 | 北京赛博云睿智能科技有限公司 | Intelligent operation and maintenance supporting method |
| CN113127187A (en) * | 2019-12-31 | 2021-07-16 | 北京百度网讯科技有限公司 | Method and apparatus for cluster scale-up |
| CN113407301A (en) * | 2021-05-22 | 2021-09-17 | 济南浪潮数据技术有限公司 | Virtual machine monitoring method, system, storage medium and equipment |
| CN113515371A (en) * | 2021-05-11 | 2021-10-19 | 上海安畅网络科技股份有限公司 | Cloud resource dividing method, device, equipment and storage medium |
| CN114138477A (en) * | 2021-11-24 | 2022-03-04 | 中国人民解放军军事科学院战争研究院 | Information system running state service resource allocation method |
| CN114615177A (en) * | 2022-03-03 | 2022-06-10 | 腾讯科技（深圳）有限公司 | Load detection method and device of cloud platform, electronic equipment and storage medium |
| CN115766474A (en) * | 2022-10-31 | 2023-03-07 | 南方电网数字平台科技(广东)有限公司 | Virtual resource life cycle management method suitable for cloud platform operation |
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090055274A1 (en) * | 2001-12-17 | 2009-02-26 | International Business Machines Corporation | Method and apparatus for distributed application execution |
| CN102681899A (en) * | 2011-03-14 | 2012-09-19 | 金剑 | Virtual computing resource dynamic management system of cloud computing service platform |
| CN105528234A (en) * | 2014-10-24 | 2016-04-27 | 中兴通讯股份有限公司 | Virtual machine migration processing method and device |
| CN106230986A (en) * | 2016-09-21 | 2016-12-14 | 南方电网科学研究院有限责任公司 | The resource adaptation dispatching patcher of a kind of electrically-based PaaS cloud platform and method |
-
2017
- 2017-02-24 CN CN201710105788.6A patent/CN106686136A/en active Pending
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20090055274A1 (en) * | 2001-12-17 | 2009-02-26 | International Business Machines Corporation | Method and apparatus for distributed application execution |
| CN102681899A (en) * | 2011-03-14 | 2012-09-19 | 金剑 | Virtual computing resource dynamic management system of cloud computing service platform |
| CN105528234A (en) * | 2014-10-24 | 2016-04-27 | 中兴通讯股份有限公司 | Virtual machine migration processing method and device |
| CN106230986A (en) * | 2016-09-21 | 2016-12-14 | 南方电网科学研究院有限责任公司 | The resource adaptation dispatching patcher of a kind of electrically-based PaaS cloud platform and method |
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107231264A (en) * | 2017-07-25 | 2017-10-03 | 北京百度网讯科技有限公司 | For the method and apparatus for the capacity for managing Cloud Server |
| CN107506241A (en) * | 2017-08-25 | 2017-12-22 | 郑州云海信息技术有限公司 | A kind of flexible method of cloud platform automatic elastic |
| WO2019144788A1 (en) * | 2018-01-24 | 2019-08-01 | 中兴通讯股份有限公司 | Resource control method and device, equipment and computer readable storage medium |
| CN109445931A (en) * | 2018-08-31 | 2019-03-08 | 安徽四创电子股份有限公司 | A kind of big data resource scheduling system and method |
| CN110809062A (en) * | 2019-11-14 | 2020-02-18 | 苏州思必驰信息科技有限公司 | Public cloud voice recognition resource calling control method and device |
| CN110809062B (en) * | 2019-11-14 | 2022-03-25 | 思必驰科技股份有限公司 | Public cloud voice recognition resource calling control method and device |
| CN113127187A (en) * | 2019-12-31 | 2021-07-16 | 北京百度网讯科技有限公司 | Method and apparatus for cluster scale-up |
| CN111708604A (en) * | 2020-05-28 | 2020-09-25 | 北京赛博云睿智能科技有限公司 | Intelligent operation and maintenance supporting method |
| CN113515371A (en) * | 2021-05-11 | 2021-10-19 | 上海安畅网络科技股份有限公司 | Cloud resource dividing method, device, equipment and storage medium |
| CN113407301A (en) * | 2021-05-22 | 2021-09-17 | 济南浪潮数据技术有限公司 | Virtual machine monitoring method, system, storage medium and equipment |
| CN114138477A (en) * | 2021-11-24 | 2022-03-04 | 中国人民解放军军事科学院战争研究院 | Information system running state service resource allocation method |
| CN114138477B (en) * | 2021-11-24 | 2022-06-03 | 中国人民解放军军事科学院战争研究院 | Information system running state service resource allocation method |
| CN114615177A (en) * | 2022-03-03 | 2022-06-10 | 腾讯科技（深圳）有限公司 | Load detection method and device of cloud platform, electronic equipment and storage medium |
| CN114615177B (en) * | 2022-03-03 | 2023-10-13 | 腾讯科技（深圳）有限公司 | Load detection method and device of cloud platform, electronic equipment and storage medium |
| CN115766474A (en) * | 2022-10-31 | 2023-03-07 | 南方电网数字平台科技(广东)有限公司 | Virtual resource life cycle management method suitable for cloud platform operation |
| CN115766474B (en) * | 2022-10-31 | 2024-04-26 | 南方电网数字平台科技(广东)有限公司 | Virtual resource life cycle management method suitable for cloud platform operation |
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