Replaceable target execution body determination method and device and storage medium

Abstract

The invention provides a replaceable target execution main body determination method and device and a storage medium, and relates to the field of target execution main body determination, the method comprises the following steps: determining at least one specified execution main body according to a target task and a current execution main body; the execution requirement of the target task is proposed by the current execution main body; the target task is a sign detection task; determining at least one target execution main body from the plurality of specified execution main bodies according to at least one of waiting duration of executing the target task by each specified execution main body, a distance between the current execution main body and each specified execution main body and a resource consumption value of executing the target task by each specified execution main body; through the method provided by the invention, under the condition that the waiting time for executing the target task by the current execution main body is relatively long, the optimal specified execution main body can be determined from the plurality of specified execution main bodies corresponding to the current execution main body to execute the target task.

Description

Technical Field

[0001] The present invention relates to the technical field of target execution subject determination, and in particular to a replaceable target execution subject determination method, device and storage medium. Background Art

[0002] In the medical field, different medical institutions have corresponding different levels. The medical level of higher-level medical institutions is relatively high, and users are more willing to choose higher-level medical institutions for medical treatment. When users go to the hospital for treatment, they usually need to undergo a series of examinations. However, the examination equipment of higher-level medical institutions is limited. When more users make appointments with the same higher-level medical institution, the waiting time for the examination will be longer and the medical treatment efficiency will be lower. Usually, higher-level medical institutions will preset several medical institutions whose examination results are mutually trustworthy. How to determine the best medical institution from several medical institutions whose examination results are mutually trustworthy has become a technical problem that needs to be solved urgently. Summary of the invention

[0003] In view of the above technical problems, the technical solution adopted by the present invention is:

[0004] According to a first aspect of the present application, an alternative method for determining a target execution subject is provided, the method comprising the following steps:

[0005] S100, determining at least one designated execution subject according to the target task and the current execution subject; wherein the designated execution subject is another execution subject whose execution result of the target task is recognized by the current execution subject; the execution requirement of the target task is proposed by the current execution subject; the target task is a vital sign detection task;

[0006] S200, determining at least one target execution subject from a plurality of designated execution subjects according to at least one of the waiting time for each designated execution subject to execute the target task, the distance between the current execution subject and each designated execution subject, and the resource consumption value for each designated execution subject to execute the target task.

[0007] Further, obtaining the label of each designated execution subject corresponding to the current execution subject includes the following steps:

[0008] S110, obtaining target graph data corresponding to the current execution subject; wherein the target graph data includes a number of nodes and edges connecting the nodes; each node corresponds to an execution subject, and the execution subjects corresponding to the nodes connected by the edges mutually recognize the execution results of the target task; the execution subjects corresponding to the nodes in the target graph data include the current execution subject and the designated execution subject;

[0009] S120, determining the execution subjects corresponding to other nodes connected to the node corresponding to the current execution subject in the target graph data as the designated execution subjects.

[0010] Furthermore, each edge in the target graph data corresponds to a weight, and the weight corresponding to the edge is used to characterize the distance between the execution entities corresponding to the nodes connected by the edge; each node is preset with the original resource consumption value corresponding to the execution of different tasks.

[0011] Further, step S200 includes the following steps:

[0012] S210, obtaining the waiting time for each designated execution subject to execute the target task, so as to obtain a waiting time list T corresponding to each designated execution subject = (T1, T2, ..., T i ,…,T n ), i = 1, 2, ..., n; where T i The waiting time for the i-th specified node to execute the target task, where n is the number of specified nodes;

[0013] S220, obtaining the weight of the edge connecting each designated node and the target node in the graph data, so as to obtain a weight list A corresponding to the designated node = (A1, A2, ..., A i , …, A n ), where A i is the weight corresponding to the i-th specified node;

[0014] S230, according to the original resource consumption values ​​corresponding to each node executing different tasks, determine the original resource consumption value corresponding to each designated node executing the target task, so as to obtain a list of original resource consumption values ​​corresponding to the designated node B = (B1, B2, ..., B i , …, B n ), where B i The original resource consumption value corresponding to the target task executed by the i-th specified execution subject;

[0015] S240: According to T, A and B, at least one target execution subject is determined from a number of designated execution subjects.

[0016] Further, step S240 includes the following steps:

[0017] S241, according to T, A and B, determine the priority corresponding to each designated execution subject to obtain a priority list λ=(λ1, λ2, ..., λ i , …, λ n ), where λ i The priority corresponding to the i-th specified execution subject;

[0018] S242: Determine a designated execution subject whose priority meets a preset condition as a target execution subject.

[0019] Furthermore, i Determine by following these steps:

[0020] S21, if the i-th designated execution subject has a preset attribute, then λ i =α1×(1-T i / MAX(T))+α2×(1-A i / MAX(A))+α3×(1-B i / MAX(B)); α1 is the first preset coefficient, α2 is the second preset coefficient, and α3 is the third preset coefficient; α1+α2+α3=1; MAX() is the preset maximum value function; the preset attribute is used to adjust the original resource consumption value;

[0021] S22, if the i-th designated execution subject does not have a preset attribute, then λ i =α4×(1-T i / MAX(T))+α5×(1-A i / MAX(A))+α6×(1-B i / MAX(B)); α4 is the fourth preset coefficient, α5 is the fifth preset coefficient, and α6 is the sixth preset coefficient; α4+α5+α6=1; α3>α6.

[0022] Furthermore, i Determine by following these steps:

[0023] S23, obtain the current time t now ;

[0024] S24, according to t now and the preset time and traffic congestion coefficient mapping table QT, determine t now The corresponding traffic congestion coefficient ω now ; Among them, QT includes several rows, each row corresponds to a time period and a traffic congestion coefficient; the traffic congestion coefficient is negatively correlated with the degree of road traffic congestion;

[0025] S25, if the i-th designated execution subject has a preset attribute, then λ i =α1×(1-T i / MAX(T))+ω now ×α2×(1-A i / MAX(A))+α3×(1-B i / MAX(B)); where α1 is the first preset coefficient, α2 is the second preset coefficient, and α3 is the third preset coefficient; α1+ω now×α2+α3=1; MAX() is the preset maximum value function;

[0026] S26, if the i-th designated execution subject does not have a preset attribute, then i =α4×(1-T i / MAX(T))+ω now ×α5×(1-A i / MAX(A))+α6×(1-B i / MAX(B)); α4 is the fourth preset coefficient, α5 is the fifth preset coefficient, and α6 is the sixth preset coefficient; α4+ω now ×α5+α6=1;α3>α6.

[0027] Furthermore, 0<ω now <1.

[0028] According to another aspect of the present application, a non-transitory computer-readable storage medium is also provided, in which at least one instruction or at least one program is stored, and the at least one instruction or at least one program is loaded and executed by a processor to implement the above-mentioned alternative target execution subject determination method.

[0029] According to another aspect of the present application, an electronic device is provided, including a processor and the above-mentioned non-transitory computer-readable storage medium.

[0030] The present invention has at least the following beneficial effects:

[0031] The alternative target execution subject determination method of the present invention determines at least one designated execution subject according to the target task and the current execution subject; wherein the designated execution subject is another execution subject whose execution result of the target task is recognized by the current execution subject; the execution requirement of the target task is proposed by the current execution subject; the target task is a vital sign detection task; at least one target execution subject is determined from a plurality of designated execution subjects according to at least one of the waiting time for each designated execution subject to execute the target task, the distance between the current execution subject and each designated execution subject, and the resource consumption value for each designated execution subject to execute the target task; thereby achieving the purpose of determining the best designated execution subject from a plurality of designated execution subjects corresponding to the current execution subject to execute the target task when the waiting time for the current execution subject to execute the target task is long.

[0032] Furthermore, when determining the target execution subject from several designated execution subjects, multiple factors are comprehensively considered, including the waiting time for each designated execution subject to execute the target task, the distance between the current execution subject and each designated execution subject, and the original resource consumption value of each designated execution subject to execute the target task. This makes the determined target execution subject more ideal in terms of time and resource consumption value, and more in line with user needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] 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 description of the embodiments. 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 creative work.

[0034] Figure 1 A flowchart of an alternative target execution subject determination method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0036] It should be noted that, based on the present disclosure, those skilled in the art should understand that an aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement a device and / or practice a method. In addition, other structures and / or functionalities other than one or more of the aspects described herein can be used to implement this device and / or practice this method.

[0037] The following will refer to Figure 1 The flowchart of the alternative target execution subject determination method shown introduces an alternative target execution subject determination method.

[0038] The alternative target execution subject determination method may include the following steps:

[0039] S100, determining at least one designated execution subject according to the target task and the current execution subject; wherein the designated execution subject is another execution subject whose execution result of the target task is recognized by the current execution subject; the execution requirement of the target task is proposed by the current execution subject; the target task is a vital sign detection task.

[0040] In this embodiment, the target task may be a physical sign detection task performed by the user in a medical institution, such as a CT scan, color Doppler ultrasound scan, etc. performed by the user; the current executing entity may be the medical institution where the target user is currently located; the label of the current executing entity may be the name corresponding to the current executing entity.

[0041] It is understandable that there may be several other users queuing up to perform the target task in the current execution entity where the target user is located, and the target user may need to wait for a long time to perform the target task in the current execution entity; it should be noted that the current execution entity, that is, the current medical institution where the user is located, will have several designated execution entities preset, and the pointing execution entity can be understood as other execution entities whose execution results of the target task are mutually recognized by the current execution entity, that is, other medical institutions; for example: Medical Institution 1 is the current execution entity, and Medical Institution 2 is a corresponding designated execution entity, and Medical Institution 1 and Medical Institution 2 mutually recognize the CT examination results; if the waiting time for the current execution entity to perform the target task is long, the user can input the labels of the target task and the current execution entity into the relevant equipment, and the relevant equipment will further obtain each designated execution entity corresponding to the current execution entity.

[0042] In some embodiments, obtaining the label of each designated execution subject corresponding to the current execution subject includes the following steps:

[0043] S110, obtain the target graph data corresponding to the current execution subject; wherein the target graph data includes a number of nodes and edges connecting the nodes; each node corresponds to an execution subject, and the execution subjects corresponding to the nodes connected by the edges mutually recognize the execution results of the target task; the execution subjects corresponding to the nodes in the target graph data include the current execution subject and the designated execution subject.

[0044] In this embodiment, the target graph data may be graph data corresponding to the target area, and the target area may be any urban area. All execution entities within the target area may be regarded as nodes, and the execution entities that mutually recognize the execution results of the target tasks may be connected through edges, thereby obtaining the target graph data corresponding to the current execution entity.

[0045] S120, determining the execution subjects corresponding to other nodes connected to the node corresponding to the current execution subject in the target graph data as the designated execution subjects.

[0046] In this embodiment, the node corresponding to the label of the current execution subject can be determined in the target graph data, and then each other node is traversed. If any other node is connected to the node corresponding to the label of the current execution subject through an edge, the execution subject corresponding to the node is determined as the designated execution subject.

[0047] S200, determining at least one target execution subject from a plurality of designated execution subjects according to at least one of the waiting time for each designated execution subject to execute the target task, the distance between the current execution subject and each designated execution subject, and the resource consumption value for each designated execution subject to execute the target task.

[0048] In some embodiments, each edge in the target graph data corresponds to a weight, and the weight corresponding to the edge is used to characterize the distance between the execution entities corresponding to the nodes connected by the edge; each node is preset with a resource consumption value corresponding to executing different tasks.

[0049] In this embodiment, the distance between any two execution entities is known data, and the distance between the two execution entities can be used as the weight of the edge connecting the nodes corresponding to the two execution entities; the resource consumption values ​​corresponding to executing different tasks can be understood as the prices or other resources corresponding to executing different vital sign detection tasks, such as medical insurance or self-funded resources.

[0050] In some embodiments, step S200 includes the following steps:

[0051] S210, obtaining the waiting time for each designated execution subject to execute the target task, so as to obtain a waiting time list T corresponding to each designated execution subject = (T1, T2, ..., T i ,…,T n ), i = 1, 2, ..., n; where T i The waiting time for the i-th specified node to execute the target task, where n is the number of specified nodes.

[0052] In this embodiment, for any designated execution subject, the waiting time for the designated execution subject to execute the target task can be obtained through the reservation system of the designated execution subject, thereby obtaining T.

[0053] S220, obtaining the weight of the edge connecting each designated node and the target node in the graph data, so as to obtain a weight list A corresponding to the designated node = (A1, A2, ..., A i , …, A n ), where A i is the weight corresponding to the i-th specified node.

[0054] In this embodiment, the weight of each edge connecting each designated node and the target node in the graph data can be obtained, thereby obtaining A.

[0055] S230, according to the original resource consumption values ​​corresponding to each node executing different tasks, determine the original resource consumption value corresponding to each designated node executing the target task, so as to obtain a list of original resource consumption values ​​corresponding to the designated node B = (B1, B2, ..., B i , …, B n ), where B i The original resource consumption value corresponding to the target task executed by the i-th specified execution entity.

[0056] In this embodiment, the original resource consumption values ​​of the execution subject corresponding to each node in the graph data for executing different tasks are different. For example, the price of a medical institution corresponding to a certain execution subject for executing a CT examination is different from the price of a color Doppler ultrasound. The original resource consumption values ​​of the execution subject corresponding to each node for executing different tasks can be listed in an exhaustive manner, and then the original resource consumption value corresponding to each specified execution subject executing the target task can be determined to obtain B.

[0057] S240: According to T, A and B, at least one target execution subject is determined from a number of designated execution subjects.

[0058] In some embodiments, step S240 may include the following steps:

[0059] S241, according to T, A and B, determine the priority corresponding to each designated execution subject to obtain a priority list λ=(λ1, λ2, ..., λ i , …, λ n ), where λ i The priority corresponding to the i-th specified execution entity.

[0060] In some embodiments, i This can be determined by the following steps:

[0061] S21, if the i-th designated execution subject has a preset attribute, then λ i =α1×(1-T i / MAX(T))+α2×(1-A i / MAX(A))+α3×(1-B i / MAX(B)); α1 is the first preset coefficient, α2 is the second preset coefficient, and α3 is the third preset coefficient; α1+α2+α3=1; MAX() is the preset maximum value function; the preset attributes are used to adjust the original resource consumption value.

[0062] In this embodiment, the existence of preset attributes for the i-th designated execution subject can be understood as the i-th designated execution subject can use medical insurance, and the coefficients corresponding to using medical insurance and not being able to use medical insurance are different; the waiting time for each designated execution subject to execute the target task can be obtained through the real-time queuing information of the medical institution.

[0063] S22, if the i-th designated execution subject does not have a preset attribute, then λ i =α4×(1-T i / MAX(T))+α5×(1-A i / MAX(A))+α6×(1-B i / MAX(B)); α4 is the fourth preset coefficient, α5 is the fifth preset coefficient, and α6 is the sixth preset coefficient; α4+α5+α6=1; α3>α6.

[0064] In this embodiment, the absence of preset attributes for the i-th designated execution subject can be understood as the i-th designated execution subject cannot use medical insurance.

[0065] In this embodiment, if the i-th designated execution subject has a preset attribute, that is, if the i-th designated execution subject can use medical insurance when executing the target task, its corresponding original resource consumption value will be further reduced, and the calculation weight of the resource consumption value should be increased; therefore, the third preset coefficient corresponding to the resource consumption value is greater than the sixth preset coefficient; if the i-th designated execution subject has a preset attribute, then λ i In terms of i , A i and B i The larger the value is, the longer the waiting time, distance and resource consumption are. Therefore, the priority corresponding to the i-th designated execution subject is lower; thus, it is more in line with the logic and habit of users to select designated execution subjects.

[0066] In some embodiments, i It is also determined by the following steps:

[0067] S23, obtain the current time t now .

[0068] S24, according to t now and the preset time and traffic congestion coefficient mapping table QT, determine t now The corresponding traffic congestion coefficient ω now ; Among them, QT includes several rows, each row corresponds to a time period and a traffic congestion coefficient; the traffic congestion coefficient is negatively correlated with the degree of road traffic congestion.

[0069] In this embodiment, it can be understood that the traffic congestion conditions in the target area are different at different dates and time periods. For example, during the working and off-get off work time periods on weekdays, the traffic is relatively congested, while during the non-working and off-get off work time periods on weekdays, the traffic is relatively smooth. Holidays are another type of traffic congestion situation. By statistically analyzing a large amount of historical data, a preset time and traffic congestion coefficient mapping table QT can be obtained. QT records several time periods and corresponding traffic congestion coefficients. The more congested the time period, the smaller the corresponding traffic congestion coefficient. 0<ω now <1.

[0070] S25, if the i-th designated execution subject has a preset attribute, then λ i =α1×(1-T i / MAX(T))+ω now ×α2×(1-A i / MAX(A))+α3×(1-B i / MAX(B)); where α1 is the first preset coefficient, α2 is the second preset coefficient, and α3 is the third preset coefficient; α1+ω now ×α2+α3=1; MAX() is the preset maximum value function.

[0071] S26, if the i-th designated execution subject does not have a preset attribute, then i =α4×(1-T i / MAX(T))+ω now ×α5×(1-A i / MAX(A))+α6×(1-B i / MAX(B)); α4 is the fourth preset coefficient, α5 is the fifth preset coefficient, and α6 is the sixth preset coefficient; α4+ω now ×α5+α6=1;α3>α6.

[0072] In this embodiment, it can be understood that the traffic congestion conditions in the target area are different at different dates and time periods. For example, during the working and off-get off work time periods on weekdays, the traffic is relatively congested, while during the non-working and off-get off work time periods on weekdays, the traffic is relatively smooth. Holidays are another type of traffic congestion situation. By statistically analyzing a large amount of historical data, a preset time and traffic congestion coefficient mapping table QT can be obtained. QT records several time periods and corresponding traffic congestion coefficients. The more congested the time period, the smaller the corresponding traffic congestion coefficient. 0<ω now <1.

[0073] In this embodiment, according to the current time t now And the preset time and traffic congestion coefficient mapping table QT, determine t nowThe corresponding traffic congestion coefficient ω now ;ω now It will affect the time taken from the current execution subject to the designated execution subject, and the time taken from the current execution subject to the designated execution subject is also related to the distance between the current execution subject and the designated execution subject. Therefore, ω now By multiplying the distance term, the weight of the distance term has been adjusted, and in combination with the current traffic congestion level, a target execution entity that can replace the current execution entity is determined, making the determined target execution entity more reasonable.

[0074] S242: Determine a designated execution subject whose priority meets a preset condition as a target execution subject.

[0075] In some embodiments, a designated execution subject with the highest priority may be determined as a target execution subject that can replace the current execution subject.

[0076] In this embodiment, the distance between the designated execution subject with the highest priority and the current execution subject, the waiting time and the resource consumption value are optimal in comprehensive consideration. Therefore, the designated execution subject with the highest priority is determined as the target execution subject that can replace the current execution subject.

[0077] In some embodiments, the first several designated execution entities with the highest priority may also be determined as target execution entities that can replace the current execution entity, and then the user can make a selection based on his or her own situation.

[0078] In some embodiments, the designated execution subject which is closest to the current execution subject, has the shortest waiting time for executing the target task, and has the smallest resource consumption value may also be determined as the target execution subject; the user may select according to his / her own situation.

[0079] The alternative target execution subject determination method of this embodiment obtains each designated execution subject corresponding to the current execution subject in response to obtaining the labels of the target task and the current execution subject; determines the priority corresponding to each designated execution subject according to whether each designated execution subject has a preset attribute, the waiting time for each designated execution subject to execute the target task, the distance between the current execution subject and each designated execution subject, and the original resource consumption value of each designated execution subject to execute the target task; determines the designated execution subject whose priority meets the preset conditions as the target execution subject; thereby achieving the purpose of determining the best designated execution subject from several designated execution subjects corresponding to the current execution subject to execute the target task when the waiting time for the current execution subject to execute the target task is long.

[0080] Furthermore, when determining the target execution subject from a number of designated execution subjects, multiple factors are comprehensively considered, including whether each designated execution subject has preset attributes, the waiting time for each designated execution subject to execute the target task, the distance between the current execution subject and each designated execution subject, and the original resource consumption value of each designated execution subject to execute the target task. This makes the determined target execution subject more ideal in terms of time and resource consumption value dimensions, and better meets user needs; moreover, it can make full use of the resource allocation attributes to improve resource utilization and the execution efficiency of target tasks.

[0081] In addition, although the steps of the method in the present disclosure are described in a specific order in the drawings, this does not require or imply that the steps must be performed in this specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0082] An embodiment of the present invention also provides a non-transitory computer-readable storage medium, which can be set in an electronic device to store at least one instruction or at least one program related to implementing a method in a method embodiment. The at least one instruction or the at least one program is loaded and executed by the processor to implement the method provided in the above embodiment.

[0083] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0084] Computer readable signal media may include data signals propagated in baseband or as part of a carrier wave, in which readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. Readable signal media may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0085] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the foregoing.

[0086] Program code for performing the operations of the present application may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, or interpreted languages ​​such as Python, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a separate software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0087] An embodiment of the present invention further provides an electronic device, comprising a processor and the aforementioned non-transitory computer-readable storage medium.

[0088] The electronic device is merely an example and should not bring any limitation to the functions and scope of use of the embodiments of the present application.

[0089] The electronic device is presented in the form of a general-purpose computing device. The components of the electronic device may include, but are not limited to: the at least one processor mentioned above, the at least one memory mentioned above, and a bus connecting different system components (including the memory and the processor).

[0090] The memory stores program codes, which can be executed by the processor, so that the processor executes the steps in various embodiments described in this specification.

[0091] The memory may include readable media in the form of volatile memory, such as random access memory (RAM) and / or cache memory, and may further include read only memory (ROM).

[0092] The memory may also include a program / utility having a set (at least one) of program modules, such program modules including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include an implementation of a network environment.

[0093] The bus may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus architectures.

[0094] The electronic device may also communicate with one or more external devices (e.g., keyboards, pointing devices, Bluetooth devices, mobile phones, pads, smart speakers, robots, etc.), and may also communicate with one or more devices that enable a user to interact with the electronic device, and / or communicate with any device that enables the electronic device to communicate with one or more other computing devices (e.g., routers, modems, etc.). This communication may be performed through an input / output (I / O) interface. In addition, the electronic device may also communicate with one or more networks (e.g., local area networks (LANs), wide area networks (WANs), and / or public networks, such as the Internet) through a network adapter. The network adapter communicates with other modules of the electronic device through a bus. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, etc.

[0095] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, including several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the implementation of the present disclosure.

[0096] An embodiment of the present invention further provides a computer program product, which includes program code. When the program product is run on an electronic device, the program code is used to enable the electronic device to execute the steps of the method according to various exemplary embodiments of the present invention described above in this specification.

[0097] Although some specific embodiments of the present invention have been described in detail by way of example, it should be understood by those skilled in the art that the above examples are only for illustration, not for limiting the scope of the present invention. It should also be understood by those skilled in the art that various modifications may be made to the embodiments without departing from the scope and spirit of the present invention.

Claims

1. An alternative method for determining a target execution subject, characterized in that: The following steps are involved: S100, determining at least one designated execution subject according to the target task and the current execution subject; wherein the designated execution subject is another execution subject whose execution result of the target task is recognized by the current execution subject; the execution requirement of the target task is proposed by the current execution subject; the target task is a vital sign detection task; S200, determining at least one target execution subject from a plurality of designated execution subjects according to at least one of the waiting time for each designated execution subject to execute the target task, the distance between the current execution subject and each designated execution subject, and the resource consumption value for each designated execution subject to execute the target task.

2. The method for determining an alternative target execution subject according to claim 1, characterized in that: Obtaining the label of each specified execution subject corresponding to the current execution subject includes the following steps: S110, obtaining target graph data corresponding to the current execution subject; wherein the target graph data includes a number of nodes and edges connecting the nodes; each node corresponds to an execution subject, and the execution subjects corresponding to the nodes connected by the edges mutually recognize the execution results of the target task; the execution subjects corresponding to the nodes in the target graph data include the current execution subject and the designated execution subject; S120, determining the execution subjects corresponding to other nodes connected to the node corresponding to the current execution subject in the target graph data as the designated execution subjects.

3. The method for determining an alternative target execution subject according to claim 2, characterized in that: Each edge in the target graph data corresponds to a weight, and the weight corresponding to the edge is used to characterize the distance between the execution entities corresponding to the nodes connected by the edge; each node is preset with the original resource consumption value corresponding to the execution of different tasks.

4. The method for determining an alternative target execution subject according to claim 3, characterized in that: Step S200 includes the following steps: S210, obtaining the waiting time for each designated execution subject to execute the target task, so as to obtain a waiting time list T corresponding to each designated execution subject = (T1, T2, ..., T i ,…,T n ), i = 1, 2, ..., n; where T i The waiting time for the i-th specified node to execute the target task, where n is the number of specified nodes; S220, obtaining the weight of the edge connecting each designated node and the target node in the graph data, so as to obtain a weight list A corresponding to the designated node = (A1, A2, ..., A i , …, A n ), where A i is the weight corresponding to the i-th specified node; S230, according to the original resource consumption values ​​corresponding to each node executing different tasks, determine the original resource consumption value corresponding to each designated node executing the target task, so as to obtain a list of original resource consumption values ​​corresponding to the designated node B = (B1, B2, ..., B i , …, B n ), where B i The original resource consumption value corresponding to the target task executed by the i-th specified execution subject; S240: According to T, A and B, at least one target execution subject is determined from a number of designated execution subjects.

5. The method for determining an alternative target execution subject according to claim 4, characterized in that: Step S240 includes the following steps: S241, according to T, A and B, determine the priority corresponding to each designated execution subject to obtain a priority list λ=(λ1, λ2, ..., λ i , …, λ n ), where λ i The priority corresponding to the i-th specified execution subject; S242: Determine a designated execution subject whose priority meets a preset condition as a target execution subject.

6. The method for determining an alternative target execution subject according to claim 5, characterized in that: λ i Determine by following these steps: S21, if the i-th designated execution subject has a preset attribute, then λ i =α1×(1-T i / MAX(T))+α2×(1-A i / MAX(A))+α3×(1-B i / MAX(B)); α1 is the first preset coefficient, α2 is the second preset coefficient, and α3 is the third preset coefficient; α1+α2+α3=1; MAX() is the preset maximum value function; The preset attribute is used to adjust the original resource consumption value; S22, if the i-th designated execution subject does not have a preset attribute, then λ i =α4×(1-T i / MAX(T))+α5×(1-A i / MAX(A))+α6×(1-B i / MAX(B)); α4 is the fourth preset coefficient, α5 is the fifth preset coefficient, and α6 is the sixth preset coefficient; α4+α5+α6=1; α3>α6.

7. The method for determining an alternative target execution subject according to claim 6, characterized in that: λ i Determine by following these steps: S23, obtain the current time t now ; S24, according to t now and the preset time and traffic congestion coefficient mapping table QT, determine t now The corresponding traffic congestion coefficient ω now ; Among them, QT includes several rows, each row corresponds to a time period and a traffic congestion coefficient; the traffic congestion coefficient is negatively correlated with the degree of road traffic congestion; S25, if the i-th designated execution subject has a preset attribute, then λ i =α1×(1-T i / MAX(T))+ω now ×α2×(1-A i / MAX(A))+α3×(1-B i / MAX(B)); where α1 is the first preset coefficient, α2 is the second preset coefficient, and α3 is the third preset coefficient; α1+ω now ×α2+α3=1; MAX() is the preset maximum value function; S26, if the i-th designated execution subject does not have a preset attribute, then i =α4×(1-T i / MAX(T))+ω now ×α5×(1-A i / MAX(A))+α6×(1-B i / MAX(B)); α4 is the fourth preset coefficient, α5 is the fifth preset coefficient, and α6 is the sixth preset coefficient; α4+ω now ×α5+α6=1;α3>α6.

8. The method for determining an alternative target execution subject according to claim 5, characterized in that: 0<ω now <1。 9. A non-transitory computer-readable storage medium, wherein at least one instruction or at least one program is stored in the storage medium, characterized in that: The at least one instruction or the at least one program is loaded and executed by the processor to implement the alternative target execution subject determination method as described in any one of claims 1-8.

10. An electronic device, characterized in that: The method comprises a processor and the non-transitory computer-readable storage medium of claim 9.

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