CN113590342A - Resource allocation method and system in cloud computing system - Google Patents
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Abstract
The application relates to the technical field of cloud computing, in particular to a resource allocation method and system in a cloud computing system, which comprises the following steps: acquiring a characteristic parameter of an access request; calculating a selection index for selecting the virtual server according to the obtained characteristic parameters; taking a virtual server meeting the selection index requirement in the virtual servers as a target to be selected; obtaining an optimal virtual server from the target to be selected by considering the residual life value of the physical server; and processing the access request through the optimal virtual server. The method and the device can reasonably distribute the resources of the cloud computing system, and ensure the performance of the cloud computing system.
Description
Technical Field
The present application relates to the field of cloud computing technologies, and in particular, to a method and a system for resource allocation in a cloud computing system.
Background
More and more applications are now migrating to the "cloud" such as various "cloud disk" storage that is exposed in life. In fact, "clouds" are not new, have been around for over 10 years, and are expanding into all areas. It is anticipated that in the next 10 years, almost all applications will be deployed to the cloud to provide a wide variety of services through the "cloud".
Therefore, as more and more applications are deployed to a remote location, the demand for resources in the cloud computing system will be higher and higher, and how to reasonably allocate the resources of the cloud computing system to ensure the performance of the cloud computing system is a technical problem that needs to be solved urgently by those skilled in the art at present.
Disclosure of Invention
The application provides a resource allocation method and system in a cloud computing system, which are used for reasonably allocating resources of the cloud computing system and ensuring the performance of the cloud computing system.
In order to solve the technical problem, the application provides the following technical scheme:
a resource allocation method in a cloud computing system comprises the following steps: step S110, acquiring characteristic parameters of the access request; step S120, calculating a selection index for selecting the virtual server according to the obtained characteristic parameters; step S130, taking a virtual server meeting the selection index requirement in the virtual servers as a target to be selected; step S140, obtaining an optimal virtual server from the target to be selected by considering the residual life value of the physical server; and step S150, processing the access request through the optimal virtual server.
The resource allocation method in the cloud computing system as described above, wherein preferably, the feature weight corresponding to the feature parameter is obtained according to the feature parameter; and obtaining a selection index for selecting the virtual server according to the obtained characteristic parameters and the characteristic weights corresponding to the characteristic parameters.
The resource allocation method in the cloud computing system as described above, wherein preferably, the resource remaining indicators of all the virtual servers belonging to the cloud computing data center are calculated; and comparing the obtained selection index with the resource residual index of each virtual server to select the virtual server meeting the selection index requirement, and taking the selected virtual server as a target to be selected.
The resource allocation method in the cloud computing system as described above, preferably, in a case that all the virtual servers do not meet the requirement of the selection index, one or more new virtual servers are created, or some virtual servers are destroyed first, then one or more new virtual servers are created, and then the computing capability of one or more original virtual servers is adjusted so as to meet the requirement of the selection index.
The resource allocation method in the cloud computing system as described above, wherein preferably, the remaining lifetime value of the physical server includes: the residual life value of the memory, the residual life value of the hard disk and the residual life value of the CPU.
A resource allocation system in a cloud computing system, comprising: the system comprises a characteristic acquisition module, an index calculation module, a virtual server selection module and an optimal virtual server confirmation module; the characteristic acquisition module acquires characteristic parameters of the access request; the index calculation module calculates a selection index for selecting the virtual server according to the obtained characteristic parameters; the virtual server selection module takes a virtual server meeting the selection index requirement in the virtual servers as a target to be selected; and the optimal virtual server confirmation module considers the residual life value of the physical server which depends on the optimal virtual server, obtains the optimal virtual server from the target to be selected, and processes the access request through the optimal virtual server.
In the resource allocation system in the cloud computing system, preferably, the index calculation module obtains a feature weight corresponding to the feature parameter according to the feature parameter, and obtains a selection index for selecting the virtual server according to the obtained feature parameter and the feature weight corresponding to the feature parameter.
In the resource allocation system in the cloud computing system, preferably, the virtual server selection module calculates resource remaining indicators of all virtual servers belonging to the cloud computing data center, compares the obtained selection indicator with the resource remaining indicator of each virtual server to select a virtual server meeting the selection indicator requirement, and uses the selected virtual server as the target to be selected.
The resource allocation system in the cloud computing system as described above, preferably, in a case that all the virtual servers do not meet the requirement of the selection index, the virtual server selection module creates one or more new virtual servers, or the virtual server selection module destroys some virtual servers first, and then creates one or more new virtual servers, or the virtual server selection module adjusts the computing capability of one or more original virtual servers, so that the computing capability of the one or more original virtual servers meets the requirement of the selection index.
The resource allocation system in the cloud computing system as described above, wherein preferably, the remaining lifetime value of the physical server includes: the residual life value of the memory, the residual life value of the hard disk and the residual life value of the CPU.
In order to solve the technical problem, according to the resource allocation method and system in the cloud computing system provided by the application, under the condition that the requirement of the selection index is met, the residual life value of the physical server on which the virtual server in the cloud computing system depends is considered, so that the physical resource of the physical server can be guaranteed to be utilized in a balanced manner, and only under the condition that the requirement of the selection index is not met, the virtual server in the cloud computing system is created, destroyed or adjusted, so that the change frequency of the virtual server is reduced, and the performance of the cloud computing system is improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and other drawings can be obtained by those skilled in the art according to the drawings.
Fig. 1 is a flowchart of a resource allocation method in a cloud computing system according to an embodiment of the present application;
fig. 2 is a schematic diagram of a resource allocation system in a cloud computing system according to an embodiment of the present application.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative only and should not be construed as limiting the invention.
Example one
As shown in fig. 1, the present application provides a resource allocation method in a cloud computing system, including the following steps:
step S110, acquiring characteristic parameters of the access request;
the server of the cloud computing data center comprises a plurality of physical servers and a plurality of virtual servers erected on the physical servers, and in the application, physical resources (such as a memory, a hard disk space and a CPU) of the physical servers are expected to be utilized in a balanced manner, and the virtual servers erected on the physical servers are expected to reduce expenses as much as possible on the premise of meeting computing requirements, namely, the dynamic creation or destruction frequency of the virtual servers is reduced as much as possible, and the frequency of adjusting the computing capacity of the virtual servers is reduced as much as possible.
Receiving an access request sent by a terminal, and acquiring characteristic parameters of the access request, wherein the characteristic parameters comprise: category parameters, required memory parameters, required hard disk parameters, required CPU parameters, and the like. The feature parameter sets are combined to form the feature parameter set
Wherein
is the 1 st characteristic parameter,
Is the 2 nd characteristic parameter,
Is the 3 rd characteristic parameter,
Is as follows
The characteristic parameters of the first and second groups are,
is the number of elements in the set. For example:
as category parameter (category parameter can be browsing web page, playing multimedia)Execution program file, etc.),
for the required memory parameters,
The required hard disk parameters,
Are the required CPU parameters.
Step S120, calculating a selection index for selecting the virtual server according to the obtained characteristic parameters;
each characteristic parameter has a preset characteristic weight, so that the characteristic weight corresponding to the characteristic parameter is obtained according to the characteristic parameter, and the characteristic weights are collected together to form a characteristic weight set
Wherein
the feature weight corresponding to the 1 st feature parameter,
the feature weight corresponding to the 2 nd feature parameter,
the feature weight corresponding to the 3 rd feature parameter,
is as follows
The feature weight corresponding to each feature parameter,
is the number of elements in the set.
According to the obtained characteristicsAnd obtaining a selection index for selecting the virtual server by the parameters and the characteristic weights corresponding to the parameters. Specifically, a selection index for selecting the virtual server is calculated according to the following formula:
wherein
for the selection index to be used for selecting a virtual server,
for the first acquired in the access request
The characteristic parameters of the first and second groups are,
is composed of
The weight of the feature of (a) is,
is the number of elements in the set.
Since the category parameters in the feature parameters are considered when calculating the selection index for selecting the virtual server, for example: browsing web pages, playing multimedia, executing program files, etc., so the calculated selection indicators reflect the types related to the access request to some extent, for example: if the user only needs to browse the webpage, the virtual server with less residual total memory amount, total hard disk amount and total CPU amount which can be applied can be selected as the target to be selected according to the calculated selection index so as to carry out the next operation; and if the user wants to watch the video, the virtual server with more residual memory total amount, hard disk total amount and CPU total amount which can be applied can be selected as the target to be selected according to the calculated selection index so as to carry out the next operation.
Step S130, taking a virtual server meeting the selection index requirement in the virtual servers as a target to be selected;
and calculating resource residual indexes of all virtual servers belonging to the cloud computing data center. Specifically, each virtual server has an operation status parameter, a memory occupancy rate, a hard disk occupancy rate, and a CPU utilization rate according to
And calculating to obtain the resource residual index of each virtual server. Wherein,
the resource residual index of the virtual server is obtained;
as an operation status parameter, if the virtual server is in an operation status
Is 1, if the virtual server is in a shutdown state, then
Is 0;
in order to achieve the memory usage rate,
the influence factor of the memory occupancy rate on the resource residual index is obtained;
as the occupancy rate of the hard disk,
the hard disk occupancy rate is an influence factor of the resource residual index;
in order to be able to use the CPU utilization,
and the CPU utilization factor is the influence factor of the resource residual index.
And comparing the obtained selection index with the resource residual index of each virtual server to select the virtual server meeting the selection index requirement, and taking the selected virtual server as a target to be selected. In particular, if
The virtual server meets the requirement of the selection index, the virtual server is taken as a target to be selected, and if the virtual server meets the requirement of the selection index, the virtual server is taken as the target to be selected
If the virtual server does not meet the requirement of the index, the virtual server is not listed as the target to be selected, wherein
To adjust the constant, it is an empirical value, taking the value 1.235.
Under the condition that all the virtual servers do not meet the requirement of the selection index, if the cloud computing data center has idle physical server resources (memory resources, hard disk resources, CPU resources and the like) meeting the requirement (namely meeting the requirement of processing the access request), one or more new virtual servers are created, so that the created new virtual servers meet the requirement of the selection index; or if the cloud computing data center does not have idle physical server resources meeting the requirements, destroying some virtual servers, and then creating one or more new virtual servers so as to enable the virtual servers to meet the selection index requirements; or, if the cloud computing data center has a certain amount of idle physical server resources, but the idle physical server resources do not meet the requirement of creating a new virtual server meeting the selection index requirement, adjusting the computing capacity of one or more original virtual servers to enable the computing capacity to meet the selection index requirement. By the virtual servers meeting the selection index requirement, the optimal virtual server can be selected from the virtual servers meeting the selection index to process the access request.
Step S140, obtaining an optimal virtual server from the target to be selected by considering the residual life value of the physical server;
specifically, the physical servers on which the virtual servers depend are of a lifetime, and the remaining lifetime values of the physical servers include: the residual life value of the memory, the residual life value of the hard disk, the residual life value of the CPU and the like. The residual life values of the physical servers depended by the virtual servers are integrated together to form a residual life value set
Wherein
the 1 st remaining life value of the physical server,
Is the 2 nd remaining life value of the physical server,
Is a physical server
The value of the remaining life of the battery,
is the number of elements in the set. For example:
is the residual life value of the memory of the physical server,
Is the residual life value of the hard disk of the physical server,
Is the remaining life value of the CPU of the physical server.
Obtaining the state value of each virtual server in the target to be selected through the following formula
. Wherein,
the impact of the remaining lifetime value of the physical server on which the virtual server depends on the state value of the virtual server is weighted,
the influence weight of the resource residual index of the virtual server on the state value of the resource residual index is determined,
，
，
can be obtained by utilizing ant colony algorithm or neural network training
And
of course, they can be obtained empirically;
is a physical server
The value of the remaining life of the battery,
is as follows
The difference between the remaining life value and its standard life value.
Step S150, processing the access request through the optimal virtual server;
and after the optimal virtual server is selected, processing the access request through the optimal virtual server, and sending the obtained processing result to the terminal as the response of the access request.
Example two
As shown in fig. 2, the present application further provides a resource allocation system 200 in a cloud computing system, including: a feature acquisition module 210, an index calculation module 220, a virtual server selection module 230, and an optimal virtual server validation module 240.
The feature obtaining module 210 obtains feature parameters of the access request.
The server of the cloud computing data center comprises a plurality of physical servers and a plurality of virtual servers erected on the physical servers, and in the application, physical resources (such as a memory, a hard disk space and a CPU) of the physical servers are expected to be utilized in a balanced manner, and the virtual servers erected on the physical servers are expected to reduce expenses as much as possible on the premise of meeting computing requirements, namely, the dynamic creation or destruction frequency of the virtual servers is reduced as much as possible, and the frequency of adjusting the computing capacity of the virtual servers is reduced as much as possible.
Receiving an access request sent by a terminal, and acquiring characteristic parameters of the access request, wherein the characteristic parameters comprise: category parameters, required memory parameters, required hard disk parameters, required CPU parameters, and the like. The feature parameter sets are combined to form the feature parameter set
Wherein
is the 1 st characteristic parameter,
Is the 2 nd characteristic parameter,
Is the 3 rd characteristic parameter,
Is as follows
The characteristic parameters of the first and second groups are,
is the number of elements in the set. For example:
for category parameters (category parameters may be browsing web pages, playing multimedia, executing program files, etc.)
For the required memory parameters,
The required hard disk parameters,
Are the required CPU parameters.
The index calculation module 220 calculates a selection index for selecting the virtual server according to the obtained characteristic parameters.
Each characteristic parameter has a preset characteristic weight, so that the characteristic weight corresponding to the characteristic parameter is obtained according to the characteristic parameter, and the characteristic weights are collected together to form a characteristic weight set
Wherein
the feature weight corresponding to the 1 st feature parameter,
the feature weight corresponding to the 2 nd feature parameter,
the feature weight corresponding to the 3 rd feature parameter,
is as follows
The feature weight corresponding to each feature parameter,
is the number of elements in the set.
And obtaining a selection index for selecting the virtual server according to the obtained characteristic parameters and the characteristic weights corresponding to the characteristic parameters. Specifically, a selection index for selecting the virtual server is calculated according to the following formula:
wherein
for the selection index to be used for selecting a virtual server,
for the first acquired in the access request
The characteristic parameters of the first and second groups are,
is composed of
The weight of the feature of (a) is,
is the number of elements in the set.
Since the category parameters in the feature parameters are considered when calculating the selection index for selecting the virtual server, for example: browsing web pages, playing multimedia, executing program files, etc., so the calculated selection indicators reflect the types related to the access request to some extent, for example: if the user only needs to browse the webpage, the virtual server with less residual total memory amount, total hard disk amount and total CPU amount which can be applied can be selected as the target to be selected according to the calculated selection index so as to carry out the next operation; and if the user wants to watch the video, the virtual server with more residual memory total amount, hard disk total amount and CPU total amount which can be applied can be selected as the target to be selected according to the calculated selection index so as to carry out the next operation.
The virtual server selection module 230 takes the virtual server satisfying the selection index requirement in the virtual servers as the target to be selected.
And calculating resource residual indexes of all virtual servers belonging to the cloud computing data center. Specifically, each virtual server has an operation status parameter, a memory occupancy rate, a hard disk occupancy rate, and a CPU utilization rate according to
And calculating to obtain the resource residual index of each virtual server. Wherein,
the resource residual index of the virtual server is obtained;
as an operation status parameter, if the virtual server is in an operation status
Is 1, if the virtual server is downState of then
Is 0;
in order to achieve the memory usage rate,
the influence factor of the memory occupancy rate on the resource residual index is obtained;
as the occupancy rate of the hard disk,
the hard disk occupancy rate is an influence factor of the resource residual index;
in order to be able to use the CPU utilization,
and the CPU utilization factor is the influence factor of the resource residual index.
And comparing the obtained selection index with the resource residual index of each virtual server to select the virtual server meeting the selection index requirement, and taking the selected virtual server as a target to be selected. In particular, if
If the virtual server meets the requirement of the selection index, the virtual server is taken as the target to be selected, and if the virtual server meets the requirement of the selection index, the virtual server is taken as the target to be selected
If the virtual server does not meet the requirement of the index, the virtual server is not listed as the target to be selected, wherein
To adjust the constantIs an empirical value, taking the value of 1.235.
Under the condition that all the virtual servers do not meet the requirement of the selection index, if the cloud computing data center has idle physical server resources (memory resources, hard disk resources, CPU resources and the like) meeting the requirement (namely meeting the requirement of processing the access request), one or more new virtual servers are created, so that the created new virtual servers meet the requirement of the selection index; or if the cloud computing data center does not have idle physical server resources meeting the requirements, destroying some virtual servers, and then creating one or more new virtual servers so as to enable the virtual servers to meet the selection index requirements; or, if the cloud computing data center has a certain amount of idle physical server resources, but the idle physical server resources do not meet the requirement of creating a new virtual server meeting the selection index requirement, adjusting the computing capacity of one or more original virtual servers to enable the computing capacity to meet the selection index requirement. By the virtual servers meeting the selection index requirement, the optimal virtual server can be selected from the virtual servers meeting the selection index to process the access request.
The optimal virtual server confirmation module 240 obtains an optimal virtual server from the target to be selected in consideration of the remaining lifetime value of the dependent physical server, so as to process the access request through the optimal virtual server.
Specifically, the physical servers on which the virtual servers depend are of a lifetime, and the remaining lifetime values of the physical servers include: the residual life value of the memory, the residual life value of the hard disk, the residual life value of the CPU and the like. The residual life values of the physical servers depended by the virtual servers are integrated together to form a residual life value set
Wherein
is the 1 st remaining life value of the physical server,
Is the 2 nd remaining life value of the physical server,
Is a physical server
The value of the remaining life of the battery,
is the number of elements in the set. For example:
is the residual life value of the memory of the physical server,
Is the residual life value of the hard disk of the physical server,
Is the remaining life value of the CPU of the physical server.
Obtaining the state value of each virtual server in the target to be selected through the following formula
. Wherein,
the impact of the remaining lifetime value of the physical server on which the virtual server depends on the state value of the virtual server is weighted,
the influence weight of the resource residual index of the virtual server on the state value of the resource residual index is determined,
，
，
can be obtained by utilizing ant colony algorithm or neural network training
And
of course, they can be obtained empirically;
is a physical server
The value of the remaining life of the battery,
is as follows
The difference between the remaining life value and its standard life value.
And after the optimal virtual server is selected, processing the access request through the optimal virtual server, and sending the obtained processing result to the terminal as the response of the access request.
According to the method and the device, under the condition that the requirement of the selection index is met, the residual life value of the physical server on which the virtual server depends in the cloud computing system can be considered, so that the physical resource of the physical server can be guaranteed to be utilized in a balanced mode, and only under the condition that the requirement of the selection index is not met, the virtual server in the cloud computing system can be created, destroyed or adjusted, so that the change frequency of the virtual server is reduced, and the performance of the cloud computing system is improved.
It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof. The present embodiments are therefore to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned.
Furthermore, it should be understood that although the present description refers to embodiments, not every embodiment may contain only a single embodiment, and such description is for clarity only, and those skilled in the art should integrate the description, and the embodiments may be combined as appropriate to form other embodiments understood by those skilled in the art.
Claims (10)
1. A resource allocation method in a cloud computing system is characterized by comprising the following steps:
step S110, acquiring characteristic parameters of the access request;
step S120, calculating a selection index for selecting the virtual server according to the obtained characteristic parameters;
step S130, taking a virtual server meeting the selection index requirement in the virtual servers as a target to be selected;
step S140, obtaining an optimal virtual server from the target to be selected by considering the residual life value of the physical server;
and step S150, processing the access request through the optimal virtual server.
2. The method according to claim 1, wherein the resource allocation method comprises,
obtaining a feature weight corresponding to the feature parameter according to the feature parameter;
and obtaining a selection index for selecting the virtual server according to the obtained characteristic parameters and the characteristic weights corresponding to the characteristic parameters.
3. The method according to claim 1 or 2, wherein the resource allocation method includes the steps of,
calculating resource residual indexes of all virtual servers belonging to the cloud computing data center;
and comparing the obtained selection index with the resource residual index of each virtual server to select the virtual server meeting the selection index requirement, and taking the selected virtual server as a target to be selected.
4. The method according to claim 3, wherein the resource allocation method is further characterized in that,
under the condition that all the virtual servers do not meet the requirement of the selection index, one or more new virtual servers are created, or some virtual servers are destroyed firstly, then one or more new virtual servers are created, and then the computing capacity of one or more original virtual servers is adjusted to enable the computing capacity to meet the requirement of the selection index.
5. The method according to claim 1 or 2, wherein the remaining life value of the physical server comprises: the residual life value of the memory, the residual life value of the hard disk and the residual life value of the CPU.
6. A resource allocation system in a cloud computing system, comprising: the system comprises a characteristic acquisition module, an index calculation module, a virtual server selection module and an optimal virtual server confirmation module;
the characteristic acquisition module acquires characteristic parameters of the access request;
the index calculation module calculates a selection index for selecting the virtual server according to the obtained characteristic parameters;
the virtual server selection module takes a virtual server meeting the selection index requirement in the virtual servers as a target to be selected;
and the optimal virtual server confirmation module considers the residual life value of the physical server which depends on the optimal virtual server, obtains the optimal virtual server from the target to be selected, and processes the access request through the optimal virtual server.
7. The resource allocation system of claim 6, wherein the index calculation module obtains a feature weight corresponding to the feature parameter according to the feature parameter, and obtains a selection index for selecting the virtual server according to the obtained feature parameter and the feature weight corresponding to the feature parameter.
8. The resource allocation system in the cloud computing system according to claim 6 or 7, wherein the virtual server selection module calculates resource remaining indicators of all virtual servers belonging to the cloud computing data center, compares the obtained selection indicator with the resource remaining indicator of each virtual server to select a virtual server meeting the selection indicator requirement, and uses the selected virtual server as a target to be selected.
9. The resource allocation system in the cloud computing system according to claim 8, wherein the virtual server selection module creates one or more new virtual servers when all the virtual servers do not meet the requirement of the selection index, or the virtual server selection module destroys some virtual servers first and then creates one or more new virtual servers, or the virtual server selection module adjusts the computing capability of one or more original virtual servers to meet the requirement of the selection index.
10. The resource allocation system in the cloud computing system according to claim 6 or 7, wherein the remaining life value of the physical server includes: the residual life value of the memory, the residual life value of the hard disk and the residual life value of the CPU.
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| CN114546603A (en) * | 2022-04-24 | 2022-05-27 | 睿至科技集团有限公司 | Data processing method and system applied to Internet of things |
| CN114844899A (en) * | 2022-04-28 | 2022-08-02 | 中国工商银行股份有限公司 | Server selection method and device, processor and electronic equipment |
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