Resource management method and device for para-virtualization platform, equipment, medium and program product
By adopting resource management methods on the semi-virtualized platform, obtaining task process information and priority information, determining resource demand curves and residual curves, and formulating target resource management strategies, the problem of inefficiency in resource management and scheduling of the fully virtualized system is solved, and more efficient hardware resource utilization and dynamic resource adjustment are achieved.
Patent Information
- Application Number
- CN202411737775.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-11-29
- Publication Date
- 2025-03-04
AI Technical Summary
Fully virtualized systems are inefficient in resource management and scheduling, and the system architecture is relatively more complex because they need to handle complete hardware virtualization.
The resource management method of the paravirtualized platform is adopted to obtain the process information and priority information of the target task, determine the resource demand curve and resource residual curve, formulate target resource management strategies, and dynamically adjust resource allocation and task scheduling.
It improves the utilization rate of hardware resources, reduces idleness, supports dynamic resource adjustment and task scheduling, and adapts to changes in business load.
Smart Images
Figure CN119557054A_ABST
Abstract
Description
Technical Field
[0001] The embodiments of the present invention relate to the technical field of virtualization platform resource management, and in particular to a resource management method, device, equipment, medium and program product for a paravirtualization platform. Background Art
[0002] Virtualization usually requires a hypervisor to achieve complete hardware abstraction, which may introduce additional performance overhead. Since full virtualization requires each virtual machine to be completely isolated when starting a virtual machine, the startup time of full virtualization is usually longer. Because the hypervisor needs to perform more initialization and resource allocation, the resources are completely isolated, so it is inefficient in resource management and scheduling. The system architecture of full virtualization is relatively more complex because it needs to handle complete hardware virtualization. Summary of the invention
[0003] The purpose of the present invention is to at least provide a resource management method, device, equipment, medium and program product for a semi-virtualized platform, which can at least solve the problem that the virtual machine monitoring program needs to perform more initialization and complete isolation of resource allocation, so the resource management and scheduling are inefficient, and the fully virtualized system architecture is relatively more complicated because it needs to handle complete hardware virtualization. Through the resource management method of the semi-virtualized platform, physical resources (such as CPU, memory and storage, etc.) can be effectively divided into multiple virtual machines, allowing multiple operating systems to run in parallel on the same hardware, which can improve the utilization rate of hardware resources and reduce idleness. The present invention supports dynamic resource adjustment and task scheduling, and can easily increase or decrease virtual resources as needed to adapt to changes in business load.
[0004] To solve the above technical problems, this application proposes five aspects.
[0005] In a first aspect, the present application provides a resource management method for a paravirtualized platform, comprising: obtaining process information and priority information of a target task; determining a resource demand curve of resources demanded over time when the target task is executed in a virtual machine based on the priority information and the process information; obtaining a first resource remaining curve of remaining resources in the paravirtualized platform that changes over time; and determining a target resource management strategy for the target task based on the first resource remaining curve and the resource demand curve.
[0006] In some embodiments, the process information includes: a process topology map and computing amount information of each process; the resource demand curve of the resource demand changing over time when the target task is executed in the virtual machine according to the priority information and the process information includes: dividing the target task into multiple computing stages according to the process topology map; determining the maximum resource demand of each computing stage according to the process information and computing amount information in each computing stage; obtaining a preset priority resource ratio table; determining the resource adjustment ratio of the target task according to the priority resource ratio table and the priority information; determining the target resource demand of each computing stage according to the maximum resource demand and the resource adjustment ratio; determining the execution time of each computing stage according to the target resource demand of each computing stage and the computing amount information; determining the resource demand curve of the target task according to the target resource demand and the execution time of each computing stage.
[0007] In some embodiments, obtaining a first resource remaining curve of remaining resources changing over time in a para-virtualized platform includes: obtaining execution progress information and task resource management policies of each task being executed in the para-virtualized platform; determining the resource remaining amount of the para-virtualized platform at each future moment according to the execution progress information and the task resource management policy of each task being executed; and determining a first resource remaining curve of the resource remaining amount of the para-virtualized platform changing over time according to the resource remaining amount of the para-virtualized platform at each future moment.
[0008] In some embodiments, determining the remaining resources of the para-virtualized platform at each moment in the future based on the execution progress information of each executing task and the task resource management strategy includes: obtaining the total resources of the para-virtualized platform; determining the resource demand of each executing task at each moment in the future based on the execution progress information of each executing task and the task resource management strategy; determining the remaining resources of the para-virtualized platform at each moment in the future based on the total resources and the resource demand of each executing task at each moment in the future.
[0009] In some embodiments, determining the target resource management strategy for the target task based on the first resource remaining curve and the resource demand curve includes: determining the start execution time of the target task based on the first resource remaining curve and the resource demand curve; determining the target resource management strategy for the target task based on the start execution time and the resource demand curve.
[0010] In some embodiments, determining the start execution time of the target task based on the first resource remaining curve and the resource demand curve includes: determining multiple quasi-execution time points that allow the target task to be executed based on the first resource remaining curve and the resource demand curve; predicting the second resource remaining curve of the semi-virtual platform and the end time of the target task when executing the target task according to the quasi-execution time points based on each of the quasi-execution time points and the resource demand curve; determining the resource management evaluation of each quasi-execution time point based on the second resource remaining curve and the end time; and determining the start execution time among multiple quasi-execution time points based on the resource management evaluation.
[0011] In the second aspect, the present application proposes a resource management device for a para-virtualization platform, comprising: a first acquisition module, used to obtain process information and priority information of a target task; a first determination module, used to determine a resource demand curve of resources demanded over time when the target task is executed in a virtual machine based on the priority information and the process information; a second acquisition module, used to obtain a first resource remaining curve of remaining resources in the para-virtualization platform that changes over time; and a second determination module, used to determine a target resource management strategy for the target task based on the first resource remaining curve and the resource demand curve.
[0012] In a third aspect, the present application proposes a computer electronic production device, characterized in that it includes a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the steps of any one of the methods described in the first aspect.
[0013] In a fourth aspect, the present application proposes a computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of any one of the methods described in the first aspect are implemented.
[0014] In a fifth aspect, the present application proposes a computer program product, comprising a computer program, which implements the steps of any one of the methods described in the first aspect when executed by a processor.
[0015] This application solves the problem that because the virtual machine monitor needs to perform more initialization and resource allocation, the resources are completely isolated, so the efficiency in resource management and scheduling is low, and the fully virtualized system architecture is relatively more complex because it needs to handle complete hardware virtualization. Through paravirtualization technology, physical resources (such as CPU, memory, storage, etc.) can be effectively divided into multiple virtual machines, allowing multiple operating systems to run in parallel on the same hardware, which can improve the utilization of hardware resources and reduce idleness. The present invention supports dynamic resource adjustment and task scheduling, and can easily increase or decrease virtual resources as needed to adapt to changes in business load. BRIEF DESCRIPTION OF THE DRAWINGS
[0016] One or more embodiments are exemplarily described by the pictures in the corresponding drawings, and these exemplary descriptions do not constitute limitations on the embodiments.
[0017] Figure 1 A main flow chart of a resource management method for a paravirtualized platform provided in an embodiment of the present application;
[0018] Figure 2 This is a main structural block diagram of a resource management device for a semi-virtualized platform provided in an embodiment of the present application. DETAILED DESCRIPTION
[0019] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the embodiments of the present application will be described in detail below in conjunction with the accompanying drawings. However, it will be appreciated by those skilled in the art that in the present application, many technical details are proposed in order to enable the reader to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present application can also be implemented. The division of the following embodiments is for the convenience of description, and the specific implementation of the present application should not be construed as any limitation, and the various embodiments can be combined and referenced with each other under the premise of no contradiction.
[0020] Virtualization usually requires a hypervisor to achieve complete hardware abstraction, which may introduce additional performance overhead. Since full virtualization requires each virtual machine to be completely isolated when starting a virtual machine, the startup time of full virtualization is usually longer. Because the hypervisor needs to perform more initialization and resource allocation, the resources are completely isolated, so it is inefficient in resource management and scheduling. The system architecture of full virtualization is relatively more complex because it needs to handle complete hardware virtualization.
[0021] In order to solve the above technical problems, the present invention proposes a resource management method for a semi-virtualized platform. The implementation details of the method for determining the bandwidth of this embodiment are specifically described below. The following content is only the implementation details provided for the convenience of understanding and is not necessary for implementing this solution.
[0022] Embodiment 1:
[0023] like Figure 1As shown, the present application provides a resource management method for a semi-virtualized platform, and the method system is applied to electronic production equipment, and the electronic production equipment can be a server, a mobile terminal, a computer, a cloud platform, etc. The function implemented by the production equipment data processing provided in the embodiment of the present application can be implemented by calling the program code by the processor of the electronic production equipment, wherein the program code can be stored in a computer storage medium. The resource management method of the semi-virtualized platform includes:
[0024] Step S1: Obtain the process information and priority information of the target task.
[0025] In scientific research, virtual machines are mainly used to provide a simulation environment and a computing environment to perform specified computing tasks. However, in some practical situations, the resource allocation of virtual machines will allocate computing resources according to the maximum computing demand of the computing task. However, for computing tasks, the amount of computing required is staged, and the amount of computing in different stages is different. Therefore, when executing the low computing stage of the computing task, the computing resources in the virtual machine will be wasted. Moreover, since the computing resources allocated to the established virtual machine are the maximum computing resources required for the computing task, it will also increase the time to create the virtual machine. Therefore, in order to solve the above problems, this application proposes a semi-virtualization platform, in which computing resources can be allocated to computing tasks according to the needs of computing tasks. Each computing task can be regarded as a virtual machine, but there is no absolute isolation between conventional virtual machines, so that the physical resources of the computing device can be well utilized, and the invalid resource occupation in the process of creating virtual machines can be reduced.
[0026] In order to achieve the above-mentioned effects, the present application needs to manage resources for each task that needs to be executed by a paravirtual platform to achieve the effect of a paravirtual machine. Therefore, before the paravirtual machine executes the task, it is necessary to analyze the target task to determine the resource allocation strategy for the target task, and adjust the resources used to execute the target task in real time according to the target resource allocation strategy during the execution of the target task. Different target tasks have different computing process information and priority information generated according to user needs, and the computing process information and priority information will affect the resource management strategy results, so in this application, it is necessary to first obtain the process information and priority information of the target task, where the process information of the target task is generally expressed through a process topology diagram.
[0027] Step S2: determining a resource demand curve of resources required over time when the target task is executed in the virtual machine according to the priority information and the process information.
[0028] In some embodiments, step S2 "determining, according to the priority information and the process information, a resource demand curve of resources required over time when the target task is executed in the virtual machine" includes:
[0029] Step S21: Divide the target task into multiple calculation stages according to the process topology diagram.
[0030] The execution of the target task needs to be performed according to the process topology diagram, and some processes in the process topology diagram can be performed synchronously, so in this application, the target task will be divided into multiple calculation stages according to the execution order in the process topology diagram.
[0031] Step S22: determining the maximum resource requirement of each calculation stage according to the process information and the calculation amount information in each calculation stage.
[0032] Since the computational amount of each process is clearly defined in the process topology diagram, the computational amount of each computational stage can be obtained. After the computational amount of each computational stage is clearly defined, the maximum resource requirement of each computational stage can be determined.
[0033] Step S23: Obtain a preset priority resource ratio table.
[0034] Step S24: determining the resource adjustment ratio of the target task according to the priority resource ratio table and the priority information.
[0035] Since a semi-virtual machine can allow multiple tasks to be executed simultaneously, this will cause serious overlap in the stages with the largest amount of computation of multiple tasks, resulting in unreasonable allocation of resources for the semi-virtual machine. Therefore, in this application, it is necessary to impose certain restrictions on the execution efficiency of the target task according to the priority of the target task. The higher the priority, the lower the restriction on the execution efficiency. Therefore, a priority resource ratio table is set up in the application, and the resource adjustment ratios corresponding to different priorities, that is, the restriction ratio of execution efficiency, are recorded in the priority resource ratio table. Therefore, the resource adjustment ratio for executing the target task can be determined through the priority information of the target task and the priority resource ratio table.
[0036] Step S25: determining the target resource requirement of each calculation stage according to the maximum resource requirement and the resource adjustment ratio.
[0037] Step S26: determining the execution time of each computing stage according to the target resource demand of each computing stage and the computing amount information.
[0038] Since the maximum resource requirement of each calculation has been determined, the maximum resource requirement and resource adjustment ratio can be used to determine how much resources should be allocated to the target task in each calculation stage of the corresponding priority, that is, the target resource requirement. Since the calculation amount information of each calculation stage has been clarified, the execution time required to complete each calculation stage can be predicted based on the calculation amount information and the target resource requirement.
[0039] Step S27: determining the resource requirement curve of the target task according to the target resource requirements required for each calculation stage and the execution duration.
[0040] After obtaining the execution time, because there is a linear time relationship between each calculation stage, the total execution time to complete the entire target task and the target resource demand corresponding to each moment of the total execution time can be obtained, and then the resource demand curve that changes with time can be obtained.
[0041] Step S3: obtaining a first resource remaining curve showing changes of remaining resources in the paravirtualized platform over time.
[0042] In some embodiments, step S3 of "obtaining a first resource remaining curve of remaining resources in the paravirtualized platform changing over time" includes:
[0043] Step S31: Obtaining the execution progress information and task resource management strategy of each task being executed in the paravirtualized platform.
[0044] Step S32: determining the remaining amount of resources of the paravirtualization platform at each moment in the future according to the execution progress information of each task being executed and the task resource management strategy.
[0045] In some embodiments, step S32 of "determining the remaining amount of resources of the paravirtualization platform at each moment in the future according to the execution progress information of each task being executed and the task resource management strategy" includes:
[0046] Step S321: Obtain the total amount of resources of the para-virtualized platform.
[0047] Step S322: determining the resource requirements of each of the tasks being executed at each moment in the future according to the execution progress information of each of the tasks being executed and the task resource management strategy.
[0048] Step S323: determining the remaining amount of resources of the paravirtualization platform at each moment in the future according to the total amount of resources and the resource demand of each task being executed at each moment in the future.
[0049] Step S33: determining a first resource surplus curve showing changes of the resource surplus of the para-virtualization platform over time according to the resource surplus of the para-virtualization platform at each future moment.
[0050] Since there are multiple tasks being executed in the para-virtualized platform at the same time, and each task has its own resource management strategy, the resource demand of each executing task at each future moment can be determined by obtaining the execution progress of each task in the para-virtualized platform and the corresponding resource management strategy. After superimposing the resource demand of multiple tasks at each future moment, the resource occupancy of the para-virtualized platform at each future moment can be obtained. Since the total amount of resources of the para-virtualized platform is known, the remaining amount of resources of the para-virtualized platform at each future moment can be obtained, and then the first resource remaining curve of the remaining amount of resources of the para-virtualized platform changing with time under the current task execution state can be obtained.
[0051] Step S4: determining a target resource management strategy for the target task according to the first resource surplus curve and the resource demand curve.
[0052] In some embodiments, step S4 "determining a target resource management strategy for the target task according to the first resource remaining curve and the resource demand curve" includes:
[0053] Step S41: determining the start time of execution of the target task according to the first resource remaining curve and the resource demand curve.
[0054] In some embodiments, step S41 "determining the start execution time of the target task according to the first resource remaining curve and the resource demand curve" includes:
[0055] Step S411: determining a plurality of quasi-execution time points allowing execution of the target task according to the first resource surplus curve and the resource demand curve.
[0056] Step S412: predicting, according to each of the quasi-execution time points and the resource demand curve, a second resource remaining curve of the para-virtualized platform and an end time of the target task when the target task is executed according to the quasi-execution time point.
[0057] Step S413: determining the resource management evaluation of each quasi-execution time point according to the second resource remaining curve and the end time.
[0058] Step S414: Determine the execution start time from a plurality of quasi-execution time points according to the resource management evaluation.
[0059] Step S42: determining a target resource management strategy for the target task according to the execution start time and the resource demand curve.
[0060] Since the time periods when the maximum amount of resources is required for the execution of different tasks are not the same, but it is possible that the maximum resource demand periods of multiple execution tasks are in the same time period, in order to better utilize the resources of the semi-virtualized platform and execute more tasks at the same time, it is necessary to plan the start execution time of the target task in this application so that the maximum resource demand periods between different tasks are not in the same time period, which can greatly improve the resource utilization efficiency of the semi-virtualized platform. It is also necessary to consider the end time of each task. Therefore, in this application, multiple quasi-execution time points that can be used to execute the target task are first determined based on the first resource remaining curve and the resource demand curve. However, the second resource remaining curves generated when executing the target task at different execution time points are different, and the resource utilization rates represented by these second resource remaining curves are different, which will have different impacts on the execution of subsequent tasks. Therefore, in this application, it is necessary to perform resource management evaluation on each second resource remaining curve and the corresponding end time, wherein different weight coefficients are given to target tasks of different priorities, so as to obtain a more reasonable second resource remaining curve. The quasi-time point corresponding to the second resource remaining curve is the start execution time. After determining the start execution time, the target resource management strategy of the target task can be determined according to the start execution time and the corresponding resource demand curve, and resources can be allocated in real time according to the target resource management strategy during the execution of the target task.
[0061] The method of the present application solves the problem that the virtual machine monitor needs to perform more initialization and complete isolation of resource allocation, so the resource management and scheduling are inefficient, and the fully virtualized system architecture is relatively more complex because it needs to handle complete hardware virtualization. It can effectively divide the physical resources (such as CPU, memory, storage, etc.) of the semi-virtualized platform into multiple virtual machines according to task requirements, allowing multiple operating systems to run in parallel on the same hardware, which can improve the utilization of hardware resources and reduce idleness. The present invention supports dynamic resource adjustment and task scheduling, and can easily increase or decrease virtual resources as needed to adapt to changes in business load.
[0062] Embodiment 2:
[0063] Based on the foregoing embodiments, an embodiment of the present application provides a resource management device for a semi-virtualized platform. The modules included in the device and the units included in the modules can be implemented by a processor in a computer device; of course, they can also be implemented by a specific logic circuit; in the implementation process, the processor can be a central processing unit (CPU, Central Processing Unit), a microprocessor (MPU, Microprocessor Unit), a digital signal processor (DSP, Digital Signal Processing) or a field programmable gate array (FPGA, Field Programmable Gate Array), etc.
[0064] like Figure 2 As shown, a resource management device for a paravirtualized platform includes: a first acquisition module 1, a first determination module 2, a second acquisition module 3 and a second determination module 4.
[0065] The first acquisition module 1 is used to acquire the process information and priority information of the target task. The first determination module 2 is used to determine the resource demand curve of the target task when the target task is executed in the virtual machine according to the priority information and the process information. The second acquisition module 3 is used to obtain the first resource remaining curve of the remaining resources in the paravirtualization platform that changes with time. The second determination module 4 is used to determine the target resource management strategy for the target task according to the first resource remaining curve and the resource demand curve.
[0066] Each module in the resource management device of the above-mentioned semi-virtualized platform can be implemented in whole or in part by software, hardware and a combination thereof. Each of the above-mentioned modules can be embedded in or independent of the processor in the device in the form of hardware, or can be stored in the memory in the processing device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules. It should be noted that the division of modules in the embodiments of the present application is schematic and is only a logical function division. There may be other division methods in actual implementation.
[0067] Embodiment 3:
[0068] In a third aspect, the present application provides a computer electronic production device, comprising a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any one of the methods described in the first aspect.
[0069] Among them, the memory and the processor are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and memories together. The bus can also connect various other circuits such as peripherals, voltage regulators, and power management circuits, which are well known in the art and are therefore not further described herein. The bus interface provides an interface between the bus and the transceiver. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor is transmitted on a wireless medium via an antenna, and further, the antenna also receives data and transmits the data to the processor.
[0070] The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory can be used to store data used by the processor when performing operations.
[0071] Embodiment 4:
[0072] In a fourth aspect, the present application proposes a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of any one of the methods described in the first aspect.
[0073] Embodiment 5:
[0074] In a fifth aspect, the present application proposes a computer program product, comprising a computer program / instructions, characterized in that when the computer program is executed by a processor, the steps of any one of the methods described in the first aspect are implemented.
[0075] Those skilled in the art can understand that all or part of the steps in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including a number of instructions to enable a device (which can be a single-chip microcomputer, chip, etc.) or a processor to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as: ROM), random access memory (Random Access Memory, referred to as: RAM), disk or optical disk and other media that can store program codes.
[0076] Those skilled in the art will appreciate that the above embodiments are specific embodiments for implementing the present application, and in actual applications, various changes may be made thereto in form and detail without departing from the spirit and scope of the present application.
Claims
1. A resource management method for a paravirtualized platform, characterized in that: include: Obtain process information and priority information of target tasks; Determine, according to the priority information and the process information, a resource demand curve of resources required to execute the target task in the virtual machine over time; Obtaining a first resource remaining curve of remaining resources in the paravirtualization platform changing over time; A target resource management strategy for the target task is determined according to the first resource surplus curve and the resource demand curve.
2. The method according to claim 1, characterized in that The process information includes: a process topology diagram and computing amount information of each process; the resource demand curve of the resource demand that changes over time when the target task is executed in the virtual machine according to the priority information and the process information includes: Dividing the target task into multiple calculation stages according to the process topology diagram; Determine the maximum resource requirement of each computing stage according to the process information and computing amount information in each computing stage; Get the preset priority resource ratio table; Determine the resource adjustment ratio of the target task according to the priority resource ratio table and the priority information; Determine the target resource requirement for each computing stage according to the maximum resource requirement and the resource adjustment ratio; Determining the execution time of each computing stage according to the target resource demand of each computing stage and the computing amount information; The resource requirement curve of the target task is determined according to the target resource requirement and the execution time in each calculation stage.
3. The method according to claim 1, characterized in that Obtaining a first resource remaining curve of remaining resources in a paravirtualized platform changing over time, including: Obtain the execution progress information and task resource management strategy of each task being executed in the paravirtualization platform; Determine the remaining amount of resources of the paravirtualization platform at each moment in the future according to the execution progress information of each task being executed and the task resource management strategy; A first resource surplus curve showing changes of the resource surplus of the para-virtualization platform over time is determined according to the resource surplus of the para-virtualization platform at each future moment.
4. The method according to claim 3, characterized in that The determining the remaining amount of resources of the paravirtualization platform at each moment in the future according to the execution progress information of each task being executed and the task resource management strategy includes: Obtaining the total amount of resources of the paravirtualized platform; Determine the resource requirements of each task being executed at each moment in the future according to the execution progress information of each task being executed and the task resource management strategy; The remaining amount of resources of the paravirtualization platform at each moment in the future is determined according to the total amount of resources and the resource demand amount of each task being executed at each moment in the future.
5. The method according to claim 1, characterized in that The determining of the target resource management strategy for the target task according to the first resource remaining curve and the resource demand curve includes: Determining a start time of executing the target task according to the first resource remaining curve and the resource demand curve; A target resource management strategy for the target task is determined according to the execution start time and the resource demand curve.
6. The method according to claim 5, characterized in that The step of determining the start execution time of the target task according to the first resource remaining curve and the resource demand curve includes: Determining a plurality of quasi-execution time points allowing execution of the target task according to the first resource surplus curve and the resource demand curve; According to each of the quasi-execution time points and the resource demand curve, predict a second resource remaining curve of the para-virtualized platform and an end time of the target task when the target task is executed according to the quasi-execution time point; Determining a resource management evaluation at each quasi-execution time point according to the second resource remaining curve and the end time; The execution start time is determined from a plurality of quasi-execution time points according to the resource management evaluation.
7. A resource management device for a paravirtualized platform, characterized in that: include: The first acquisition module is used to acquire the process information and priority information of the target task; A first determination module is used to determine a resource demand curve of resource demand changes over time when the target task is executed in the virtual machine according to the priority information and the process information; A second acquisition module is used to acquire a first resource remaining curve of the remaining resources in the paravirtualization platform changing with time; The second determination module is used to determine a target resource management strategy for the target task according to the first resource surplus curve and the resource demand curve.
8. A computer electronic production equipment, characterized in that: The invention comprises a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.
9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.
10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.