Resource allocation method, device, readable medium and electronic device

Abstract

The present invention discloses a resource allocation method, device, readable medium, and electronic device. The method includes determining target resources for constructing a mathematical model based on data provided by a data provider and a mathematical model requirement of a model demander; determining a target resource provider based on the target resources; determining virtual resources to be transferred from the target resource provider to the data provider based on the data and mathematical model provided by the data provider; and determining virtual resources to be transferred to the target resource provider based on the virtual resources obtained by the model demander by calling the mathematical model and the current resources provided by each target resource provider. The technical solution provided by the present invention reduces the risks borne by data providers, encourages more data providers to join joint learning, and allocates virtual resources to target resource providers after the mathematical model is called to generate virtual resources, thereby making the allocation of virtual resources reasonable.

Description

Technical Field

[0001] The present invention relates to the field of energy, and in particular to a resource allocation method, device, readable medium and electronic device. Background Art

[0002] With the rapid development of internet technology, user data has become an increasingly important resource, enabling the training of various mathematical models. However, not every energy user can collect the massive amounts of user data needed to train accurate mathematical models. This has led to the emergence of federated learning. However, training a mathematical model often requires high investment, while the returns provided by the model services are uncertain and delayed. Therefore, in order to encourage individual energy users to participate in federated learning, it is crucial to determine a reasonable resource allocation method. Summary of the Invention

[0003] The present invention provides a resource allocation method, device, readable medium and electronic device, which utilize the target resource provider to provide timely virtual resource returns to the data provider, reduce the risks borne by the data provider, encourage more data providers to join the joint learning, and transfer part of the virtual resources to the target resource provider after the mathematical model is called to generate virtual resources, so that the allocation of virtual resources is reasonable.

[0004] In a first aspect, the present invention provides a resource allocation method, comprising:

[0005] Determining target resources for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirements of the model demander;

[0006] Determining a target resource provider based on the target resource;

[0007] Determining, based on the data provided by the data provider and the mathematical model, the virtual resources that the target resource provider is to transfer to the data provider;

[0008] Based on the virtual resources obtained by the model demander by calling the mathematical model and the current resources provided by each of the target resource providers, the virtual resources to be transferred to the target resource providers are determined.

[0009] Preferably,

[0010] The determining of the virtual resources to be transferred to the target resource providers based on the virtual resources acquired by the model demander by calling the mathematical model and the current resources provided by each of the target resource providers includes:

[0011] Determining the virtual resources acquired by the model demander by calling the mathematical model based on the number of times the mathematical model is called;

[0012] Determining a ratio coefficient between the current resources provided by each target resource provider and the target resources;

[0013] The virtual resources to be transferred to the target resource provider are determined based on the virtual resources obtained by the model demander by calling the mathematical model and the proportional coefficient.

[0014] Preferably,

[0015] The method further comprises:

[0016] Determining whether the sum of current resources provided by each of the target resource providers is less than the target resource;

[0017] If yes, determining the resource difference between the target resource and the sum of current resources provided by each target resource provider;

[0018] The virtual resources to be transferred to the data provider are determined based on the virtual resources obtained by the model demander by calling the mathematical model, the resource difference, and the contribution ratio of the data provided by the data provider to the mathematical model.

[0019] Preferably,

[0020] Before determining the target resources for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirements of the model demander, the method further includes:

[0021] Get the metadata list provided by the data provider;

[0022] Based on the metadata list, a model demander is selected.

[0023] Preferably,

[0024] The determining, based on the data provided by the data provider and the mathematical model, the virtual resources to be transferred from the target resource provider to the data provider comprises:

[0025] Determining the contribution ratio of the data provided by the data provider to the mathematical model;

[0026] The virtual resources to be transferred from the target resource provider to the data provider are determined based on the contribution ratio of the data provided by the data provider to the mathematical model.

[0027] Preferably,

[0028] Determining the contribution ratio of the data provided by the data provider to the mathematical model includes:

[0029] Determining the degree of decrease in the loss function of the mathematical model before and after the data provided by the data provider is added to the mathematical model;

[0030] Based on the degree of decrease, the contribution ratio of the data provided by the data provider to the mathematical model is determined.

[0031] In a second aspect, the present invention provides a resource allocation device, comprising:

[0032] A target resource determination module is used to determine target resources for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirements of the model demander;

[0033] A provider determination module, configured to determine a target resource provider based on the target resource;

[0034] a virtual resource determination module, configured to determine the virtual resources to be transferred from the target resource provider to the data provider based on the data provided by the data provider and the mathematical model;

[0035] The virtual resource transfer module is used to determine the virtual resources to be transferred to the target resource providers based on the virtual resources obtained by the model demander calling the mathematical model and the current resources provided by each of the target resource providers.

[0036] Preferably,

[0037] The virtual resource transfer module includes:

[0038] a virtual resource determining unit, configured to determine, based on the number of times the mathematical model is called, the virtual resources acquired by the model demander by calling the mathematical model;

[0039] a proportional coefficient determining unit, configured to determine a proportional coefficient between the current resources provided by each target resource provider and the target resources;

[0040] The virtual resource transfer unit is configured to determine the virtual resources to be transferred to the target resource provider based on the virtual resources obtained by the model demander by calling the mathematical model and the proportional coefficient.

[0041] In a third aspect, the present invention provides a readable medium comprising an execution instruction. When a processor of an electronic device executes the execution instruction, the electronic device executes any method described in the first aspect.

[0042] 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 executes any method described in the first aspect.

[0043] The present invention provides a resource allocation method, device, readable medium, and electronic device. The method determines the target resources for constructing a mathematical model based on data provided by a data provider and the mathematical model requirements of a model demander. The method then determines the target resource provider based on the target resources, and determines the virtual resources to be transferred from the target resource provider to the data provider based on the data and mathematical model provided by the data provider. The transfer of the virtual resources is timely, so that the risks and costs during the mathematical model training period are shared by the target resource provider. After the mathematical model is successfully constructed, the mathematical model is allocated to the model demander, who calls the mathematical model to obtain the virtual resources transferred by the model demander due to calling the mathematical model. The virtual resources to be transferred to the target resource provider are determined based on the current resources provided by the target resource provider. The technical solution provided by the present invention reduces the risks borne by the data provider, encourages more data providers to join the federated learning, and can reasonably allocate virtual resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0045] Figure 1 A schematic diagram of a flow chart of a first resource allocation method provided in an embodiment of the present invention;

[0046] Figure 2 A schematic diagram of a flow chart of a second resource allocation method provided in an embodiment of the present invention;

[0047] Figure 3 A schematic diagram of a flow chart of a third resource allocation method provided in an embodiment of the present invention;

[0048] Figure 4 A schematic diagram of a fourth resource allocation method provided in an embodiment of the present invention;

[0049] Figure 5 This is a flow chart of a fifth resource allocation method provided in an embodiment of the present invention;

[0050] Figure 6 A schematic diagram of a sixth resource allocation method provided in an embodiment of the present invention;

[0051] Figure 7 A schematic diagram of the structure of a resource allocation device provided in an embodiment of the present invention;

[0052] Figure 8A schematic diagram of the structure of a virtual resource transfer module in a resource allocation device provided in an embodiment of the present invention;

[0053] Figure 9 The figure is a schematic structural diagram of an electronic device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the embodiments described are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0055] like Figure 1 As shown, an embodiment of the present invention provides a resource allocation method, the method comprising:

[0056] Step 11: determining target resources for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirements of the model demander;

[0057] Step 12: determining a target resource provider based on the target resource;

[0058] Step 13: determining the virtual resources to be transferred from the target resource provider to the data provider based on the data provided by the data provider and the mathematical model;

[0059] Step 14: Determine the virtual resources to be transferred to the target resource providers based on the virtual resources obtained by the model demander by calling the mathematical model and the current resources provided by each of the target resource providers.

[0060] In the above embodiment, the target resources for constructing the mathematical model are determined based on the data provided by the data provider and the mathematical model requirements of the model demander. Then, based on the target resources, the target resource provider is determined. And based on the data and mathematical model provided by the data provider, the virtual resources to be transferred from the target resource provider to the data provider are determined. The transfer of the virtual resources is timely so that the risks and costs during the mathematical model training period are shared by the target resource provider. After the mathematical model is successfully constructed, the mathematical model is assigned to the model demander. The model demander calls the mathematical model, thereby obtaining the virtual resources transferred by the model demander due to calling the mathematical model, and determining the virtual resources to be transferred to the target resource provider based on the current resources provided by the target resource provider. The technical solution provided by this embodiment reduces the risks borne by the data provider, encourages more data providers to join the joint learning, and can reasonably allocate virtual resources.

[0061] like Figure 2 As shown, in one embodiment of the present invention, step 14 determines the virtual resources to be transferred to the target resource provider based on the virtual resources obtained by the model demander by calling the mathematical model and the current resources provided by each of the target resource providers, including:

[0062] Step 141: determining the virtual resources acquired by the model demander by calling the mathematical model based on the number of times the mathematical model is called;

[0063] Step 142, determining a ratio coefficient between the current resources provided by each target resource provider and the target resources;

[0064] Step 143 : Determine the virtual resources to be transferred to the target resource provider based on the virtual resources obtained by the model demander by calling the mathematical model and the proportional coefficient.

[0065] In the above embodiment, after the mathematical model is successfully constructed, the mathematical model is assigned to the model demander. The model demander calls the mathematical model. The virtual resources transferred from the model demander to the joint center are related to the number of calls to the mathematical model. Therefore, the number of calls to the mathematical model is determined, thereby determining the virtual resources obtained by the model demander from calling the mathematical model, that is, determining the amount of virtual resources transferred to the joint center by the model demander. Specifically, the more times the mathematical model is called, the greater the amount of virtual assets transferred to the joint center. Further, the current resources provided by the target resource provider are determined. Each target resource provider provides a different amount of current resources. Therefore, it is necessary to determine a ratio coefficient between the current resources provided by each target resource provider and the target resources. The more current resources the target resource provider provides, the larger the corresponding ratio coefficient. Based on the virtual resources obtained by the model demander from calling the mathematical model and the ratio coefficient, the virtual resources transferred to the target resource provider are determined. After the current resources previously invested by the target resource provider are obtained by the mathematical model and allocated to the model demander for use, a portion of the virtual resources are transferred to the target resource provider, thereby making resource allocation more reasonable.

[0066] like Figure 3 As shown, in one embodiment of the present invention, the method further includes:

[0067] Step 15: determine whether the sum of the current resources provided by each target resource provider is less than the target resource;

[0068] Step 16: If yes, determine the resource difference between the target resource and the sum of the current resources provided by each target resource provider;

[0069] Step 17: Determine the virtual resources to be transferred to the data provider based on the virtual resources obtained by the model demander by calling the mathematical model, the resource difference, and the contribution ratio of the data provided by the data provider to the mathematical model.

[0070] In the above embodiment, there may be a situation where the total current resources provided by the target resource provider is less than the target resources. At this time, the cost and risk of the early training of the mathematical model cannot be borne by the target resource provider alone, that is, when the target resource provider transfers virtual resources to the data provider, it is impossible to transfer all the corresponding virtual resources to the data provider. At this time, the data provider still needs to bear part of the risk of the early mathematical model training. After the mathematical model is allocated to the model demander for use, the virtual resources obtained by calling the mathematical model should not only be allocated to the target resource provider, but also to the data provider. Therefore, when the total current resources provided by each target resource provider is less than the target resource, the resource gap between the target resource and the total current resources provided by each target provider is determined, and then the virtual resources transferred to the data provider are determined based on the virtual resources obtained by the model demander calling the mathematical model, the resource difference, and the contribution ratio of the data provided by the data provider to the mathematical model. In one possible implementation, the virtual resource share that each data provider should obtain is determined based on the product of the resource difference and the contribution ratio of the data provided by the data provider to the mathematical model. The virtual resource share and the virtual resources obtained by the model demander when calling the mathematical model are used to determine the virtual resources to be transferred to the data provider. This allows the target resource provider and the data provider to share the risk during the training of the mathematical model. After the mathematical model is allocated to the model demander, the virtual resources obtained by the model demander when calling the mathematical model need to be allocated to the target resource provider and the data provider, making the resource allocation reasonable and encouraging more data providers and target resource providers to join the joint learning. Of course, if it is determined that the sum of the current resources provided by each target resource provider is equal to the target resource, there is no need to perform steps 16 and 17, and the current process can be ended.

[0071] like Figure 4 As shown, in one embodiment of the present invention, before determining the target resources for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirements of the model demander in step 11, the method further includes:

[0072] Step 18: Obtain the metadata list provided by the data provider;

[0073] Step 19: Select a model demander based on the metadata list.

[0074] In the above embodiment, in order to reduce the risk of data provision, the data provider initially provides a metadata list, wherein the metadata list is not real data but a description of the data. After obtaining the metadata list provided by the data provider, the joint center selects a model demander based on the metadata list. After obtaining the model demander, the data provider can provide real data for subsequent mathematical model training, avoiding the situation where no model demander calls the mathematical model after the data provider provides real data for mathematical model training, thereby reducing the risk of data provision by the data provider. Specifically, based on the comparison between the descriptive words in the metadata list and the descriptive words of the model required by the model demander to be selected, the model demander with the same number of descriptive words exceeding a preset number is selected to ensure that the model demander ultimately obtains the required mathematical model.

[0075] like Figure 5 As shown, in one embodiment of the present invention, step 13 determines the virtual resources to be transferred from the target resource provider to the data provider based on the data provided by the data provider and the mathematical model, including:

[0076] Step 131, determining the contribution ratio of the data provided by the data provider to the mathematical model;

[0077] Step 132: Determine the virtual resources to be transferred from the target resource provider to the data provider based on the contribution ratio of the data provided by the data provider to the mathematical model.

[0078] In the above embodiment, different data providers provide different data, and their contribution ratios to the mathematical model are different. Therefore, it is necessary to determine the contribution ratios of the data provided by the data providers to the mathematical model to ensure reasonable allocation of resources.

[0079] like Figure 6 As shown, 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:

[0080] Step 1311, determining 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;

[0081] Step 1312: Determine the contribution ratio of the data provided by the data provider to the mathematical model based on the degree of decrease.

[0082] In the above embodiment, to determine the contribution percentage of the data provided by the data provider to the mathematical model, the degree of decrease in 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 percentage of the data provided by the data provider to the mathematical model is determined based on the decrease. Specifically, the greater the decrease in the loss function, the greater the contribution percentage of the data provided by the data provider to the mathematical model. The greater the contribution percentage of the data provided by the data provider to the mathematical model, the greater the share of virtual resources obtained by the data provider, thereby ensuring reasonable resource allocation.

[0083] Based on the same inventive concept as the above method, Figure 7 As shown, an embodiment of the present invention provides a resource allocation device, including:

[0084] A target resource determination module 71 is used to determine target resources for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirements of the model demander;

[0085] A provider determination module 72 is configured to determine a target resource provider based on the target resource;

[0086] A virtual resource determination module 73, configured to determine the virtual resources to be transferred from the target resource provider to the data provider based on the data provided by the data provider and the mathematical model;

[0087] The virtual resource transfer module 74 is configured to determine the virtual resources to be transferred to the target resource providers based on the virtual resources obtained by the model demander by calling the mathematical model and the current resources provided by each of the target resource providers.

[0088] The virtual resource transfer module 74 includes:

[0089] A virtual resource determining unit 741 is configured to determine the virtual resources acquired by the model demander by calling the mathematical model based on the number of times the mathematical model is called;

[0090] A proportionality coefficient determining unit 742 is configured to determine a proportionality coefficient between the current resources provided by each target resource provider and the target resources;

[0091] The virtual resource transfer unit 743 is configured to determine the virtual resources to be transferred to the target resource provider based on the virtual resources obtained by the model demander by calling the mathematical model and the proportional coefficient.

[0092] For the convenience of description, the above device embodiments are described as various units or modules according to their functions. When implementing the present invention, the functions of each unit or module can be implemented in the same or multiple software and / or hardware.

[0093] Figure 9 It is a structural diagram of an electronic device provided by an embodiment of the present invention. At the hardware level, the electronic device includes a processor 901 and a memory 902 storing execution instructions, and optionally also includes an internal bus 903 and a network interface 904. Among them, the memory 902 may include a memory 9021, such as a high-speed random access memory (Random-Access Memory, RAM), and may also include a non-volatile memory 9022 (non-volatile memory), such as at least one disk storage, etc.; the processor 901, the network interface 904 and the memory 902 can be interconnected through an internal bus 903, and the internal bus 903 can be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc.; the internal bus 903 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 9 The figure shows only one bidirectional arrow, but it does not mean 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 the execution instructions stored in the memory 902, the processor 901 executes the method in any embodiment of the present invention and is at least used to perform the following steps: Figures 1 to 6 The method shown.

[0094] In one possible implementation, a processor reads corresponding execution instructions from a non-volatile memory into a memory and then executes them. Alternatively, the processor may obtain corresponding execution instructions from another device to form a resource allocation device at a logical level. The processor executes the execution instructions stored in the memory to implement a resource allocation method provided in any embodiment of the present invention.

[0095] The processor may be an integrated circuit chip with signal processing capabilities. During implementation, each step of the above method can be completed by an integrated logic circuit of the hardware in the processor or instructions in the form of software. The above processor may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The various methods, steps and logic block diagrams disclosed in the embodiments of the present invention can be implemented or executed. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0096] The embodiment of the present invention further provides a computer-readable storage medium, including an execution instruction. When a processor of an electronic device executes the execution instruction, the processor executes the method provided in any embodiment of the present invention. The electronic device may be specifically as follows: Figure 9 The electronic device shown; the execution instruction is a computer program corresponding to the resource allocation device.

[0097] Those skilled in the art will appreciate that the embodiments of the present invention may be provided as methods or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware.

[0098] The various embodiments of the present invention are described in a progressive manner. Similar portions between the various embodiments can be referred to in conjunction with each other. Each embodiment focuses on the differences between the other embodiments. In particular, the device embodiments are generally similar to the method embodiments, so their description is relatively simple. For relevant portions, refer to the description of the method embodiments.

[0099] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, product, or boiler comprising a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, product, or boiler. In the absence of further limitations, an element defined by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, method, product, or boiler comprising the element.

[0100] The foregoing is merely an embodiment of the present invention and is not intended to limit the present invention. It will be apparent to those skilled in the art that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of the claims of the present invention.

Claims

1. A resource allocation method, characterized in that: include: Determining target resources for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirements of the model demander; Determining a target resource provider based on the target resource; Determining, based on the data provided by the data provider and the mathematical model, the virtual resources that the target resource provider is to transfer to the data provider; Determining the virtual resources to be transferred to the target resource providers based on the virtual resources obtained by the model demander by calling the mathematical model and the current resources provided by each of the target resource providers; The determining, based on the data provided by the data provider and the mathematical model, the virtual resources to be transferred from the target resource provider to the data provider includes: determining the contribution ratio of the data provided by the data provider to the mathematical model; and determining the virtual resources to be transferred from the target resource provider to the data provider based on the contribution ratio of the data provided by the data provider to the mathematical model; The method of determining the virtual resources to be transferred to the target resource provider based on the virtual resources obtained by the model demander by calling the mathematical model and the current resources provided by each of the target resource providers includes: determining the virtual resources obtained by the model demander by calling the mathematical model based on the number of times the mathematical model is called; determining the proportional coefficient between the current resources provided by each of the target resource providers and the target resources; and determining the virtual resources to be transferred to the target resource provider based on the virtual resources obtained by the model demander by calling the mathematical model and the proportional coefficient.

2. The resource allocation method according to claim 1, characterized in that: The method further comprises: Determining whether the sum of current resources provided by each of the target resource providers is less than the target resource; If yes, determining the resource difference between the target resource and the sum of current resources provided by each target resource provider; The virtual resources to be transferred to the data provider are determined based on the virtual resources obtained by the model demander by calling the mathematical model, the resource difference, and the contribution ratio of the data provided by the data provider to the mathematical model.

3. The resource allocation method according to claim 1, characterized in that: Before determining the target resources for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirements of the model demander, the method further includes: Get the metadata list provided by the data provider; Based on the metadata list, a model demander is selected.

4. The resource allocation method according to claim 1, wherein: Determining the contribution ratio of the data provided by the data provider to the mathematical model includes: Determining the degree of decrease in the loss function of the mathematical model before and after the data provided by the data provider is added to the mathematical model; Based on the degree of decrease, the contribution ratio of the data provided by the data provider to the mathematical model is determined.

5. A resource allocation device, characterized in that: include A target resource determination module is used to determine target resources for constructing the mathematical model based on the data provided by the data provider and the mathematical model requirements of the model demander; A provider determination module, configured to determine a target resource provider based on the target resource; a virtual resource determination module, configured to determine the virtual resources to be transferred from the target resource provider to the data provider based on the data provided by the data provider and the mathematical model; A virtual resource transfer module, configured to determine the virtual resources to be transferred to the target resource providers based on the virtual resources obtained by the model demander by calling the mathematical model and the current resources provided by each of the target resource providers; The determining, based on the data provided by the data provider and the mathematical model, the virtual resources to be transferred from the target resource provider to the data provider includes: determining the contribution ratio of the data provided by the data provider to the mathematical model; and determining the virtual resources to be transferred from the target resource provider to the data provider based on the contribution ratio of the data provided by the data provider to the mathematical model; The virtual resource transfer module includes: a virtual resource determination unit, which is used to determine the virtual resources obtained by the model demander by calling the mathematical model based on the number of times the mathematical model is called; a proportional coefficient determination unit, which is used to determine the proportional coefficient between the current resources provided by each target resource provider and the target resources; and a virtual resource transfer unit, which is used to determine the virtual resources to be transferred to the target resource provider based on the virtual resources obtained by the model demander by calling the mathematical model and the proportional coefficient. 6 . A readable medium comprising an execution instruction, wherein when a processor of an electronic device executes the execution instruction, the electronic device executes the method according to claim 1 . 7 . 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 executes the method according to claim 1 .

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