CN106528270A - Automatic migration method and system of virtual machine based on OpenStack cloud platform - Google Patents
Automatic migration method and system of virtual machine based on OpenStack cloud platform Download PDFInfo
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- CN106528270A CN106528270A CN201611007753.0A CN201611007753A CN106528270A CN 106528270 A CN106528270 A CN 106528270A CN 201611007753 A CN201611007753 A CN 201611007753A CN 106528270 A CN106528270 A CN 106528270A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F9/00—Arrangements for program control, e.g. control units
- G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
- G06F9/44—Arrangements for executing specific programs
- G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
- G06F9/45533—Hypervisors; Virtual machine monitors
- G06F9/45558—Hypervisor-specific management and integration aspects
- G06F2009/4557—Distribution of virtual machine instances; Migration and load balancing
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Abstract
The invention discloses an automatic migration method of a virtual machine based on a cloud platform. The method comprises the following steps: determining the migration time of virtual machines according to the load of a host server; setting the weight according to the ratio of the resource usage on the host server and calculating the migration amount, and selecting the virtual machine with a larger migration value as a virtual machine to be migrated; and randomly selecting the migration target server of the virtual machine to be migrated according to the remaining resource on the host server and the probability value. The invention also relates to a system, comprising a migration time determination unit, a virtual machine to be migrated determination unit, and a migration target server determination unit. The automatic migration method and system disclosed by the invention have the effects that the load of the server is predicted by using an exponential smoothing method, and thus unnecessary migration overhead can be avoided; the target server is selected in a probability mode, so the clustering effect can be avoided; and the weight is set according to the usage of the resource during the entire process of migrating the virtual machines, and thus the operation bottlenecks of the cloud platform can be more easily discovered.
Description
Technical field
The present invention relates to cloud platform calculating field, and more particularly, to a kind of void based on OpenStack cloud platforms
Plan machine Autonomic Migration Framework method level system.
Background technology
Open1tack is the cloud computing management platform project of increasing income of current most main flow, has been combined by several main components
To complete specific works.OpenStack supports almost all kinds of cloud environment, project objective be to provide enforcement it is simple, can be big
The unified cloud computing management platform of Expansion, abundant, standard.OpenStack is provided the foundation by various complementary services
Facility services the solution of (IaaS), and it is integrated to carry out that each service provides API.
OpenStack virtual machines due to reasons such as the hardware limitation of machine itself, load excessives, are made in running
The stability of primary physical main frame is reduced all night, therefore in order to ensure the quality of virtual machine service, when load excessive occurs in certain main frame
When, need the partial virtual machine for running main frame migration to discharge resource.When migration operation occurs, virtual machine can be from source master
Machine is backuped to the data of virtual machine on destination host by network data transmission with certain moving method, has completed to migrate
Journey.The migration of virtual machine, is exactly the transfer of data in fact, and the data being transferred mainly include two parts:Static data：It is stored in
Local virtual machine image file, including rear end mirror image and the single increment image file of virtual machine；Dynamic data：Internal memory is interior deficiency
Data when plan machine runs, the data in internal memory are the data of dynamic change, and the size of the load of virtual machine operation is directly affected
The time length of migration.
Although OpenStack is had been realized in the main flow Intel Virtualization Technology such as VMware, KVM, XenServer, XCP at present
Support, but it is powerful due to KVM technologies, it is first-selected underlying virtual technology that current KVM is remained.Traditional KVM is virtual
Machine migration includes static migrating, 2 kinds of modes of dynamic migration, and dynamic migration includes the dynamic migration based on shared storage and based on this
2 kinds of implementation methods of dynamic migration of ground storage.
Static migrating is also referred to as general migration or offline migration, refers in the state of virtual machine shuts down or suspends from one
Platform host's physical host moves to the process of another host's physical host.Because the file system of virtual machine is set up in virtual machine
Above mirror image, so in the case where virtual machine shuts down, it is only necessary to simply migrate virtual machine image and corresponding configuration file
To on an other physical host.If necessary to preserve the state before virtual machine (vm) migration, virtual machine is suspended before migration,
Then copy state is finally rebuild virtual machine state in purpose host physical host and recovery is held to purpose host's physical host
OK.The transition process of this mode needs the operation for explicitly stopping virtual machine.
Dynamic migration is also referred to as online migration, while referring to that various services normally run in virtual machine is ensured, by
Dummy machine system moves to the process of another host's physical host from host's physical host.Dynamic migration mainly includes two
Kind of mode, dynamic migration method based on shared storage and based on locally stored virtual machine migration method.
Referred between sourcesink primary physical main frame and purpose host's physical host based on the dynamic migration method of shared storage
Using the centralized shared of SAN (storage area network) or NAS (network attached storage) etc
External equipment, the image file and associated profile needed for virtual machine operation are stored in middle shared external equipment.This
Sample, completes migration by only needing to for virutal machine memory to perform state transition in host's physical host in transition process.
Block migration is also referred to as based on locally stored virtual machine (vm) migration, the disk mirroring file and correlation of virtual machine is referred to
Configuration file is stored in sourcesink primary physical main frame, and transition process first has to complete disk mirroring file migration to purpose host
In physical host, virutal machine memory is performed into state transition again then migration can be completed in host's physical host.
Virtual machine (vm) migration process under cloud environment is mainly by three committed steps：1. most preferably, i.e., when physical node migrate
It is determined that migration opportunity；2. select which virtual machine (vm) migration can make expense it is less, release resource it is more, i.e., virtual machine to be migrated
Selection；3. cloud environment may have a large amount of server groups into by optimal on virtual machine (vm) migration to which server, that is, the mesh for migrating
The selection of mark server.The migration work of virtual machine in cloud platform, task granularity are big, and the data volume transmitted during migration is also big, because
And migration overhead be can not ignore.Secondly, the migration strategy of most virtual machines is based only upon the load of threshold value, i.e. Node station
The upper bound of load threshold is exceeded, then the Node station just triggers a migration；So, momentary load peak value will trigger virtual machine
Migration, easily causes the waste on unnecessary migration overhead.Finally, in cloud platform, multiple servers are believed based on identical load
Breath may select same server as destination node, cause selected destination node to load and sharply increase, cause group
Poly- effect.
With flourishing for cloud computing technology currently with OpenStack as representative, increasing enterprises and individuals
User starts to put in the research and development use of OpenStack.As an inappropriate virtual machine (vm) migration determines to cause very
Big expense, the equilibrium for finding suitable moving method at present to ensure OpenStack cloud platform resources are utilized and become one
New breakthrough mouth.
The content of the invention
In order to solve the above problems, according to an aspect of the invention, there is provided a kind of based on OpenStack cloud platforms
Virtual machine Autonomic Migration Framework method, methods described include：
The virtual machine (vm) migration time is determined according to the load of home server, wherein the load of the home server includes：
The utilization rate of CPU, internal memory and bandwidth；
The ratio used according to resource in the home server sets weight computation migration amount, select migration value compared with
Big virtual machine is used as virtual machine to be migrated；And
The virtual machine to be migrated is randomly choosed according to probit according to the remaining situation of resource in the home server
Migration destination server.
Preferably, wherein using the EXSMOOTH in time series forecasting technology in follow-up time to home server
Loading condition calculated, when load more than setting threshold value for a period of time when trigger transition condition.
Preferably, wherein continuing the time in the rear and to the formula that the loading condition of home server is calculated being：
Wherein, Zt+1For the loading condition of the home server at t+1 moment, α is weight coefficient.
Preferably, wherein the computing formula of the migration amount is：
Rp=(Cicq+Mimq+Lilq)/mq,
Wherein, the utilization rate of the CPU of server i, internal memory and bandwidth is respectively Ci、MiAnd Li, the virtual machine q on server i
The usage amount of CPU, internal memory and bandwidth be respectively cq、mqAnd lq, RpFor the migration amount of virtual machine q.
Preferably, wherein the computing formula of the probability is：
Wherein, XiFor the surplus resources of server i, PiFor the probability of selection target server.
Preferably, wherein the computing formula of the surplus resources of the server i is：
Xi=C × (1-Ci)+M×(1-Mi)+L×(1-Li),
Wherein, the utilization rate of the CPU of whole server cluster, internal memory and bandwidth respectively C, M and L, the CPU of server i,
The utilization rate of internal memory and bandwidth is respectively Ci、MiAnd Li。
According to another aspect of the present invention, there is provided a kind of virtual machine Autonomic Migration Framework system based on cloud platform, it is described
System includes：
Migration time determining unit, determines the virtual machine (vm) migration time according to the load of home server, wherein the host
The load of server includes：The utilization rate of CPU, internal memory and bandwidth；
Virtual machine determining unit to be migrated, sets weight according to the ratio that resource in the home server is used and calculates
Migration amount, the virtual machine for selecting migration value larger is used as virtual machine to be migrated；And
Migration destination server determining unit, according to the remaining situation of resource in the home server according to probit with
Machine selects the migration destination server of the virtual machine to be migrated.
The beneficial effects of the present invention is：
1. load of the present invention using the method for exponential smoothing to server be predicted, it is to avoid load it is instantaneous extremely
Value causes unnecessary migration overhead.
2. the present invention provide method not in a fixed manner by virtual machine (vm) migration to the best server node of performance,
And allow for the CPU and internal memory two indices of server selection target server in a probabilistic manner, it is to avoid bunching effect.
3., when being related to the evaluation index of resource during the entire process of virtual machine is migrated, set according to the service condition of resource
Different weights are put, rather than is treated on an equal basis, be more beneficial for finding the operation bottleneck of cloud platform.
Description of the drawings
By reference to the following drawings, the illustrative embodiments of the present invention can be more fully understood by：
Fig. 1 is the flow chart figure of the migration virtual machine Autonomic Migration Framework method 100 according to embodiment of the present invention；And
Fig. 2 is the structural representation of the virtual machine Autonomic Migration Framework system 200 according to embodiment of the present invention.
Specific embodiment
With reference now to accompanying drawing, the illustrative embodiments of the present invention are introduced, however, the present invention can be with many different shapes
Formula is implementing, and is not limited to embodiment described herein, there is provided these embodiments are to disclose at large and fully
The present invention, and the scope of the present invention is fully passed on to person of ordinary skill in the field.For showing for being illustrated in the accompanying drawings
Term in example property embodiment is not limitation of the invention.In the accompanying drawings, identical cells/elements are attached using identical
Icon is remembered.
Unless otherwise stated, term (including scientific and technical terminology) used herein has to person of ordinary skill in the field
It is common to understand implication.Further it will be understood that the term limited with the dictionary being usually used, is appreciated that and which
The linguistic context of association area has consistent implication, and is not construed as Utopian or excessively formal meaning.
Present invention is generally directed to the virtual machine (vm) migration problem of OpenStack cloud platforms, it is proposed that a kind of to ensure OpenStack
The method that cloud platform resources balance is utilized.The method is just touched more than the threshold duration for setting for a period of time according to the load of virtual machine
Deportation is moved, it is to avoid the instantaneous extremum of load causes unnecessary migration overhead.Select to consume host according to the index of definition
Machine resource is more but the less virtual machine of transmitted data amount is being migrated, and does not finally arrive virtual machine (vm) migration in a fixed manner
The best server node of performance, and allow for the CPU and internal memory two indices of server selection target in a probabilistic manner
Server, it is to avoid bunching effect.
The premise of technical scheme is the server configures identical situation in cloud platform, is moved in whole virtual machine
During shifting, various resources are not equal to treat, but distribute different weights according to the service condition of resource at this stage.Example
Such as, the utilization rate of server CPU is higher at this stage, illustrates that available cpu resource is shorter, then in the negative of calculation server
During load, weight shared by which is larger.Assume whole server cluster of a certain moment CPU, internal memory and bandwidth utilization rate be respectively C,
The utilization rate of the CPU, internal memory and bandwidth of M and L, server i is respectively Ci, Mi and Li, then the load Zi for server i is counted
Calculating formula is：Zi=C × Ci+M×Mi+L×Li, the Xi of server i surplus resources is calculated as Xi=C × (1-Ci)+M×(1-Mi)
+L×(1-Li)。
Fig. 1 is the flow chart figure of the migration virtual machine Autonomic Migration Framework method 100 according to embodiment of the present invention.Such as Fig. 1 institutes
Show, the Autonomic Migration Framework method 100 determines virtual machine according to the load of home server in step 101 from the beginning of step 101 place
Migration time, wherein the load of the home server includes：The utilization rate of CPU, internal memory and bandwidth.
The index that server load is primarily upon includes the service condition of CPU, internal memory and bandwidth, in order to avoid the wink of load
When the unnecessary migration that causes of peak value, determine for load just to trigger transition condition for a period of time more than the threshold value of setting.It is preferred that
Ground, wherein being entered to the loading condition of home server in follow-up time using the EXSMOOTH in time series forecasting technology
Row is calculated, and triggers transition condition when loading more than the threshold value for setting for a period of time.Preferably, wherein continuing the time pair in the rear
The formula that the loading condition of home server is calculated is：
Where it is assumed that the load value sequence of change calculations is over time：z1, z2..., zt-1, Zt+1For the t+1 moment
Home server loading condition, α is weight coefficient.Can see that weight coefficient is decayed according to geometrical progression, more closely
Data flexible strategy it is bigger, more remote data flexible strategy are less, and flexible strategy sum be equal to 1.Compared with threshold value come really according to the value of prediction
Whether the virtual machine in the fixed server needs migration.
Preferably, weight computation migration are set according to the ratio that resource in the home server is used in step 102
Amount, the virtual machine for selecting migration value larger is used as virtual machine to be migrated.Preferably, wherein the computing formula of the migration amount
For：
Rp=(Cicq+Mimq+Lilq)/mq,
Wherein, the utilization rate of the CPU of server i, internal memory and bandwidth is respectively Ci、MiAnd Li；Virtual machine q on server i
The usage amount of CPU, internal memory and bandwidth be respectively cq、mqAnd lq；RpFor the migration amount of virtual machine q.
At present, the iteration copy of the mainly virutal machine memory mirror image that the online migration of virtual machine is relied on, due to internal memory mirror
As very big, so network bandwidth resources are topmost migration overheads in transition process.In view of virtual machine place server
The service condition of resource, sets different weights to show its significance level, shared by predominantly CPU, internal memory and bandwidth utilization rate
Weight, will take that server resource is more and the less virtual machine (vm) migration of committed memory is on other servers.
Preferably, randomly choosed according to probit according to the remaining situation of resource in the home server in step 103
The migration destination server of the virtual machine to be migrated.Multiple migration operations occur at certain moment selects combination property best simultaneously
Server as destination server, the decline for causing performance using increasing sharply of resource in the node short time can be caused, so
It is not fixed selection when destination server is selected, but according to the remaining situation of server resource according to certain probability
At random come select migrate destination server.The number between one [0,1] is generated using random function, is then scolded at which according to this
The probability space of individual destination server is determining migration destination server.
Preferably, wherein the computing formula of the probability is：
Wherein, XiFor the surplus resources of server i, PiFor the probability of selection target server, and the destination server for selecting
Probability and be 1.
Preferably, wherein the computing formula of the surplus resources of the server i is：
Xi=C × (1-Ci)+M×(1-Mi)+L×(1-Li),
Wherein, the utilization rate of the CPU of whole server cluster, internal memory and bandwidth respectively C, M and L, the CPU of server i,
The utilization rate of internal memory and bandwidth is respectively Ci、MiAnd Li。
Fig. 2 is the structural representation of the virtual machine Autonomic Migration Framework system 200 according to embodiment of the present invention.As shown in Fig. 2
The Autonomic Migration Framework system 200 includes：Migration time determining unit 201, virtual machine determining unit 202 to be migrated and migration target
Server determining unit 203.When migration time determining unit 201 determines virtual machine (vm) migration according to the load of home server
Between, wherein the load of the home server includes：The utilization rate of CPU, internal memory and bandwidth.
Preferably, virtual machine determining unit to be migrated 202 according to resource in the home server using ratio set
Determine weight computation migration amount, the virtual machine for selecting migration value larger is used as virtual machine to be migrated.
Preferably, migrating remaining situation of the destination server determining unit 203 according to resource in the home server
The migration destination server of the virtual machine to be migrated is randomly choosed according to probit.
The present invention is described by reference to a small amount of embodiment.However, it is known in those skilled in the art, as
What subsidiary Patent right requirement was limited, except the present invention other embodiments disclosed above equally fall the present invention's
In the range of.
Normally, all terms for using in the claims are all solved in the usual implication of technical field according to them
Release, unless clearly defined in addition wherein.It is all of to be all opened ground with reference to " one/described/be somebody's turn to do [device, component etc.] "
At least one of described device, component etc. example is construed to, unless otherwise expressly specified.Any method disclosed herein
Step all need not be run with disclosed accurate order, unless explicitly stated otherwise.
Claims (7)
1. a kind of virtual machine Autonomic Migration Framework method based on cloud platform, it is characterised in that methods described includes：
The virtual machine (vm) migration time is determined according to the load of home server, wherein the load of the home server includes：CPU、
The utilization rate of internal memory and bandwidth；
Weight computation migration amount are set according to the ratio that resource in the home server is used, selects migration value larger
Virtual machine is used as virtual machine to be migrated；And
Moving for the virtual machine to be migrated is randomly choosed according to probit according to the remaining situation of resource in the home server
Move destination server.
2. method according to claim 1, it is characterised in that using the EXSMOOTH in time series forecasting technology
The loading condition of home server is calculated in follow-up time, the triggering when loading more than the threshold value for setting for a period of time is moved
Shifting condition.
3. method according to claim 2, it is characterised in that continue loading condition of the time to home server in the rear
The formula of calculating is：
Wherein, Zt+1For the loading condition of the home server at t+1 moment, α is weight coefficient.
4. method according to claim 1, it is characterised in that the computing formula of the migration amount is：
Rp=(Cicq+Mimq+Lilq)/mq,
Wherein, the utilization rate of the CPU of server i, internal memory and bandwidth is respectively Ci、MiAnd Li, the virtual machine q's on server i
The usage amount of CPU, internal memory and bandwidth is respectively cq、mqAnd lq, RpFor the migration amount of virtual machine q.
5. method according to claim 1, it is characterised in that the computing formula of the probability is：
Wherein, XiFor the surplus resources of server i, PiFor the probability of selection target server.
6. method according to claim 5, it is characterised in that the computing formula of the surplus resources of the server i is：
Xi=C × (1-Ci)+M×(1-Mi)+L×(1-Li),
Wherein, the utilization rate of the CPU of whole server cluster, internal memory and bandwidth is respectively C, M and L, the CPU of server i, internal memory
C is respectively with the utilization rate of bandwidthi、MiAnd Li。
7. a kind of virtual machine Autonomic Migration Framework system based on cloud platform, it is characterised in that the system includes：
Migration time determining unit, determines the virtual machine (vm) migration time according to the load of home server, wherein the hosted service
The load of device includes：The utilization rate of CPU, internal memory and bandwidth；
Virtual machine determining unit to be migrated, sets weight computation migration according to the ratio that resource in the home server is used
Amount, the virtual machine for selecting migration value larger is used as virtual machine to be migrated；And migration destination server determining unit, according to institute
The remaining situation for stating resource in home server randomly chooses the migration destination service of the virtual machine to be migrated according to probit
Device.
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| CN111274230B (en) * | 2020-03-26 | 2024-03-08 | 北京奇艺世纪科技有限公司 | Data migration management method, device, equipment and storage medium |
| CN115878329A (en) * | 2023-02-02 | 2023-03-31 | 天翼云科技有限公司 | Host resource scheduling method and device, electronic equipment and storage medium |
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