Resource allocation method and device of radio frequency identification tag, equipment, medium and product

Abstract

The invention relates to a radio frequency identification tag resource allocation method and device, equipment, a medium and a product. The method comprises the following steps: constructing a first sub-objective function based on the power consumption of each hardware module in the radio frequency identification system, the battery capacity of a tag in the radio frequency identification system, the service life of the tag and the relationship among resource allocation proportions corresponding to each hardware module in the tag, and constructing a second sub-objective function based on the task requirements of the hardware modules, the working efficiency of the tag and the relationship among the resource allocation proportions corresponding to the hardware modules in the tag, and then solving the first sub-objective function and the second sub-objective function by taking maximization of the service life and the working efficiency of the tag as a target, so as to obtain the resource allocation proportions of the hardware modules in the tag. And obtaining the resource allocation proportion corresponding to each hardware module in the tag, so that tag resources can be allocated for various hardware modules in the multi-mode RFID system.

Description

Technical Field

[0001] The present application relates to the field of radio frequency identification technology, and in particular to a resource allocation method, device, equipment, medium and product for a radio frequency identification tag. Background Art

[0002] In recent years, with the rapid development of Internet of Things technology, Radio Frequency Identification (RFID) technology has been widely used in intelligent monitoring, logistics management, environmental monitoring and other fields due to its high efficiency and low cost. RFID systems are usually composed of tags and base stations. Among them, tags rely on internal power to maintain operation and can actively send signals to the base station; the base station is responsible for receiving, decoding and further processing tag signals.

[0003] However, with the advancement of technology, RFID systems have gradually developed into intelligent nodes that integrate multimodal sensing and perception. For example, in industrial environment monitoring, a tag in an RFID system may be connected to multiple hardware modules at the same time, such as a radio frequency module, a microcontroller unit (MCU), a temperature sensor, a humidity sensor, a gas sensor, and a vibration sensor. Therefore, how to allocate tag resources to multiple hardware modules in a multimodal RFID system has become a technical problem that needs to be solved urgently in this field. Summary of the invention

[0004] Based on this, it is necessary to provide a resource allocation method, device, equipment, medium and product for radio frequency identification tags that can allocate tag resources to multiple hardware modules in a multimodal RFID system in response to the above technical problems.

[0005] In a first aspect, the present application provides a method for allocating resources of a radio frequency identification tag. The method comprises:

[0006] Constructing a first sub-objective function based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the life of the tag, and the resource allocation ratio corresponding to each hardware module in the tag;

[0007] Based on the relationship between the task requirements of each hardware module, the work efficiency of the label and the resource allocation ratio corresponding to each hardware module in the label, construct a second sub-objective function;

[0008] With the goal of maximizing the life span and working efficiency of the tag, the first sub-objective function and the second sub-objective function are solved to obtain the resource allocation ratio corresponding to each hardware module in the tag.

[0009] In one embodiment, aiming to maximize the lifespan and working efficiency of the tag, the first sub-objective function and the second sub-objective function are solved to obtain the resource allocation ratios corresponding to each hardware module in the tag, including:

[0010] According to the first sub-problem corresponding to the first sub-objective function and the second sub-problem corresponding to the second sub-objective function, determine the neighborhood of the target sub-problem; the target sub-problem is either the first sub-problem or the second sub-problem;

[0011] Within this neighborhood, solve the sub-objective function corresponding to the target sub-problem to obtain the initial resource allocation scheme corresponding to the target sub-problem;

[0012] According to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem, determine the resource allocation ratios corresponding to each hardware module in the tag.

[0013] In one embodiment, within this neighborhood, solving the sub-objective function corresponding to the target sub-problem to obtain the initial resource allocation scheme corresponding to the target sub-problem includes:

[0014] Within this neighborhood, based on crossover operation and mutation operation, determine the intermediate solution of the sub-objective function;

[0015] Based on the gradient descent method, update this intermediate solution to obtain the initial resource allocation scheme corresponding to the target sub-problem.

[0016] In one embodiment, within this neighborhood, based on crossover operation and mutation operation, determine the intermediate solution of the sub-objective function:

[0017] Randomly determine the initial solution of the sub-objective function from within this neighborhood;

[0018] Based on this crossover operation and this mutation operation, update this initial solution to obtain the intermediate solution of the sub-objective function.

[0019] In one embodiment, according to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem, determining the resource allocation ratios corresponding to each hardware module in the tag includes:

[0020] Obtain the first weight corresponding to the first sub-problem and the second weight corresponding to the second sub-problem;

[0021] Based on this first weight and this second weight, perform weighted aggregation on the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem to obtain the target resource allocation scheme;

[0022] Determine the resource allocation ratio corresponding to each of the hardware modules in the tag according to the target resource allocation scheme.

[0023] In one embodiment, determine the neighborhood of the target sub-problem according to the first sub-problem corresponding to the first sub-objective function and the second sub-problem corresponding to the second sub-objective function:

[0024] If the target sub-problem is the first sub-problem, then determine the second sub-problem as the neighborhood of the target sub-problem;

[0025] If the target sub-problem is the second sub-problem, then determine the first sub-problem as the neighborhood of the target sub-problem.

[0026] In a second aspect, the present application also provides a resource allocation device for a radio frequency identification tag. The device includes:

[0027] A first construction module, configured to construct a first sub-objective function based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the lifespan of the tag, and the resource allocation ratio corresponding to each of the hardware modules in the tag;

[0028] A second construction module, configured to construct a second sub-objective function based on the relationship between the task requirements of each of the hardware modules, the working efficiency of the tag, and the resource allocation ratio corresponding to each of the hardware modules in the tag;

[0029] A solving module, configured to solve the first sub-objective function and the second sub-objective function with the goal of maximizing the lifespan and working efficiency of the tag, so as to obtain the resource allocation ratio corresponding to each of the hardware modules in the tag.

[0030] In a third aspect, the present application also provides a computer device, including a memory and a processor, where the memory stores a computer program, and when the processor executes the computer program, the steps of any of the above methods are implemented.

[0031] In a fourth aspect, the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0032] In a fifth aspect, the present application also provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of any of the above methods are implemented.

[0033] The above resource allocation method, device, equipment, medium and product of the radio frequency identification tag construct a first sub-objective function based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the life of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, and construct a second sub-objective function based on the relationship between the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratio corresponding to each hardware module in the tag. Then, with the goal of maximizing the life and working efficiency of the tag, the first sub-objective function and the second sub-objective function are solved to obtain the resource allocation ratio corresponding to each hardware module in the tag, so as to realize the allocation of tag resources for multiple hardware modules in a multi-modal RFID system. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 is an internal structure diagram of a computer device provided by an embodiment of the present application;

[0035] Figure 2 is a flowchart of a resource allocation method for a radio frequency identification tag provided by an embodiment of the present application;

[0036] Figure 3 is a flowchart of a method for determining a resource allocation ratio provided by an embodiment of the present application;

[0037] Figure 4 is a flowchart of a method for determining an initial resource allocation scheme provided by an embodiment of the present application;

[0038] Figure 5 is a flowchart of a method for determining an intermediate solution provided by an embodiment of the present application;

[0039] Figure 6 is a flowchart of another method for determining a resource allocation ratio provided by an embodiment of the present application;

[0040] Figure 7 is a flowchart of a resource allocation method for a multi-modal sensing tag provided by an embodiment of the present application;

[0041] Figure 8 is a block diagram of a resource allocation device for a radio frequency identification tag provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0042] In order to make the objectives, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0043] In recent years, with the rapid development of Internet of Things technology, Radio Frequency Identification (RFID) technology has been widely used in intelligent monitoring, logistics management, environmental monitoring and other fields due to its high efficiency and low cost. RFID systems are usually composed of tags and base stations. Among them, tags rely on internal power to maintain operation and can actively send signals to the base station; the base station is responsible for receiving, decoding and further processing tag signals.

[0044] However, with the advancement of technology, RFID systems have gradually developed into intelligent nodes that integrate multimodal sensing and perception. For example, in industrial environment monitoring, a tag in an RFID system may be connected to multiple hardware modules such as a radio frequency module, a microcontroller unit (MCU), a temperature sensor, a humidity sensor, a gas sensor, and a vibration sensor at the same time. This highly integrated RFID system also brings the following challenges. First, the hardware resource consumption of multiple hardware modules has increased significantly, and how to efficiently manage power consumption has become one of the core issues in the design of RFID systems; secondly, the battery capacity of tags and base stations is limited. In the case of unreasonable resource allocation, the battery life of tags and base stations may be difficult to meet actual needs; finally, different hardware modules have different importance and task priorities in specific scenarios, and hardware resources need to be flexibly allocated to improve the overall work efficiency of the system. Therefore, how to allocate tag resources for multiple hardware modules in a multimodal RFID system has become a technical problem that needs to be solved in this field.

[0045] The resource allocation method of the radio frequency identification tag provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown. Figure 1 is an internal structure diagram of a computer device provided in an embodiment of the present application. The computer device may be a server, and its internal structure diagram may be as follows Figure 1 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, a resource allocation method for a radio frequency identification tag is implemented.

[0046] Those skilled in the art will understand that Figure 1The structure shown is only a block diagram of some structures related to the solution of this application, and does not constitute a limitation on the computer device to which the solution of this application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine some components, or have different component arrangements.

[0047] In one embodiment, as Figure 2 shown, Figure 2 is a schematic flowchart of a resource allocation method for a radio frequency identification tag provided by an embodiment of this application. This method can be applied to Figure 1 the computer device in, and this method includes the following steps:

[0048] S201, based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the life of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, construct a first sub-objective function.

[0049] In one embodiment, the hardware modules in the radio frequency identification system may include, for example, a radio frequency module, a microcontroller unit (MCU), a temperature sensor, a humidity sensor, a gas sensor, a vibration sensor, and an inertial measurement unit (IMU), etc.

[0050] Exemplarily, based on the relationship between the power consumption of each hardware module, the battery capacity of the tag, the life of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, a first sub-objective function as shown in the following formula (1) can be constructed :

[0051] (1)

[0052] In formula (1), is the battery capacity of the tag, is the total power consumption of the hardware modules in the radio frequency identification system, then is used to represent the life of the tag, is the resource allocation ratio corresponding to each hardware module, where is the total number of hardware modules, is the th resource allocation ratio corresponding to the hardware module.

[0053] Optionally, the total power consumption of the hardware modules in the radio frequency identification system can be determined based on the following formula (2):

[0054] (2)

[0055] In formula (2), is the power consumption of the th hardware module.

[0056] In one embodiment, the resource allocation ratios corresponding to the respective hardware modules satisfy the constraint conditions shown in the following formula (3):

[0057] (3)

[0058] S202. Based on the relationship among the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratios corresponding to the respective hardware modules in the tag, construct a second sub-objective function.

[0059] In the embodiments of the present application, a second sub-objective function as shown in the following formula (4) can be constructed based on the relationship among the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratios corresponding to the respective hardware modules in the tag :

[0060] (4)

[0061] In formula (4), is the task requirement of the th hardware module, then is used to represent the working efficiency of the tag.

[0062] S203. With the goal of maximizing the lifespan and working efficiency of the tag, solve the first sub-objective function and the second sub-objective function to obtain the resource allocation ratios corresponding to the respective hardware modules in the tag.

[0063] In one embodiment, a multi-objective problem with the goal of maximizing the lifespan and working efficiency of the tag can be decomposed into multiple single-objective problems, that is, solve the first sub-objective function with the goal of maximizing the lifespan of the tag to obtain a first initial resource allocation scheme, and solve the second sub-objective function with the goal of maximizing the working efficiency of the tag to obtain a second initial resource allocation scheme, and then determine the resource allocation ratios corresponding to the respective hardware modules in the tag according to the first initial resource allocation scheme and the second initial resource allocation scheme.

[0064] Exemplarily, the second sub-problem corresponding to the second sub-objective function can be determined as the domain of the first sub-objective function. In this domain, the first sub-objective function is solved with the goal of maximizing the lifespan of the tag to obtain a first initial resource allocation scheme. And the first sub-problem corresponding to the first sub-objective function is determined as the domain of the second sub-objective function. In this domain, the second sub-objective function is solved with the goal of maximizing the working efficiency of the tag to obtain a second initial resource allocation scheme. Then, according to the first initial resource allocation scheme and the second initial resource allocation scheme, the resource allocation ratio corresponding to each hardware module in the tag is determined.

[0065] In the embodiments of the present application, based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the lifespan of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, a first sub-objective function is constructed. And based on the relationship between the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, a second sub-objective function is constructed. Then, with the goal of maximizing the lifespan and working efficiency of the tag, the first sub-objective function and the second sub-objective function are solved to obtain the resource allocation ratio corresponding to each hardware module in the tag, so as to be able to allocate tag resources for multiple hardware modules in a multi-modal RFID system.

[0066] Refer to Figure 3 , Figure 3 is a schematic flowchart of a method for determining a resource allocation ratio provided by an embodiment of the present application. This embodiment relates to a possible implementation manner of solving the first sub-objective function and the second sub-objective function with the goal of maximizing the lifespan and working efficiency of the tag to obtain the resource allocation ratio corresponding to each hardware module in the tag. On the basis of the above embodiments, the above S203 includes the following steps:

[0067] S301, according to the first sub-problem corresponding to the first sub-objective function and the second sub-problem corresponding to the second sub-objective function, determine the neighborhood of the target sub-problem.

[0068] Wherein, the target sub-problem is any one of the first sub-problem and the second sub-problem.

[0069] Optionally, if the target sub-problem is the first sub-problem, the second sub-problem can be used as the domain of the first sub-problem; if the target sub-problem is the second sub-problem, the first sub-problem can be used as the domain of the second sub-problem.

[0070] S302, in the neighborhood, solve the sub-objective function corresponding to the target sub-problem to obtain the initial resource allocation scheme corresponding to the target sub-problem.

[0071] Optionally, the sub-objective function corresponding to the target sub-problem can be solved based on global crossover and mutation operations within a neighborhood to obtain an initial resource allocation scheme corresponding to the target sub-problem.

[0072] Alternatively, the intermediate solution of the sub-objective function corresponding to the target sub-problem can be determined based on global crossover and mutation operations within a neighborhood first, and then the intermediate solution can be updated based on the gradient descent method to obtain an initial resource allocation scheme corresponding to the target sub-problem, thereby further improving the accuracy of the determined initial resource allocation scheme.

[0073] S303. Determine the resource allocation ratio corresponding to each hardware module in the tag according to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem.

[0074] Optionally, the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem can be weighted and aggregated to obtain a target resource allocation scheme, and then the resource allocation ratio corresponding to each hardware module in the tag can be determined according to the target resource allocation scheme.

[0075] Alternatively, the objective function for radio frequency identification tag resource allocation can also be determined according to the first sub-objective function and the second sub-objective function, and then the objective function values can be determined respectively according to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem. The initial resource allocation scheme corresponding to the maximum objective function value is determined as the target resource allocation scheme, and then the resource allocation ratio corresponding to each hardware module in the tag is determined according to the target resource allocation scheme.

[0076] Exemplarily, the first sub-objective function and the second sub-objective function can be aggregated into the objective function for radio frequency identification tag resource allocation based on weighted aggregation or Chebyshev aggregation method.

[0077] In the embodiments of the present application, according to the first sub-problem corresponding to the first sub-objective function and the second sub-problem corresponding to the second sub-objective function, the neighborhood of the target sub-problem is determined. Within the neighborhood, the sub-objective function corresponding to the target sub-problem is solved to obtain an initial resource allocation scheme corresponding to the target sub-problem. According to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem, the resource allocation ratio corresponding to each hardware module in the tag is determined. Thus, when solving the sub-objective function corresponding to the target sub-problem, referring to the solutions within the neighborhood can accelerate convergence, reduce the computational complexity, and improve the robustness of the solution of the sub-objective function at the same time. And determining the target resource allocation scheme based on the optimal solutions of the two sub-objective functions can further improve the accuracy of resource allocation.

[0078] Refer to Figure 4 , Figure 4It is a schematic flow chart of a method for determining an initial resource allocation scheme provided by an embodiment of the present application. This embodiment relates to a possible implementation manner of how to solve a sub-objective function corresponding to a target sub-problem within a neighborhood to obtain an initial resource allocation scheme corresponding to the target sub-problem. Based on the above embodiment, the above S302 includes the following steps:

[0079] S401, within the neighborhood, determine an intermediate solution of the sub-objective function based on the crossover operation and the mutation operation.

[0080] In one embodiment, an initial solution (i.e., the parent solution) can be randomly selected within the domain of the target sub-problem, and then the initial solution of the target sub-problem is continuously updated based on the crossover operation and the mutation operation in the genetic algorithm until the termination condition is satisfied, and the solution obtained by the last update is determined as the intermediate solution of the sub-objective function.

[0081] Exemplarily, the termination condition may include that the solution of the sub-objective function converges or reaches the maximum number of iterations, and the above termination condition can be expressed as the following formula (5):

[0082] (5)

[0083] In formula (5), is the allowable error range, is the maximum number of iterations.

[0084] S402, update the intermediate solution based on the gradient descent method to obtain an initial resource allocation scheme corresponding to the target sub-problem.

[0085] Exemplarily, assume that the intermediate solution of the target sub-problem is , then the intermediate solution can be continuously updated based on the gradient descent method until the termination condition is satisfied, and the solution obtained by the last update is determined as the target solution of the target sub-problem, and then the target solution of the target sub-problem is determined as the initial resource allocation scheme corresponding to the target sub-problem.

[0086] Optionally, the process of updating the intermediate solution based on the gradient descent method can be expressed as the following formula (6):

[0087] (6)

[0088] In formula (6), is the step size, is the gradient of the target sub-function .

[0089] Based on the above formula (6), if the target sub-function is the first sub-objective function, the intermediate solution of the first sub-objective function can be updated based on the following formula (7):

[0090] (7)

[0091] Alternatively, if the target sub-function is the second sub-objective function, the intermediate solution of the second sub-objective function can be updated based on the following formula (8):

[0092] (8)

[0093] In the embodiments of the present application, within the neighborhood, based on the crossover operation and the mutation operation, the intermediate solution of the sub-objective function is determined, and the intermediate solution is updated based on the gradient descent method to obtain the initial resource allocation scheme corresponding to the target sub-problem, so that the intermediate solution can be further optimized based on the gradient descent method, further improving the accuracy of the optimal solution of the target sub-function, and further improving the accuracy of the initial resource allocation scheme.

[0094] Referring to Figure 5 , Figure 5 is a schematic flowchart of a method for determining an intermediate solution provided by an embodiment of the present application. This embodiment relates to a possible implementation manner of how to determine the intermediate solution of the sub-objective function based on the crossover operation and the mutation operation within the neighborhood. Based on the above embodiment, the above S401 includes the following steps:

[0095] S501, randomly determine the initial solution of the sub-objective function from the neighborhood.

[0096] Optionally, any solution within the domain can be determined as the initial solution of the sub-objective function.

[0097] S502, update the initial solution based on the crossover operation and the mutation operation to obtain the intermediate solution of the sub-objective function.

[0098] In one embodiment, based on the crossover operation and the mutation operation in the genetic algorithm, the initial solution of the target sub-problem is continuously updated until the termination condition is met, and the solution obtained by the last update is determined as the intermediate solution of the sub-objective function.

[0099] Exemplarily, the process of updating the initial solution based on the crossover operation and the mutation operation can be represented by the following formula (9):

[0100] (9)

[0101] In formula (9), and are adjustment factors used to determine the amplitude of individual update.

[0102] Optionally, the crossover operation may include, for example, simulated binary crossover (SBX) or uniform crossover (UX), etc.

[0103] In one embodiment, the mutation operation may be, for example, a random mutation operation based on a Gaussian distribution. The random mutation operation based on a Gaussian distribution can be expressed by the following formula (10):

[0104] (10)

[0105] In formula (10), is the mutation amplitude, is the standard normal distribution.

[0106] In the embodiments of the present application, the initial solution of the sub-objective function is randomly determined from the neighborhood, and the initial solution is updated based on the crossover operation and the mutation operation to obtain the intermediate solution of the sub-objective function, which improves the calculation efficiency and accuracy of the intermediate solution, and further improves the accuracy of label resource allocation.

[0107] Referring to Figure 6 , Figure 6 is a schematic flowchart of another method for determining the resource allocation ratio provided by the embodiments of the present application. This embodiment relates to a possible implementation manner of how to determine the resource allocation ratio corresponding to each hardware module in the label according to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem. On the basis of the above embodiments, the above S303 includes the following steps:

[0108] S601, obtain the first weight corresponding to the first sub-problem and the second weight corresponding to the second sub-problem.

[0109] Optionally, the first weight corresponding to the first sub-problem and the second weight corresponding to the second sub-problem preset can be obtained.

[0110] Alternatively, the historical resource allocation data can be analyzed, and the first weight corresponding to the first sub-problem and the second weight corresponding to the second sub-problem are determined based on the historical resource allocation data.

[0111] S602, perform weighted aggregation on the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem based on the first weight and the second weight to obtain the target resource allocation scheme.

[0112] In one embodiment, the initial resource allocation scheme corresponding to the first sub-problem can be weighted based on the first weight to obtain the first intermediate resource allocation scheme, and the initial resource allocation scheme corresponding to the second sub-problem can be weighted based on the second weight to obtain the second intermediate resource allocation scheme, and then the first intermediate resource allocation scheme and the second intermediate resource allocation scheme are aggregated to obtain the target resource allocation scheme.

[0113] S603. Determine the resource allocation ratio corresponding to each hardware module in the tag according to the target resource allocation scheme.

[0114] Optionally, the resource allocation ratio corresponding to each hardware module in the target resource allocation scheme can be determined as the resource allocation ratio corresponding to each hardware module in the above tag.

[0115] In the embodiment of the present application, the first weight corresponding to the first sub-problem and the second weight corresponding to the second sub-problem are obtained, and the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem are weighted and aggregated based on the first weight and the second weight to obtain the target resource allocation scheme, and the resource allocation ratio corresponding to each hardware module in the tag is determined according to the target resource allocation scheme, so as to be able to aggregate the optimal solutions of each sub-objective function to obtain the final resource allocation ratio, while simplifying the calculation process of resource allocation and improving the accuracy of resource allocation.

[0116] Refer to Figure 7 , Figure 7 is a schematic flow chart of a resource allocation method for a multi-modal perception tag provided by an embodiment of the present application. The method includes the following steps:

[0117] S701. Based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the service life of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, construct a first sub-objective function.

[0118] S702. Based on the relationship between the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, construct a second sub-objective function.

[0119] S703. Determine the second sub-problem as the neighborhood of the first sub-problem, and determine the first sub-problem as the neighborhood of the second sub-problem.

[0120] S704. Randomly determine the initial solution of the sub-objective function from the neighborhood, and update the initial solution based on the crossover operation and the mutation operation to obtain the intermediate solution of the sub-objective function.

[0121] S705. Update the intermediate solution based on the gradient descent method to obtain the initial resource allocation scheme corresponding to the target sub-problem.

[0122] S706. Determine the resource allocation ratio corresponding to each hardware module in the tag according to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem.

[0123] It should be understood that although the steps in the flowcharts involved in the above-described embodiments are sequentially shown according to the indication of the arrows, these steps are not necessarily executed sequentially in the order indicated by the arrows. Unless there is a clear indication in this article, the execution of these steps has no strict order limit, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above-described embodiments may include multiple steps or multiple stages. These steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be executed alternately or alternately with at least a part of other steps or steps or stages in other steps.

[0124] Based on the same inventive concept, the embodiments of the present application also provide a resource allocation device for a radio frequency identification tag for implementing the resource allocation method of the radio frequency identification tag involved above. The solution provided by this device to solve the problem is similar to the solution described in the above method. Therefore, the specific limitations in one or more embodiments of the resource allocation device for the radio frequency identification tag provided below can refer to the limitations on the resource allocation method of the radio frequency identification tag in the above text, and will not be repeated here.

[0125] In one embodiment, as Figure 8 shown, Figure 8 is a structural block diagram of a resource allocation device for a radio frequency identification tag provided by an embodiment of the present application. The device 800 includes:

[0126] A first construction module 801, configured to construct a first sub-objective function based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the life of the tag, and the resource allocation ratio corresponding to each hardware module in the tag.

[0127] A second construction module 802, configured to construct a second sub-objective function based on the relationship between the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratio corresponding to each hardware module in the tag.

[0128] A solving module 803, configured to solve the first sub-objective function and the second sub-objective function with the goal of maximizing the life and working efficiency of the tag, so as to obtain the resource allocation ratio corresponding to each hardware module in the tag.

[0129] In one of the embodiments, the solving module 803 includes:

[0130] A first determination unit, configured to determine a neighborhood of a target sub-problem according to a first sub-problem corresponding to a first sub-objective function and a second sub-problem corresponding to a second sub-objective function; the target sub-problem is any one of the first sub-problem and the second sub-problem.

[0131] A solution unit, configured to solve a sub-objective function corresponding to the target sub-problem within the neighborhood to obtain an initial resource allocation scheme corresponding to the target sub-problem.

[0132] A second determination unit, configured to determine a resource allocation ratio corresponding to each hardware module in the label according to an initial resource allocation scheme corresponding to the first sub-problem and an initial resource allocation scheme corresponding to the second sub-problem.

[0133] In one embodiment, the solution unit includes:

[0134] A first determination subunit, configured to determine an intermediate solution of the sub-objective function within the neighborhood based on a crossover operation and a mutation operation;

[0135] An update subunit, configured to update the intermediate solution based on the gradient descent method to obtain an initial resource allocation scheme corresponding to the target sub-problem.

[0136] In one embodiment, the first determination subunit is specifically configured to randomly determine an initial solution of the sub-objective function within the neighborhood; update the initial solution based on a crossover operation and a mutation operation to obtain an intermediate solution of the sub-objective function.

[0137] In one embodiment, the second determination unit includes:

[0138] An acquisition subunit, configured to acquire a first weight corresponding to the first sub-problem and a second weight corresponding to the second sub-problem;

[0139] A weighted aggregation subunit, configured to perform weighted aggregation on an initial resource allocation scheme corresponding to the first sub-problem and an initial resource allocation scheme corresponding to the second sub-problem based on the first weight and the second weight to obtain a target resource allocation scheme;

[0140] A second determination subunit, configured to determine a resource allocation ratio corresponding to each hardware module in the label according to the target resource allocation scheme.

[0141] In one embodiment, the first determination unit includes:

[0142] A third determination subunit, configured to, if the target sub-problem is the first sub-problem, determine the second sub-problem as the neighborhood of the target sub-problem.

[0143] A fourth determination subunit, configured to, if the target sub-problem is the second sub-problem, determine the first sub-problem as the neighborhood of the target sub-problem.

[0144] Each module in the above resource allocation device of the radio frequency identification tag can be implemented in whole or in part by software, hardware, and their combination. Each of the above modules can be embedded in or independent of the processor in the computer device in the form of hardware, or stored in the memory in the computer device in the form of software, so that the processor can call and execute the operations corresponding to each of the above modules.

[0145] In one embodiment, a computer device is provided, including a memory and a processor. A computer program is stored in the memory. When the processor executes the computer program, the following steps are implemented:

[0146] Based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the life of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, a first sub-objective function is constructed;

[0147] Based on the relationship between the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, a second sub-objective function is constructed;

[0148] With the goal of maximizing the life and working efficiency of the tag, solve the first sub-objective function and the second sub-objective function to obtain the resource allocation ratio corresponding to each hardware module in the tag.

[0149] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0150] According to the first sub-problem corresponding to the first sub-objective function and the second sub-problem corresponding to the second sub-objective function, determine the neighborhood of the target sub-problem; the target sub-problem is any one of the first sub-problem and the second sub-problem;

[0151] In the neighborhood, solve the sub-objective function corresponding to the target sub-problem to obtain the initial resource allocation scheme corresponding to the target sub-problem;

[0152] According to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem, determine the resource allocation ratio corresponding to each hardware module in the tag.

[0153] In one embodiment, when the processor executes the computer program, the following steps are also implemented:

[0154] In the neighborhood, based on the crossover operation and the mutation operation, determine the intermediate solution of the sub-objective function;

[0155] Based on the gradient descent method, update the intermediate solution to obtain the initial resource allocation scheme corresponding to the target sub-problem.

[0156] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0157] Randomly determine an initial solution of the sub-objective function from the neighborhood;

[0158] Update the initial solution based on the crossover operation and the mutation operation to obtain an intermediate solution of the sub-objective function.

[0159] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0160] Obtain the first weight corresponding to the first sub-problem and the second weight corresponding to the second sub-problem;

[0161] Perform weighted aggregation on the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem based on the first weight and the second weight to obtain the target resource allocation scheme;

[0162] Determine the resource allocation ratio corresponding to each hardware module in the tag according to the target resource allocation scheme.

[0163] In one embodiment, when the processor executes the computer program, the following steps are further implemented:

[0164] If the target sub-problem is the first sub-problem, then determine the second sub-problem as the neighborhood of the target sub-problem;

[0165] If the target sub-problem is the second sub-problem, then determine the first sub-problem as the neighborhood of the target sub-problem.

[0166] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0167] Based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the life of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, construct a first sub-objective function;

[0168] Based on the relationship between the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, construct a second sub-objective function;

[0169] With the goal of maximizing the life and working efficiency of the tag, solve the first sub-objective function and the second sub-objective function to obtain the resource allocation ratio corresponding to each hardware module in the tag.

[0170] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0171] Determine the neighborhood of the target sub-problem according to the first sub-problem corresponding to the first sub-objective function and the second sub-problem corresponding to the second sub-objective function; the target sub-problem is any one of the first sub-problem and the second sub-problem;

[0172] Within the neighborhood, solve the sub-objective function corresponding to the target sub-problem to obtain the initial resource allocation scheme corresponding to the target sub-problem;

[0173] Determine the resource allocation ratio corresponding to each hardware module in the label according to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem.

[0174] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0175] Within the neighborhood, determine the intermediate solution of the sub-objective function based on the crossover operation and the mutation operation;

[0176] Update the intermediate solution based on the gradient descent method to obtain the initial resource allocation scheme corresponding to the target sub-problem.

[0177] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0178] Randomly determine the initial solution of the sub-objective function from the neighborhood;

[0179] Update the initial solution based on the crossover operation and the mutation operation to obtain the intermediate solution of the sub-objective function.

[0180] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0181] Obtain the first weight corresponding to the first sub-problem and the second weight corresponding to the second sub-problem;

[0182] Perform weighted aggregation on the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem based on the first weight and the second weight to obtain the target resource allocation scheme;

[0183] Determine the resource allocation ratio corresponding to each hardware module in the label according to the target resource allocation scheme.

[0184] In one embodiment, when the computer program is executed by a processor, the following steps are further implemented:

[0185] If the target sub-problem is the first sub-problem, then determine the second sub-problem as the neighborhood of the target sub-problem;

[0186] If the target sub-problem is the second sub-problem, then determine the first sub-problem as the neighborhood of the target sub-problem.

[0187] In one embodiment, a computer program product is provided, including a computer program which, when executed by a processor, implements the following steps:

[0188] Based on the relationship among the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the life of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, construct a first sub-objective function;

[0189] Based on the relationship among the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratio corresponding to each hardware module in the tag, construct a second sub-objective function;

[0190] With the goal of maximizing the life and working efficiency of the tag, solve the first sub-objective function and the second sub-objective function to obtain the resource allocation ratio corresponding to each hardware module in the tag.

[0191] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0192] According to the first sub-problem corresponding to the first sub-objective function and the second sub-problem corresponding to the second sub-objective function, determine the neighborhood of the target sub-problem; the target sub-problem is any one of the first sub-problem and the second sub-problem;

[0193] Within the neighborhood, solve the sub-objective function corresponding to the target sub-problem to obtain the initial resource allocation scheme corresponding to the target sub-problem;

[0194] According to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem, determine the resource allocation ratio corresponding to each hardware module in the tag.

[0195] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0196] Within the neighborhood, based on the crossover operation and the mutation operation, determine the intermediate solution of the sub-objective function;

[0197] Based on the gradient descent method, update the intermediate solution to obtain the initial resource allocation scheme corresponding to the target sub-problem.

[0198] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0199] Randomly determine the initial solution of the sub-objective function from within the neighborhood;

[0200] Based on the crossover operation and the mutation operation, update the initial solution to obtain the intermediate solution of the sub-objective function.

[0201] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0202] Obtain the first weight corresponding to the first sub - problem and the second weight corresponding to the second sub - problem;

[0203] Based on the first weight and the second weight, perform weighted aggregation on the initial resource allocation scheme corresponding to the first sub - problem and the initial resource allocation scheme corresponding to the second sub - problem to obtain the target resource allocation scheme;

[0204] Determine the resource allocation ratio corresponding to each hardware module in the label according to the target resource allocation scheme.

[0205] In one embodiment, when the computer program is executed by the processor, the following steps are further implemented:

[0206] If the target sub - problem is the first sub - problem, then determine the second sub - problem as the neighborhood of the target sub - problem;

[0207] If the target sub - problem is the second sub - problem, then determine the first sub - problem as the neighborhood of the target sub - problem.

[0208] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memories can include read-only memory (ROM), magnetic tapes, floppy disks, flash memories, optical memories, high-density embedded non-volatile memories, resistive random access memories (ReRAM), magnetoresistive random access memories (MRAM), ferroelectric random access memories (FRAM), phase change memories (PCM), graphene memories, etc. Volatile memories can include random access memory (RAM) or external cache memories, etc. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The databases involved in the embodiments provided in the present application can include at least one of relational databases and non-relational databases. Non-relational databases can include distributed databases based on blockchain, etc., without limitation. The processors involved in the embodiments provided in the present application can be general-purpose processors, central processors, graphics processors, digital signal processors, programmable logic devices, data processing logics based on quantum computing, etc., without limitation.

[0209] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity of description, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, it should be considered as the scope described in this specification.

[0210] The above-described embodiments only represent several implementation manners of the present application. Their descriptions are relatively specific and detailed, but they should not be construed as limiting the patent scope of the present application. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present application, several modifications and improvements can still be made, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

Claims

1. A resource allocation method for a radio frequency identification tag, characterized in that, The method includes: Construct a first sub-objective function based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the lifespan of the tag, and the resource allocation ratio corresponding to each hardware module in the tag; Construct a second sub-objective function based on the relationship between the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratio corresponding to each hardware module in the tag; With the goal of maximizing the lifespan and working efficiency of the tag, solve the first sub-objective function and the second sub-objective function to obtain the resource allocation ratio corresponding to each hardware module in the tag.

2. The method according to claim 1, wherein The step of solving the first sub-objective function and the second sub-objective function with the goal of maximizing the lifespan and working efficiency of the tag to obtain the resource allocation ratio corresponding to each hardware module in the tag includes: Determine the neighborhood of the target sub-problem according to the first sub-problem corresponding to the first sub-objective function and the second sub-problem corresponding to the second sub-objective function; the target sub-problem is any one of the first sub-problem and the second sub-problem; Solve the sub-objective function corresponding to the target sub-problem within the neighborhood to obtain the initial resource allocation scheme corresponding to the target sub-problem; Determine the resource allocation ratio corresponding to each hardware module in the tag according to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem.

3. The method according to claim 2, characterized in that, The step of solving the sub-objective function corresponding to the target sub-problem within the neighborhood to obtain the initial resource allocation scheme corresponding to the target sub-problem includes: Within the neighborhood, determine the intermediate solution of the sub-objective function based on the crossover operation and the mutation operation; Update the intermediate solution based on the gradient descent method to obtain the initial resource allocation scheme corresponding to the target sub-problem.

4. The method according to claim 2, wherein The step of determining the intermediate solution of the sub-objective function based on the crossover operation and the mutation operation within the neighborhood: Randomly determine the initial solution of the sub-objective function from within the neighborhood; Update the initial solution based on the crossover operation and the mutation operation to obtain the intermediate solution of the sub-objective function.

5. The method according to any one of claims 2 to 4, characterized in that, The step of determining the resource allocation ratio corresponding to each hardware module in the tag according to the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem includes: Obtain the first weight corresponding to the first sub-problem and the second weight corresponding to the second sub-problem; Perform weighted aggregation on the initial resource allocation scheme corresponding to the first sub-problem and the initial resource allocation scheme corresponding to the second sub-problem based on the first weight and the second weight to obtain the target resource allocation scheme; Determine the resource allocation ratio corresponding to each hardware module in the tag according to the target resource allocation scheme.

6. The method according to any one of claims 2-4, characterized in that, The step of determining the neighborhood of the target sub-problem according to the first sub-problem corresponding to the first sub-objective function and the second sub-problem corresponding to the second sub-objective function: If the target sub-problem is the first sub-problem, then determine the second sub-problem as the neighborhood of the target sub-problem; If the target sub-problem is the second sub-problem, then determine the first sub-problem as the neighborhood of the target sub-problem.

7. A resource allocation device for a radio frequency identification tag, characterized in that, The device includes: A first construction module, configured to construct a first sub-objective function based on the relationship between the power consumption of each hardware module in the radio frequency identification system, the battery capacity of the tag in the radio frequency identification system, the lifespan of the tag, and the resource allocation ratio corresponding to each hardware module in the tag; A second construction module, configured to construct a second sub-objective function based on the relationship between the task requirements of each hardware module, the working efficiency of the tag, and the resource allocation ratio corresponding to each hardware module in the tag; A solving module, configured to solve the first sub-objective function and the second sub-objective function with the goal of maximizing the lifespan and working efficiency of the tag, so as to obtain the resource allocation ratio corresponding to each hardware module in the tag.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When this computer program is executed by the processor, it implements the steps of the method according to any one of claims 1 to 6.

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