CN114580806A - Resource allocation method, device, readable medium and electronic equipment - Google Patents
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Abstract
The invention discloses a resource allocation method, a device, a readable medium and electronic equipment, wherein the method comprises the steps of determining target resources for constructing a mathematical model based on data provided by a data provider and mathematical model requirements of a model demander; determining a target resource provider based on the target resource; determining a virtual resource transferred to the data provider by a target resource provider based on the data provided by the data provider and a mathematical model; and determining the virtual resources transferred to the target resource providers based on the virtual resources acquired by calling the mathematical model by the model demander and the current resources provided by each target resource provider. The technical scheme provided by the invention reduces the risk born by the data provider, encourages more data providers to join in the joint learning, and allocates the virtual resources to the target resource provider after the mathematical model is called to generate the virtual resources, so that the allocation of the virtual resources is reasonable.
Description
Technical Field
The present invention relates to the field of energy, and in particular, to a resource allocation method, device, readable medium, and electronic device.
Background
With the rapid development of internet technology, user data becomes more and more important resources, and various mathematical models can be trained based on the user data. However, not every energy user can collect massive user data and train an accurate mathematical model, which makes joint learning become a trend, but training a mathematical model often requires high investment cost, and the return provided by the model service is uncertain and delayed, so it is crucial to determine a reasonable resource allocation method to encourage each energy user to participate in joint learning.
Disclosure of Invention
The invention provides a resource allocation method, a resource allocation device, a readable medium and electronic equipment, which utilize a target resource provider to provide a data provider with a timely virtual resource return, reduce the risk born by the data provider, encourage more data providers to join in joint learning, and transfer part of virtual resources to the target resource provider after a mathematical model is called to generate the virtual resources, so that the allocation of the virtual resources is reasonable.
In a first aspect, the present invention provides a resource allocation method, including:
determining a target resource for constructing the mathematical model based on data provided by a data provider and mathematical model requirements of a model demander;
determining a target resource provider based on the target resource;
determining a virtual resource to be transferred by the target resource provider to the data provider based on the data provided by the data provider and the mathematical model;
and determining the virtual resources transferred to the target resource providers based on the virtual resources acquired by calling the mathematical model by the model demander and the current resources provided by each target resource provider.
Preferably, the first and second electrodes are formed of a metal,
the step of determining the virtual resource transferred to the target resource provider based on the virtual resource acquired by the model demander calling the mathematical model and the current resource provided by each target resource provider comprises:
determining virtual resources obtained by calling the mathematical model by the model demander based on the number of times the mathematical model is called;
determining a proportionality coefficient between the current resource and the target resource provided by each target resource provider;
and determining the virtual resource transferred to the target resource provider based on the virtual resource acquired by calling the mathematical model by the model demander and the proportionality coefficient.
Preferably, the first and second electrodes are formed of a metal,
the method further comprises the following steps:
judging whether the sum of the current resources provided by each target resource provider is smaller than the target resource or not;
if yes, determining a resource difference value of the target resource and the sum of the current resources provided by each target resource provider;
and determining the virtual resource transferred to the data provider based on the virtual resource acquired by calling the mathematical model by the model demander, the resource difference and the contribution ratio of the data provided by the data provider to the mathematical model.
Preferably, the first and second electrodes are formed of a metal,
before the determining a target resource for building the mathematical model based on the data provided by the data provider and the mathematical model requirement of the model demander, the method further comprises:
acquiring a metadata list provided by a data provider;
and selecting a model demander based on the metadata list.
Preferably, the first and second electrodes are formed of a metal,
the determining a virtual resource that the target resource provider transfers to the data provider based on the data provided by the data provider and the mathematical model comprises:
determining a contribution proportion of data provided by the data provider to the mathematical model;
determining a virtual resource that the target resource provider transfers to the data provider based on a contribution ratio of data provided by the data provider to the mathematical model.
Preferably, the first and second liquid crystal display panels are,
the determining the contribution proportion of the data provided by the data provider to the mathematical model comprises:
determining the descending degree of a loss function of the mathematical model before and after the data provided by the data provider is added into the mathematical model;
based on the degree of decline, determining a contribution proportion of data provided by the data provider to the mathematical model.
In a second aspect, the present invention provides a resource allocation apparatus, including:
the target resource determining module is used for determining target resources for constructing the mathematical model based on data provided by a data provider and the mathematical model requirement of a model demander;
the provider determining module is used for determining a target resource provider based on the target resource;
a virtual resource determining module, configured to determine, based on the data provided by the data provider and the mathematical model, a virtual resource to be transferred by the target resource provider to the data provider;
and the virtual resource transfer module is used for determining the virtual resources transferred to the target resource providers based on the virtual resources acquired by calling the mathematical model by the model demander and the current resources provided by each target resource provider.
Preferably, the first and second electrodes are formed of a metal,
the virtual resource transfer module comprises:
the virtual resource determining unit is used for determining the virtual resource acquired by the mathematical model called by the model demander based on the called times of the mathematical model;
the proportion coefficient determining unit is used for determining the proportion coefficient of the current resource and the target resource provided by each target resource provider;
and the virtual resource transfer unit is used for determining the virtual resource transferred to the target resource provider based on the virtual resource acquired by calling the mathematical model by the model demander and the proportionality coefficient.
In a third aspect, the invention provides a readable medium comprising executable instructions, which when executed by a processor of an electronic device, perform the method according to any of the first aspect.
In a fourth aspect, the present invention provides an electronic device, comprising a processor and a memory storing execution instructions, wherein when the processor executes the execution instructions stored in the memory, the processor performs the method according to any one of the first aspect.
The invention provides a resource allocation method, a device, a readable medium and electronic equipment, wherein the method determines a target resource for constructing a mathematical model according to data provided by a data provider and mathematical model requirements of a model demander, then determines a target resource provider according to the target resource, and determines a virtual resource transferred from the target resource provider to the data provider according to the data and the mathematical model provided by the data provider, the transfer of the virtual resource has timeliness so that risks and costs in a training period of the mathematical model are shared by the target resource provider, after the mathematical model is successfully constructed, the mathematical model is allocated to the model demander, and the model demander calls the mathematical model, so that the virtual resource transferred by the model demander due to calling the mathematical model can be obtained, and according to the current resource provided by the target resource provider, a virtual resource to transfer to a target resource provider is determined. The technical scheme provided by the invention reduces the risk born by the data provider, encourages more data providers to join in joint learning, and can reasonably configure virtual resources.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed for the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a schematic flowchart of a first resource allocation method according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a second resource allocation method according to an embodiment of the present invention;
fig. 3 is a flowchart illustrating a third resource allocation method according to an embodiment of the present invention;
fig. 4 is a schematic flowchart of a fourth resource allocation method provided in the embodiment of the present invention;
fig. 5 is a flowchart illustrating a fifth resource allocation method according to an embodiment of the present invention;
fig. 6 is a flowchart illustrating a sixth resource allocation method according to an embodiment of the present invention;
fig. 7 is a schematic structural diagram of a resource allocation apparatus according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of a virtual resource transfer module in a resource allocation apparatus according to an embodiment of the present invention;
fig. 9 is a schematic structural diagram of an electronic device provided in an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be described in detail and completely with reference to the following embodiments and accompanying drawings. It is to be understood that the described embodiments are merely exemplary of the invention, and not restrictive of the full scope of the invention. All other embodiments, which can be obtained by a person skilled in the art without making any creative effort based on the embodiments in the present invention, belong to the protection scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a resource allocation method, where the method includes:
and step 14, determining the virtual resources transferred to the target resource providers based on the virtual resources acquired by calling the mathematical model by the model demander and the current resources provided by each target resource provider.
In the above embodiment, the target resource for constructing the mathematical model is determined according to the data provided by the data provider and the mathematical model requirement of the model demander, then according to the target resource, determining a target resource provider, and according to the data provided by the data provider and the mathematical model, determining the virtual resource transferred by the target resource provider to the data provider, the transfer of the virtual resource is timely, so that the risk and the cost of the mathematical model training period are shared by the target resource provider, after the mathematical model is successfully built, the mathematical model is distributed to a model demander, the model demander calls the mathematical model, therefore, the virtual resources transferred by the model demand party due to the calling of the mathematical model can be obtained, and the virtual resources transferred to the target resource provider are determined according to the current resources provided by the target resource provider. According to the technical scheme provided by the embodiment, the risk born by the data provider is reduced, more data providers are encouraged to join in joint learning, and the virtual resources can be reasonably configured.
As shown in fig. 2, in an embodiment of the present invention, the step 14 determines, based on the virtual resource obtained by the model demander invoking the mathematical model and the current resource provided by each target resource provider, a virtual resource to be transferred to the target resource provider, including:
In the above embodiment, after the mathematical model is successfully constructed, the mathematical model is allocated to the model demander, the model demander calls the mathematical model, and the virtual resources transferred to the joint center from the model demand direction are related to the number of calls of the mathematical model, so that the number of calls of the mathematical model is determined, and thus the virtual resources obtained by calling the mathematical model by the model demander, that is, the number of virtual resources transferred to the joint center from the model demand direction is determined. Further determining current resources provided by target resource providers, wherein the amount of the current resources provided by each target resource provider is different, so that the proportionality coefficient between the current resources provided by each target resource provider and the target resources needs to be determined, and the more current resources provided by the target resource providers, the larger the proportionality coefficient is; the method comprises the steps of determining virtual resources transferred to a target resource provider according to virtual resources and a proportionality coefficient obtained by calling a mathematical model by a model demander, and transferring part of the virtual resources to the target resource provider after current resources input by the target resource provider in the early stage are allocated to the model demander by the mathematical model to use the obtained virtual resources, so that the resource allocation is reasonable.
As shown in fig. 3, in an embodiment of the present invention, the method further includes:
and step 17, determining the virtual resources transferred to the data provider based on the virtual resources acquired by calling the mathematical model by the model demander, the resource difference and the contribution ratio of the data provided by the data provider to the mathematical model.
In the above embodiment, there may be a case that the total of the current resources provided by the target resource provider is smaller than the target resource, at this time, the mathematical model early training cost and risk cannot be borne by the target resource provider alone, that is, when the target resource provider transfers the virtual resource to the data provider, the data provider cannot perform all corresponding virtual resource transfers, and at this time, the data provider still needs to bear the risk of part of the early mathematical model training, after the mathematical model is allocated to the model demander for use, the virtual resource acquired because the mathematical model is called at this time should be allocated not only to the target resource provider but also to the data provider, so that when the total of the current resources provided by each target resource provider is smaller than the target resource, the resource gap between the target resource and the total of the current resources provided by each target provider is determined, and then according to the virtual resources obtained by calling the mathematical model by the model demander, the resource difference and the contribution ratio of the data provided by the data provider to the mathematical model, determining the virtual resources transferred to the data provider. In a possible implementation manner, according to the product of the resource difference and the contribution ratio of data provided by the data providers to the mathematical model, the virtual resource share which each data provider should obtain is determined, and the virtual resource share and the virtual resource obtained by calling the mathematical model by the model demander are used for determining the virtual resource transferred to the data provider, so that the target resource provider and the data provider share the risk together during the training of the mathematical model, and after the mathematical model is allocated to the model demander, the virtual resource obtained by calling the mathematical model by the model demander needs to be allocated to the target resource provider and the data provider, so that the resource allocation is reasonable, and more data providers and target resource providers are encouraged to be added into the joint learning. Of course, if the sum of the current resources provided by each target resource provider is determined to be equal to the target resource, the current process may be ended without executing steps 16 and 17.
As shown in fig. 4, in an embodiment of the present invention, before determining, in step 11, a target resource for building the mathematical model based on data provided by a data provider and a mathematical model requirement of a model demander, the method further includes:
and 19, selecting a model demander based on the metadata list.
In the above embodiment, in order to reduce the risk of providing data, the data provider initially provides a metadata list, where the metadata list is not real data but describes data, after the combination center obtains the metadata list provided by the data provider, a model demander is selected according to the metadata list, and after obtaining the model demander, the data provider can provide real data to perform subsequent mathematical model training, so as to avoid a situation that no model demander calls the mathematical model after the data provider provides real data to perform mathematical model training, thereby reducing the risk of providing data by the data provider, specifically, a model demander with the same number of descriptors above a preset number is selected according to a comparison between descriptors in the metadata list and descriptors of models required by model demanders to be selected, so as to ensure that the mathematical model required by the model demander is finally acquired.
As shown in fig. 5, in an embodiment of the present invention, the step 13 of determining the virtual resource transferred from the target resource provider to the data provider based on the data provided by the data provider and the mathematical model includes:
In the above embodiment, different data providers provide different data, and the contribution ratio to the mathematical model is different, so that the contribution ratio of the data provided by the data providers to the mathematical model needs to be determined to ensure the reasonability of the allocation of resources.
As shown in fig. 6, in one embodiment of the present invention, the step 131 of determining the contribution ratio of the data provided by the data provider to the mathematical model includes:
In the above embodiment, in order to determine the contribution ratio of the data provided by the data provider in the mathematical model, the degree of decrease of the loss function of the mathematical model before and after the data provided by the data provider is added to the mathematical model is determined, and the contribution ratio of the data provided by the data provider in the mathematical model is determined according to the degree of decrease. Specifically, the larger the degree of decrease of the loss function is, the larger the contribution ratio of the data provided by the data provider to the mathematical model is, and the larger the contribution ratio of the data provided by the data provider in the mathematical model is, the more the virtual resource share is acquired by the data provider, so that the resource allocation is reasonable.
Based on the same inventive concept as the method described above, as shown in fig. 7, an embodiment of the present invention provides a resource allocation apparatus, including:
a target resource determining module 71, configured to determine a target resource for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirement of the model demander;
a provider determining module 72, configured to determine a target resource provider based on the target resource;
a virtual resource determining module 73, configured to determine, based on the data provided by the data provider and the mathematical model, a virtual resource to be transferred by the target resource provider to the data provider;
and a virtual resource transfer module 74, configured to determine, based on the virtual resource obtained by the model demander calling the mathematical model and the current resource provided by each target resource provider, a virtual resource to be transferred to the target resource provider.
The virtual resource transfer module 74 includes:
the virtual resource determining unit 741 is configured to determine, based on the number of times that a mathematical model is called, a virtual resource that is obtained by calling the mathematical model by the model demander;
a proportionality coefficient determining unit 742, configured to determine proportionality coefficients of a current resource and a target resource provided by each target resource provider;
a virtual resource transferring unit 743, configured to determine, based on the virtual resource obtained by the model demander invoking the mathematical model and the scaling factor, a virtual resource to be transferred to the target resource provider.
For convenience of description, the above device embodiments are described with functions divided into various units or modules, and the functions of the units or modules may be implemented in one or more software and/or hardware when implementing the present invention.
Fig. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present invention. On the hardware level, the electronic device includes a processor 901 and a memory 902 storing execution instructions, and optionally further includes an internal bus 903 and a network interface 904. The Memory 902 may include a Memory 9021, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory 9022 (e.g., at least 1 disk Memory); the processor 901, the network interface 904, and the memory 902 may be connected to each other by an internal bus 903, and the internal bus 903 may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, an EISA (Extended Industry Standard Architecture) bus, or the like; the internal bus 903 may be divided into an address bus, a data bus, a control bus, etc., which is indicated by a double-headed arrow in fig. 9 for convenience of illustration, but does not indicate that there is only one bus or one type of bus. Of course, the electronic device may also include hardware required for other services. When the processor 901 executes execution instructions stored by the memory 902, the processor 901 performs the method in any of the embodiments of the present invention, and at least for performing the method as shown in fig. 1 to 6.
In a possible implementation manner, the processor reads the corresponding execution instruction from the nonvolatile memory into the memory and then runs the corresponding execution instruction, and can also obtain the corresponding execution instruction from other equipment, so as to form a resource allocation device on a logic level. The processor executes the execution instructions stored in the memory to implement a resource allocation method provided in any embodiment of the invention through the executed execution instructions.
The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or instructions in the form of software. The Processor may be a general-purpose Processor, including a Central Processing Unit (CPU), a Network Processor (NP), and the like; but also Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other Programmable logic devices, discrete Gate or transistor logic devices, discrete hardware components. The various methods, steps and logic blocks disclosed in the embodiments of the present invention may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
Embodiments of the present invention further provide a computer-readable storage medium, which includes an execution instruction, and when a processor of an electronic device executes the execution instruction, the processor executes a method provided in any one of the embodiments of the present invention. The electronic device may specifically be the electronic device shown in fig. 9; the execution instruction is a computer program corresponding to the resource allocation device.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects.
The embodiments of the present invention are described in a progressive manner, and the same and similar parts among the embodiments can be referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, as for the apparatus embodiment, since it is substantially similar to the method embodiment, the description is relatively simple, and for the relevant points, reference may be made to the partial description of the method embodiment.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or boiler that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or boiler. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or boiler that comprises the element.
The above description is only an example of the present invention, and is not intended to limit the present invention. Various modifications and alterations to this invention will become apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the scope of the claims of the present invention.
Claims (10)
1. A method for resource allocation, comprising:
determining a target resource for constructing the mathematical model based on data provided by a data provider and mathematical model requirements of a model demander;
determining a target resource provider based on the target resource;
determining a virtual resource that the target resource provider transfers to the data provider based on the data provided by the data provider and the mathematical model;
and determining the virtual resources transferred to the target resource providers based on the virtual resources acquired by calling the mathematical model by the model demander and the current resources provided by each target resource provider.
2. The method according to claim 1, wherein the determining the virtual resource to be transferred to the target resource provider based on the virtual resource obtained by the model demander invoking the mathematical model and the current resource provided by each target resource provider comprises:
determining virtual resources obtained by calling the mathematical model by the model demander based on the number of times the mathematical model is called;
determining a proportionality coefficient between the current resource and the target resource provided by each target resource provider;
and determining the virtual resource transferred to the target resource provider based on the virtual resource acquired by calling the mathematical model by the model demander and the proportionality coefficient.
3. The method of claim 1, further comprising:
judging whether the sum of the current resources provided by each target resource provider is smaller than the target resource or not;
if yes, determining a resource difference value of the target resource and the sum of the current resources provided by each target resource provider;
and determining the virtual resource transferred to the data provider based on the virtual resource acquired by calling the mathematical model by the model demander, the resource difference and the contribution ratio of the data provided by the data provider to the mathematical model.
4. The resource allocation method according to claim 1, wherein before determining the target resource for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirement of the model demander, the method further comprises:
acquiring a metadata list provided by a data provider;
and selecting a model demander based on the metadata list.
5. The method of claim 1, wherein determining the virtual resource that the target resource provider transfers to the data provider based on the data provided by the data provider and the mathematical model comprises:
determining the contribution proportion of the data provided by the data provider to the mathematical model;
determining a virtual resource that the target resource provider transfers to the data provider based on a contribution ratio of data provided by the data provider to the mathematical model.
6. The method of claim 5, wherein determining the contribution of the data provided by the data provider to the mathematical model comprises:
determining the degree of reduction of a loss function of the mathematical model before and after the data provided by the data provider is added into the mathematical model;
based on the degree of decline, determining a contribution proportion of data provided by the data provider to the mathematical model.
7. A resource allocation apparatus, comprising
The target resource determining module is used for determining target resources for constructing the mathematical model based on data provided by a data provider and mathematical model requirements of a model demander;
a provider determining module, configured to determine a target resource provider based on the target resource;
a virtual resource determining module, configured to determine, based on the data provided by the data provider and the mathematical model, a virtual resource to be transferred by the target resource provider to the data provider;
and the virtual resource transfer module is used for determining the virtual resources transferred to the target resource providers based on the virtual resources acquired by calling the mathematical model by the model demander and the current resources provided by each target resource provider.
8. The apparatus of claim 7, wherein the virtual resource transfer module comprises:
the virtual resource determining unit is used for determining the virtual resource acquired by the mathematical model called by the model demander based on the called times of the mathematical model;
the proportion coefficient determining unit is used for determining the proportion coefficient of the current resource and the target resource provided by each target resource provider;
and the virtual resource transfer unit is used for determining the virtual resource transferred to the target resource provider based on the virtual resource acquired by calling the mathematical model by the model demander and the proportionality coefficient.
9. A readable medium comprising executable instructions which, when executed by a processor of an electronic device, cause the electronic device to perform the method of any of claims 1 to 6.
10. An electronic device comprising a processor and a memory storing execution instructions, the processor performing the method of any of claims 1-6 when the processor executes the execution instructions stored by the memory.
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| CN202011388549.4A CN114580806A (en) | 2020-12-01 | 2020-12-01 | Resource allocation method, device, readable medium and electronic equipment |
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| CN202011388549.4A CN114580806A (en) | 2020-12-01 | 2020-12-01 | Resource allocation method, device, readable medium and electronic equipment |
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| CN114580806A true CN114580806A (en) | 2022-06-03 |
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