CN119739521A - Resource scheduling method, device, equipment, medium and product of cloud platform - Google Patents
Resource scheduling method, device, equipment, medium and product of cloud platform Download PDFInfo
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- G—PHYSICS
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- 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
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
- G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
- G06F9/5027—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals
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- G—PHYSICS
- G06—COMPUTING OR CALCULATING; 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
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- G06F9/44536—Selecting among different versions
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- G06—COMPUTING OR CALCULATING; 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
- G06F9/46—Multiprogramming arrangements
- G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
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- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/08—Configuration management of networks or network elements
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- H04L67/00—Network arrangements or protocols for supporting network services or applications
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Abstract
The disclosure provides a resource scheduling method, device, equipment, medium and product of a cloud platform, relates to the technical field of computers, and particularly relates to the technical field of cloud platforms and resource allocation. The cloud resource instance allocation method comprises the steps of receiving a cloud resource instance allocation request, determining device version priorities of at least two physical machines according to device version numbers of physical machines bearing cloud resources, wherein the device version numbers correspond to versions of running software on the physical machines, and scheduling the cloud resource instance on the physical machines according to the device version priorities so as to respond to the cloud resource instance allocation request. According to the embodiment of the disclosure, the scheduling scheme of cloud resources provided by the physical machine can be optimized, and reasonable scheduling of cloud resources on the cloud platform is realized.
Description
Technical Field
The disclosure relates to the field of computer technology, and in particular, to a cloud platform and a resource allocation technology.
Background
The cloud platform is a technology capable of providing cloud resources for a user side. The cloud platform may provide cloud cell phone services, cloud desktop services, and other cloud resource services. Taking cloud mobile phone service as an example, the cloud platform manages a large number of cloud mobile phone instances, when a user requests to obtain the cloud mobile phone service, the cloud platform distributes idle cloud mobile phone instances to the user, and when the user finishes accessing, the cloud mobile phone instances are released. A large number of cloud handset instances are run carried by different physical machines. While physical machines have a need for maintenance upgrades, which require downtime to implement.
In the prior art, if the physical machine to be maintained and upgraded is forcibly stopped, not only the cloud mobile phone service being provided for the user is interrupted, but also the resource shortage of the cloud mobile phone instance is possibly caused, so that the service of the user is not well reflected.
Disclosure of Invention
The disclosure provides a resource scheduling method, device, equipment, medium and product of a cloud platform to optimize a scheduling scheme of cloud resources provided by a physical machine.
According to an aspect of the present disclosure, there is provided a resource scheduling method of a cloud platform, including:
Receiving a cloud resource instance allocation request;
Determining the device version priorities of at least two physical machines according to the device version numbers of the physical machines bearing cloud resources, wherein the device version numbers correspond to the versions of running software on the physical machines;
and scheduling the cloud resource instance on the physical machine according to the equipment version priority to respond to the cloud resource instance allocation request.
According to another aspect of the present disclosure, there is provided a resource scheduling apparatus of a cloud platform, including:
The request receiving module is used for receiving a cloud resource instance allocation request;
The system comprises a version priority determining module, a cloud resource processing module and a cloud resource processing module, wherein the version priority determining module is used for determining the device version priorities of at least two physical machines according to the device version numbers of the physical machines bearing the cloud resources, wherein the device version numbers correspond to the versions of running software on the physical machines;
And the cloud resource scheduling module is used for scheduling cloud resource instances on the physical machine according to the equipment version priority so as to respond to the cloud resource instance allocation request.
According to another aspect of the present disclosure, there is provided an electronic device including:
At least one processor, and
A memory communicatively coupled to the at least one processor, wherein,
The memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of scheduling resources of a cloud platform according to any of the embodiments of the present disclosure.
According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing the computer to perform the resource scheduling method of the cloud platform of any embodiment of the present disclosure.
According to another aspect of the present disclosure, there is provided a computer program product comprising a computer program which, when executed by a processor, implements a resource scheduling method of a cloud platform according to any embodiment of the present disclosure.
According to the technical scheme, the device version priorities of at least two physical machines are determined according to the device version numbers of the physical machines bearing cloud resources, cloud resource instances on the physical machines are scheduled according to the device version priorities, so that cloud resource instance allocation requests are responded, the cloud resource instances are scheduled and allocated according to the device version numbers of the physical machines bearing the cloud resource instances, the priority influence of the device version numbers is considered during cloud resource scheduling and allocation, the scheduling strategy of cloud resources on the physical machines is optimized, and further reasonable scheduling of the cloud resources on the cloud platform is achieved.
It should be understood that the description in this section is not intended to identify key or critical features of the embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following specification.
Drawings
The drawings are for a better understanding of the present solution and are not to be construed as limiting the present disclosure. Wherein:
fig. 1 is a schematic diagram of a resource scheduling method of a cloud platform according to an embodiment of the present disclosure;
fig. 2 is a schematic diagram of another resource scheduling method of a cloud platform according to an embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a resource scheduling method of a further cloud platform provided according to an embodiment of the present disclosure;
Fig. 4 is a flowchart of a resource scheduling method of a cloud platform according to an embodiment of the present disclosure;
Fig. 5 is a schematic structural diagram of a resource scheduling device of a cloud platform according to an embodiment of the present disclosure;
Fig. 6 is a block diagram of an electronic device used to implement a method of resource scheduling for a cloud platform of an embodiment of the present disclosure.
Detailed Description
Exemplary embodiments of the present disclosure are described below in conjunction with the accompanying drawings, which include various details of the embodiments of the present disclosure to facilitate understanding, and should be considered as merely exemplary. Accordingly, one of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the present disclosure. Also, descriptions of well-known functions and constructions are omitted in the following description for clarity and conciseness.
Fig. 1 is a schematic diagram of a resource scheduling method of a cloud platform according to an embodiment of the present disclosure, where the embodiment of the present disclosure may be applicable to a case of scheduling and allocating cloud resource instances on the cloud platform. The method can be executed by a resource scheduling device of a cloud platform, and the device can be realized in a hardware and/or software mode and can be configured in electronic equipment. Referring to fig. 1, the method specifically includes the following:
s110, receiving a cloud resource instance allocation request;
S120, determining the device version priorities of at least two physical machines according to the device version numbers of the physical machines bearing the cloud resources, wherein the device version numbers correspond to the versions of running software on the physical machines;
S130, scheduling the cloud resource instance on the physical machine according to the equipment version priority to respond to the cloud resource instance allocation request.
The cloud resource instance allocation request may be understood as an instruction requesting to perform an operation of allocating a cloud resource instance. In the embodiment of the present disclosure, the triggering manner of generating the cloud resource instance allocation request may include multiple types. Optionally, the cloud resource instance allocation request can be generated under the condition that a triggering operation of a user for a preset cloud resource service request control is received, or the cloud resource instance allocation request can be generated under the condition that the fact that the audio information received by the user side comprises a triggering word associated with requesting cloud service is detected, or the cloud resource instance allocation request can be generated under the condition that the fact that the received instruction comprises a cloud service request triggering instruction is detected. It will be appreciated that the cloud resource instance is typically a virtual computer on a cloud server, having its own operating system, processor, memory, storage control, network connection, and other resources. In the embodiment of the disclosure, the cloud resource instance may include a cloud mobile phone instance. The cloud mobile phone instance is one or more virtual mobile phones with a native operating system which are virtualized in the cloud based on cloud server technology. The virtual mobile phone is almost different from the entity mobile phone in function, and a user can log in and request a cloud mobile phone instance through a related application program on an entity terminal (such as a computer, a tablet or a mobile phone and the like) to obtain the same use experience as the entity mobile phone. Optionally, the cloud resource instances may further include cloud desktop instances that provide cloud desktop services, cloud resource instances that provide other cloud resource services, and so on.
In the embodiment of the disclosure, in the case that the user requests to obtain the cloud resource service, in order to enable the user to obtain the cloud resource service on the entity terminal, a cloud resource instance allocation request may be generated and sent to the cloud platform. Further, under the condition that the cloud platform receives the cloud resource instance allocation request, the device version priorities of at least two physical machines can be determined according to the device version numbers of the physical machines bearing the cloud resources.
The physical machine is usually referred to as an independent server or a hardware server, and is an actual entity device. The physical machine may be composed of hardware devices, including processors, memories, hard disks, video cards, etc., which together form a complete computer system. In a cloud computing environment, a physical machine serves as a base device and can bear cloud resources. In the embodiment of the present disclosure, the physical machine may be an ARM chip. The ARM chip is a processor chip based on an ARM architecture and has the advantages of low power consumption, high performance, flexibility, safety and the like. The ARM chip can bear a plurality of cloud resource instances as one physical machine. For example, an ARM chip can bear 8 cloud resource instances as one physical machine. A plurality of ARM chip arrays form a server. That is, a plurality of ARM chips may be organized in an array to form a server. For example, one server may be arranged in an array from 96 ARM chips. The cloud platform comprises a plurality of servers and is used for bearing a large number of cloud resource instances.
Where the device version number is typically a unique number or combination of numbers assigned to a particular device or device software program for identifying its version and update status. The device version number corresponds to the version of the running software on the physical machine. In general, the physical machine is upgraded, and typically, all software running on the physical machine is upgraded. Furthermore, the device version number obtained after the physical machine is upgraded can represent the software version of all the software sets running on the physical machine. The device version number may generally be used to mark the overall version of software running on the physical machine, including hardware drivers, feature packages, kernel software, and any upgradeable software associated with the device, among others. The device version priority may be understood as a rule for determining the allocation order of cloud resource instances of the physical machine according to the device version number. In other words, the priority order of the device version priorities may correspond to the cloud resource instance allocation order of the physical machines.
It should be noted that the cloud platform includes a plurality of servers, and each server may include a plurality of physical machines. In the running process of the server, in order to improve the running performance of the server, the physical machine in the server can be maintained and upgraded. In general, in order to ensure that a server can normally provide cloud resource services, maintenance and upgrade are usually performed on physical machines in batches. In this case, there may be a case where the device version numbers of the plurality of physical machines included in the server are not identical, that is, the device version numbers of the upgraded physical machines are not identical to the device version numbers of the physical machines to be upgraded. And because the physical machine needs to be stopped when being maintained and upgraded, when the physical machine which needs to be maintained and upgraded is forcibly stopped, not only can the cloud resource service which is being provided for the user be interrupted, but also the condition of resource shortage of the cloud resource instance can be caused. Therefore, in view of the above situation, when the cloud resource instance is scheduled, the device version number of the physical machine may be used as a basis for allocation scheduling of the cloud resource instance, and the physical machines to be maintained and upgraded and/or the physical machines to be maintained and upgraded are determined according to the device version number of the physical machine carrying the cloud resource, and the priority order of the device versions of the physical machines is determined to be lower than the priority order of the device versions of the physical machines that do not need to be maintained and upgraded at present. Furthermore, the cloud resource instance on the physical machine can be scheduled according to the device version priority of the physical machine so as to respond to the cloud resource instance allocation request.
In the embodiment of the disclosure, the method for determining the device version priorities of at least two physical machines according to the device version numbers of the carried physical machines may include at least two methods, and optionally, determining the device version priorities according to the high-low order represented by the device version numbers, or determining the device version priorities according to whether the device version numbers meet preset maintenance upgrading conditions.
After determining the device version priorities of the at least two physical machines, the device version priorities of the at least two physical machines may be compared. And further, a target physical machine capable of carrying out cloud resource instance scheduling can be determined according to the comparison result, a plurality of cloud resource instances on the target physical machine are scheduled, a target cloud resource instance meeting cloud resource service requirements of a request sending object of a cloud resource instance allocation request is determined in the plurality of cloud resource instances on the physical machine, and the target cloud resource instance is allocated to the cloud resource instance allocation request so as to respond to the cloud resource instance allocation request.
According to the technical scheme, the device version priorities of at least two physical machines are determined according to the device version numbers of the physical machines bearing cloud resources, cloud resource instances on the physical machines are scheduled according to the device version priorities, so that cloud resource instance allocation requests are responded, the cloud resource instances are scheduled and allocated according to the device version numbers of the physical machines bearing the cloud resource instances, the priority influence of the device version numbers is considered during cloud resource scheduling and allocation, the scheduling strategy of cloud resources on the physical machines is optimized, and further reasonable scheduling of the cloud resources on the cloud platform is achieved.
On the basis of the above embodiment, the shutdown processing may be performed on the physical machine in the idle state. Specifically, when all cloud resource instances on any physical machine are released into an idle state, stopping the physical machine.
Wherein, the cloud resource instance is released generally refers to an operation of removing the cloud resource instance from the cloud server and releasing its related resources when the user no longer needs the cloud resource instance (i.e., the cloud resource instance is no longer used) in the cloud computing environment. The cloud resource instance being in an idle state may generally refer to the cloud resource instance being currently unused.
In the embodiment of the disclosure, when the user no longer uses the allocated cloud resource instance, the cloud resource instance may be released. Further, for a plurality of physical machines on the server, when all cloud resource instances on any physical machine are released to be in an idle state, it may be indicated that all cloud resource instances on the physical machine are not currently used. Furthermore, the physical machine can be shut down to upgrade and restart the version of the physical machine. The cloud resource upgrading method has the advantages that when the physical machine needs to be shut down for maintenance, the cloud resource instance on the physical machine can be gradually released on the premise that the operation of the cloud platform is not affected, and then the normal use of the cloud resource service by a user is not affected when the physical machine needing to be upgraded and maintained is upgraded and restarted, and the effect of continuously rolling and upgrading the physical machine on the cloud platform under the condition that the use of the user is not affected is achieved.
Fig. 2 is a schematic diagram of another resource scheduling method of a cloud platform according to an embodiment of the present disclosure, where a specific scheme for determining device version priorities is further optimized on the basis of the foregoing embodiment. As shown in fig. 2:
s210, receiving a cloud resource instance allocation request;
s220, determining the device version priorities of at least two physical machines according to the device version numbers of the physical machines bearing the cloud resources, wherein the device version numbers correspond to the versions of running software on the physical machines;
the above operation S220 specifically includes the following steps:
S221, determining the respective device version priorities of at least two physical machines according to the device version numbers of the physical machines bearing cloud resources and the sequence from high to low of the device version numbers, wherein the priority order of the device version priorities corresponds to the high-low sequence of the device version numbers;
And S230, scheduling the cloud resource instance on the physical machine according to the equipment version priority to respond to the cloud resource instance allocation request.
The priority order of the device version priorities corresponds to the high-low order of the device version numbers. That is, the higher the device version number of the physical machine, the higher the device version priority corresponding to the physical machine, i.e. the higher the device version priority, and the lower the device version number of the physical machine, the later the device version priority corresponding to the physical machine, i.e. the lower the device version priority.
Generally, the higher the device version number, the newer the device version of the physical machine may be indicated, and the more maintenance-free the physical machine is, and the lower the device version number, the more maintenance-free the physical machine is.
In the embodiment of the disclosure, under the condition that a cloud resource instance allocation request is received, device version numbers of a plurality of physical machines carrying cloud resources in a cloud platform can be obtained. Further, the plurality of physical machines can be ordered according to the order from high to low of the device version numbers, and an ordered physical machine queue is obtained. Further, priority weights can be set for each physical machine in the physical machine queue in turn according to the high-low order of the device version numbers, the physical machine with the highest device version number sets the highest priority weight, the physical machine with the next device version number sets the lower priority weight, and so on. Further, the device priorities of the at least two physical machines can be determined according to the priority weights of the physical machines. The device of the physical machine with higher priority weight has higher priority, and the device of the physical machine with lower priority weight has lower priority.
Further, when the cloud resource instance scheduling is performed, the device priority of the physical machine can be used as one of determining factors of the cloud resource instance scheduling sequence. And further, scheduling the cloud resource instance on the physical machine according to the equipment priority and the original resource scheduling policy. For at least two physical machines, the physical machines can be evaluated according to the original resource scheduling strategy so as to obtain initial scheduling evaluation values of the physical machines. Further, the priority weight of the device priority representing the physical machine and the initial scheduling evaluation value of the physical machine can be processed according to a preset data processing mode, so that the total scheduling evaluation value of the physical machine is obtained. Further, a target physical machine capable of carrying out cloud resource instance scheduling can be determined according to the total scheduling evaluation value of the physical machine, a plurality of cloud resource instances on the target physical machine are scheduled, a target cloud resource instance meeting cloud resource service requirements of a request sending object of a cloud resource instance allocation request is determined in the cloud resource instances on the physical machine, and the target cloud resource instance is allocated to the cloud resource instance allocation request so as to respond to the cloud resource instance allocation request. The data processing manner may include addition, multiplication or other processing manners.
According to the technical scheme, the device version priorities of at least two physical machines are determined according to the device version numbers of the physical machines bearing cloud resources and the sequence from high to low of the device version numbers, the effect of determining the priority sequence of the device version priorities according to the high-low sequence of the device version numbers is achieved, and further, the effect of preferentially distributing cloud resource instances on the physical machines with high device version numbers is achieved, so that the physical machines with low device version numbers can be idle to be convenient for upgrading the device versions of the physical machines.
Fig. 3 is a schematic diagram of a resource scheduling method of another cloud platform according to an embodiment of the present disclosure, where a specific scheme of determining device version priorities is further optimized on the basis of the foregoing embodiment. As shown in fig. 3:
s310, receiving a cloud resource instance allocation request;
s320, determining the device version priorities of at least two physical machines according to the device version numbers of the physical machines bearing the cloud resources, wherein the device version numbers correspond to the versions of running software on the physical machines;
the above operation S320 specifically includes the following steps:
s321, according to the device version numbers of the physical machines bearing cloud resources, determining that the device version priorities of the physical machines are low priorities, and determining that the device version priorities of other physical machines are high priorities;
s330, scheduling the cloud resource instance on the physical machine according to the equipment version priority to respond to the cloud resource instance allocation request.
The set version number condition may be a predetermined criterion for screening the device version number. In the embodiment of the present disclosure, the device version priorities of the physical machines may be classified into low priorities and high priorities according to a set version number condition. The device priority of the physical machine to which the device version number meeting the condition of setting the version number belongs is low priority, and the cloud resource instance scheduling sequence of the physical machine with the device priority being low priority is lower than that of the physical machine with the device priority being high priority. In general, determining the device priority of the physical machine as a low priority, delaying the scheduling sequence of the cloud resource instance on the physical machine may generally include at least two situations that the physical machine needs to be maintained and upgraded and/or the device version of the physical machine is unstable (for example, the device version is a test version). Thus, the condition contents included in the set version number condition may include contents for identifying whether the device version of the physical machine requires maintenance upgrade and/or whether the device version of the physical machine is a test version, and the like. Optionally, the set version number condition comprises at least one of the following device version numbers with test marks, the device version numbers with marks to be maintained, the device version numbers belonging to the configured version range to be maintained, the device version numbers after being ordered from high to low and meeting the set proportion, and the device version numbers being lower than the set maintenance version numbers.
Wherein the test identifier may be information for identifying the test version. The test identity may be any form of information. Alternatively, the test identifier may be at least one of a Chinese identifier, a numerical identifier, and an English identifier (such as alpha, beta, RC, etc.). It should be noted that, the existence of the test identifier in the device version number may characterize that a software version of at least one software of all software running in the physical machine is a test version. The identification to be maintained may be information for identifying the device version to be and/or to which upgrade maintenance is to be performed. The identification to be maintained can be identification information set by user definition or identification information set by default of the system. Optionally, the identifier to be maintained may be at least one of a chinese identifier, a numerical identifier and an english identifier. It should be noted that, the identifier to be maintained in the device version number may represent that a software version of at least one piece of software running in the physical machine is a software version to be upgraded and maintained and/or a software version to be upgraded and maintained. The version range to be maintained can be understood as a preconfigured device version number interval to be subjected to upgrade maintenance. The set proportion may be any proportion, alternatively 1%, 5%, 10% or 20% or the like. The latter device version number may be a later-arranged device version number. The set maintenance version number may be a preset version number of a device version to be subjected to upgrade maintenance and/or to be subjected to upgrade maintenance. The set maintenance version number can be used as a determination standard for determining whether the physical machine to which the device version number belongs needs upgrading maintenance.
It should be noted that, after the physical machine is upgraded, the corresponding device version number will be higher than the device version number before the upgrade. Furthermore, the relatively high device version number of the physical machine may indicate that the physical machine is a physical machine that has recently completed an upgrade and is not currently being upgraded, and the relatively low device version number of the physical machine may indicate that the physical machine may be a physical machine to be upgraded and/or that is to be upgraded and maintained. After the device version numbers are ordered from high to low, the physical machine to which the device version numbers arranged at the back position belong may be a physical machine to be subjected to upgrading maintenance and/or a physical machine to be subjected to upgrading maintenance. Further, after the device version numbers are sorted from high to low, the following device version numbers satisfying the preset ratio may be used as one of the conditions for setting the version numbers.
In the embodiment of the disclosure, in the case that the device version of the physical machine is the test version, there may be cases where an unrepaired error is included or performance is unstable. Furthermore, when the cloud resource instance is allocated, the cloud resource allocation sequence of the physical machine is backward under the condition that the equipment version of the physical machine is the test version. Further, the device version priority of the physical machine is relatively low. In the case that the device version of the physical machine is the device version to be subjected to upgrade maintenance and/or the device version to be subjected to upgrade maintenance, the upgrade maintenance is performed on the device version, and the physical machine needs to be implemented. Assuming that the cloud resource instance on the physical machine is allocated to the user, when the physical machine is upgraded and maintained, the physical machine is stopped, so that the cloud resource service being provided for the user is interrupted, and the resource shortage of the cloud resource instance can be caused. Furthermore, when the cloud resource instance is allocated, the cloud resource allocation sequence of the physical machine is backward under the condition that the equipment version of the physical machine is the equipment version to be subjected to upgrade maintenance and/or the equipment version to be subjected to upgrade maintenance. Further, the device version priority of the physical machine is relatively low. Thus, the set version number condition may include at least one of a device version number having a test identifier, a device version number having a to-be-maintained identifier, the device version number belonging to a configured to-be-maintained version range, a subsequent device version number meeting a set proportion after the device version number is ordered from high to low, and a device version number lower than the set maintenance version number.
As an optional implementation manner of the embodiment of the present disclosure, in a case where a cloud resource instance allocation request is received, device version numbers of a plurality of physical machines that bear cloud resources in a cloud platform may be obtained. Further, for a plurality of device version numbers, the device version numbers can be analyzed according to a set version number condition. Further, in the case where it is determined that the device version number satisfies the condition of setting the version number, it may be determined that the device priority of the physical machine to which the device version number belongs is a low priority. Further, in the case where the device priority is determined to be a physical machine of low priority, the device priority of the other physical machines than the physical machine for which the device priority has been determined may be determined to be high priority.
Further, after determining the device priorities of at least two physical machines, the cloud resource instances on the physical machines may be scheduled according to the device version priorities, so as to respond to the cloud resource instance allocation request.
Optionally, scheduling the cloud resource instance on the physical machine according to the device version priority to respond to the cloud resource instance allocation request comprises determining a physical machine range with low priority and a physical machine range with high priority according to the device version priority, and selecting a target cloud resource instance from the cloud resource instance on the physical machine range with high priority according to a set scheduling policy to allocate to the cloud resource instance allocation request.
The set scheduling policy may be a preset cloud resource instance scheduling policy. Optionally, setting the scheduling policy may include at least one of according to a location to which an object that initiates the cloud resource instance allocation request belongs, according to a terminal address that sends the cloud resource instance allocation request, according to a number of cloud resource instances allocated on the physical machine, and according to a type of software and/or a number of software running on the cloud resource instance.
As an optional implementation manner of the embodiment of the present disclosure, in a case where device priorities of at least two physical machines are obtained, the obtained device priorities include a low priority and a high priority. Further, according to the device priority, the physical machines can be divided into a physical machine range with low priority and a physical machine range with high priority, and cloud resource instances on each physical machine in the physical machine range with high priority are used as cloud resource instances capable of being allocated in a dispatching mode. Further, selecting a target cloud resource instance corresponding to the cloud resource instance allocation request from the cloud resource instances capable of being allocated in a scheduling mode according to a set scheduling policy. Further, the target cloud resource instance can be allocated to a request terminal for sending a cloud resource instance allocation request, so that the request terminal obtains cloud resource service according to the allocated target cloud resource instance.
According to the technical scheme, the device version numbers of the physical machines bearing cloud resources are used for determining that the device version priorities of the physical machines are low in priority and determining that the device version priorities of other physical machines are high in priority according to the device version numbers of the physical machines bearing cloud resources, further, the physical machine range with the low priority and the physical machine range with the high priority are determined according to the device version priorities, and from cloud resource instances on the physical machine range with the high priority, a target cloud resource instance is selected according to a set scheduling strategy and allocated to cloud resource instance allocation requests, so that the effect of scheduling and allocating the cloud resource instances on the physical machine range with the high priority in priority is achieved.
On the basis of the technical scheme provided by the embodiment, when the target cloud resource instance is selected according to the set policy, the cloud resource instance on the physical machine range with the high priority can be selected from the cloud resource instances on the physical machine range with the low priority under the condition that the optional cloud resource instance does not exist in the cloud resource instance on the physical machine range with the high priority.
Optionally, the resource scheduling method of the cloud platform further comprises the step of selecting the target cloud resource instance from cloud resource instances on a physical machine range with low priority according to a set scheduling policy if no selectable cloud resource instance exists when selecting the target cloud resource instance from cloud resource instances on a physical machine range with high priority according to the set scheduling policy, and distributing the target cloud resource instance to a cloud resource instance distribution request.
As an optional implementation manner of the embodiment of the present disclosure, if, when a target cloud resource instance is selected according to a set scheduling policy from cloud resource instances on a physical machine range of a high priority, there is no optional cloud resource instance that conforms to the set scheduling policy, then the cloud resource instance on each physical machine in the physical machine range of the low priority may be used as a candidate cloud resource instance. Further, selecting a target cloud resource instance corresponding to the cloud resource instance allocation request from the candidate cloud resource instances according to a set scheduling policy, for example, scheduling according to a regional attribution policy or a load balancing policy. Further, the target cloud resource instance can be allocated to a request terminal for sending a cloud resource instance allocation request, so that the request terminal obtains cloud resource service according to the allocated target cloud resource instance. The cloud platform resource scheduling method has the advantages that the integrity of the cloud platform resource scheduling strategy is enhanced, the corresponding cloud resource instance can be fed back when a user requests the cloud resource instance, and the normal use of the cloud resource service by the user is ensured.
In the embodiment of the disclosure, cloud resource instances on the physical machine of the test version and/or cloud resource instances on the physical machine to be subjected to upgrade maintenance may exist in target cloud resource instances allocated to users. Or there may be a case where the target cloud resource instance allocated to the user is a cloud resource instance on a physical machine range with high priority, but the cloud resource service provided by the cloud resource instance cannot meet the service requirement of the user. Aiming at the situation, in order to continuously upgrade and optimize the cloud resource instance on the cloud platform, the feedback opinion of the user on the cloud resource instance can be obtained in the application process of the cloud resource instance. Furthermore, the device version priority of the physical machine can be updated according to feedback opinion of the user on the cloud resource instance so as to adjust the cloud resource instance allocation sequence of the physical machine.
Optionally, the resource scheduling method of the cloud platform further comprises the step of updating the device version priority corresponding to the device version number corresponding to the physical machine according to feedback opinion of a user on services provided by the cloud resource instance in the physical machine.
The feedback opinion may be feedback of a service provided by the cloud resource instance by the user. The feedback opinion may include a positive feedback opinion and/or a negative feedback opinion.
As an optional implementation manner of the embodiment of the present disclosure, in a case where a cloud resource instance is allocated to a user so that the user obtains a cloud resource service based on the allocated cloud resource instance, feedback opinion of the user on the cloud resource service provided by the cloud resource instance may be obtained. Further, the obtained feedback opinion can be sent to the cloud platform, so that the cloud platform updates the device version priority corresponding to the device version number corresponding to the physical machine to which the cloud resource instance belongs according to the feedback opinion. The device version priority adjustment method has the advantages that the effect of adjusting and updating the device version priority corresponding to the device version number of the physical machine according to the feedback opinion of the user is achieved, the proportion of the test version can be adjusted according to the feedback of the user, the trial proportion of the test version is increased, and upgrading and optimizing of the physical machine in the cloud platform are facilitated.
For example, under the assumption that a test identifier exists in a device version number of a physical machine to which a cloud resource instance allocated to a user belongs and a received feedback opinion of the user on a service provided by the cloud resource instance is a forward feedback opinion, a device version priority corresponding to a device version number corresponding to the physical machine to which the cloud resource instance belongs may be increased. Under the condition that the physical machine to which the cloud resource instance allocated to the user belongs is a physical machine in the physical machine range with high priority and the received feedback opinion of the user on the service provided by the cloud resource instance is a negative feedback opinion, the device version priority corresponding to the device version number corresponding to the physical machine to which the cloud resource instance belongs can be reduced.
Fig. 4 is a flow chart of a resource scheduling method of a cloud platform according to an embodiment of the present disclosure, where the embodiment is a preferred embodiment of the foregoing embodiment, and a technical solution provided by the embodiment of the present disclosure is described by taking a cloud resource instance as a cloud mobile phone instance as an example. As shown in fig. 4, the method of this embodiment may specifically include:
1. the cloud mobile phone platform manager configures the device version number which is allocated preferentially in advance;
2. A cloud mobile phone platform manager opens a switch which is preferentially allocated according to the appointed version;
3. the cloud mobile phone user applies for a cloud mobile phone instance and sends a cloud mobile phone instance allocation request to the cloud mobile phone platform;
4. Under the condition that the cloud mobile phone platform receives a cloud mobile phone instance allocation request, an allocable cloud mobile phone instance pool can be determined, and cloud mobile phone instances meeting user application conditions are selected from the allocable cloud mobile phone instance pool;
5. If the switch which is preferentially allocated according to the appointed version is turned on, an allocable cloud mobile phone instance pool can be constructed according to the preconfigured equipment version number which is preferentially allocated, and cloud mobile phone instances meeting the application condition of the user are selected from the allocable cloud mobile phone instance pool;
6. If the optional cloud mobile phone instance does not exist in the assignable cloud mobile phone instance pool, the assignable cloud mobile phone instance can be randomly selected;
7. if the switch which is preferentially allocated according to the appointed version is closed, the allocable cloud mobile phone instance can be randomly selected;
8. and feeding back the cloud mobile phone instances meeting the user application conditions to cloud mobile phone users applying for the cloud mobile phone instances based on the cloud mobile phone platform.
According to the technical scheme, the device version priorities of at least two physical machines are determined according to the device version numbers of the physical machines bearing cloud resources, cloud resource instances on the physical machines are scheduled according to the device version priorities, so that cloud resource instance allocation requests are responded, the cloud resource instances are scheduled and allocated according to the device version numbers of the physical machines bearing the cloud resource instances, the priority influence of the device version numbers is considered during cloud resource scheduling and allocation, the scheduling strategy of cloud resources on the physical machines is optimized, and further reasonable scheduling of the cloud resources on the cloud platform is achieved.
Fig. 5 is a schematic structural diagram of a resource scheduling device of a cloud platform according to an embodiment of the present disclosure, where the embodiment of the present disclosure is applicable to a case of scheduling and allocating cloud resource instances on the cloud platform. The device is realized by software and/or hardware, and is specifically configured in the electronic equipment with certain data operation capability.
The resource scheduling device 500 of the cloud platform shown in fig. 5 comprises a request receiving module 510, a version priority determining module 520 and a cloud resource scheduling module 530. Wherein,
A request receiving module 510, configured to receive a cloud resource instance allocation request;
The version priority determining module 520 is configured to determine device version priorities of at least two physical machines according to device version numbers of physical machines carrying cloud resources, where the device version numbers correspond to versions of running software on the physical machines;
the cloud resource scheduling module 530 is configured to schedule cloud resource instances on the physical machine according to the device version priority, so as to respond to the cloud resource instance allocation request.
According to the technical scheme, the device version priorities of at least two physical machines are determined according to the device version numbers of the physical machines bearing cloud resources, cloud resource instances on the physical machines are scheduled according to the device version priorities, so that cloud resource instance allocation requests are responded, the cloud resource instances are scheduled and allocated according to the device version numbers of the physical machines bearing the cloud resource instances, the priority influence of the device version numbers is considered during cloud resource scheduling and allocation, the scheduling strategy of cloud resources on the physical machines is optimized, and further reasonable scheduling of the cloud resources on the cloud platform is achieved.
Further, the physical machine is an ARM chip, a plurality of ARM chip arrays form a server, and the cloud platform comprises a plurality of servers.
Further, the version priority determining module 520 includes:
The device comprises a first version priority determining unit, a second version priority determining unit and a third version priority determining unit, wherein the first version priority determining unit is used for determining the respective device version priorities of at least two physical machines according to the device version numbers of the physical machines bearing cloud resources and the sequence from high to low of the device version numbers, and the priority order of the device version priorities corresponds to the high-low sequence of the device version numbers.
Further, the version priority determining module 520 includes:
the second version priority determining unit is used for determining that the device version priority of the physical machine is low in priority and determining that the device version priorities of other physical machines are high in priority according to the device version numbers of the physical machines bearing cloud resources and the device version numbers meeting the set version number conditions.
Further, setting the version number condition includes at least one of:
The device version number has a test identifier;
The device version number has an identifier to be maintained;
The equipment version number belongs to the configured version range to be maintained;
after the device version numbers are ordered from high to low, the following device version numbers meeting the set proportion are obtained;
the device version number is lower than the set maintenance version number.
Further, the cloud resource scheduling module 530 includes:
A physical machine range determining unit configured to determine a physical machine range with a low priority and a physical machine range with a high priority according to the device version priority;
the cloud resource instance selection unit is used for selecting a target cloud resource instance from cloud resource instances on a physical machine range with high priority according to a set scheduling policy and distributing the target cloud resource instance to the cloud resource instance distribution request.
Further, the resource scheduling device of the cloud platform further comprises:
And the target cloud resource instance selection module is used for selecting the target cloud resource instance from the cloud resource instance on the physical machine scope of the low priority according to the set scheduling policy and distributing the target cloud resource instance to the cloud resource instance distribution request if the optional cloud resource instance does not exist when the target cloud resource instance is selected according to the set scheduling policy from the cloud resource instance on the physical machine scope of the high priority.
Further, the resource scheduling device of the cloud platform further comprises:
and the physical machine shutdown module is used for shutting down any physical machine when all cloud resource instances on the physical machine are released to be in an idle state.
Further, the resource scheduling device of the cloud platform further comprises:
And the version priority updating module is used for updating the device version priority corresponding to the device version number corresponding to the physical machine according to the feedback opinion of the user on the service provided by the cloud resource instance in the physical machine.
The resource scheduling device of the cloud platform can execute the resource scheduling method of the cloud platform provided by any embodiment of the disclosure, and has the corresponding functional modules and beneficial effects of executing the point cloud labeling method.
In the technical scheme of the disclosure, the related personal information of the user is collected, stored, used, processed, transmitted, provided, disclosed and the like, all conform to the regulations of related laws and regulations and do not violate the popular public order.
According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.
Fig. 6 illustrates a schematic block diagram of an example electronic device 600 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed herein.
As shown in fig. 6, the apparatus 600 includes a computing unit 601 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 602 or a computer program loaded from a storage unit 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the device 600 may also be stored. The computing unit 601, ROM 602, and RAM 603 are connected to each other by a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.
Various components in the device 600 are connected to the I/O interface 605, including an input unit 606, e.g., keyboard, mouse, etc., an output unit 607, e.g., various types of displays, speakers, etc., a storage unit 608, e.g., magnetic disk, optical disk, etc., and a communication unit 609, e.g., network card, modem, wireless communication transceiver, etc. The communication unit 609 allows the device 600 to exchange information/data with other devices via a computer network, such as the internet, and/or various telecommunication networks.
The computing unit 601 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 601 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 601 performs the respective methods and processes described above, for example, a resource scheduling method of a cloud platform. For example, in some embodiments, the resource scheduling method of the cloud platform may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 608. In some embodiments, part or all of the computer program may be loaded and/or installed onto the device 600 via the ROM 602 and/or the communication unit 609. When the computer program is loaded into RAM 603 and executed by computing unit 601, one or more steps of the resource scheduling method of the cloud platform described above may be performed. Alternatively, in other embodiments, the computing unit 601 may be configured to perform the resource scheduling method of the cloud platform in any other suitable way (e.g., by means of firmware).
Various implementations of the systems and techniques described here above can be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), complex Programmable Logic Devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include being implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be a special or general purpose programmable processor, operable to receive data and instructions from, and to transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user, for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback), and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a Local Area Network (LAN), a Wide Area Network (WAN) blockchain network, and the Internet.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service are overcome. The server may also be a server of a distributed system or a server that incorporates a blockchain.
Artificial intelligence is the discipline of studying the process of making a computer mimic certain mental processes and intelligent behaviors (e.g., learning, reasoning, thinking, planning, etc.) of a person, both hardware-level and software-level techniques. The artificial intelligence hardware technology generally comprises technologies such as a sensor, a special artificial intelligence chip, cloud computing, distributed storage, big data processing and the like, and the artificial intelligence software technology mainly comprises a computer vision technology, a voice recognition technology, a natural language processing technology, a machine learning/deep learning technology, a big data processing technology, a knowledge graph technology and the like.
Cloud computing (cloud computing) refers to a technical system that a shared physical or virtual resource pool which is elastically extensible is accessed through a network, resources can comprise servers, operating systems, networks, software, applications, storage devices and the like, and resources can be deployed and managed in an on-demand and self-service mode. Through cloud computing technology, high-efficiency and powerful data processing capability can be provided for technical application such as artificial intelligence and blockchain, and model training.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps recited in the present disclosure may be performed in parallel, sequentially, or in a different order, provided that the desired results of the technical solutions provided by the present disclosure are achieved, and are not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (21)
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