Cloud host computing power providing method and system, server, device and storage medium

Abstract

This disclosure provides a method and system for providing cloud server computing power, relating to the field of cloud computing technology. The method includes: determining the remaining computing power points of each of multiple point-based cloud server instances with shared points attributes; determining the predicted computing power consumption points of each of the multiple point-based cloud server instances; and when the remaining computing power points of a target point-based cloud server instance among the multiple point-based cloud server instances with shared points attributes are less than its predicted computing power consumption points, sharing the remaining computing power points of the other point-based cloud server instances with the target point-based cloud server instance. This method, based on point-based cloud server instances, allows multiple point-based cloud server instances with the same specifications to share computing power, thereby reducing computing power waste of point-based cloud server instances, effectively improving the overall utilization rate of computing power of multiple point-based cloud server instances purchased by the user, and reducing the user's resource usage costs.

Description

Technical Field

[0001] This disclosure relates to the field of cloud technology, and in particular to a method and system for providing cloud server computing power, a cloud server points server, electronic devices and computer-readable storage media, and products. Background Technology

[0002] Cloud computing platforms typically offer two main types of cloud server instance specifications: standard cloud server instances and burstable cloud server instances (often referred to by cloud vendors as burstable or burstable performance specifications). Standard cloud server instances purchase and allocate computing resources based on specifications (i.e., CPU and memory, such as 1 core and 4GB), and are billed based on the allocated computing resources regardless of user usage. Burdenable cloud server instances, on the other hand, allow cloud server instances to accumulate idle computing power over a period of time. In addition to CPU and memory, their specification parameters include a "baseline performance" parameter, which is in percentage format. The number of cores in the specification is only the upper limit of vCPUs allocated by the system; "number of cores * baseline performance" is the actual resource purchased. For example, in a 2-core, 4GB RAM, 20% base performance vCPU instance, the user pays for 2 * 20% = 0.4 cores. This means the system provides computing power to the instance based on 0.4 cores. However, when the cloud server's CPU utilization drops below 20%, unused computing power accumulates. When sufficient computing power is available, the instance can run at over 20% utilization. If the accumulated computing power is exhausted, the system will limit the cloud server instance to base performance. Furthermore, since the cloud server instance is configured with 2 cores, regardless of the accumulated computing power, the instance can only use a maximum of 2 vCPUs.

[0003] These cloud server instances are called "point-based" because they introduce the concept of "CPU points" to quantify computing power. For example, 1 point is defined as the amount of computation completed by one vCPU running at 100% utilization for 1 minute (one vCPU running at 50% utilization for 2 minutes is equivalent to consuming 1 point; similarly, two vCPUs running at 100% utilization for 0.5 minutes is also equivalent to consuming 1 point). In this way, the amount of computation accumulated or consumed by a cloud server instance during continuous operation can be converted into points, without needing to simultaneously focus on the three dimensions reflecting computing power: core count, utilization, and duration.

[0004] The cumulative computing power of point-based cloud server instances enables them to dynamically allocate computing power, reducing computing power waste at the single cloud server instance level. Therefore, they are more economical than ordinary cloud server instance specifications.

[0005] However, optimizing the computing power of cloud servers to improve the efficiency of computing power utilization has always been a technical requirement in the industry.

[0006] It should be noted that the information disclosed in the background section above is only used to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] In view of this, the present disclosure provides a method and system, electronic device and computer-readable medium and product for sharing computing power among cloud hosts, which can overcome to some extent the problem of low efficiency in providing computing power by cloud hosts in related technologies.

[0008] Other features and advantages of this disclosure will become apparent from the following detailed description, or may be learned in part from practice of this disclosure.

[0009] According to a first aspect of the present disclosure, a method for providing cloud server computing power is proposed, comprising: determining the remaining computing power points of each of a plurality of point-based cloud server instances having shared points attributes, wherein the point-based cloud server instances having shared points attributes are point-based cloud server instances of the same specification; determining the predicted computing power consumption points of each of the plurality of point-based cloud server instances having shared points attributes; and when the remaining computing power points of a target point-based cloud server instance among the plurality of point-based cloud server instances having shared points attributes are less than the predicted computing power consumption points of the target point-based cloud server instance, sharing the remaining computing power points of other point-based cloud server instances having shared points attributes to the target point-based cloud server instance.

[0010] In one embodiment of this disclosure, determining the remaining computing power points of each of the multiple point-based cloud host instances with shared point attributes includes: determining the remaining computing power points of each of the multiple point-based cloud host instances with shared point attributes based on cloud host instance information.

[0011] In one embodiment of this disclosure, determining the predicted computing power consumption points of each of the plurality of point-based cloud host instances with shared points attributes includes: determining the predicted computing power consumption points of each of the plurality of point-based cloud host instances with shared points attributes within a predetermined time period based on the current CPU utilization.

[0012] In one embodiment of this disclosure, when the remaining computing power points of a target point-based cloud server instance among the plurality of point-based cloud server instances with shared points attributes are less than the predicted computing power consumption points of the target point-based cloud server instance, sharing the remaining computing power points of other point-based cloud server instances with shared points attributes to the target point-based cloud server instance includes: determining whether the remaining computing power points of the target point-based cloud server instance are less than the predicted computing power consumption points of the target point-based cloud server instance; when the remaining computing power points of the target point-based cloud server instance are less than the predicted computing power consumption points of the target point-based cloud server instance, issuing... A points request is issued to request the sharing of remaining computing power points of other points-based cloud host instances with shared points attributes; in response to the points request, it is determined whether the remaining computing power points of other points-based cloud host instances with shared points attributes meet the predicted computing power point consumption of the target points-based cloud host instance; when the remaining computing power points of other points-based cloud host instances meet the predicted computing power point consumption of the target points-based cloud host instance, the points usage to be shared with the target points-based cloud host instance is determined, and a points application is sent to instruct the remaining computing power points of other points-based cloud host instances to be shared with the target points-based cloud host instance.

[0013] In one embodiment of this disclosure, the method further includes: determining the computing power points allocated to each point-based cloud host instance within a predetermined time period based on the predicted computing power points consumed by each point-based cloud host instance within a predetermined time period in the following manner: when the predicted computing power points consumed by a point-based cloud host instance within a predetermined time period are less than or equal to the remaining computing power points of the point-based cloud host instance, determining that the computing power points allocated to the point-based cloud host instance within a predetermined time period are equal to the predicted computing power points consumed by the point-based cloud host instance within a predetermined time period; when the predicted computing power points consumed by a point-based cloud host instance within a predetermined time period are greater than the remaining computing power points of the point-based cloud host instance, allocating the remaining computing power points of other point-based cloud host instances within a predetermined time period to the point-based cloud host instance.

[0014] According to a second aspect of the present disclosure, a cloud server points server is proposed, comprising: a CSG module, configured to store attribute information of multiple points-based cloud server instances having shared points attributes, and record the predicted computing power consumption points of each points-based cloud server instance within a predetermined period; and a points controller, configured to receive the predicted computing power consumption points of each points-based cloud server instance within a predetermined period sent by each cloud server points agent, send the predicted computing power consumption points to the CSG module, determine the computing power points allocated to each points-based cloud server instance within a predetermined period based on the predicted computing power consumption points of each points-based cloud server instance within a predetermined period, and send the computing power points allocated to each points-based cloud server instance within a predetermined period to the corresponding cloud server points agent to allocate computing power to each points-based cloud server instance.

[0015] In one embodiment of this disclosure, the points controller determines the computing power points allocated to each points-based cloud host instance within a predetermined time period based on the predicted computing power points consumed by each instance within a predetermined time period in the following manner: when the predicted computing power points consumed by a points-based cloud host instance within a predetermined time period are less than or equal to the remaining computing power points of the instance, the computing power points allocated to the instance within the predetermined time period are determined to be equal to the predicted computing power points consumed by the instance within the predetermined time period; when the predicted computing power points consumed by a points-based cloud host instance within a predetermined time period are greater than the remaining computing power points of the instance, the remaining computing power points of other points-based cloud host instances within the predetermined time period are allocated to the instance.

[0016] According to a third aspect of the present disclosure, a cloud server computing power provision system is proposed, including the aforementioned cloud server points server and cloud server points agent; wherein, the cloud server points agent corresponds to a points-based cloud server instance, and is used to predict the predicted computing power points to be consumed for a predetermined time based on the utilization rate data of the points-based cloud server instance, and send the predicted computing power points to be consumed by the points-based cloud server instance to the cloud server points server; and receive the computing power points allocated to the points-based cloud server instance within the predetermined time period sent by the cloud server points server.

[0017] According to a fourth aspect of the present disclosure, a cloud server points server is proposed, comprising: a first determining unit, configured to determine the remaining computing power points of each of a plurality of points-based cloud server instances having shared points attributes, wherein the points-based cloud server instances having shared points attributes are points-based cloud server instances of the same specification; a second determining unit, configured to determine the predicted computing power points consumed by each of the plurality of points-based cloud server instances having shared points attributes; and a processing unit, configured to share the remaining computing power points of other points-based cloud server instances having shared points attributes to the target points-based cloud server instance when the remaining computing power points of a target points-based cloud server instance among the plurality of points-based cloud server instances having shared points attributes are less than its predicted computing power points consumed.

[0018] According to a fifth aspect of the present disclosure, an electronic device is provided, comprising: one or more processors; and a storage system for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the cloud host shared computing power method described in any of the preceding claims.

[0019] According to a sixth aspect of the present disclosure, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the cloud host computing power provision method described in any of the preceding claims.

[0020] According to a seventh aspect of the present disclosure, a computer program product is provided, comprising: a computer program / instructions that, when executed by a processor, implement the cloud host computing power provision method described in any of the preceding claims.

[0021] According to certain embodiments of this disclosure, a method, system, electronic device, computer-readable medium, and product for sharing computing power of cloud servers are provided. The method includes: when the remaining computing power points of a target point-type cloud server instance among multiple point-type cloud server instances with shared point attributes do not meet its predicted computing power consumption points, the remaining computing power points of the multiple point-type cloud server instances are shared to the target point-type cloud server instance. That is, based on the point-type cloud server instance, multiple point-type cloud server instances with the same specifications are allowed to share computing power, thereby reducing the computing power waste of point-type cloud server instances and effectively improving the overall computing power utilization rate of multiple point-type cloud server instances purchased by the user.

[0022] It should be understood that the above general description and the following detailed description are merely exemplary and do not limit this disclosure. Attached Figure Description

[0023] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure. The drawings described below are merely some embodiments of this disclosure, and those skilled in the art will be able to derive other drawings from these drawings without any inventive effort.

[0024] Figure 1 A flowchart illustrating a method for providing cloud server computing power according to an embodiment of the present disclosure is shown.

[0025] Figure 2 A flowchart illustrating a method for providing cloud server computing power according to another embodiment of this disclosure is shown;

[0026] Figure 3 This diagram illustrates a system architecture of a cloud server computing power provision system according to an embodiment of the present disclosure.

[0027] Figure 4 A flowchart illustrating a method for providing cloud server computing power according to yet another embodiment of the present disclosure;

[0028] Figure 5 A schematic diagram of the structure of a cloud server computing power provision system according to an embodiment of the present disclosure is shown; and

[0029] Figure 6 A schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure is shown. Detailed Implementation

[0030] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the embodiments set forth herein; rather, they are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary embodiments to those skilled in the art. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted.

[0031] The described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this disclosure. However, those skilled in the art will recognize that the technical solutions of this disclosure can be practiced with one or more specific details omitted, or other methods, components, systems, steps, etc., can be employed. In other instances, well-known methods, systems, implementations, or operations are not shown or described in detail to avoid obscuring aspects of this disclosure.

[0032] The accompanying drawings are merely illustrative of this disclosure, and the same reference numerals in the drawings denote the same or similar parts, thus omitting repeated descriptions of them. Some block diagrams shown in the drawings do not necessarily correspond to physically or logically independent entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor systems and / or microcontroller systems.

[0033] The flowchart shown in the accompanying drawings is merely illustrative and does not necessarily include all content and steps, nor does it require execution in the described order. For example, some steps may be broken down, while others may be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.

[0034] In this specification, the terms “a,” “an,” “the,” “the,” and “at least one” are used to indicate the presence of one or more elements / components / etc.; the terms “comprising,” “including,” and “having” are used to indicate an open-ended inclusion and to mean that there may be other elements / components / etc. in addition to the listed elements / components / etc.; the terms “first,” “second,” and “third,” etc., are used only as markings and are not a limitation on the number of objects.

[0035] The following is an explanation of the relevant terms used in this disclosure.

[0036] 1) Integration. Integration is a unit of measurement for normalized computing power. 1 integration is equivalent to the computing power of 1 vCPU running at 100% utilization for 1 minute (vCPU × utilization × running time = 1).

[0037] Example: One vCPU running at 50% utilization for 2 minutes is equivalent to consuming 1 point; two vCPUs running at 25% utilization for 2 minutes are also equivalent to consuming 1 point.

[0038] 2) Baseline Performance. The CPU performance that a cloud server instance can continuously obtain is a relative value expressed as a percentage, and its reference point is the vCPU in the cloud server instance specification. When a cloud server instance runs at baseline performance, the points consumed per minute are equal to the points issued by the system.

[0039] Example: Suppose that the baseline performance of a points-based cloud server instance is 20%, meaning that the points issued by the system can guarantee that the cloud server instance will continue to run at 20% utilization.

[0040] 3) CPU Credit Balance. Credits accumulated when a bursty cloud server instance runs below baseline performance can be used for subsequent performance bursts.

[0041] Example: If a cloud server instance consistently runs at 10% CPU utilization, it accumulates 2 (vCPU) × 10% (baseline performance - actual performance) × 1 (minute) = 0.2 points per minute. After running continuously for 10 minutes after startup, the CPU point balance is 2 points.

[0042] 4) Maximum CPU Points Balance. The maximum CPU points balance refers to the maximum amount of CPU points that can be accumulated.

[0043] Instances of the same type of points-based cloud server have a total CPU points balance limit to ensure that, in extreme cases, simultaneous use of CPU points will not exceed the physical server's computing power limit. Once the CPU points balance reaches the limit, points will no longer accumulate.

[0044] The inventors of this application have discovered that while point-based cloud server instances in related technologies achieve dynamic allocation of computing power over time through point accumulation, the accumulated points can only be used for the consumption of that specific cloud server instance, and there is an accumulation cap. When a customer purchases multiple point-based cloud server instances simultaneously, but their operating conditions differ, there may be a moment when the utilization rate of a particular point-based cloud server instance increases, but because the accumulated points are exhausted, it can only operate at baseline performance, while other cloud server instances still have a large number of points available at the same time. From the user's perspective, there is still a possibility of wasted computing power, and there is room for further optimization.

[0045] To address the technical problem in related technologies that accumulated points can only be used for consumption by their own cloud host instance and that there is an accumulation limit for points, resulting in a cloud host instance being able to run at baseline performance when its accumulated points are exhausted, while other cloud host instances still have a large number of points available at the same time, this disclosure provides a method for sharing points (computing power) among cloud host instances of the same specification based on logical grouping, and a method for predicting the amount of points used within a certain period based on historical usage data, and making decisions on the flow of points based on the predicted data.

[0046] In this disclosure, the terms "remaining computing power points" and "predicted computing power consumption points" refer to computing resources such as CPU and memory related to cloud hosts, and have clear physical and technical meanings.

[0047] Figure 1 A flowchart illustrating a method for providing cloud server computing power according to an embodiment of this disclosure is shown. Figure 1 As shown, the method includes the following steps S102 to S106.

[0048] S102, determine the remaining computing power points of each of the multiple point-based cloud server instances with shared point attributes, wherein the point-based cloud server instances with shared point attributes are point-based cloud server instances of the same specification. The remaining computing power points correspond to the remaining computing power of the point-based cloud server instance. In one embodiment, the remaining computing power points represent the remaining computing power within a predetermined time period.

[0049] S104, determine the predicted computing power consumption points for each of the multiple point-based cloud host instances with shared point attributes. The predicted computing power consumption points correspond to the computing power that the point-based cloud host instance needs to consume, as predicted. In one embodiment, the predicted computing power consumption points represent the expected computing power to be consumed within a predetermined time period.

[0050] S106, when the remaining computing power points of the target point-based cloud host instance among multiple point-based cloud host instances with shared points attributes are less than the predicted computing power points consumed by the target point-based cloud host instance, the remaining computing power points of other point-based cloud host instances with shared points attributes are shared to the target point-based cloud host instance.

[0051] According to certain embodiments of this disclosure, a method for sharing computing power among cloud servers is provided. When the remaining computing power points of a target point-based cloud server instance among multiple point-based cloud server instances with shared point attributes do not meet its predicted computing power consumption points, the remaining computing power points of the multiple point-based cloud server instances are shared to the target point-based cloud server instance. That is, based on point-based cloud server instances, multiple point-based cloud server instances with the same specifications are allowed to share computing power, thereby reducing the computing power waste of point-based cloud server instances, effectively improving the overall computing power utilization rate of multiple point-based cloud server instances purchased by the user, and reducing the user's resource usage costs.

[0052] This disclosure provides a method for sharing computing power among cloud hosts. Figure 2 A flowchart illustrating a method for providing cloud server computing power according to another embodiment of this disclosure is shown.

[0053] like Figure 2 As shown in step S201, determine the remaining computing power points of each of the multiple point-based cloud host instances with shared point attributes based on the cloud host instance information.

[0054] S202, based on the current CPU utilization, determine the predicted computing power points to be consumed by each of the multiple point-based cloud host instances with shared point attributes within a predetermined time period.

[0055] S203, when the remaining computing power points of the target point-based cloud host instance among multiple point-based cloud host instances with shared point attributes are less than its predicted computing power consumption points, a point request is issued to request the sharing of the remaining points of other point-based cloud host instances.

[0056] S204, in response to the points request, determine whether the remaining computing power points of other points-based cloud host instances with shared points attributes meet the predicted computing power points consumption of the target points-based cloud host instance.

[0057] S205, when the remaining computing power points of other point-based cloud host instances meet the predicted computing power points consumption of the target point-based cloud host instance, determine the amount of points to be shared with the target point-based cloud host instance, and send a points application to instruct the remaining computing power points of other point-based cloud host instances to be shared with the target point-based cloud host instance.

[0058] According to certain embodiments of the present disclosure, a cloud server sharing computing power method is provided. When the remaining computing power points of a target point-type cloud server instance among multiple point-type cloud server instances with shared point attributes do not meet its predicted computing power consumption points, the remaining computing power points of multiple point-type cloud server instances are shared to the target point-type cloud server instance. That is, based on point-type cloud server instances, multiple point-type cloud server instances with the same specifications are allowed to share computing power, thereby reducing the computing power waste of point-type cloud server instances, effectively improving the overall computing power utilization rate of multiple point-type cloud server instances purchased by the user, and reducing the user's resource usage costs.

[0059] Figure 3 A schematic diagram of the system architecture of a cloud server computing power provision system according to an embodiment of the present disclosure is shown.

[0060] In one embodiment, the main service module in the points-based cloud host instance implementation mechanism is the points-based cloud host instance service module, such as the points server (Credit Server) 32. This points server 32 is independent of other modules within the cloud host system and provides related services when creating points-based cloud host instances. Operations such as creation, deletion, and modification of points-based cloud host instances are synchronized to the points server 32 through modules like controller 31. The points controller 305 of the points server 32, based on cloud host instance scheduling information, sends points control tasks to the points agent (CreditAgent) 304 on the host machine 33 where the points-based cloud host instance resides. The points agent 304 controls the computing power of the points-based cloud host instance based on the cloud host instance specifications and points accumulation by configuring the shared points group (CSG).

[0061] In one embodiment, the cloud host points server 32 includes: a shared points group (CSG) module 306, used to store attribute information of multiple points-based cloud host instances with shared points attributes, and record the predicted computing power points consumed by each points-based cloud host instance within a predetermined time; and a points controller 305, used to receive the predicted computing power points consumed by each points-based cloud host instance within a predetermined time from each cloud host points agent 304, send the predicted computing power points consumed to the CSG module 306, determine the computing power points allocated to each points-based cloud host instance within a predetermined time based on the predicted computing power points consumed by each points-based cloud host instance within a predetermined time, and send the computing power points allocated to each points-based cloud host instance within a predetermined time to the corresponding cloud host points agent 304 to allocate computing power to each points-based cloud host instance.

[0062] In one embodiment, the points controller determines the computing power points allocated to each points-based cloud host instance within a predetermined time period based on the predicted computing power points consumed by each instance within a predetermined time period in the following manner: when the predicted computing power points consumed by a points-based cloud host instance within a predetermined time period are less than or equal to the points balance of the points-based cloud host instance, the computing power points allocated to the points-based cloud host instance within the predetermined time period are determined to be equal to the predicted computing power points consumed by the points-based cloud host instance within the predetermined time period; when the predicted computing power points consumed by a points-based cloud host instance within a predetermined time period are greater than the points balance of the points-based cloud host instance, the remaining computing power points of other points-based cloud host instances within the predetermined time period are allocated to the points-based cloud host instance.

[0063] In addition, other modules can be set up in the points server, such as reporting data to the monitoring service module, storing data in the database or caching it, etc., which are not limited here.

[0064] Figure 4 A flowchart illustrating a method for providing cloud server computing power according to yet another embodiment of the present disclosure is shown. As shown in Figure 4, the method includes the following steps S400 to S411.

[0065] The S400 controller receives user operations and synchronizes them to the cloud host credit server.

[0066] The controller receives user operations such as adding, deleting, and modifying credit-based cloud host instances in the Credit Shared Group (CSG) and synchronizes them to the cloud host credit server.

[0067] S401. The cloud server points server groups multiple points-based cloud server instances of the same specifications into a shared points group. The multiple points-based cloud server instances in the shared points group are points-based cloud server instances with shared points attributes.

[0068] The sharing relationships of multiple credit-based cloud server instances are logically grouped, referred to here as a shared credit group (CSG), which is set up in the Credit Server. Cloud server instances within a group are credit-based cloud server instances of the same specification, and each credit-based cloud server instance belongs to only one shared credit group at a time. For example, a cloud server instance belonging to a specific shared credit group is referred to as a cloud server instance "with CSG attribute". Any additions, deletions, or modifications made by users to cloud server instances within a credit group are synchronously recorded in the CSG module of the Credit Server, and whether a cloud server instance has CSG attribute is also synchronized to the CreditAgent on the host machine.

[0069] S402, the points server determines the remaining computing power points of each of the multiple points-based cloud host instances with shared points attributes based on the cloud host instance information.

[0070] S403, the points agent determines the predicted computing power points to be consumed within a predetermined time period for each of multiple points-based cloud host instances with shared points attributes based on the current CPU utilization.

[0071] S404, The points agent determines whether the remaining computing power points of the target points cloud host instance among multiple points cloud host instances with shared points attributes meet its predicted computing power point consumption.

[0072] S405, when the remaining computing power points of the target point-based cloud host instance among multiple point-based cloud host instances with shared points attributes are less than its predicted computing power points, the points agent sends a points request to the points server to request sharing with the remaining computing power points of the point-based cloud host instance with remaining computing power.

[0073] S406, the points server responds to the points request and determines whether the remaining computing power points of other points cloud host instances meet their predicted computing power point consumption.

[0074] S407, when the remaining computing power points of other points-based cloud host instances meet the sum of their predicted computing power consumption points and the difference in points consumption with the target points-based cloud host instance, the points server determines the remaining computing power points-based cloud host instances and the points usage shared with the target points-based cloud host instance.

[0075] The points server responds to the points request and determines whether the remaining computing power points in the points-based cloud host instance with shared points attributes meet its predicted computing power consumption. If there are other points-based cloud host instances whose remaining computing power points meet the sum of their predicted computing power consumption and the difference in computing power consumption with the target points-based cloud host instance, then that points-based cloud host instance is determined to be a points-based cloud host instance with remaining computing power. Simultaneously, the points usage shared between the points-based cloud host instance with the target points-based cloud host instance is determined. Furthermore, there can be one or more points-based cloud host instances with remaining computing power, which is not further limited.

[0076] S408, the points server sends a points request to the points agent to instruct the remaining computing power points of the remaining computing power points of the points-based cloud host instance to be shared with the target points-based cloud host instance.

[0077] S409, the points agent predicts the estimated consumption of computing power points for the remaining computing power points-based cloud host instance within a predetermined time.

[0078] In response to a points request sent by the points server, the points agent re-predicts the expected computing power points consumption of the remaining computing power points-based cloud server instances within a predetermined time period to further determine whether the remaining computing power points-based cloud server instances meet the points consumption requirements for the next cycle. For example, after receiving a points request, the points agent immediately re-predicts the points consumption for the next cycle for the remaining computing power points-based cloud server instances based on the latest utilization data.

[0079] S410, determine whether the remaining computing power points of the remaining computing power points of the remaining computing power points of the cloud host instance meet the sum of its predicted computing power points consumption and the points usage shared with the target computing power points of the cloud host instance.

[0080] S411, when the remaining computing power points of the remaining computing power points of the cloud host instance meet the sum of its predicted computing power consumption points and the points usage shared with the target cloud host instance, the points agent will share the remaining computing power points of the remaining computing power points of the cloud host instance with the target cloud host instance.

[0081] If the remaining computing power points of a point-based cloud server instance meet the sum of its predicted computing power consumption points and the points shared with the target point-based cloud server instance, then the corresponding points will be deducted from the current points balance of the point-based cloud server instance and synchronized to the points server. The points server will then monitor the points agent of the target point-based cloud server instance, ensuring that it adds the corresponding points for the target point-based cloud server instance. If the remaining computing power points of a point-based cloud server instance do not meet the sum of its predicted computing power consumption points and the points shared with the target point-based cloud server instance, but are greater than its predicted computing power consumption points, then the excess remaining computing power points can be shared with the target point-based cloud server instance. If the remaining computing power points of a point-based cloud server instance are less than its predicted computing power consumption points, then it can refuse to share points with the target point-based cloud server instance.

[0082] For example, the Credit Server calculates the remaining computing power points for each point-based cloud host instance in each CSG based on the cloud host instance information recorded in the CSG. The CreditAgent can predict the expected computing power point consumption within minutes based on the current CPU utilization of a cloud host instance. When it predicts that a point-based cloud host instance with CSG attributes is about to run out of accumulated points, it can send a point request to the Credit Server. If other cloud host instances in its CSG have additional computing power points beyond their baseline performance, the CreditServer will proportionally send a point request to the CreditAgent on the host machine of the corresponding cloud host instance, deducting the corresponding points for use by the requesting cloud host instance. When the CreditAgent requests or responds to point requests, it involves predicting the point demand of the current cloud host instance within a certain prediction period. There are various algorithms for prediction, such as setting different prediction periods and various settings for predicting utilization within the period.

[0083] It's important to note that in the computing power provision methods among multiple points-based cloud server instances, although the basic computing configuration of a cloud server instance consists of CPU and memory resources, these resources are not provided separately but as a whole. The computing power is provided as a single unit, and the specifications of CPU and memory largely determine the underlying scheduling. Therefore, the CPU and memory included per unit of computing power, as well as the corresponding price, vary for different specifications of points-based cloud server instances. Furthermore, sharing computing power among points-based cloud server instances has a prerequisite: points-based cloud server instances of the same specifications must be able to establish a sharing relationship.

[0084] The following describes in detail the method for sharing computing power of cloud hosts in this disclosure with reference to specific embodiments, taking a prediction period of 1 minute and assuming that the cloud host instance increases from the current utilization rate to 100% at a constant rate within 1 minute as an example.

[0085] A cloud server instance A, with 2 cores and 4GB RAM, operates at 20% of its baseline performance. The system awards it 2 * 1 * 20% = 0.4 points per minute. This instance is added to a shared points group containing 5 instances of the same specifications. Assuming all 5 instances are initially offline and have accumulated points, instance A is started first and runs at 50% utilization, requiring 2 * 1 * 50% = 1 point per minute. At a certain point, instance A has only 0.3 points remaining. Following the above prediction principle, to increase CPU utilization from 50% to 100% within one minute, it needs 1.5 points in the following minute. Subtracting the 0.4 points the system will award, 0.8 points are still short. At this point, CreditAgent will send a request for 0.8 points to CreditServer. CreditServer will query the point balances and most recently reported usage rates of the other 4 cloud host instances in the shared point group associated with A, and estimate the points needed for the next minute to determine which cloud host instances to request points from.

[0086] Assuming four cloud server instances are currently powered off with a 0% utilization rate, but the prediction algorithm assumes they will increase from 0% to 100% within the next minute, requiring 2 * 1 * 100% / 2 = 1 point. If the remaining points for all four cloud server instances are greater than 1 point and greater than 1 + 0.2 = 1.2 points, the Credit Server will send a request for 0.2 points to each of the CreditAgents on the host machines of the four cloud server instances. Upon receiving the request, the CreditAgents of these four cloud server instances will re-predict the point consumption for the next cycle based on the latest utilization data. If the prediction is successful, 0.2 points will be deducted from the current point balance and synchronized with the Credit Server. Subsequently, the Credit Server can notify the CreditAgent monitoring cloud server instance A to add 0.8 points to its balance. If, based on historical data, the Credit Server of these four cloud server instances determines that only two of them may meet the requirement, they will automatically deduct the points and synchronize with the Credit Server. The Credit Server will then notify the CreditAgent monitoring cloud server instance A to add 0.8 points to its balance.

[0087] The points server in this embodiment of the disclosure can perform... Figure 4The method executed by the points server in the illustrated embodiment will not be described in detail here.

[0088] This disclosure provides a cloud server computing power provision system according to one embodiment. The system includes a cloud server points server and a cloud server points agent. This system can provide... Figure 3 The system shown includes a cloud server computing power provision system with a points server and a points agent, and the points server and points agent can execute independently. Figure 3 and Figure 4 The methods executed by the points server and points agent will not be elaborated here.

[0089] One embodiment of this disclosure provides a cloud server computing power provision system. Figure 5 A schematic diagram of the structure of a cloud server computing power provision system according to an embodiment of the present disclosure is shown. Figure 5 As shown, the cloud server computing power provision system 500 includes a first determining unit 501, a second determining unit 502, and a processing unit 503. The first determining unit 501 is used to determine the remaining computing power points of each of a plurality of point-based cloud server instances with shared points attributes, wherein the point-based cloud server instances with shared points attributes are point-based cloud server instances of the same specification; the second determining unit 502 is used to determine the predicted computing power consumption points of each of the plurality of point-based cloud server instances with shared points attributes; the processing unit 503 is used to share the remaining computing power points of other point-based cloud server instances with shared points attributes to the target point-based cloud server instance when the remaining computing power points of the target point-based cloud server instance among the plurality of point-based cloud server instances with shared points attributes are less than its predicted computing power consumption points.

[0090] The cloud server computing power providing system 500 corresponds to the cloud server shared computing power system in the method embodiment. The cloud server shared computing power system 500 can be the cloud server shared computing power system in the method embodiment, or a chip or functional module within the cloud server shared computing power system in the method embodiment. The corresponding unit of the cloud server shared computing power system 500 is used to execute... Figures 1 to 4 The corresponding steps in the method embodiment shown are performed by the cloud host shared computing power system.

[0091] The first determining unit 501, the second determining unit 502, and the processing unit 503 in the cloud host shared computing power system 500 are used to execute the processing-related steps of the cloud host shared computing power system in the method embodiment.

[0092] The cloud host shared computing power system 1000 may further include a storage unit for storing data and / or signaling. The first determining unit 501, the second determining unit 502, and the processing unit 503 may interact with or be coupled to the storage unit, for example, reading or calling the data and / or signaling in the storage unit so that the method of the above embodiment is executed.

[0093] Each of the above units can exist independently, or they can be fully or partially integrated.

[0094] Figure 6 A schematic diagram of the structure of an electronic device according to an embodiment of the present disclosure is shown. An embodiment of the present disclosure provides an electronic device. The electronic device includes a processor and a memory. The memory is used to store executable instructions of the processor. The processor is configured to perform the above-described actions by executing the executable instructions. Figures 1 to 4 A method for providing cloud server computing power in any of the embodiments shown.

[0095] The following reference Figure 6 To describe an electronic device 600 according to this embodiment of the present invention. Figure 6 The electronic device 600 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0096] like Figure 6 As shown, the electronic device 600 is manifested in the form of a general-purpose computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, and a bus 630 connecting different system components (including storage unit 620 and processing unit 610).

[0097] The storage unit stores program code that can be executed by the processing unit 610, causing the processing unit 610 to perform the steps described in the above-described method section of this specification according to various exemplary embodiments of the present invention.

[0098] Storage unit 620 may include a readable medium in the form of a volatile storage unit, such as random access memory (RAM) 6201 and / or cache memory 6202, and may further include a read-only memory (ROM) 6203.

[0099] Storage unit 620 may also include a program / utility 6206 having a set (at least one) of program modules 6206, such program modules 6206 including but not limited to: operating system, one or more application programs, other program modules and program data, each or some combination of these examples may include an implementation of a network environment.

[0100] Bus 630 can represent one or more of several types of bus structures, including a memory cell bus or memory cell controller, a peripheral bus, a graphics acceleration port, a processing unit, or a local bus using any of the various bus structures.

[0101] Electronic device 600 can also communicate with one or more external devices 700 (e.g., keyboard, pointing device, Bluetooth device, etc.), and with one or more devices that enable a user to interact with electronic device 600, and / or with any device that enables electronic device 600 to communicate with one or more other computing devices (e.g., router, modem, etc.). This communication can be performed via input / output (I / O) interface 650. Furthermore, electronic device 600 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 660. As shown, network adapter 660 communicates with other modules of electronic device 600 via bus 630. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0102] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, terminal device, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0103] At least one embodiment of this disclosure also provides a computer-readable medium for storing computer program code, the computer program including instructions for performing the cloud host computing power provision method of at least one embodiment of this disclosure described above. The readable medium may be a read-only memory (ROM) or a random access memory (RAM), and at least one embodiment of this disclosure does not limit this.

[0104] This disclosure also provides a computer program product comprising a computer program / instructions that are executed by a processor as instructions for providing cloud server computing power according to at least one embodiment of this disclosure. In some possible implementations, various aspects of the invention can also be implemented as a program product comprising program code that, when run on a terminal device, causes the terminal device to perform the steps described in the "Exemplary Methods" section according to various exemplary embodiments of the invention.

[0105] A program product for implementing the above-described method according to embodiments of the present invention is described. This product may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, the readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, apparatus, or device.

[0106] The program product may employ any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0107] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium, capable of sending, propagating, or transmitting programs for use by or in conjunction with an instruction execution system, apparatus, or device.

[0108] The program code contained on the readable medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical fiber, RF, etc., or any suitable combination thereof.

[0109] Program code for performing the operations of this invention can be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java and C++, and conventional procedural programming languages ​​such as C or similar languages. The program code can execute entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device can be connected to the user's computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0110] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to embodiments of this disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0111] Furthermore, although the steps of the method in this disclosure are described in a specific order in the accompanying drawings, this does not require or imply that the steps must be performed in that specific order, or that all the steps shown must be performed to achieve the desired result. Additional or alternative steps may be omitted, multiple steps may be combined into one step, and / or a step may be broken down into multiple steps.

[0112] From the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, mobile terminal, or network device, etc.) to execute the methods according to the embodiments of this disclosure.

[0113] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the appended claims.

Claims

1. A method for providing computing power of a cloud host, characterized in that, Comprise: a plurality of integral cloud host instances of the same specification are grouped into a shared integral group, and the shared integral group includes a plurality of integral cloud host instances with a shared integral attribute; determining the residual computing power integral of each of the plurality of integral cloud host instances with a shared integral attribute, wherein the integral cloud host instances with a shared integral attribute are integral cloud host instances of the same specification; determining the predicted consumption computing power integral of each of the plurality of integral cloud host instances with a shared integral attribute; when the residual computing power integral of a target integral cloud host instance in the plurality of integral cloud host instances with a shared integral attribute is less than the predicted consumption computing power integral of the target integral cloud host instance, sharing the residual computing power integral of other integral cloud host instances with a shared integral attribute to the target integral cloud host instance; wherein when the residual computing power integral of a target integral cloud host instance in the plurality of integral cloud host instances with a shared integral attribute is less than the predicted consumption computing power integral of the target integral cloud host instance, sharing the residual computing power integral of other integral cloud host instances with a shared integral attribute to the target integral cloud host instance comprises: determining whether the residual computing power integral of the target integral cloud host instance is less than the predicted consumption computing power integral of the target integral cloud host instance; when the residual computing power integral of the target integral cloud host instance is less than the predicted consumption computing power integral of the target integral cloud host instance, issuing an integral request to request sharing of the residual computing power integral of other integral cloud host instances with a shared integral attribute; in response to the integral request, determining whether the residual computing power integral of other integral cloud host instances with a shared integral attribute meets the predicted consumption computing power integral of the target integral cloud host instance; when the residual computing power integral of other integral cloud host instances meets the predicted consumption computing power integral of the target integral cloud host instance, determining the integral usage amount shared with the target integral cloud host instance, and sending an integral application to indicate that the residual computing power integral of other integral cloud host instances is shared with the target integral cloud host instance.

2. The method of claim 1, wherein, The determination of the residual computing power integral of each of the plurality of integral cloud host instances with a shared integral attribute comprises: determining the residual computing power integral of each of the plurality of integral cloud host instances with a shared integral attribute according to cloud host instance information.

3. The method of claim 1, wherein, The determination of the predicted consumption computing power integral of each of the plurality of integral cloud host instances with a shared integral attribute comprises: determining the predicted consumption computing power integral of each of the plurality of integral cloud host instances with a shared integral attribute within a predetermined time according to the current CPU usage rate.

4. The method of claim 1, wherein, Further comprise: determining the allocated computing power integral of each integral cloud host instance within a predetermined time based on the predicted consumption computing power integral of each integral cloud host instance within a predetermined time in the following manner: When the predicted consumed computing power credit of the integral cloud host instance in the predetermined time is less than or equal to the remaining computing power credit of the integral cloud host instance, it is determined that the computing power credit allocated to the integral cloud host instance in the predetermined time is equal to the predicted consumed computing power credit of the integral cloud host instance in the predetermined time. When the predicted consumed computing power credit of the integral cloud host instance in the predetermined time is greater than the remaining computing power credit of the integral cloud host instance, the remaining computing power credit of other integral cloud host instances in the predetermined time is allocated to the integral cloud host instance.

5. A cloud host credit server, characterized by, It comprises: A shared credit group (CSG) module is configured to group a plurality of integral cloud host instances of the same specification into a shared credit group, and the shared credit group comprises a plurality of integral cloud host instances with a shared credit attribute; attribute information of the plurality of integral cloud host instances with the shared credit attribute is stored, and the predicted consumed computing power credit of each integral cloud host instance in a predetermined period is recorded; An integral controller is configured to receive the predicted consumed computing power credit of each integral cloud host instance in a predetermined period sent by each cloud host credit agent, send the predicted consumed computing power credit to the CSG module, determine the computing power credit allocated to each integral cloud host instance in a predetermined time according to the predicted consumed computing power credit of each integral cloud host instance in the predetermined time, and send the computing power credit allocated to each integral cloud host instance in the predetermined time to the corresponding cloud host credit agent to allocate computing power to each integral cloud host instance. When the remaining computing power credit of a target integral cloud host instance among the plurality of integral cloud host instances with the shared credit attribute is less than the predicted consumed computing power credit of the target integral cloud host instance, the remaining computing power credit of other integral cloud host instances with the shared credit attribute is shared to the target integral cloud host instance, including: determining whether the remaining computing power credit of the target integral cloud host instance is less than the predicted consumed computing power credit of the target integral cloud host instance; when the remaining computing power credit of the target integral cloud host instance is less than the predicted consumed computing power credit of the target integral cloud host instance, sending an integral request to request the sharing of the remaining computing power credit of other integral cloud host instances with the shared credit attribute; in response to the integral request, determining whether the remaining computing power credit of other integral cloud host instances with the shared credit attribute meets the predicted consumed computing power credit of the target integral cloud host instance; when the remaining computing power credit of other integral cloud host instances meets the predicted consumed computing power credit of the target integral cloud host instance, determining the amount of shared credit, and sending an integral application to indicate that the remaining computing power credit of other integral cloud host instances is shared with the target integral cloud host instance.

6. The cloud host credit server of claim 5, wherein, The integral controller determines the computing power credit allocated to each integral cloud host instance in a predetermined time according to the predicted consumed computing power credit of each integral cloud host instance in the predetermined time in the following manner: when the predicted consumed computing power integral of the integral cloud host instance within the predetermined time is less than or equal to the remaining computing power integral of the integral cloud host instance, it is determined that the computing power integral allocated to the integral cloud host instance within the predetermined time is equal to the predicted consumed computing power integral of the integral cloud host instance within the predetermined time; when the predicted consumed computing power integral of the integral cloud host instance within the predetermined time is greater than the remaining computing power integral of the integral cloud host instance, the remaining computing power integral of other integral cloud host instances within the predetermined time is allocated to the integral cloud host instance. 7.A cloud host computing power providing system, characterized in that, The cloud host integral server and the cloud host integral agent of claim 5 or 6 are included. The cloud host integral agent corresponds to the integral cloud host instance, and is configured to predict the predicted consumed computing power integral of the integral cloud host instance within the predetermined time according to the usage rate data of the integral cloud host instance, send the predicted consumed computing power integral of the integral cloud host instance to the cloud host integral server, and receive the computing power integral allocated to the integral cloud host instance within the predetermined time sent by the cloud host integral server. 8.A cloud host computing power providing system, characterized in that, It includes: The grouping unit is configured to group a plurality of integral cloud host instances of the same specification into a shared integral group, and the shared integral group includes a plurality of integral cloud host instances with a shared integral attribute; The first determination unit is configured to determine the respective remaining computing power integral of a plurality of integral cloud host instances with a shared integral attribute, wherein the integral cloud host instances with a shared integral attribute are integral cloud host instances of the same specification; The second determination unit is configured to determine the respective predicted consumed computing power integral of the plurality of integral cloud host instances with a shared integral attribute. The processing unit is configured to share the residual computing power points of other integral cloud host instances with the shared integral attribute to a target integral cloud host instance when the residual computing power points of the target integral cloud host instance among the plurality of integral cloud host instances with the shared integral attribute are less than the predicted consumed computing power points of the target integral cloud host instance. When the residual computing power points of the target integral cloud host instance among the plurality of integral cloud host instances with the shared integral attribute are less than the predicted consumed computing power points of the target integral cloud host instance, the processing unit is configured to determine whether the residual computing power points of the target integral cloud host instance are less than the predicted consumed computing power points of the target integral cloud host instance; when the residual computing power points of the target integral cloud host instance are less than the predicted consumed computing power points of the target integral cloud host instance, the processing unit is configured to send an integral request to request to share the residual computing power points of other integral cloud host instances with the shared integral attribute; and in response to the integral request, the processing unit is configured to determine whether the residual computing power points of other integral cloud host instances with the shared integral attribute meet the predicted consumed computing power points of the target integral cloud host instance; when the residual computing power points of other integral cloud host instances meet the predicted consumed computing power points of the target integral cloud host instance, the processing unit is configured to determine the integral amount shared with the target integral cloud host instance, and send an integral application to indicate that the residual computing power points of other integral cloud host instances are shared with the target integral cloud host instance.

9. An electronic device, comprising: The one or more processors are configured to implement processes recited in the description and / or claims. The one or more processors are configured to implement processes recited in the description and / or claims. The one or more processors are configured to implement processes recited in the description and / or claims. The one or more processors are configured to implement processes recited in the description and / or claims.

10. A computer readable medium having stored thereon a computer program, characterized in that, The one or more processors are configured to implement processes recited in the description and / or claims.

11. A computer program product, characterised in that, ​ ​

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