WO2021057981A1 - 云计费方法、装置、云管理平台、系统及存储介质 - Google Patents

云计费方法、装置、云管理平台、系统及存储介质 Download PDF

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Publication number
WO2021057981A1
WO2021057981A1 PCT/CN2020/118162 CN2020118162W WO2021057981A1 WO 2021057981 A1 WO2021057981 A1 WO 2021057981A1 CN 2020118162 W CN2020118162 W CN 2020118162W WO 2021057981 A1 WO2021057981 A1 WO 2021057981A1
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Prior art keywords
virtual machine
parameter
cost
cloud
service
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PCT/CN2020/118162
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English (en)
French (fr)
Inventor
童遥
戚晨
王海新
程希
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中兴通讯股份有限公司
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Publication of WO2021057981A1 publication Critical patent/WO2021057981A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/02—Details
    • H04L12/14—Charging, metering or billing arrangements for data wireline or wireless communications
    • H04L12/1403—Architecture for metering, charging or billing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F9/00—Arrangements for program control, e.g. control units
    • G06F9/06—Arrangements for program control, e.g. control units using stored programs, i.e. using an internal store of processing equipment to receive or retain programs
    • G06F9/44—Arrangements for executing specific programs
    • G06F9/455—Emulation; Interpretation; Software simulation, e.g. virtualisation or emulation of application or operating system execution engines
    • G06F9/45533—Hypervisors; Virtual machine monitors
    • G06F9/45558—Hypervisor-specific management and integration aspects
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L12/00—Data switching networks
    • H04L12/02—Details
    • H04L12/14—Charging, metering or billing arrangements for data wireline or wireless communications

Definitions

  • This application relates to the field of cloud computing, for example, to a cloud billing method, device, cloud management platform, system, and storage medium.
  • Cloud computing is an important milestone in the development of distributed computing. It is an emerging technology field in computer science. It realizes the value-added information of the network in the process of transmitting computing resources and application services. At the same time, cloud resource measurement, pricing and Functional requirements such as charging have become a core issue that cloud service providers and users are concerned about.
  • the cloud billing method can be that users pay a certain fee for their cloud services per unit time regardless of resource usage, such as monthly billing. Although the user’s fee is lower, this method damages the fairness between different users . Also did not comprehensively consider congestion control and traffic management, resource utilization is low, providers have to pay a higher price in order to improve resource utilization; some cloud billing methods increase prices in the case of network congestion, prompting users to reduce business The user must specify the priority he needs when signing a contract and pay different fees for the traffic of different priorities. In this way, the user wants to get better cloud services to pay higher Costs make the overall cost high.
  • This application provides a cloud billing method, device, cloud management platform, system, and storage medium to minimize overall costs and maximize resource utilization.
  • a cloud billing method including:
  • the virtual machine usage information includes the type of virtual machine, the number of each type of virtual machine, the specifications of each type of virtual machine, and the response required from receiving the service request to the end of creating the virtual machine time;
  • a cloud billing device including:
  • the information acquisition module is configured to acquire virtual machine usage information of the business, where the virtual machine usage information includes the type of virtual machine, the number of each type of virtual machine, the specifications of each type of virtual machine, and the time from receiving a service request to creating a virtual machine. The response time required for the end of the machine;
  • the calculation module is configured to calculate the actual cost of using the virtual machine in the service according to the virtual machine use information.
  • a cloud management platform including:
  • One or more processors are One or more processors;
  • Storage device set to store one or more programs
  • the one or more processors When the one or more programs are executed by the one or more processors, the one or more processors implement the aforementioned cloud billing method.
  • a cloud billing system including: a computing node, a switch, a storage resource pool, and the aforementioned cloud management platform, the switch is respectively connected to the cloud management platform, the computing node, and the storage resource pool;
  • the computing node is set to drive a virtual machine to provide cloud services to the business
  • the storage resource pool is set as a storage virtual machine resource
  • the cloud management platform includes a business management sub-platform and a resource management sub-platform.
  • a computer-readable storage medium is also provided, and a computer program is stored on the computer-readable storage medium, and when the program is executed by a processor, the foregoing cloud charging method is implemented.
  • FIG. 1 is a flowchart of a cloud charging method provided by an embodiment
  • FIG. 2 is a flowchart of another cloud charging method provided by an embodiment
  • FIG. 3 is a schematic diagram of a cloud charging device provided by an embodiment
  • FIG. 4 is a schematic structural diagram of a cloud management platform provided by an embodiment
  • FIG. 5 is a schematic structural diagram of a cloud billing system provided by an embodiment
  • FIG. 6 is a schematic diagram of the implementation of a cloud billing system provided by an embodiment
  • Fig. 7 is a schematic structural diagram of another cloud charging system in an embodiment.
  • Cloud billing methods are usually based on computing resources and network bandwidth resources. To reduce costs, it is difficult to balance congestion control and traffic management, resulting in low resource utilization, or users who want to obtain better cloud services have to pay The higher the cost, the higher the overall cost.
  • the cloud billing method of this embodiment associates cloud resources with time utility, performs metering and billing of cloud resources from the perspective of minimizing overall costs and maximizing resource utilization, and provides a decision basis for adjusting cloud resource reservation strategies.
  • FIG. 1 is a flowchart of a cloud charging method provided in an embodiment. As shown in FIG. 1, the cloud charging method provided in this embodiment includes step 110 and step 120.
  • step 110 the virtual machine usage information of the service is obtained.
  • the virtual machine usage information includes the type of the virtual machine, the number of each type of virtual machine, the specifications of each type of virtual machine, and the location from the reception of the service request to the end of the creation of the virtual machine. The required response time.
  • step 120 the actual cost of using the virtual machine for the service is calculated according to the virtual machine use information.
  • the types of the virtual machines include reserved virtual machines, initial virtual machines, and additional virtual machines; the response time includes the pre-reservation required from receiving the service request to the end of the reserved virtual machine reservation. Leave the response time, the use response time required from receiving the service request to the end of the initial virtual machine creation, and the additional response time required from the monitoring of the service resource parameter exceeding the preset threshold to the end of the additional virtual machine creation.
  • the user can log in to the self-service portal of the cloud platform and submit a business application.
  • the business application can include the name of the business, the name of the business template, the number of virtual machines required for the business, specifications, and the type of virtual machine (network (Web) server, Database, etc.).
  • the business template stores the reservation strategy of multiple services.
  • the system will reserve the corresponding computing and storage resources for the business application according to the business template corresponding to the business, and generate the usage information of the reserved virtual machine, such as the reserved virtual machine The number of reserved virtual machines, the specifications of the reserved virtual machines, and the reserved response time, etc., where the reserved response time is the response time from the reception of the service request to the end of the reserved resources.
  • the cloud management platform Before requesting the use of virtual machines, the cloud management platform must reserve a certain number of virtual machines for each possible user. After the user requests the use of virtual machines, it does not matter whether the total amount of virtual machine resources finally used reaches the reserved resources. Users need to pay the corresponding reserved virtual machine fees for these reserved virtual machine resources.
  • the administrator can review the business request submitted by the user to verify whether the business is supported by the cloud management platform, whether the user's identity is verified, and the user's account and payment environment Perform security verification, etc., if the review fails, the business is directly rejected; if the review is passed, the initial virtual machine is created for business use, and the use information of the initial virtual machine is generated, such as the number of initial virtual machines, the initial virtual machine
  • the use response time is the response time from the receipt of the service request to the completion of the initial virtual machine creation.
  • the number and specifications of the initial virtual machine can be based on the business template.
  • the number and specifications of reserved virtual machines are determined, and may be consistent with the number or specifications of reserved virtual machines, or a certain gap may be allowed within a certain range.
  • During business operation monitor multiple business indicators (such as Hypertext Transfer Protocol (HTTP) connections, database connections, Central Processing Unit (CPU) occupancy, memory occupancy, etc.), if any If the business index exceeds the preset threshold, an additional business virtual machine is created for business use, and usage information of the additional virtual machine is generated, such as the number of additional virtual machines, the specifications of the additional virtual machines, and the additional response time, among which, the additional response time It is the response time required from the monitoring that the service resource parameter exceeds the preset threshold to the end of the creation of the additional virtual machine.
  • HTML Hypertext Transfer Protocol
  • CPU Central Processing Unit
  • Additional virtual machine means that when the total amount of resources required in the actual operation of the business exceeds the amount of resources reserved for it by the cloud platform, the virtual machine resources need to be temporarily scheduled to meet the user's demand for resources by creating additional virtual machines. When enjoying additional virtual machines, you also need to pay the corresponding additional virtual machine fees.
  • the preset threshold can be determined according to the service template or the usage information of the reserved virtual machine.
  • the actual cost of using the virtual machine for the business is related to the use information of the multiple types of virtual machines mentioned above. For example, the more the number of virtual machines of each type, the higher the specification configuration, or the longer the response time, the corresponding The higher the cost.
  • service templates corresponding to multiple types of services can be adjusted, thereby adjusting the reservation strategy to avoid reserving too many virtual machine resources and causing low resource utilization.
  • the cloud billing method provided in this embodiment associates cloud resources with time utility, objectively performs reasonable billing based on response time and the cost of providing virtual machines, takes into account time utility, and ensures fairness between users or services. It provides a decision-making basis for adjusting cloud resource reservation strategies, and realizes the minimization of overall costs and the maximization of resource utilization.
  • the actual cost is the sum of the first parameter, the second parameter, the third parameter and the equivalent time factor corresponding to the response time, where the first parameter is the cost of using a single reserved virtual machine and the reserved virtual machine
  • the second parameter is the product of the cost of the initial virtual machine and the demand variable factor
  • the cost of the initial virtual machine is the product of the cost of using a single initial virtual machine and the number of initial virtual machines
  • the third parameter is additional The product of the cost of a virtual machine and a variable demand factor.
  • the cost of an additional virtual machine is the product of the cost of using a single additional virtual machine and the number of additional virtual machines
  • the equivalent time factor is positively related to the response time
  • the demand variable factor Meet the normal distribution.
  • the actual cost can be expressed as A1+A2+A3+T0, where A1 represents the first parameter, A2 represents the second parameter, A3 represents the third parameter, and T0 represents the equivalent time factor.
  • A1 is the product of the cost of using a single reserved virtual machine and the number of reserved virtual machines
  • A2 is the product of the cost of using a single initial virtual machine, the number of initial virtual machines and the variable demand factor
  • A3 is the product of using The product of the cost of a single additional virtual machine, the number of additional virtual machines, and the variable demand factor.
  • the demand variable factor is expressed as f(x), x is a random variable.
  • the actual demand is also taken into consideration, and the uncertainty of demand will affect the random change of the cost.
  • the random demand is expressed, and the resource usage can be described more accurately, so as to achieve the optimal cost.
  • the equivalent time factor is the sum of the fifth parameter, the sixth parameter, and the sixth parameter, where the fifth parameter is the ratio of the reserved response time to the first parameter; the sixth parameter is The ratio of the use response time to the second parameter; the sixth parameter is the ratio of the additional response time to the third parameter.
  • the greater the equivalent time factor the greater the cost of providing virtual machine resources and the higher the cost of the cloud management platform.
  • the actual cost is the sum of the first parameter, the second parameter, the third parameter and the equivalent time factor corresponding to the response time; wherein, the first parameter is the use of a single The product of the cost of the reserved virtual machine and the number of reserved virtual machines; the second parameter is the product of the cost of the initial virtual machine and the demand variable factor, and the cost of the initial virtual machine is the cost of using a single initial virtual machine and the initial virtual machine.
  • the third parameter is the product of the cost of the additional virtual machine and the demand variable factor, and the cost of the additional virtual machine is the product of the cost of using a single additional virtual machine and the number of additional virtual machines; the equivalent time factor Is 0; the demand variable factor satisfies a normal distribution.
  • the preset service can be a non-low-latency service, a regular service, or a service with a low priority, such as image or video upload and storage, and regular mail sending.
  • This type of service does not require high delay. , It is allowed to wait for a longer response time and provide virtual machine resources for other low-latency services first.
  • FIG. 2 is a flowchart of another cloud charging method provided by an embodiment. As shown in FIG. 2, the method includes step 210 to step 280.
  • step 210 a service request is received.
  • the user logs in to the self-service portal of the cloud platform and submits a business request.
  • step 220 the virtual machine is reserved according to the service template corresponding to the service request.
  • step 230 when the service request passes the review, an initial virtual machine is created according to the service template.
  • step 240 it is monitored whether the service parameter exceeds a preset threshold, and if the resource exceeds the preset threshold, step 250 is executed; if the resource does not exceed the preset threshold, step 260 is executed.
  • step 250 additional virtual machines are created according to the service parameters.
  • the virtual machine resources are temporarily scheduled, and additional virtual machines are created to meet the user's needs.
  • step 260 the virtual machine usage information of the service is obtained.
  • the virtual machine usage information includes the type of virtual machine, the number of each type of virtual machine, the specifications of each type of virtual machine, and the location from the reception of the service request to the end of the creation of the virtual machine. The required response time.
  • step 270 the actual cost of using the virtual machine for the service is calculated according to the virtual machine use information.
  • step 280 the service template is updated according to a preset principle.
  • the preset principle includes: adjusting the number of reserved virtual machines, the specifications of the reserved virtual machines, and the reserved response time to minimize the actual cost.
  • the service template is updated according to the cloud charging result within a preset time period. For example, for SMS services, the use of virtual machine information and billing results within a week are counted, and it is found that there are too many virtual machine resources reserved in the service template, and each time there are remaining virtual machines that are not used, you can Adjust the reservation strategy, reduce the number or specifications of reserved virtual machines to reduce the reserved response time, and then reduce the actual cost in subsequent applications; another example, after statistics, it is found that the reserved virtual machine resources in the business template are too few. Each time you need to create additional virtual machines to support business operations, you can increase the number or specifications of reserved virtual machines, thereby increasing the reserved response time. By adjusting the strategy of reserving virtual machines (thus affecting the number, specifications, and additional response time of additional virtual machines) until the value that minimizes the actual cost is found, the reserving strategy in the business template is updated.
  • the cloud billing method of this embodiment uses demand variable factors and equivalent time factors to establish a comprehensive cloud billing model, simulates time utility and business requirements, is suitable for different types of business, and associates cloud resources with time utility, From the perspective of minimizing overall costs and maximizing resource utilization, cloud resources are metered and billed, which provides a basis for decision-making and flexible billing for adjusting cloud resource reservation strategies.
  • Fig. 3 is a schematic structural diagram of a cloud charging device provided by an embodiment. As shown in FIG. 3, the cloud charging device includes: an information acquisition module 310 and a calculation module 320.
  • the information acquisition module 310 is configured to acquire virtual machine usage information of the service, the virtual machine usage information including the type of virtual machine, the number of each type of virtual machine, the specifications of each type of virtual machine, and the time from receiving a service request to creating a virtual machine End the required response time; the calculation module 320 is configured to calculate the actual cost of using the virtual machine for the business according to the virtual machine use information.
  • the cloud billing device of this embodiment associates cloud resources with time utility, objectively performs reasonable billing based on the response time and the cost of providing virtual machines, takes into account the time utility, and ensures fairness between users or services. , To provide a decision-making basis for adjusting cloud resource reservation strategies, and to minimize overall costs and maximize resource utilization.
  • the types of the virtual machines include reserved virtual machines, initial virtual machines, and additional virtual machines; the response time includes the pre-reservation required from receiving the service request to the end of the reserved virtual machine reservation. Leave the response time, the use response time required from receiving the service request to the end of the initial virtual machine creation, and the additional response time required from the monitoring of the service resource parameter exceeding the preset threshold to the end of the additional virtual machine creation.
  • the actual cost is the sum of the first parameter, the second parameter, the third parameter and the equivalent time factor corresponding to the response time
  • the first parameter is the use of a single reserved virtual machine
  • the second parameter is the product of the cost of the initial virtual machine and the demand variable factor
  • the cost of the initial virtual machine is the cost of using a single initial virtual machine and the initial virtual machine
  • the third parameter is the product of the cost of the additional virtual machine and the demand variable factor
  • the cost of the additional virtual machine is the product of the cost of using a single additional virtual machine and the number of additional virtual machines
  • the equivalent time factor is positively correlated with the response time; the demand variable factor satisfies a normal distribution.
  • the equivalent time factor is a sum of a fifth parameter, a sixth parameter, and a sixth parameter, wherein the fifth parameter is a ratio of the reserved response time to the first parameter;
  • the sixth parameter is the ratio of the use response time to the second parameter;
  • the sixth parameter is the ratio of the additional response time to the third parameter.
  • the actual cost is the sum of the first parameter, the second parameter, the third parameter, and the equivalent time factor corresponding to the response time; wherein, the The first parameter is the product of the cost of using a single reserved virtual machine and the number of reserved virtual machines; the second parameter is the product of the cost of the initial virtual machine and the demand variable factor, and the cost of the initial virtual machine is the product of using The product of the cost of a single initial virtual machine and the number of initial virtual machines; the third parameter is the product of the cost of the additional virtual machine and the demand variable factor, and the cost of the additional virtual machine is the cost of using a single additional virtual machine and The product of the number of additional virtual machines; the equivalent time factor is 0; and the demand variable factor satisfies a normal distribution.
  • it further includes:
  • the receiving module is set to receive the service request; the reservation module is set to reserve the virtual machine according to the service template corresponding to the service request; the initial creation module is set to be based on the service request when the service request is approved.
  • the template creates an initial virtual machine; an additional creation module is set to create an additional virtual machine according to the business parameter when the monitored business parameter exceeds the preset threshold.
  • it further includes:
  • the update module is configured to update the service template according to a preset principle; the preset principle includes: adjusting the number of reserved virtual machines, the specifications of the reserved virtual machines, and the reserved response time to minimize the actual cost.
  • the cloud billing device proposed in this embodiment and the cloud billing method proposed in the foregoing embodiment belong to the same concept.
  • technical details that are not described in detail in this embodiment please refer to any of the foregoing embodiments.
  • the embodiment of the present application also provides a cloud management platform.
  • the cloud charging method may be executed by a cloud charging device, which may be implemented in software and/or hardware, and integrated in the cloud management platform.
  • the cloud management platform may be a server configured for business service management, resource management, and billing.
  • Fig. 4 is a schematic structural diagram of a cloud management platform provided by an embodiment.
  • the cloud management platform provided in this embodiment may be a server that charges for service use of virtual machines, and includes a processor 410 and a storage device 420. There may be one or more processors in the cloud management platform.
  • one processor 410 is taken as an example.
  • the processor 410 and the storage device 420 in the device may be connected by a bus or other methods. In FIG. Take the bus connection as an example.
  • the one or more programs are executed by the one or more processors 410, so that the one or more processors implement the cloud charging method described in any of the foregoing embodiments.
  • the storage device 420 in the cloud management platform can be configured to store one or more programs.
  • the programs can be software programs, computer-executable programs, and modules.
  • the program instructions/modules corresponding to the charging method include: an information acquisition module 310 and a calculation module 320).
  • the processor 410 executes multiple functional applications and data processing of the cloud management platform by running the software programs, instructions, and modules stored in the storage device 420, that is, implements the cloud billing method in the foregoing method embodiment.
  • the storage device 420 mainly includes a storage program area and a storage data area.
  • the storage program area can store an operating system and an application program required by at least one function; the storage data area can store data created according to the use of the device, etc. (as in the above implementation) The virtual machine usage information, actual cost, etc. in the example).
  • the storage device 420 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices.
  • the storage device 420 may include a memory remotely provided with respect to the processor 410, and these remote memories may be connected to a cloud management platform through a network. Examples of the aforementioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
  • the virtual machine usage information of the service is acquired, and the virtual machine usage information includes the virtual machine usage information.
  • the cloud management platform proposed in this embodiment and the cloud billing method proposed in the foregoing embodiment belong to the same concept.
  • this embodiment is capable of performing cloud billing Same effect as the method.
  • Fig. 5 is a schematic structural diagram of a cloud charging system provided by an embodiment.
  • the cloud billing system includes: a computing node 530, a switch 520, a storage resource pool 540, and the aforementioned cloud management platform 510.
  • the switch 520 is connected to the cloud management platform 510, computing node 530, and storage resource pool 540, respectively. Connection; the computing node 530 is set to drive virtual machines to provide cloud services to the business; the storage resource pool 540 is set to store virtual machine resources; the cloud management platform 510 includes a business management sub-platform and a resource management sub-platform.
  • the cloud management platform 510 is a top-level management module built on virtualized basic resources, which can be divided into two parts: a resource management sub-platform and a business management sub-platform.
  • the resource management sub-platform is directly oriented to virtual machine resources and is responsible for the allocation and invocation of resources, while the business management sub-platform is associated with service objects and is mainly responsible for the management, coordination and billing of user services.
  • service objects and is mainly responsible for the management, coordination and billing of user services.
  • Fig. 6 is a schematic diagram of the implementation of a cloud charging system provided by an embodiment.
  • the cloud management platform 510 is deployed on the dual-computer management node in the management control area, the virtualization software iECS and the cloud operation and maintenance management software iROS are deployed in the cloud management platform 510, and the management network uses 5952 Gigabit switches; computing The nodes use R5300 dual-channel servers, and the business network uses 59.6 Gigabit switches; the storage solution uses the Internet Protocol Storage Area Network (IP SAN) 10 Gigabit solution, and the storage resource pool uses the KS3200 magnetic array.
  • IP SAN Internet Protocol Storage Area Network
  • Fig. 7 is a schematic structural diagram of another cloud charging system in an embodiment.
  • the cloud management platform 510 includes a business service management platform and a resource management platform.
  • the business service management platform is set to manage multiple types of services, control business processes, charge for business use of virtual machines, and manage user personal information, etc.;
  • the resource management platform is set up for resource scheduling, management of business templates, management interfaces, management of the life cycle of virtual machines (such as initialization, creation and cancellation, etc.), automatic deployment of virtual machines, and provision of elastic capabilities (such as creating and managing additional virtual machines), Resource monitoring metrics (monitoring whether business parameters exceed thresholds), etc.
  • the cloud management platform 510 and the hardware in the infrastructure resource pool constitute a cloud billing system, which realizes computing virtualization, network virtualization, and storage virtualization, and performs comprehensive management and billing of cloud services.
  • the embodiment of the present application also provides a storage medium containing computer-executable instructions, and the computer-executable instructions are used to execute a cloud billing method when executed by a computer processor.
  • this application can be implemented by software and general-purpose hardware, and can also be implemented by hardware.
  • the technical solution of the present application can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), Random Access Memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including multiple instructions to make a computer device (which can be a personal computer, server, or network device, etc.) execute any of this application The method described in the embodiment.
  • the block diagram of any logic flow in the drawings of the present application may represent program steps, or may represent interconnected logic circuits, modules, and functions, or may represent a combination of program steps and logic circuits, modules, and functions.
  • the computer program can be stored on the memory.
  • the memory can be of any type suitable for the local technical environment and can be implemented using any suitable data storage technology, such as but not limited to ROM, RAM, optical storage devices and systems (Digital Video Disc, DVD) or optical disk ( Compact Disk, CD)) etc.
  • Computer-readable media may include non-transitory storage media.
  • the data processor can be any type suitable for the local technical environment, such as but not limited to general-purpose computers, special-purpose computers, microprocessors, digital signal processors (Digital Signal Processing, DSP), application specific integrated circuits (ASICs) ), programmable logic devices (Field-Programmable Gate Array, PFGA), and processors based on multi-core processor architecture.
  • DSP Digital Signal Processing
  • ASICs application specific integrated circuits
  • PFGA programmable logic devices
  • processors based on multi-core processor architecture such as but not limited to general-purpose computers, special-purpose computers, microprocessors, digital signal processors (Digital Signal Processing, DSP), application specific integrated circuits (ASICs) ), programmable logic devices (Field-Programmable Gate Array, PFGA), and processors based on multi-core processor architecture.
  • PFGA Field-Programmable Gate Array

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Abstract

本文公开了一种云计费方法、装置、云管理平台、系统及存储介质。该云计费方法包括：获取业务的虚拟机使用信息，其中，所述虚拟机使用信息包括虚拟机的类型、每类虚拟机的数量、每类虚拟机的规格以及从接收到业务请求到创建虚拟机结束所需的响应时间；根据所述虚拟机使用信息计算所述业务中使用虚拟机的实际费用。

Description

云计费方法、装置、云管理平台、系统及存储介质
本申请要求在2019年09月27日提交中国专利局、申请号为201910927936.1的中国专利申请的优先权，该申请的全部内容通过引用结合在本申请中。
技术领域
本申请涉及云计算领域，例如涉及一种云计费方法、装置、云管理平台、系统及存储介质。
背景技术
云计算是分布式计算发展的重要里程碑，是计算机科学中的一个新兴的技术领域，实现了网络在传输计算资源和应用服务的过程中的信息增值，与此同时，云资源的计量、定价和收费等功能需求成为云服务提供商和用户关注的核心问题。
云计费方式，可以是用户为其每单位时间的云服务支付一定的费用而与资源用量无关，例如包月计费，这种方式虽然用户的费用较低，但损坏了不同用户间的公平性，也未综合考虑拥塞控制和流量管理，资源利用率低下，提供商为了提高资源利用率也要付出更高的代价；也有的云计费方式在网络拥塞的情况下提升价格，促使用户减少业务量，或者根据优先级处理业务，用户在签约时必须指定其需要的优先级并为不同优先级的流量支付不同费用，这种方式下用户想要获得更好的云服务就要支付更高的费用，使得整体费用偏高。
发明内容
本申请提供一种云计费方法、装置、云管理平台、系统及存储介质，以实现整体费用最小化和资源利用率的最大化。
提供了一种云计费方法，包括：
获取业务的虚拟机使用信息，其中，所述虚拟机使用信息包括虚拟机的类型、每类虚拟机的数量、每类虚拟机的规格以及从接收到业务请求到创建虚拟机结束所需的响应时间；
根据所述虚拟机使用信息计算所述业务中使用虚拟机的实际费用。
还提供了一种云计费装置，包括：
信息获取模块，设置为获取业务的虚拟机使用信息，其中，所述虚拟机使 用信息包括虚拟机的类型、每类虚拟机的数量、每类虚拟机的规格以及从接收到业务请求到创建虚拟机结束所需的响应时间；
计算模块，设置为根据所述虚拟机使用信息计算所述业务中使用虚拟机的实际费用。
还提供了一种云管理平台，包括：
一个或多个处理器；
存储装置，设置为存储一个或多个程序；
当所述一个或多个程序被所述一个或多个处理器执行，使得所述一个或多个处理器实现上述的云计费方法。
还提供了一种云计费系统，包括：计算节点、交换机、存储资源池以及上述的云管理平台，所述交换机分别与所述云管理平台、所述计算节点和所述存储资源池连接；
所述计算节点设置为驱动虚拟机以向业务提供云服务；
所述存储资源池设置为存储虚拟机资源；
所述云管理平台包括业务管理子平台和资源管理子平台。
还提供了一种计算机可读存储介质，计算机可读存储介质上存储有计算机程序，该程序被处理器执行时实现上述的云计费方法。
附图说明
图1为一实施例提供的一种云计费方法的流程图；
图2为一实施例提供的另一种云计费方法的流程图；
图3为一实施例提供的一种云计费装置的示意图；
图4为一实施例提供的一种云管理平台的结构示意图；
图5为一实施例提供的一种云计费系统的结构示意图；
图6为一实施例提供的一种云计费系统的实现示意图；
图7为一实施例中的另一种云计费系统的结构示意图。
具体实施方式
下面结合附图和实施例对本申请进行说明。
云计费方法通常是根据计算资源、网络带宽资源计量计费，想要降低费用 就难以兼顾拥塞控制和流量管理，导致资源利用率低下，或者，用户想要获得更好的云服务就要支付更高的费用，整体费用偏高。本实施例的云计费方法，将云资源与时间效用关联起来，从整体费用最小化和资源利用最大化的角度进行云资源的计量计费，为调整云资源预留策略提供决策依据。
图1为一实施例提供的一种云计费方法的流程图，如图1所示，本实施例提供的云计费方法包括步骤110和步骤120。
在步骤110中，获取业务的虚拟机使用信息，所述虚拟机使用信息包括虚拟机的类型、每类虚拟机的数量、每类虚拟机的规格以及从接收到业务请求到创建虚拟机结束所需的响应时间。
在步骤120中，根据所述虚拟机使用信息计算业务使用虚拟机的实际费用。
在一实施例中，所述虚拟机的类型包括预留虚拟机、初始虚拟机和附加虚拟机；所述响应时间包括从接收到业务请求到所述预留虚拟机预留结束所需的预留响应时间、从接收到业务请求到所述初始虚拟机创建结束所需的使用响应时间以及从监测到业务资源参数超过预设阈值到所述附加虚拟机创建结束所需的附加响应时间。
本实施例中，用户可以登录云平台的自服务门户并提交业务申请，业务申请可以包括业务名称、业务模板名称、业务所需虚拟机个数、规格、虚拟机类型(网络(Web)服务器、数据库等)。业务模板中存储了多种业务的预留策略，系统会根据该业务对应的业务模板为该业务申请预留相应的计算和存储资源，并生成预留虚拟机的使用信息，例如预留虚拟机的个数、预留虚拟机的规格和预留响应时间等，其中，预留响应时间为从接收到业务请求到预留资源结束的响应时间。在请求使用虚拟机之前，云管理平台对每一个可能的用户都要预留一定数量的虚拟机，在用户提出虚拟机使用请求之后，无论其最终使用的虚拟机资源总量是否达到预留资源量，用户都需要为这些预留的虚拟机资源支付相应的预留虚拟机费用。
预留虚拟机资源结束后，可以由管理员对用户提交的业务请求进行审核，审核该业务是否为云管理平台支持的业务、该用户的身份是否通过验证、以及对该用户的账号、支付环境等进行安全验证等，如果审核不通过，则直接拒绝该业务；如果审核通过，则创建初始虚拟机供业务使用，并生成初始虚拟机的使用信息，例如初始虚拟机的个数、初始虚拟机的规格和使用响应时间等，其中，使用响应时间为从接收到业务请求到所述初始虚拟机创建结束所需的响应时间，初始虚拟机的个数和规格可根据依据业务模板为该业务的预留虚拟机的个数和规格确定，可与预留虚拟机的个数或规格一致，或者在一定范围内可以允许有一定差距。
在业务运行过程中，监控多项业务指标(例如超文本传输协议(Hypertext Transfer Protocol，HTTP)连接数、数据库连接数、中央处理器(Central Processing Unit，CPU)占用、内存占用等)，如果有业务指标超过预设阈值，则创建附加业务虚拟机供业务使用，并生成附加虚拟机的使用信息，例如附加虚拟机的个数、附加虚拟机的规格和附加响应时间等，其中，附加响应时间为从监测到业务资源参数超过预设阈值到所述附加虚拟机创建结束所需的响应时间。附加虚拟机是指业务实际运行中需要的资源总量超过了云平台为其预留的资源量时，需要临时调度虚拟机资源，以创建额外的虚拟机的方式满足用户对资源的需求，用户在享受附加虚拟机时也需要支付相应的附加虚拟机费用。预设阈值可根据业务模板或预留虚拟机的使用信息确定。
在一实施例中，业务使用虚拟机的实际费用与上述的多类虚拟机的使用信息相关，例如，每类虚拟机的个数越多或规格配置越高、或响应时间越长，则对应的费用越高。
在一实施例中，根据历史业务对虚拟机资源的历史使用情况，可以调整多类业务对应的业务模板，从而调整预留策略，避免预留过多的虚拟机资源造成资源利用率低。
本实施例提供的云计费方法，通过将云资源与时间效用关联起来，客观地根据响应时间和提供虚拟机的成本进行合理计费，考虑了时间效用，保证了用户或业务之间的公平性，为调整云资源预留策略提供决策依据，实现了整体费用最小化和资源利用率的最大化。
在一实施例中，实际费用为第一参量、第二参量、第三参量与响应时间对应的等效时间因子的和，其中，第一参量为使用单个预留虚拟机的费用与预留虚拟机的数量的乘积；第二参量为初始虚拟机的费用与需求可变因子的乘积，初始虚拟机的费用为使用单个初始虚拟机的费用与初始虚拟机的数量的乘积；第三参量为附加虚拟机的费用与需求可变因子的乘积，附加虚拟机的费用为使用单个附加虚拟机的费用与附加虚拟机的数量的乘积；等效时间因子与响应时间正相关；所述需求可变因子满足正态分布。
在一实施例中，实际费用可表示为A1+A2+A3+T0，其中，A1表示第一参量，A2表示第二参量，A3表示第三参量，T0表示等效时间因子。其中，A1为使用单个预留虚拟机的费用与预留虚拟机的数量的乘积，A2为使用单个初始虚拟机的费用、初始虚拟机的数量与需求可变因子三者的乘积，A3为使用单个附加虚拟机的费用、附加虚拟机的数量与需求可变因子三者的乘积。需求可变因子表示为f(x)，
Figure PCTCN2020118162-appb-000001
x为随机变量。本实施例在对虚拟机资源进 行分配优化的过程中，除了考虑价格、时间等因素的影响外，还考虑到实际需求量问题，需求的不确定性会影响费用随机变化。通过正态分布的需求可变因子表示随机的需求量，更准确地描述资源使用情况，从而达到费用最优。一实施例中，需求可变因子满足标准正态分布函数，即
Figure PCTCN2020118162-appb-000002
期望值u＝0，标准差σ＝1。
在一实施例中，等效时间因子为第五参量、第六参量和第六参量的和，其中，第五参量为所述预留响应时间与所述第一参量的比值；第六参量为所述使用响应时间与所述第二参量的比值；第六参量为所述附加响应时间与所述第三参量的比值。等效时间因子越大，说明云管理平台提供虚拟机资源的代价越大，费用越高。
本实施例中，等效时间因子表示为k，k＝(预留响应时间)/(预留虚拟机的费用)+(使用响应时间)/(初始虚拟机的费用)+(附加响应时间)/(附加虚拟机的费用)。
在一实施例中，在业务为预设业务的情况下，实际费用为第一参量、第二参量、第三参量与响应时间对应的等效时间因子的和；其中，第一参量为使用单个预留虚拟机的费用与预留虚拟机的数量的乘积；第二参量为初始虚拟机的费用与需求可变因子的乘积，初始虚拟机的费用为使用单个初始虚拟机的费用与初始虚拟机的数量的乘积；第三参量为附加虚拟机的费用与需求可变因子的乘积，附加虚拟机的费用为使用单个附加虚拟机的费用与附加虚拟机的数量的乘积；所述等效时间因子为0；所述需求可变因子满足正态分布。
本实施例中，预设业务可以为非低时延业务、定时业务、优先级低的业务，例如图像或视频的上传和保存、定时发送邮件等业务，这类业务对时延的要求不高，允许等待较长的响应时间而先为其他低时延业务提供虚拟机资源，这种情况下，等效时间因子表示为k，k＝0，即响应时间不参与计费。
图2为一实施例提供的另一种云计费方法的流程图，如图2所示，该方法包括步骤210至步骤280。
在步骤210中，接收业务请求。本步骤中，用户登录云平台的自服务门户并提交业务请求。
在步骤220中，根据所述业务请求对应的业务模板预留虚拟机。
在步骤230中，在所述业务请求通过审核的情况下，根据所述业务模板创建初始虚拟机。
在步骤240中，监测业务参数是否超过预设阀值，如果资源超过预设阀值， 则执行步骤250；如果资源未超过预设阀值，执行步骤260。
在步骤250中，根据所述业务参数创建附加虚拟机。本步骤中，在用户实际应用中需要的资源总量超过了云管理平台为其预留的资源量的情况下，临时调度虚拟机资源，创建附加虚拟机以满足用户需求。
在步骤260中，获取业务的虚拟机使用信息，所述虚拟机使用信息包括虚拟机的类型、每类虚拟机的数量、每类虚拟机的规格以及从接收到业务请求到创建虚拟机结束所需的响应时间。
在步骤270中，根据所述虚拟机使用信息计算业务使用虚拟机的实际费用。
在步骤280中，按照预设原则更新所述业务模板。
在一实施例中，所述预设原则包括：调整预留虚拟机的数量、预留虚拟机的规格和预留响应时间，使得所述实际费用最小。
在一实施例中，根据预设时间段内的云计费结果更新业务模板。例如，对于短信类业务，对一周内的虚拟机的使用信息和计费结果进行统计，发现业务模板中预留的虚拟机资源偏多，每次都有剩余的虚拟机不被使用，则可调整预留策略，降低预留虚拟机的数量或规格从而减少预留响应时间，进而在之后的应用中可以降低实际费用；又如，统计后发现业务模板中预留的虚拟机资源偏少，每次都需要创建附加的虚拟机才能支持业务运行，则可提高预留虚拟机的数量或规格，从而增大预留响应时间。通过调整预留虚拟机的策略(从而影响附加虚拟机的数量、规格和附加响应时间)，直到找到使实际费用最小的值，实现业务模板中预留策略的更新。
本实施例的云计费方法，利用需求可变因子和等效时间因子建立全面的云计费模型，模拟时间效用和业务需求，适用于不同类型的业务，将云资源与时间效用关联起来，从整体费用最小化和资源利用最大化的角度进行云资源的计量计费，为调整云资源预留策略提供决策依据，灵活计费。
本申请实施例还提供一种云计费装置。图3为一实施例提供的云计费装置的结构示意图。如图3所示，所述云计费装置包括：信息获取模块310和计算模块320。
信息获取模块310，设置为获取业务的虚拟机使用信息，所述虚拟机使用信息包括虚拟机的类型、每类虚拟机的数量、每类虚拟机的规格以及从接收到业务请求到创建虚拟机结束所需的响应时间；计算模块320，设置为根据所述虚拟机使用信息计算业务使用虚拟机的实际费用。
本实施例的云计费装置，通过将云资源与时间效用关联起来，客观地根据响应时间和提供虚拟机的成本进行合理计费，考虑了时间效用，保证了用户或 业务之间的公平性，为调整云资源预留策略提供决策依据，实现了整体费用最小化和资源利用率的最大化。
在一实施例中，所述虚拟机的类型包括预留虚拟机、初始虚拟机和附加虚拟机；所述响应时间包括从接收到业务请求到所述预留虚拟机预留结束所需的预留响应时间、从接收到业务请求到所述初始虚拟机创建结束所需的使用响应时间以及从监测到业务资源参数超过预设阈值到所述附加虚拟机创建结束所需的附加响应时间。
在一实施例中，所述实际费用为第一参量、第二参量、第三参量与所述响应时间对应的等效时间因子的和，其中，所述第一参量为使用单个预留虚拟机的费用与预留虚拟机的数量的乘积；所述第二参量为初始虚拟机的费用与需求可变因子的乘积，所述初始虚拟机的费用为使用单个初始虚拟机的费用与初始虚拟机的数量的乘积；所述第三参量为附加虚拟机的费用与需求可变因子的乘积，所述附加虚拟机的费用为使用单个附加虚拟机的费用与附加虚拟机的数量的乘积；所述等效时间因子与所述响应时间正相关；所述需求可变因子满足正态分布。
在一实施例中，所述等效时间因子为第五参量、第六参量和第六参量的和，其中，所述第五参量为所述预留响应时间与所述第一参量的比值；所述第六参量为所述使用响应时间与所述第二参量的比值；所述第六参量为所述附加响应时间与所述第三参量的比值。
在一实施例中，在业务为预设业务的情况下，所述实际费用为第一参量、第二参量、第三参量与所述响应时间对应的等效时间因子的和；其中，所述第一参量为使用单个预留虚拟机的费用与预留虚拟机的数量的乘积；所述第二参量为初始虚拟机的费用与需求可变因子的乘积，所述初始虚拟机的费用为使用单个初始虚拟机的费用与初始虚拟机的数量的乘积；所述第三参量为附加虚拟机的费用与需求可变因子的乘积，所述附加虚拟机的费用为使用单个附加虚拟机的费用与附加虚拟机的数量的乘积；所述等效时间因子为0；所述需求可变因子满足正态分布。
在一实施例中，还包括：
接收模块，设置为接收业务请求；预留模块，设置为根据所述业务请求对应的业务模板预留虚拟机；初始创建模块，设置为在所述业务请求通过审核的情况下，根据所述业务模板创建初始虚拟机；附加创建模块，设置为在监测到业务参数超过预设阀值的情况下，根据所述业务参数创建附加虚拟机。
在一实施例中，还包括：
更新模块，设置为按照预设原则更新所述业务模板；所述预设原则包括：调整预留虚拟机的数量、预留虚拟机的规格和预留响应时间，使得所述实际费用最小。
本实施例提出的云计费装置与上述实施例提出的云计费方法属于同一构思，未在本实施例中详尽描述的技术细节可参见上述任意实施例，并且本实施例具备与执行云计费方法相同的效果。
本申请实施例还提供一种云管理平台。所述云计费方法可以由云计费装置执行，该云计费装置可以通过软件和/或硬件的方式实现，并集成在所述云管理平台中。所述云管理平台可以为设置为业务服务管理、资源管理和计费的服务器。
图4为一实施例提供的一种云管理平台的结构示意图。如图4所示，本实施例提供的一种云管理平台，可以为对业务使用虚拟机进行计费的服务器，包括：处理器410和存储装置420。该云管理平台中的处理器可以是一个或多个，图4中以一个处理器410为例，所述设备中的处理器410和存储装置420可以通过总线或其他方式连接，图4中以通过总线连接为例。
所述一个或多个程序被所述一个或多个处理器410执行，使得所述一个或多个处理器实现上述任一实施例所述的云计费方法。
该云管理平台中的存储装置420作为一种计算机可读存储介质，可设置为存储一个或多个程序，所述程序可以是软件程序、计算机可执行程序以及模块，如本申请实施例中云计费方法对应的程序指令/模块(例如，附图3所示的云计费装置中的模块，包括：信息获取模块310和计算模块320)。处理器410通过运行存储在存储装置420中的软件程序、指令以及模块，从而执行云管理平台的多种功能应用以及数据处理，即实现上述方法实施例中的云计费方法。
存储装置420主要包括存储程序区和存储数据区，其中，存储程序区可存储操作系统、至少一个功能所需的应用程序；存储数据区可存储根据设备的使用所创建的数据等(如上述实施例中的虚拟机使用信息、实际费用等)。此外，存储装置420可以包括高速随机存取存储器，还可以包括非易失性存储器，例如至少一个磁盘存储器件、闪存器件、或其他非易失性固态存储器件。在一些实例中，存储装置420可包括相对于处理器410远程设置的存储器，这些远程存储器可以通过网络连接至云管理平台。上述网络的实例包括但不限于互联网、企业内部网、局域网、移动通信网及其组合。
并且，当上述云管理平台中所包括一个或者多个程序被所述一个或者多个处理器410执行时，实现如下操作：获取业务的虚拟机使用信息，所述虚拟机 使用信息包括虚拟机的类型、每类虚拟机的数量、每类虚拟机的规格以及从接收到业务请求到创建虚拟机结束所需的响应时间；根据所述虚拟机使用信息计算业务使用虚拟机的实际费用。
本实施例提出的云管理平台与上述实施例提出的云计费方法属于同一构思，未在本实施例中详尽描述的技术细节可参见上述任意实施例，并且本实施例具备与执行云计费方法相同的效果。
本申请实施例还提供一种云计费系统。图5为一实施例提供的云计费系统的结构示意图。如图5所示，所述云计费系统包括：计算节点530、交换机520、存储资源池540以及上述的云管理平台510，交换机520分别与云管理平台510、计算节点530和存储资源池540连接；计算节点530设置为驱动虚拟机以向业务提供云服务；存储资源池540设置为存储虚拟机资源；云管理平台510包括业务管理子平台和资源管理子平台。
本实施例中，云管理平台510是建立在虚拟化的基础资源之上的顶层管理模块，可以将其分为资源管理子平台和业务管理子平台两部分。资源管理子平台直接面向虚拟机资源，负责资源的分配、调用，而业务管理子平台则与服务对象相关联，主要负责对用户的服务进行管理、协调以及计费处理。通过云管理平台，可以实现虚拟机的自动化部署，为用户提供弹性的计算服务，对资源进行有效监控和调度，因此大大提高了云计算环境下的资源利用率。
图6为一实施例提供的一种云计费系统的实现示意图。如图6所示，云管理平台510部署在管理控制区域的管理节点双机上，云管理平台510中部署虚拟化软件iECS和云运营运维管理软件iROS，管理网络使用5952千兆交换机；计算节点使用R5300双路服务器，业务网络使用5960万兆交换机；存储方案使用网际互连协议存储局域网络(Internet Protocol Storage Area Network，IP SAN)万兆方案，存储资源池使用KS3200磁阵。
图7为一实施例中的另一种云计费系统的结构示意图。如图7所示，云管理平台510包括业务服务管理平台和资源管理平台，业务服务管理平台设置为管理多类业务、控制业务流程、业务使用虚拟机的计费以及管理用户的个人信息等；资源管理平台设置为资源调度、管理业务模板、管理接口、管理虚拟机的生命周期(如初始化、创建和取消等)、虚拟机的自动化部署、弹性能力提供(例如创建和管理附加虚拟机)、资源监控度量(监控业务参数是否超过阈值)等。云管理平台510与基础设施资源池中的硬件构成云计费系统，实现计算虚拟化、网络虚拟化、存储虚拟化，对云服务进行完善的管理和计费。
本申请实施例还提供一种包含计算机可执行指令的存储介质，计算机可执行指令在由计算机处理器执行时用于执行一种云计费方法。
通过以上关于实施方式的描述，本申请可借助软件及通用硬件来实现，也可以通过硬件实现。基于这样的理解，本申请的技术方案可以以软件产品的形式体现出来，该计算机软件产品可以存储在计算机可读存储介质中，如计算机的软盘、只读存储器(Read-Only Memory,ROM)、随机存取存储器(Random Access Memory,RAM)、闪存(FLASH)、硬盘或光盘等，包括多个指令用以使得一台计算机设备(可以是个人计算机，服务器，或者网络设备等)执行本申请任意实施例所述的方法。
以上所述，仅为本申请的示例性实施例而已，并非用于限定本申请的保护范围。
本申请附图中的任何逻辑流程的框图可以表示程序步骤，或者可以表示相互连接的逻辑电路、模块和功能，或者可以表示程序步骤与逻辑电路、模块和功能的组合。计算机程序可以存储在存储器上。存储器可以具有任何适合于本地技术环境的类型并且可以使用任何适合的数据存储技术实现，例如但不限于ROM、RAM、光存储器装置和系统(数码多功能光碟(Digital Video Disc，DVD)或光盘(Compact Disk，CD))等。计算机可读介质可以包括非瞬时性存储介质。数据处理器可以是任何适合于本地技术环境的类型，例如但不限于通用计算机、专用计算机、微处理器、数字信号处理器(Digital Signal Processing，DSP)、专用集成电路(Application Specific Integrated Circuit，ASIC)、可编程逻辑器件(Field-Programmable Gate Array，PFGA)以及基于多核处理器架构的处理器。

Claims (11)

  1. 一种云计费方法，应用于云管理平台，包括：
    获取业务的虚拟机使用信息，其中，所述虚拟机使用信息包括虚拟机的类型、每类虚拟机的数量、每类虚拟机的规格以及从接收到业务请求到创建虚拟机结束所需的响应时间；
    根据所述虚拟机使用信息计算所述业务中使用虚拟机的实际费用。
  2. 根据权利要求1所述的方法，其中，所述虚拟机的类型包括预留虚拟机、初始虚拟机和附加虚拟机；
    所述响应时间包括从接收到所述业务请求到所述预留虚拟机预留结束所需的预留响应时间、从接收到所述业务请求到所述初始虚拟机创建结束所需的使用响应时间以及从监测到业务资源参数超过预设阈值到所述附加虚拟机创建结束所需的附加响应时间。
  3. 根据权利要求2所述的方法，其中，所述实际费用为第一参量、第二参量、第三参量与所述响应时间对应的等效时间因子的和，其中，
    所述第一参量为使用单个预留虚拟机的费用与预留虚拟机的数量的乘积；
    所述第二参量为初始虚拟机的费用与需求可变因子的乘积，所述初始虚拟机的费用为使用单个初始虚拟机的费用与初始虚拟机的数量的乘积；
    所述第三参量为附加虚拟机的费用与所述需求可变因子的乘积，所述附加虚拟机的费用为使用单个附加虚拟机的费用与附加虚拟机的数量的乘积；
    所述等效时间因子与所述响应时间正相关；
    所述需求可变因子满足正态分布。
  4. 根据权利要求3所述的方法，其中，所述等效时间因子为第五参量、第六参量和第六参量的和，其中，
    所述第五参量为所述预留响应时间与所述第一参量的比值；
    所述第六参量为所述使用响应时间与所述第二参量的比值；
    所述第六参量为所述附加响应时间与所述第三参量的比值。
  5. 根据权利要求1所述的方法，其中，在所述业务为预设业务的情况下，所述实际费用为第一参量、第二参量、第三参量与所述响应时间对应的等效时间因子的和；其中，
    所述第一参量为使用单个预留虚拟机的费用与预留虚拟机的数量的乘积；
    所述第二参量为初始虚拟机的费用与需求可变因子的乘积，所述初始虚拟 机的费用为使用单个初始虚拟机的费用与初始虚拟机的数量的乘积；
    所述第三参量为附加虚拟机的费用与所述需求可变因子的乘积，所述附加虚拟机的费用为使用单个附加虚拟机的费用与附加虚拟机的数量的乘积；
    所述等效时间因子为0；
    所述需求可变因子满足正态分布。
  6. 根据权利要求1-5中任一项所述的方法，在所述获取业务的虚拟机使用信息之前，还包括：
    接收所述业务请求；
    根据所述业务请求对应的业务模板预留虚拟机；
    在所述业务请求通过审核的情况下，根据所述业务模板创建初始虚拟机；
    在监测到业务资源参数超过预设阀值的情况下，根据所述业务资源参数创建附加虚拟机。
  7. 根据权利要求6所述的方法，还包括：
    按照预设原则更新所述业务模板；
    其中，所述预设原则包括：调整预留虚拟机的数量、预留虚拟机的规格和预留响应时间。
  8. 一种云计费装置，包括：
    信息获取模块，设置为获取业务的虚拟机使用信息，其中，所述虚拟机使用信息包括虚拟机的类型、每类虚拟机的数量、每类虚拟机的规格以及从接收到业务请求到创建虚拟机结束所需的响应时间；
    计算模块，设置为根据所述虚拟机使用信息计算所述业务中使用虚拟机的实际费用。
  9. 一种云管理平台，包括：
    至少一个处理器；
    存储装置，设置为存储至少一个程序；
    当所述至少一个程序被所述至少一个处理器执行，使得所述至少一个处理器实现如权利要求1-7中任一项所述的云计费方法。
  10. 一种云计费系统，包括：计算节点、交换机、存储资源池以及如权利要求9所述的云管理平台，所述交换机分别与所述云管理平台、所述计算节点和所述存储资源池连接；
    所述计算节点设置为驱动虚拟机以向业务提供云服务；
    所述存储资源池设置为存储虚拟机资源；
    所述云管理平台包括业务管理子平台和资源管理子平台。
  11. 一种计算机可读存储介质，存储有计算机程序，其中，所述程序被处理器执行时实现如权利要求1-7中任一项所述的云计费方法。
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