Resource Scheduling Method, Apparatus, and Device

Abstract

The present disclosure provides a resource scheduling method, apparatus, and device. Here, the method includes receiving a service request with attached service needs, generating a resource provider list formed by a resource provider that meets the service needs based on the service needs and the state of the resource provider side, selecting a target resource provider from the resource provider list based on the resource provider list and first information, where the first information is used to indicate a global optimization goal, and invoking the target resource provider to perform a service.

Description

Technical Field

[0001] (Cross-reference to Related Applications) This disclosure claims priority based on a Chinese patent application with application number 202210836035.3 filed in China on July 15, 2022, and all its contents are incorporated herein by reference. This disclosure relates to the field of communication technologies, and particularly to resource scheduling methods, apparatuses, and devices.

Background Art

[0002] In related network scheduling policies, for service scheduling, based on a single user service request, a single optimal is achieved by matching the user's service request with the most optimal node considering the user's service request. However, the single optimal is not always the globally optimal in terms of performance.

[0003] Since the network state and the resource information of the data center are not mutually recognized, when a user requests a certain service, the network cannot request the service to the optimal service node, which affects the user experience and causes a decrease in the computing resource efficiency within the network.

Summary of the Invention

Problems to be Solved by the Invention

[0004] This disclosure provides a resource scheduling method, apparatus, and device. By introducing a global optimization objective, from the perspective of global optimization, the resource service efficiency within the network can be improved by scheduling service requests to the most optimal target resource supply side to perform services.

Means for Solving the Problems

[0005] To solve the above technical problems, this disclosure proposes the following technical solutions.

[0006] A resource scheduling method, the method comprising: Receiving a service request with associated service needs; Generating a resource supply side list formed by a resource supply side that meets the service needs based on the service needs and the state of the resource supply side; Selecting a target resource supply side from the resource supply side list based on the resource supply side list and first information, wherein the first information is used to indicate a global optimization target; Invoking the target resource supply side to perform a service.

[0007] Optionally, after invoking the target resource supply side to perform a service, the method further comprises: When the service meets the global optimization target, further sending second information to a first resource side, where the first resource side includes a resource usage side and / or a resource supply side, and the second information is used to incentivize the first resource side to conform to the global optimization target.

[0008] Optionally, the incentive indicated by the second information is determined based on the global optimization target.

[0009] Optionally, when the global optimization target includes a first global optimization target corresponding to a global transaction resource volume indicator, the incentive has a positive correlation with the transaction resource volume of this service; When the global optimization target includes a second global optimization target corresponding to a global total resource transaction amount indicator, the incentive has a positive correlation with the total resource transaction amount of this service; When the global optimization target includes a third global optimization target corresponding to a global energy consumption indicator, the incentive has a negative correlation with the energy consumption of this service. When the global optimization target includes a fourth global optimization target corresponding to a global service stability index, the incentive has a positive correlation with the stability of the current service. When the global optimization target includes a fifth global optimization target corresponding to a global carbon emission index, the incentive has a negative correlation with the carbon emission index of the current service.

[0010] Optionally, based on the resource supply side list and the first information, selecting a target resource supply side from the resource supply side list includes selecting a resource supply side that reports a predicted value of the global optimization target from the resource supply side list to form a target resource supply side list; and selecting a resource supply side that meets the service needs from the target resource supply side list as the target resource supply side.

[0011] Optionally, the predicted value of the global optimization target is calculated by the resource supply side based on the service needs and the historical resource target data of the resource supply side.

[0012] Optionally, the global optimization target includes at least one of a first global optimization target corresponding to a global transaction resource quantity index, a second global optimization target corresponding to a global total resource transaction amount index, a third global optimization target corresponding to a global energy consumption index, a fourth global optimization target corresponding to a global service stability index, and a fifth global optimization target corresponding to a global carbon emission index.

[0013] Embodiments of the present disclosure further propose a resource scheduling device, and the device includes an acquisition module configured to receive a service request with attached service needs. Generating a resource supply side list formed by a resource supply side that meets the business needs based on the business needs and the state of the resource supply side; selecting a target resource supply side from the resource supply side list based on the resource supply side list and first information, where the first information is used to indicate a global optimization target; and calling the target resource supply side to perform a service. A processing module configured to execute the above is included.

[0014] Optionally, the apparatus Further includes an incentive module configured to transmit second information to a first resource side when the service meets the global optimization target, where the first resource side includes a resource usage side and / or a resource supply side, and the second information is used to incentivize the first resource side to conform to the global optimization target.

[0015] Embodiments of the present disclosure further propose a computer device, which includes a processor and a memory storing a computer program. When the computer program is executed by the processor, the above method is executed.

[0016] Embodiments of the present disclosure further propose a computer-readable storage medium for storing instructions. When the instructions are executed by a computer, the computer executes the above method.

Advantages of the Invention

[0017] The above means of the present disclosure have at least the following beneficial effects. In the above means of the present disclosure, a service request accompanied by a service need initiated by the user side is received, and based on the service need and the state of the resource supply side, a resource supply side list formed by the resource supply side that meets the service need is generated. Based on the resource supply side list and the first information used to indicate the global optimization goal, a target resource supply side is selected from the resource supply side list, and the target resource supply side is called to perform a computing power service. In this way, from multiple perspectives of global optimization, by scheduling the service request to the optimal target resource supply side to perform the service, the resource service efficiency in the network can be improved.

Brief Description of the Drawings

[0018]

Figure 1

Figure 2

Figure 3

Embodiments for Carrying Out the Invention

[0019] Hereinafter, exemplary embodiments of the present disclosure will be described in more detail with reference to the drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure should not be limited by the embodiments described herein and can be implemented in various forms. In contrast, providing these embodiments is for the purpose of enabling a more complete understanding of the present disclosure and fully communicating the scope of the present disclosure to those skilled in the art.

[0020] As shown in FIG. 1, an embodiment of the present disclosure proposes a resource scheduling method, and the method may include the following steps 11 to 14.

[0021] In step 11, a service request is received, and the service request is accompanied by a computing power service need.

[0022] In step 12, based on the business needs and the status of the resource supply side, a resource supply side list formed by the resource supply side that meets the business needs is generated.

[0023] In step 13, based on the resource supply side list and the first information, a target resource supply side is selected from the supply side list, where the first information is used to indicate the global optimization target of each resource supply side in the resource supply side list.

[0024] The global optimization target is a target value corresponding to at least one service indicator of all resource supply sides. Here, the global optimization target includes at least one of a first global optimization target corresponding to the global transaction resource volume indicator, a second global optimization target corresponding to the global total resource transaction amount indicator, a third global optimization target corresponding to the global energy consumption indicator, a fourth global optimization target corresponding to the global service stability indicator, and a fifth global optimization target corresponding to the global carbon emission indicator.

[0025] It should be noted that the resources according to the embodiments of the present disclosure may be computing power resources, service resources, and / or network resources, etc.

[0026] In step 14, the target resource supply side is called to provide services.

[0027] In the embodiment of the present disclosure, a service requirement accompanied by business needs initiated by the user side is received, and based on the business needs and the state of the resource supply side, a resource supply side list formed by the resource supply side that meets the business needs is generated. Based on the resource supply side list and the global optimization target, which is the target value corresponding to at least one service indicator of all resource supply sides, a target resource supply side is selected from the resource supply side list, and the target resource supply side is called to provide services. In this way, from multiple perspectives of global optimization, by scheduling the service requirements to the optimal target resource supply side to provide services, the resource service efficiency in the network can be improved.

[0028] In an alternative embodiment of the present disclosure, after step 14 above, the method further includes the following step 15.

[0029] In step 15, when the service meets the global optimization target, the first resource side is sent the second information. Here, the first resource side includes the resource user side and / or the resource supply side, and the second information is used to incentivize the first resource side to conform to the global optimization target. An incentive can be indicated from the second information. The incentive is sent in the form of a credit value and can encourage the resource supply side and the user side to actively conform to the global optimization target.

[0030] Here, when the user side is the computing power user side and the supply side is the computing power resource or computing power service supply side, the computing power incentive is determined by the global optimization goal. For example, regarding the global transaction computing power index, the larger the transaction computing power of this computing power service, the greater the computing power incentive; regarding the global total computing power transaction amount index, the larger the total computing power transaction amount of this computing power service, the greater the computing power incentive; regarding the global computing power energy consumption index, the smaller the computing power energy consumption of this computing power service, the greater the computing power incentive; regarding the global computing power service stability index, the greater the computing power service stability of this computing power service, the greater the computing power incentive; regarding the global carbon emission index, the smaller the carbon emission of this computing power service, the greater the computing power incentive.

[0031] The same can be applied to network resources. Regarding the global transaction network resource volume index, the larger the transaction volume of this network resource service, the greater the incentive; regarding the global total network resource transaction amount index, the larger the total transaction amount of this network resource service, the greater the incentive; regarding the global energy consumption index, the smaller the energy consumption of this network resource service, the greater the incentive; regarding the global service stability index, the greater the stability of this network resource service, the greater the incentive; regarding the global carbon emission index, the smaller the carbon emission of this network resource service, the greater the incentive.

[0032] In one selectable embodiment of the present disclosure, in step 12, taking the computing power resource or computing power service as an example, the computing power trading platform generates a list of computing power supply sides (P1, P2, P3) that meet the current business needs based on the computing power business needs and the status of the computing power supply side.

[0033] In step 13, the resource trading platform combines the global optimization goals based on the computing power supply side list, and selects an appropriate target resource supply side (such as P1) from the supply side lists that meet the business needs.

[0034] In another alternative embodiment of the present disclosure, step 13 may include the following steps 131 to 132.

[0035] In step 131, select a resource supply side that reports the predicted value of the global optimization goal from the resource supply side list to form a target resource supply side list. Here, the predicted value of the global optimization goal is calculated by the resource supply side based on the business needs and the historical resource target data of the resource supply side.

[0036] In step 132, select a resource supply side that meets the business needs from the target resource supply side list as the target resource supply side.

[0037] In this embodiment, the resource supply side can combine its historical resource target data and the current business needs to predict the predicted value of the current global optimization goal.

[0038] In this case, there may be a resource supply side that does not have the ability to report the global optimization goal (for example, P1 does not have this ability, while P2 and P3 have this ability). Based on the resource supply side list and the reporting status of the global optimization goal, preferentially select from the resource supply sides that report the global optimization goal (such as P2, P3), and select an appropriate target resource supply side (such as P2) from the resource supply side list that meets the business needs.

[0039] In this embodiment, on the premise of satisfying a single user resource service request, an optimal selection is made again in combination with the global optimization goal. The resource trading platform makes a decision by combining the global optimization goal reported from the resource supply side, and schedules service for business requirements to the optimal target resource supply side from multiple perspectives of global optimization, so as to improve the resource service efficiency in the network.

[0040] The following describes the specific implementation process of the above embodiment with reference to FIG. 2. For example, when the lowest global carbon emission is set as the optimization goal, the global optimization goal is set to the lowest global carbon emission, and the computing power resources or computing power services are taken as an example for the following description.

[0041] The computing power scheduling method considering the global optimization goal includes the following process.

[0042] In step 1, the computing power using side (C1) issues a computing power service request with attached computing power service needs.

[0043] In step 2, the computing power trading platform generates a list of computing power supply sides (P1, P2, P3) that meet the current service needs based on the computing power service needs and the state of the computing power supply side.

[0044] In step 3, based on the computing power global optimization goal, the computing power trading platform needs to obtain the predicted carbon emissions of the computing power services of the computing power supply sides in the computing power supply side list.

[0045] Optionally, the computing power supply side can combine its historical carbon emission data, combine the current computing power transaction volume, etc., to predict the carbon emissions of the current computing power service. For example, regarding the historical carbon emission data of the computing power supply side, if the business need is a carbon emission need of 50 units and the carbon emissions of the actually provided computing power service is 80, when the current business need is a carbon emission need of 100 units, it can be predicted that the carbon emissions of the current computing power service is 160. Here, only an example is given for explanation, and it is not limited to this type of prediction method.

[0046] In addition, there may be a computing power supply side that does not have the ability to report computing power carbon emissions (for example, P1 does not have this ability, while P2 and P3 have this ability).

[0047] In step 4, based on the computing power supply side list and the carbon emission reporting status, preferentially select from the computing power supply sides that report computing power carbon emissions information (for example, P2, P3), and select an appropriate computing power supply side (for example, P2) from the computing power supply side list that meets the business needs.

[0048] In step 5, the computing power trading platform sends the final transaction decision information to the target computing power supply side (P2) to start the current computing power service.

[0049] Furthermore, in order to encourage the computing power supply side and the computing power using side to contribute to the global optimization goal, computing power incentives that meet the global optimization goal can be sent.

[0050] In step 6, the computing power trading platform monitors the provision status of the current computing power service, determines whether the current service has been completed as promised, and if it has been completed, determines that the current service meets the global optimization goal (P2, C1).

[0051] In step 7, incentive instruction information is transmitted, and a computing power incentive is transmitted for the current computing power user side and the computing power supply side (P2, C1). Optionally, the computing power incentive value is determined in consideration of the carbon emissions of the current computing power service. For example, the lower the carbon emissions of the current computing power service, the higher the computing power incentive value, and the specific value can be calculated according to the actual scenario.

[0052] In the above embodiment of the present disclosure, under the premise of meeting a single user requirement, an optimal selection is made again in combination with the global optimization goal. The computing power trading platform needs to make a decision by combining the global optimization goal prediction value reported by the computing power supply side. After a single service that meets the global optimization goal is completed, an incentive is transmitted to the participating user side and the computing power provider. The incentive can be transmitted in the form of a credit value and is used to encourage the user side and the provider to actively conform to the global optimization goal.

[0053] As shown in FIG. 3, the embodiment of the present disclosure further provides a resource scheduling device 30, which includes the following acquisition module 31 and processing module 32.

[0054] The acquisition module 31 is configured to receive a service request with associated service needs.

[0055] The processing module 32 is configured to generate a resource supply side list formed by a resource supply side that meets the service needs based on the service needs and the state of the resource supply side, and select a target resource supply side from the resource supply side list based on the resource supply side list and the first information, where the first information is used to indicate the global optimization goal, and call the target resource supply side to perform a service.

[0056] Optionally, the resource scheduling device 30 further includes an incentive module 33.

[0057] The incentive module 33 is configured to transmit second information to the first resource side when the service meets the global optimization goal, where the first resource side includes a resource usage side and / or a resource supply side, and the second information is used to incentivize the first resource side to conform to the global optimization goal.

[0058] Optionally, the incentive indicated by the second information is determined based on the global optimization goal.

[0059] Optionally, when the global optimization goal includes a first global optimization goal corresponding to a global transaction resource quantity index, the incentive has a positive correlation with the transaction resource quantity of the current service. When the global optimization goal includes a second global optimization goal corresponding to a global total resource transaction amount index, the incentive has a positive correlation with the total resource transaction amount of the current service. When the global optimization goal includes a third global optimization goal corresponding to a global energy consumption index, the incentive has a negative correlation with the energy consumption of the current service. When the global optimization goal includes a fourth global optimization goal corresponding to a global service stability index, the incentive has a positive correlation with the stability of the current service. When the global optimization goal includes a fifth global optimization goal corresponding to a global carbon emission index, the incentive has a negative correlation with the carbon emission index of the current service.

[0060] Optionally, selecting a target resource supply side from the resource supply side list based on the resource supply side list and the first information includes: selecting a resource supply side that reports a global optimization goal predicted value from the resource supply side list to form a target resource supply side list; and selecting a resource supply side that meets the service needs from the target resource supply side list as the target resource supply side.

[0061] Optionally, the global optimization target predicted value is calculated by the resource supply side based on the service needs and the historical resource target data of the resource supply side.

[0062] Optionally, the global optimization target is a first global optimization target corresponding to a global transaction resource quantity index, a second global optimization target corresponding to a global total resource transaction amount index, a third global optimization target corresponding to a global energy consumption index, a fourth global optimization target corresponding to a global service stability index, and at least one of a fifth global optimization target corresponding to a global carbon emission index.

[0063] It should be noted that all implementation manners in the above method embodiments can be applied to the device embodiments, and the same technical effects can also be achieved.

[0064] The embodiments of the present disclosure further propose a computer device including a processor and a memory storing a computer program. When the computer program is executed by the processor, the above method is executed. All implementation manners in the above method embodiments can be applied to this embodiment, and the same technical effects can also be achieved.

[0065] The embodiments of the present disclosure further propose a computer-readable storage medium including instructions. When the instructions are executed by a computer, the computer executes the above method. All implementation manners in the above method embodiments can be applied to this embodiment, and the same technical effects can also be achieved.

[0066] A person skilled in the art can recognize that each example unit and algorithm step described in relation to the embodiments disclosed herein can be implemented by electronic hardware or a combination of computer software and electronic hardware. These functions can be executed by hardware or software according to the specific application and design constraints of the technical solution. A person skilled in the art can use different methods for each specific application to realize the described functions, but this realization is not considered to exceed the scope of the present disclosure.

[0067] The specific operation processes of the above-described systems, devices, and units can refer to the corresponding processes in the method embodiments described above for the sake of ease and conciseness of description, and a person skilled in the art can clearly understand that no further description will be given here.

[0068] In the embodiments according to the present disclosure, it should be understood that the disclosed devices and methods may be implemented in other ways. For example, the above-described device embodiments are merely illustrative. For example, the division of units is merely a division of logical functions. When actually implemented, a plurality of units or components may be combined, or integrated into another system, or some features may be ignored or not executed, etc., and there may be other division methods. In another aspect, the couplings or direct couplings or communication connections shown or discussed with each other may be indirect couplings or communication connections through some interfaces, devices or units, and may be in electrical, mechanical, or other forms.

[0069] The units described as the separated components may or may not be physically separated. Also, the components shown as units may or may not be physical units, that is, they may be located in one place or distributed among a plurality of network elements. The purpose of this embodiment can be realized by selecting some or all of the units according to actual needs.

[0070] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may physically exist alone, or two or more units may be integrated into one unit.

[0071] When the above functions are realized as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on such understanding, the technical solution of the present disclosure is in the form of a software product stored in a storage medium containing some instructions for executing all or some of the steps of the methods described in each embodiment of the present disclosure, essentially or contributing to the relevant technology, or embodying a part of the technical solution thereof. On the other hand, the aforementioned storage medium includes various media capable of storing program codes, such as USB disks, removable hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0072] Furthermore, in the apparatus and method of the present disclosure, it is obvious that each component or each step can be decomposed and / or recombined again. These decompositions and / or recombinations should be regarded as equivalent schemes of the present disclosure. Also, the steps of executing the above series of processes can be executed in chronological order in the order described naturally, but it is not necessarily required to be executed in chronological order, and some steps can be executed in parallel or independently of each other. A person skilled in the art can understand all or any steps or components of the method and apparatus of the present disclosure, and can be realized by hardware, firmware, software, or a combination thereof, which can be realized by any computing device (including a processor, a storage medium, etc.) or a network of computing devices using their basic programming skills after reading the description of the present disclosure by those skilled in the art.

[0073] Therefore, the object of the present disclosure can also be achieved by executing a program or a set of programs on any computing device. The computing device may be a known general-purpose device. Therefore, the object of the present disclosure can also be achieved only by providing a program product including program code for realizing the method or device. That is, such a program product also constitutes the present disclosure, and a storage medium storing such a program product also constitutes the present disclosure. Obviously, the storage medium may be any known storage medium or any storage medium to be developed in the future. Also, in the device and method of the present disclosure, it is obvious that each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent schemes of the present disclosure. Also, the steps of executing the above series of processes can be executed in chronological order in the order described naturally, but it is not necessarily required to be executed in chronological order. Some steps can be executed in parallel or independently of each other.

[0074] The above is a preferred embodiment of the present disclosure, and it should be pointed out that those skilled in the art can make some improvements and refinements that should be regarded as within the protection scope of the present disclosure without departing from the principle of the present disclosure.

Claims

1. A resource scheduling method, comprising: receiving a service request with associated service needs; generating a resource provider list formed by resource providers that meet the service needs based on the service needs and the state of the resource providers; selecting a target resource provider from the resource provider list based on the resource provider list and first information, where the first information is used to indicate a global optimization goal; invoking the target resource provider to provide a service.

2. After invoking the target resource provider to provide a service, if the service meets the global optimization goal, further comprising transmitting second information to a first resource side, where the first resource side includes a resource user side and / or a resource provider side, and the second information is used to incentivize the first resource side to conform to the global optimization goal. The resource scheduling method according to Claim 1.

3. The incentive indicated by the second information is determined based on the global optimization goal. The resource scheduling method according to Claim 2.

4. If the global optimization goal includes a first global optimization goal corresponding to a global transaction resource quantity indicator, the incentive has a positive correlation with the transaction resource quantity of the current service; If the global optimization goal includes a second global optimization goal corresponding to a global total resource transaction amount indicator, the incentive has a positive correlation with the total resource transaction amount of the current service; If the global optimization goal includes a third global optimization goal corresponding to a global energy consumption indicator, the incentive has a negative correlation with the energy consumption of the current service; If the global optimization goal includes a fourth global optimization goal corresponding to a global service stability indicator, the incentive has a positive correlation with the stability of the current service; If the global optimization goal includes a fifth global optimization goal corresponding to a global carbon emission indicator, the incentive has a negative correlation with the carbon emission indicator of the current service. The resource scheduling method according to Claim 3.

5. Selecting a target resource provider from the resource provider list based on the resource provider list and first information is Selecting a resource supply side that reports a predicted value of a global optimization target from among the resource supply side lists to form a target resource supply side list; Selecting a resource supply side that matches the service needs from among the target resource supply side lists to be the target resource supply side, the resource scheduling method according to claim 1.

6. The resource scheduling method according to claim 5, wherein the predicted value of the global optimization target is calculated by the resource supply side based on the service needs and historical resource target data of the resource supply side.

7. The global optimization target is a first global optimization target corresponding to a global transaction resource volume indicator; a second global optimization target corresponding to a global total resource transaction amount indicator; a third global optimization target corresponding to a global energy consumption indicator; a fourth global optimization target corresponding to a global service stability indicator; a fifth global optimization target corresponding to a global carbon emission indicator, the resource scheduling method according to any one of claims 1 to 6, including at least one of them.

8. A resource scheduling device, comprising an acquisition module configured to receive a service request with attached service needs; generating a resource supply side list formed by a resource supply side that matches the service needs based on the service needs and the state of the resource supply side, and selecting a target resource supply side from among the resource supply side lists based on the resource supply side list and first information, wherein the first information is used to indicate a global optimization target, and a processing module configured to call the target resource supply side to perform a service, the resource scheduling device.

9. Further comprising an incentive module configured to transmit second information to a first resource side when the service matches the global optimization target, wherein the first resource side includes a resource usage side and / or a resource supply side, and the second information is used to incentivize the first resource side to conform to the global optimization target, the resource scheduling device according to claim 8.

10. A computer device including a processor and a memory storing a computer program, wherein when the computer program is executed by the processor, the method according to any one of claims 1 to 7 is executed.

11. A computer-readable storage medium for storing instructions, wherein when the instructions are executed by a computer, the computer executes the method according to any one of claims 1 to 7.

Images