CN105511952B - Resource self-migration method and system based on cloud computing platform - Google Patents
Resource self-migration method and system based on cloud computing platform Download PDFInfo
- Publication number
- CN105511952B CN105511952B CN201410487099.2A CN201410487099A CN105511952B CN 105511952 B CN105511952 B CN 105511952B CN 201410487099 A CN201410487099 A CN 201410487099A CN 105511952 B CN105511952 B CN 105511952B
- Authority
- CN
- China
- Prior art keywords
- resources
- resource
- physical machine
- virtual machine
- computing
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Images
Abstract
The invention provides a resource self-migration method and system based on a cloud computing platform, belongs to the technical field of cloud computing, and can solve the problem that an existing resource balancing mechanism of cloud computing cannot guarantee that computing resources and storage resources are allocated to the same physical machine. The invention discloses a resource self-migration method based on a cloud computing platform, which comprises the following steps: mirroring the configured computing resources and storage resources for the virtual machine to the corresponding physical machine; and inquiring whether the computing resources and the management resources configured for the virtual machine are mirrored on the same physical machine, if not, positioning the physical machine where the storage resources are located, and automatically migrating the computing resources to the physical machine where the storage resources are located.
Description
Technical Field
The invention belongs to the technical field of cloud computing, and particularly relates to a resource self-migration method and system based on a cloud computing platform.
Background
Resource balancing mechanism of cloudstock (cloud computing): when a virtual machine is created, started or restarted on a cloud computing platform, corresponding computing resources and storage resources need to be allocated to the virtual machine, and as cloud computing can monitor the use condition of the resources in real time and select a proper physical machine to respectively deploy the computing resources and the storage resources of the virtual machine according to the monitoring result, the computing resources and the storage resources of the virtual machine are often deployed on different physical machines.
The virtual machine live migration technology comprises the following steps: the live migration is called dynamic migration or real-time migration, so that the IT operation and maintenance personnel can migrate the running virtual machine from one physical machine to another physical machine without pause time. The method and the system have the advantages that the running state of the whole virtual machine is migrated from one physical machine to another physical machine in a hot mode, after migration, the virtual machine still runs smoothly, and a user cannot perceive any difference.
AutoCS (cloud management platform): the method is a secondary development based on a cloudstock API (Application programming interface), adds more management functions, shields some specific operations of a bottom layer, and provides a strong use environment with an interface-friendly function for an end user.
The inventor finds that at least the following problems exist in the prior art: the resource balancing mechanism of cloud computing cannot guarantee that allocated computing resources and storage resources are on the same physical machine, and if the computing resources and the storage resources are not on the same physical machine, slow operation of the physical machine is caused, and meanwhile, IO efficiency is low.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a resource self-migration method and system based on a cloud computing platform, which can ensure that computing resources and storage resources of an applied virtual machine are on the same physical machine, maximize IO efficiency and simultaneously do not destroy the original function of shared storage, aiming at the problems existing in the existing resource balancing mechanism of cloud computing.
The technical scheme adopted for solving the technical problem of the invention is a resource self-migration method based on a cloud computing platform, which is characterized by comprising the following steps:
mirroring the configured computing resources and storage resources for the virtual machine to the corresponding physical machine;
and inquiring whether the computing resources and the management resources configured for the virtual machine are mirrored on the same physical machine, if not, positioning the physical machine where the storage resources are located, and automatically migrating the computing resources to the physical machine where the storage resources are located.
Preferably, before mirroring the configured computing resources and storage resources for the virtual machine onto the corresponding physical machine, the method further includes:
and creating a virtual machine cluster, and configuring computing resources and storage resources for each virtual machine.
Preferably, configuring the computing resources and the storage resources for each virtual machine specifically includes:
and configuring computing resources and storage resources for each virtual machine through a cloud computing application program interface.
Preferably, when mirroring the computing resources and the storage resources of the virtual machine onto the corresponding physical machine, the method further includes:
and recording the address of the virtual machine and the addresses of the physical machines to which the computing resources and the storage resources are respectively mirrored so as to position the physical machine where the storage resources are located.
Preferably, before mirroring the computing resources and the storage resources of the virtual machine onto the corresponding physical machine, the method further includes:
and detecting the load condition of each physical machine through the cloud management platform, and starting mirroring the virtual machine from the physical machine with the lightest load.
Further preferably, the self-migration of the computing resource to the physical machine where the storage resource is located is performed starting from the physical machine with the lightest load, and the self-migration of the computing resource mirrored by the virtual machine is performed.
Preferably, the querying whether the computing resource and the management resource of the virtual machine are on the same physical machine, if the virtual machine is working normally, after the self-migration of the computing resource to the physical machine where the storage resource is located is not performed, the method further includes:
and periodically detecting the mirror image condition of the computing resource and the storage resource of each virtual machine through the cloud management platform.
The technical scheme adopted for solving the technical problem of the invention is a resource self-migration system based on a cloud computing platform, which comprises the following steps:
the resource management module is used for configuring corresponding computing resources and storage resources for each virtual machine;
the resource detection module is used for detecting whether the computing resources and the storage resources of each virtual machine are mirrored to the corresponding physical machine;
and the resource migration module is used for migrating the computing resource and the storage resource which are detected by the resource detection module and are not on the same physical machine, so that the computing resource is migrated to the physical machine where the storage resource is located.
Preferably, the resource recording module is configured to record an address of each virtual machine, and an address of a computing resource and a management resource of each virtual machine mirrored on the physical machine.
The invention has the beneficial effects that:
according to the resource self-migration method and system based on the cloud computing platform, the problem that a resource balance mechanism of cloud computing cannot guarantee that distributed computing resources and storage resources are on the same physical machine is solved according to actual requirements, the computing resources and the storage resources of the applied virtual machine are on the same physical machine, IO efficiency is maximized, and original functions of shared storage are not damaged.
Drawings
FIG. 1 is a schematic process diagram of self-migration in example 1 of the present invention;
fig. 2 is a flowchart of a resource self-migration method based on a cloud computing platform according to embodiment 1 of the present invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments.
The application scenarios of the embodiment mainly include the following four scenarios:
first, when a user creates a virtual machine, the resource balancing mechanism of cloud computing may cause the computing resources and storage resources to be allocated to different physical machines (HOST).
Second, when the user restarts the virtual machine, the cloud computing rebalances the computing resources and the storage resources of the virtual machine, and the computing resources and the storage resources are allocated to different physical machines.
Third, under certain abnormal conditions, such as split brain, the computing resources of the virtual machine may self-migrate.
Fourth, when a physical machine storing a virtual machine image is down, the storage resources of the virtual machine may also be self-migrated.
In this embodiment, the positioning process of the storage resource is as follows: according to the existing mechanism of Glusterfs, a randomly generated UUID (universally unique identifier) is processed by a hash algorithm, and then a physical machine list is obtained, so that the position of a physical machine where a storage resource is located is determined. In the embodiment, the generated UUID is intercepted before being called by the hash algorithm, and the value of the UUID is stored in the database. And calling an API provided by Glusterfs, taking the intercepted UUID as a parameter to obtain a physical machine list where the storage resource is located so as to complete the positioning of the storage resource, and after the positioning is completed, migrating the computing resource to the storage resource through thermal migration. The storage resources can also be located based on the interface development API provided by other types of File systems (such as GFS, Google File System).
The specific resource migration method and system are as follows.
Example 1:
with reference to fig. 1 and 2, the present embodiment provides a resource self-migration method based on a cloud computing platform, which includes the following steps:
step one, creating a virtual machine cluster, and configuring computing resources and storage resources for each virtual machine.
The step may specifically be: the cloud computing platform detects computing resources and storage resources of the virtual machine images, analyzes load conditions of all the physical machines, starts the virtual machines from the physical machine with the lightest load, and a user calls an Application Program Interface (API) of cloud computing through the cloud management platform to configure corresponding computing resources and storage resources for all the virtual machines.
And step two, mirroring the computing resources and the storage resources of the virtual machine to the corresponding physical machine.
While the step is carried out, the cloud management platform automatically records the address of the virtual machine and the address of the physical machine to which the computing resource and the storage resource are respectively mirrored, so as to judge whether the computing resource and the storage resource are supposed to be on the same physical machine in the following process.
And thirdly, inquiring whether the computing resources and the management resources of the virtual machine are on the same physical machine or not through the cloud management platform, if so, executing the next step, and otherwise, executing the next step after the computing resources are self-migrated to the physical machine where the storage resources are located.
When the self-migration occurs, the self-migration is started from the virtual machine corresponding to the physical machine with the lightest load, and the computing resource and the storage resource are migrated to the same physical.
And step four, the virtual machine works normally.
And step five, the cloud computing platform periodically inquires a mechanism, periodically detects the positions of the computing resources and the storage resources of the virtual machine, and immediately triggers the self-migration of the computing resources if the computing resources and the storage resources are not on the same physical machine.
According to the method, the problem that a resource balancing mechanism of cloud computing cannot guarantee that allocated computing resources and storage resources are on the same physical machine is solved, the computing resources and the storage resources of the applied virtual machine are on the same physical machine, IO efficiency is maximized, and original functions of shared storage are not damaged. Meanwhile, based on a cloud computing REST API and a monitoring API provided by a Glusterfs (a file system developed by Gluster corporation, which is a combination of various different storage servers, these servers are mutually converged by ethernet or Infiniband technology of infinite bandwidth and remote direct memory access RDMA, and finally form a large parallel file system network), a cloud management platform is utilized to monitor the distribution of computing resources and storage resources in the whole life cycle of a virtual machine, and the distribution of the computing resources is adjusted in real time, so as to achieve the purpose that the computing resources and the storage resources coexist in the same physical machine.
Example 2:
the embodiment provides a resource self-migration system of a cloud computing platform, which includes:
the resource management module is used for configuring corresponding computing resources and storage resources for each virtual machine; the resource detection module is used for detecting whether the computing resources and the storage resources of each virtual machine are mirrored to the corresponding physical machine; and the resource migration module is used for migrating the computing resource and the storage resource which are detected by the resource detection module and are not on the same physical machine, so that the computing resource is migrated to the physical machine where the storage resource is located.
When the resource self-migration system based on the cloud computing platform of this embodiment further includes: and the resource recording module is used for recording the address of each virtual machine, and the address of the computing resource and the management resource of each virtual machine mirrored to the physical machine.
The system of the present embodiment can operate according to the method described in embodiment 1, and is not described in detail herein.
It will be understood that the above embodiments are merely exemplary embodiments taken to illustrate the principles of the present invention, which is not limited thereto. It will be apparent to those skilled in the art that various modifications and improvements can be made without departing from the spirit and substance of the invention, and these modifications and improvements are also considered to be within the scope of the invention.
Claims (6)
1. A resource self-migration method based on a cloud computing platform is characterized by comprising the following steps:
detecting the load condition of each physical machine through a cloud management platform, and starting mirroring the virtual machines from the physical machine with the lightest load;
mirroring the configured computing resources and storage resources for the virtual machine to the corresponding physical machine;
inquiring whether the computing resources and the storage resources configured for the virtual machine are mirrored on the same physical machine, if not, positioning the physical machine where the storage resources are located, and self-migrating the computing resources to the physical machine where the storage resources are located, wherein when the computing resources and the storage resources of the virtual machine are mirrored on the corresponding physical machine, the method further comprises the following steps: and recording the address of the virtual machine and the addresses of the physical machines to which the computing resources and the storage resources are respectively mirrored so as to position the physical machine where the storage resources are located.
2. The cloud computing platform-based resource self-migration method according to claim 1, wherein before mirroring the configured computing resources and storage resources for the virtual machine onto the corresponding physical machine, further comprising:
and creating a virtual machine cluster, and configuring computing resources and storage resources for each virtual machine.
3. The resource self-migration method based on the cloud computing platform according to claim 2, wherein configuring computing resources and storage resources for each virtual machine specifically comprises:
and configuring computing resources and storage resources for each virtual machine through a cloud computing application program interface.
4. The resource self-migration method based on the cloud computing platform according to claim 1, wherein the self-migration of the computing resources to the physical machine on which the storage resources are located is performed by self-migrating the computing resources mirrored by the virtual machine, starting from the physical machine with the lightest load.
5. The cloud computing platform-based resource self-migration method according to any one of claims 1 to 4, further comprising:
the cloud management platform periodically detects the mirror image condition of the computing resources and the storage resources of each virtual machine.
6. A resource self-migration system based on a cloud computing platform is characterized by comprising:
the resource management module is used for configuring corresponding computing resources and storage resources for each virtual machine;
the resource detection module is used for detecting whether the computing resources and the storage resources of each virtual machine are mirrored to the corresponding physical machine, detecting the load condition of each physical machine and starting mirroring the virtual machines from the physical machine with the lightest load;
the resource migration module is used for migrating the computing resources detected by the resource detection module and the storage resources which are not on the same physical machine, so that the computing resources are migrated to the physical machine where the storage resources are located;
and the resource recording module is used for recording the address of each virtual machine, and the address of the computing resource and the storage resource of each virtual machine mirrored to the physical machine.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410487099.2A CN105511952B (en) | 2014-09-22 | 2014-09-22 | Resource self-migration method and system based on cloud computing platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201410487099.2A CN105511952B (en) | 2014-09-22 | 2014-09-22 | Resource self-migration method and system based on cloud computing platform |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105511952A CN105511952A (en) | 2016-04-20 |
| CN105511952B true CN105511952B (en) | 2020-02-04 |
Family
ID=55719958
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410487099.2A Active CN105511952B (en) | 2014-09-22 | 2014-09-22 | Resource self-migration method and system based on cloud computing platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105511952B (en) |
Families Citing this family (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112130955A (en) * | 2020-09-02 | 2020-12-25 | 中国电子科技网络信息安全有限公司 | Virtual machine scheduling method based on converged framework cloud platform |
| CN112241304B (en) * | 2020-10-12 | 2023-09-26 | 北京计算机技术及应用研究所 | Loongson cluster super-fusion resource scheduling method and device and Loongson cluster |
| CN113467941A (en) * | 2021-06-25 | 2021-10-01 | 北京汇钧科技有限公司 | Method and device for sharing information |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102546735A (en) * | 2011-01-04 | 2012-07-04 | 中兴通讯股份有限公司 | Cloud computing system, cloud computing method and cloud |
| CN102801806A (en) * | 2012-08-10 | 2012-11-28 | 薛海强 | Cloud computing system and cloud computing resource management method |
| CN103002044A (en) * | 2012-12-18 | 2013-03-27 | 武汉大学 | Method for improving processing capability of multi-platform intelligent terminal |
| WO2013097147A1 (en) * | 2011-12-29 | 2013-07-04 | 华为技术有限公司 | Cloud computing system and method for managing storage resources therein |
| CN103248659A (en) * | 2012-02-13 | 2013-08-14 | 北京华胜天成科技股份有限公司 | Method and system for dispatching cloud computed resources |
| CN103595780A (en) * | 2013-11-08 | 2014-02-19 | 中国人民解放军理工大学 | Cloud computing resource scheduling method based on repeat removing |
| CN103593226A (en) * | 2013-11-04 | 2014-02-19 | 国云科技股份有限公司 | Method for improving IO performance of disc of virtual machine |
| CN103856502A (en) * | 2012-11-29 | 2014-06-11 | 北京华胜天成科技股份有限公司 | Method and NAS cluster system for realizing mirror image document thermal migration of virtual machine |
| CN104008002A (en) * | 2014-06-17 | 2014-08-27 | 电子科技大学 | Target host selection method for deploying virtual machine under cloud platform environment |
-
2014
- 2014-09-22 CN CN201410487099.2A patent/CN105511952B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102546735A (en) * | 2011-01-04 | 2012-07-04 | 中兴通讯股份有限公司 | Cloud computing system, cloud computing method and cloud |
| WO2013097147A1 (en) * | 2011-12-29 | 2013-07-04 | 华为技术有限公司 | Cloud computing system and method for managing storage resources therein |
| CN103248659A (en) * | 2012-02-13 | 2013-08-14 | 北京华胜天成科技股份有限公司 | Method and system for dispatching cloud computed resources |
| CN102801806A (en) * | 2012-08-10 | 2012-11-28 | 薛海强 | Cloud computing system and cloud computing resource management method |
| CN103856502A (en) * | 2012-11-29 | 2014-06-11 | 北京华胜天成科技股份有限公司 | Method and NAS cluster system for realizing mirror image document thermal migration of virtual machine |
| CN103002044A (en) * | 2012-12-18 | 2013-03-27 | 武汉大学 | Method for improving processing capability of multi-platform intelligent terminal |
| CN103593226A (en) * | 2013-11-04 | 2014-02-19 | 国云科技股份有限公司 | Method for improving IO performance of disc of virtual machine |
| CN103595780A (en) * | 2013-11-08 | 2014-02-19 | 中国人民解放军理工大学 | Cloud computing resource scheduling method based on repeat removing |
| CN104008002A (en) * | 2014-06-17 | 2014-08-27 | 电子科技大学 | Target host selection method for deploying virtual machine under cloud platform environment |
Non-Patent Citations (1)
| Title |
|---|
| A virtual machine based task scheduling approach to improving data locality for virtualized Hadoop;Ruiqi Sun1,2，Jie Yang2;《2014 IEEE/ACIS 13th International Conference on Computer and Information Science (ICIS)》;20140606;第297-302页 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN105511952A (en) | 2016-04-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11226847B2 (en) | Implementing an application manifest in a node-specific manner using an intent-based orchestrator | |
| CN107689953B (en) | Multi-tenant cloud computing-oriented container security monitoring method and system | |
| CN110865867B (en) | Method, device and system for discovering application topological relation | |
| CN106982236B (en) | Information processing method, device and system | |
| CN107451147B (en) | Method and device for dynamically switching kafka clusters | |
| US20160191304A1 (en) | Layer 3 high availability router | |
| CN104182288A (en) | Method for automatically testing power consumption of server cluster system | |
| US20170060671A1 (en) | Anomaly recovery method for virtual machine in distributed environment | |
| CN103064717B (en) | A kind of apparatus and method of parallel installation of software for cluster system | |
| CN109213571B (en) | Memory sharing method, container management platform and computer readable storage medium | |
| WO2018121334A1 (en) | Web application service providing method, apparatus, electronic device and system | |
| CN104166589A (en) | Heartbeat package processing method and device | |
| CN108491163B (en) | Big data processing method and device and storage medium | |
| CN112202853B (en) | Data synchronization method, system, computer device and storage medium | |
| CN113204353B (en) | Big data platform assembly deployment method and device | |
| CN105511952B (en) | Resource self-migration method and system based on cloud computing platform | |
| US9921878B1 (en) | Singleton coordination in an actor-based system | |
| CN107943615B (en) | Data processing method and system based on distributed cluster | |
| CN103810038A (en) | Method and device for transferring virtual machine storage files in HA cluster | |
| EP3391208A2 (en) | Automatic system response to external field-replaceable unit (fru) process | |
| CN105323271B (en) | Cloud computing system and processing method and device thereof | |
| US10855563B2 (en) | Supplementing log messages with metadata | |
| CN108228272B (en) | WEB container generation processing method, equipment and server | |
| US9348672B1 (en) | Singleton coordination in an actor-based system | |
| CN112583740B (en) | Network communication method and device |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| TA01 | Transfer of patent application right | ||
| TA01 | Transfer of patent application right |
Effective date of registration: 20191105 Address after: No. 1-1 Suning Avenue, Xuzhuang Software Park, Xuanwu District, Nanjing City, Jiangsu Province, 210000 Applicant after: Suning cloud computing Co., Ltd Address before: 210042 Jiangsu, Xuanwu District, Nanjing, Nanjing Road, No. 1, building No. 15 Applicant before: Yun Shang Group Plc of Suning |
|
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20201117 Address after: No.1-9 Suning Avenue, Xuanwu District, Nanjing City, Jiangsu Province Patentee after: NANJING SUNING ELECTRONIC INFORMATION TECHNOLOGY Co.,Ltd. Address before: No. 1-1 Suning Avenue, Xuzhuang Software Park, Xuanwu District, Nanjing City, Jiangsu Province, 210000 Patentee before: Suning Cloud Computing Co.,Ltd. |