Control method, device and electronic equipment

Abstract

The present application discloses a control method, device and electronic device, and the control method includes: obtaining user information and task information corresponding to a target range; wherein the target range includes multiple sub-ranges, the user information includes at least the actual number and rated number of users corresponding to each sub-range, and the task information includes at least the number of published tasks and the number of completed tasks corresponding to each sub-range; determining a first load value based on the actual number and the rated number, and determining a second load value based on the number of published tasks and the number of completed tasks; determining a load balancing coefficient corresponding to the target range based on the first load value and the second load value; when the load balancing coefficient meets the diversion condition, determining, for each sub-range, a weight value of the task corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and the attribute information of the task corresponding to the sub-range; and performing diversion control on users based on the weight value.

Description

Technical Field

[0001] The present application relates to the field of control technology, and in particular to a control method, device and electronic equipment. Background Art

[0002] Currently, amusement parks are experiencing an increasing variety of attractions, attracting an increasing number of users. However, there are situations where a large number of users want to experience the same attraction at the same time. This leads to long queues for that attraction and can also cause other attractions in the park to be idle, resulting in low user efficiency and wasted resources. Summary of the Invention

[0003] The purpose of the embodiments of the present application is to provide a control method, device and electronic equipment.

[0004] In a first aspect, an embodiment of the present application provides a control method, including:

[0005] Obtaining user information and task information corresponding to a target range; wherein the target range includes multiple sub-ranges, the user information includes at least the actual number and the rated number of users corresponding to each sub-range, and the task information includes at least the number of tasks issued and completed for each sub-range;

[0006] determining a first load value based on the actual quantity and the rated quantity, and determining a second load value based on the published quantity and the completed quantity;

[0007] determining a load balancing coefficient corresponding to the target range based on the first load value and the second load value;

[0008] When the load balancing coefficient satisfies the diversion condition, for each sub-range, based on the actual number and rated number of users corresponding to the sub-range and attribute information of the task corresponding to the sub-range, a weight value of the task corresponding to the sub-range is determined;

[0009] Based on the weight value, the user is diverted and controlled.

[0010] In a possible implementation manner, the traffic distribution condition includes that the load balancing coefficient is greater than or equal to a first threshold value, and that the load balancing coefficient is less than the first threshold value and greater than or equal to a second threshold value;

[0011] The performing diversion control on the user based on the weight value includes:

[0012] When the load balancing coefficient is greater than or equal to a first threshold, performing diversion control on the user based on the weight value according to a first diversion strategy;

[0013] When the load balancing coefficient is less than the first threshold and greater than or equal to the second threshold, the user is diverted and controlled based on the weight value according to the second diversion strategy.

[0014] In a possible implementation, performing diversion control on users based on the weight values ​​according to the first diversion strategy includes:

[0015] For each sub-range, determining a sub-load balancing coefficient corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and the number of tasks issued and completed corresponding to the sub-range;

[0016] Determine the sub-range corresponding to the maximum sub-load balancing coefficient as the target sub-range;

[0017] From all users corresponding to the target sub-range, some users are screened out and determined as target users, so as to perform diversion control on the target users.

[0018] In a possible implementation, screening out some users from all users corresponding to the target sub-range to determine them as target users, so as to perform diversion control on the target users, includes:

[0019] For each user corresponding to the target sub-range, determining whether, among all weight values ​​corresponding to the user, there is a weight value whose difference with the weight value corresponding to the target sub-range is less than a threshold;

[0020] If so, determining that the user is the target user;

[0021] For each target user, determine a weight value having the smallest difference between all weight values ​​corresponding to the target user and the weight value corresponding to the target sub-range;

[0022] The task corresponding to the weight value having the smallest difference between the weight values ​​corresponding to the target sub-range is assigned to the target user.

[0023] In a possible implementation, performing traffic diversion control on users based on the weight values ​​according to the first diversion strategy further includes:

[0024] For each sub-range, determining a sub-load balancing coefficient corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and the number of tasks issued and completed corresponding to the sub-range;

[0025] Determine the sub-range corresponding to the maximum sub-load balancing coefficient as the target sub-range;

[0026] For each user corresponding to the target sub-range, updating the weight value corresponding to the user according to the first updating method;

[0027] Assign the task corresponding to the largest weight value among the updated weight values ​​to the user.

[0028] In a possible implementation, performing diversion control on users based on the weight value according to the second diversion strategy includes:

[0029] For each user, update the weight value corresponding to the user according to the second updating method;

[0030] Determining the assignment probability of each of the tasks based on the updated weight value;

[0031] Assign the task with the highest probability to the user.

[0032] In a possible implementation, the control method further includes:

[0033] When the load balancing coefficient does not satisfy the diversion condition, obtaining reference information of each user; wherein the reference information includes at least age, task participation, queuing behavior, and recommended behavior;

[0034] sorting users corresponding to each sub-range based on the age, the task participation, the queuing behavior, and the recommendation behavior to obtain a user queue;

[0035] Obtaining status information and / or a user request of the sub-range; wherein the status information at least includes whether the task corresponding to the sub-range is pending, in progress, or completed; and the user request indicates that the user requests to exit the user queue corresponding to the sub-range;

[0036] The user queue is updated based on the status information and / or the user request.

[0037] In a possible implementation, the control method further includes:

[0038] Determining a waiting time for a user to execute a task corresponding to a sub-range based on the user queue, the rated number, and the execution time corresponding to the task;

[0039] The required waiting time is transmitted to the terminal corresponding to the user, so that the terminal displays the required waiting time.

[0040] In a second aspect, an embodiment of the present application further provides a control device, comprising:

[0041] an acquisition module configured to acquire user information and task information corresponding to a target range; wherein the target range includes multiple sub-ranges, the user information includes at least the actual number and the rated number of users corresponding to each sub-range, and the task information includes at least the number of tasks issued and completed for each sub-range;

[0042] a first determining module configured to determine a first load value based on the actual quantity and the rated quantity, and to determine a second load value based on the published quantity and the completed quantity;

[0043] a second determining module configured to determine a load balancing coefficient corresponding to the target range based on the first load value and the second load value;

[0044] a third determining module configured to, when the load balancing coefficient satisfies the diversion condition, determine, for each sub-range, a weight value of the task corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and attribute information of the task corresponding to the sub-range;

[0045] The control module is configured to perform diversion control on users based on the weight value.

[0046] In a third aspect, an embodiment of the present application further provides an electronic device comprising: a processor and a memory, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via a bus, and when the machine-readable instructions are executed by the processor, the steps of any one of the control methods described above are performed.

[0047] In an embodiment of the present application, after determining that users within the target range need to be diverted and controlled based on the user information and task information corresponding to the target range, the weight value of the task corresponding to the sub-range is further determined to divert and control the users based on the weight value, thereby effectively avoiding the problem that the actual number corresponding to one sub-range is large and the actual number corresponding to another sub-range is small, to a certain extent, ensure the user queuing efficiency and resource (sub-range) utilization, and greatly improve the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in this application or the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in this application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative labor.

[0049] Figure 1A flow chart of a control method provided by the present application is shown;

[0050] Figure 2 A flow chart showing a control method provided by the present application for performing diversion control on users based on weight values ​​according to a first diversion strategy;

[0051] Figure 3 A flowchart showing another method of controlling user diversion based on weight values ​​according to a first diversion strategy in a control method provided by the present application is shown;

[0052] Figure 4 A flow chart showing a control method provided by the present application for performing diversion control on users based on weight values ​​according to a second diversion strategy;

[0053] Figure 5 A schematic structural diagram of a control device provided by the present application is shown;

[0054] Figure 6 A schematic structural diagram of an electronic device provided in this application is shown. DETAILED DESCRIPTION

[0055] Various aspects and features of the present application are described herein with reference to the accompanying drawings.

[0056] It should be understood that various modifications may be made to the embodiments of the present application. Therefore, the above description should not be considered as limiting, but merely as an example of an embodiment. Other modifications within the scope and spirit of the present application will occur to those skilled in the art.

[0057] The accompanying drawings, which are incorporated in and constitute a part of the specification, illustrate embodiments of the present application and, together with the general description of the present application given above and the detailed description of the embodiments given below, serve to explain the principles of the present application.

[0058] These and other characteristics of the present application will become apparent from the following description of a preferred form of embodiment given as a non-limiting example with reference to the accompanying drawings.

[0059] It should also be understood that although the present application has been described with reference to certain specific examples, those skilled in the art will be able to implement many other equivalent forms of the present application that have the features described in the claims and are therefore within the scope of protection defined thereby.

[0060] The above and other aspects, features and advantages of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings.

[0061] Specific embodiments of the present application will be described hereinafter with reference to the accompanying drawings; however, it should be understood that the embodiments described are merely examples of the present application and may be implemented in a variety of ways. Familiar and / or repetitive functions and structures are not described in detail to avoid obscuring the present application with unnecessary or redundant details. Therefore, the specific structural and functional details described herein are not intended to be limiting, but rather serve merely as a basis and representative basis for the claims to teach those skilled in the art to variously utilize the present application with substantially any suitable detailed structure.

[0062] This specification may use the phrases "in one embodiment," "in another embodiment," "in yet another embodiment," or "in other embodiments," which may all refer to one or more of the same or different embodiments according to the present application.

[0063] On the one hand, the present application provides a control method. It should be noted that the application scenario of the embodiment of the present application is a scenario where a user experiences various attractions in an amusement park. Here, the target scope is the amusement park, the sub-scope is a certain attraction, and the task is for the user to determine the attraction they want to experience (and generate a queue for the attraction).

[0064] Figure 1 A flow chart of a control method provided in an embodiment of the present application is shown, wherein the specific steps include S101-S105.

[0065] S101, obtaining user information and task information corresponding to the target range; wherein the target range includes multiple sub-ranges, the user information includes at least the actual number and the rated number of users corresponding to each sub-range, and the task information includes at least the number of tasks published and completed corresponding to each sub-range.

[0066] In a specific implementation, the target range includes multiple sub-ranges, meaning the amusement park includes multiple attractions. For each sub-range within the target range, the actual number corresponding to that sub-range is obtained, where the actual number is the number of users currently in the queue corresponding to that sub-range. The rated number of users corresponding to the sub-range is the maximum number of users that the sub-range can accommodate. The number of tasks issued for a sub-range is the number of users who have queued for that sub-range, and the number of tasks completed for a sub-range is the number of users who have performed the preset actions for that sub-range.

[0067] Obtaining user information and task information corresponding to the target range means obtaining the actual number and rated number of users corresponding to each sub-range within the target range, as well as the number of published and completed tasks corresponding to each sub-range.

[0068] It is worth noting that the actual quantity, released quantity and completed quantity are subject to change.

[0069] S102 , determining a first load value based on the actual quantity and the rated quantity, and determining a second load value based on the published quantity and the completed quantity.

[0070] After obtaining the actual number and rated number of users corresponding to each sub-range and the number of tasks published and completed corresponding to each sub-range, a first load value is determined based on the actual number and the rated number. As one example, the ratio of the actual number to the rated number is determined as the first load value.

[0071] Likewise, when the second load value is determined based on the number of releases and the number of completions, the ratio between the number of completions and the number of releases may be determined as the second load value.

[0072] S103: Determine a load balancing coefficient corresponding to the target range based on the first load value and the second load value.

[0073] After obtaining the first load value and the second load value corresponding to each sub-range, the load balancing coefficient corresponding to the target range is further determined based on the first load value and the second load value. Optionally, a first sum of the first load values ​​corresponding to all sub-ranges and a second sum of the second load values ​​corresponding to all sub-ranges can be calculated, and the first sum and the second sum are calculated using the balancing weight corresponding to the user information and the balancing weight corresponding to the task information to obtain the load balancing coefficient corresponding to the target range. As another example, a first mean of the first load values ​​corresponding to all sub-ranges and a second mean of the second load values ​​corresponding to all sub-ranges can be calculated, and the first mean and the second mean are calculated using the balancing weight corresponding to the user information and the balancing weight corresponding to the task information to obtain the load balancing coefficient corresponding to the target range.

[0074] In the embodiment of the present application, when determining the load balancing coefficient corresponding to the target range based on the first load value and the second load value, the following formula (1) is used.

[0075] B load = α × L queue + β × L task (1)

[0076] Among them, B load Indicates the load balancing coefficient corresponding to the target range, L queue Indicates the first load value, L task represents the second load value, α represents the balance weight corresponding to the user information, β represents the balance weight corresponding to the task information, and the sum of α and β is 1.

[0077] The load balancing coefficient represents a queue condition within a target range, and the queue condition may include heavy congestion, moderate congestion, and no congestion.

[0078] S104 , when the load balancing coefficient meets the diversion condition, for each sub-range, based on the actual number and rated number of users corresponding to the sub-range and attribute information of the task corresponding to the sub-range, determine the weight value of the task corresponding to the sub-range.

[0079] After determining the load balancing coefficient corresponding to the target range, it is further determined whether the load balancing coefficient meets the diversion condition. The diversion condition includes the load balancing coefficient being greater than or equal to a first threshold, and the load balancing coefficient being less than the first threshold and greater than or equal to a second threshold, where the first threshold is greater than the second threshold. Optionally, when determining whether the load balancing coefficient meets the diversion condition, the load balancing coefficient is compared with the first threshold and the second threshold, respectively, or directly compared with the second threshold. If the load balancing coefficient is greater than or equal to the second threshold, it indicates that the load balancing coefficient meets the diversion condition.

[0080] If the load balancing factor satisfies the splitting conditions, a weight is determined for each sub-range based on the actual number of users in that sub-range, the rated number of users, and the attribute information of the tasks in that sub-range. The weight represents the degree to which the user performs the task. For example, if Task A assigned to User 1 has a weight of 167, and Task B assigned to User 1 has a weight of 180, then Task B will be assigned to User 1 first.

[0081] In one example, the weight value of the task corresponding to the sub-range is determined according to the following formula (2).

[0082] W original = W load + W difficulty (2)

[0083] Among them, W original Indicates the weight value of the task corresponding to the sub-range, W load Indicates the user weight value corresponding to the sub-range, W difficulty Indicates the task weight value corresponding to the sub-range.

[0084] In one example, the user weight value for a sub-range is determined using the actual number and rated number of users corresponding to the sub-range. Specifically, the user weight value is determined as the first standard value / (actual number / rated number). For example, the first standard value is 50%, the actual number of users corresponding to sub-range A is 100, and the rated number is 30. This means that 100 users want to perform the task corresponding to sub-range A. If sub-range A is a roller coaster, the corresponding task is to ride the roller coaster. At this time, 100 users are queuing to ride the roller coaster, and the roller coaster can accommodate 30 users at a time. Based on this, the user weight value for sub-range A is 50 / (100 / 30) = 15.

[0085] In another example, the task weight corresponding to the sub-range is determined using the attribute information and rated quantity of the task corresponding to the sub-range. The task attribute information includes at least the execution time required to execute the task once. Optionally, the second standard value / (execution time / rated quantity) is determined as the user weight. For example, in the above example, if the execution time required to execute a task in sub-range A, i.e., start a roller coaster, is 10 minutes, then the task weight corresponding to sub-range A is 50 / (10 / 30) = 150.

[0086] In summary, the weight value of the task corresponding to sub-range A is 15+150=165.

[0087] S105: Perform diversion control on users based on the weight values.

[0088] After determining the weight values ​​of the tasks corresponding to each sub-range, the users are diverted and controlled based on the weight values.

[0089] Optionally, when users are diverted and controlled based on weight values, for the scenario where the load balancing coefficient is greater than or equal to the first threshold, that is, the sub-range is severely congested, the users are diverted and controlled based on the weight values ​​according to the first diversion strategy; for the scenario where the load balancing coefficient is less than the first threshold and greater than or equal to the second threshold, that is, the sub-range is moderately congested, the users are diverted and controlled based on the weight values ​​according to the second diversion strategy.

[0090] As an example, Figure 2 A flow chart of performing diversion control on users based on weight values ​​according to a first diversion strategy is shown, wherein the specific steps include S201-S203.

[0091] S201 , for each sub-range, determining a sub-load balancing coefficient corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and the published number and completed number of tasks corresponding to the sub-range.

[0092] S202: Determine the sub-range corresponding to the maximum sub-load balancing coefficient as the target sub-range.

[0093] S203: Filter out some users from all users corresponding to the target sub-range and determine them as target users, so as to perform diversion control on the target users.

[0094] If the load balancing coefficient is greater than or equal to the first threshold, for each sub-range, the sub-load balancing coefficient corresponding to the sub-range is determined based on the actual and rated number of users corresponding to the sub-range, as well as the number of tasks posted and completed corresponding to the sub-range. The method for calculating the sub-load balancing coefficient for a sub-range is the same as the method for calculating the load balancing coefficient for the target range, and is not further described here.

[0095] After obtaining the sub-load balancing coefficients corresponding to each sub-range, the maximum sub-load balancing coefficient is determined from all sub-load balancing coefficients. The sub-range corresponding to the maximum sub-load balancing coefficient is then determined as the target sub-range. The target sub-range has a large number of users, and traffic diversion control is required for the users corresponding to the target sub-range.

[0096] For example, from all users corresponding to the target sub-range, some users are screened out and determined as target users to perform diversion control on the target users. Optionally, for each user corresponding to the target sub-range, it is determined whether there is a weight value among all weight values ​​corresponding to the user whose difference with the weight value corresponding to the target sub-range is less than a threshold.

[0097] In practice, each user may claim tasks for multiple sub-ranges, generating queues for multiple attractions. Each task is assigned a weight value. Therefore, if a user claims tasks for multiple sub-ranges, they will have multiple weight values ​​associated with them. Furthermore, the user's multiple weight values ​​are traversed to determine whether any weight value differs from the weight value corresponding to the target sub-range by less than a threshold.

[0098] If there is a weight value whose difference between the weight values ​​corresponding to the target sub-range is less than the threshold weight value, the user is determined to be the target user, that is, other tasks can be assigned to the target user. The target user can be all users or some users corresponding to the target sub-range.

[0099] Furthermore, for each target user, the weight value with the smallest difference between the weight values ​​corresponding to the target sub-range and the weight values ​​corresponding to the target sub-range is determined, so as to assign the task corresponding to the weight value with the smallest difference between the weight values ​​corresponding to the target sub-range to the target user.

[0100] From the above, allocating tasks other than the tasks corresponding to the target sub-range to the target user can effectively avoid a large number of users queuing up to execute the tasks corresponding to the target sub-range at the same time, thereby improving the user's queuing efficiency to a certain extent and thus improving the user experience; at the same time, it can also alleviate the load corresponding to the target sub-range, that is, reduce the sub-load balancing coefficient corresponding to the target sub-range, and accordingly improve the resource utilization of the sub-ranges corresponding to other tasks.

[0101] Another example, Figure 3 Another flowchart of performing diversion control on users based on weight values ​​according to the first diversion strategy is shown, wherein the specific steps include S301-S304.

[0102] S301 , for each sub-range, determining a sub-load balancing coefficient corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and the published number and completed number of tasks corresponding to the sub-range.

[0103] S302: Determine the sub-range corresponding to the maximum sub-load balancing coefficient as the target sub-range.

[0104] S303: For each user corresponding to the target sub-range, update the weight value corresponding to the user according to the first updating method.

[0105] S304: Allocate the task corresponding to the largest weight value among the updated weight values ​​to the user.

[0106] As another example, an embodiment of the present application further provides another first diversion strategy to adapt to different diversion scenarios through different first diversion strategies. When performing diversion control on users based on weight values ​​according to another first diversion strategy, for each sub-range, a sub-load balancing coefficient corresponding to the sub-range is determined based on the actual number and rated number of users corresponding to the sub-range and the number of tasks published and completed corresponding to the sub-range.

[0107] Similarly, after obtaining the sub-load balancing coefficient corresponding to each sub-range, the maximum sub-load balancing coefficient is determined from all sub-load balancing coefficients. The sub-range corresponding to the maximum sub-load balancing coefficient is then determined as the target sub-range. The target sub-range has a large number of users, and traffic diversion control is required for the users corresponding to the target sub-range.

[0108] Furthermore, for each user corresponding to the target sub-range, the weight value corresponding to the user is updated according to the first updating method. If the user has multiple weight values, the weight value corresponding to the task corresponding to each sub-range is updated. Optionally, the first updating method can refer to the following formula (3).

[0109] Wi,new = W i,original + k × (L queue,i / L max ) (3)

[0110] Among them, W i,new represents the updated weight value of the task corresponding to sub-range i, W i,original represents the weight value of the task corresponding to sub-range i before the update, k represents the adjustment coefficient, L queue,i represents the first load value of sub-range i, L max Indicates the maximum load value of sub-range i (which can be determined by the attributes of the sub-range or set manually).

[0111] After updating the weights for each user, the task corresponding to the largest weight among the updated weights is assigned to that user. The task corresponding to the largest weight among the updated weights may not be the task corresponding to the target sub-range. This achieves the goal of diverting users within the target sub-range, thereby ensuring user queuing efficiency and resource (sub-range) utilization, significantly improving the user experience.

[0112] As an example, Figure 4 A flow chart of performing diversion control on users based on weight values ​​according to the second diversion strategy is shown, wherein the specific steps include S401-S403.

[0113] S401: For each user, update the weight value corresponding to the user according to the second updating method.

[0114] S402: Determine the allocation probability of each task based on the updated weight value.

[0115] S403: Allocate the task corresponding to the maximum allocation probability to the user.

[0116] When the load balancing coefficient is less than the first threshold and greater than or equal to the second threshold, for each user, the weight value corresponding to the user is updated according to the second updating method. Optionally, the second updating method can refer to the following formula (4).

[0117] W i,new = W i,original × (1-L queue,i / L max ) (4)

[0118] Among them, W i,newrepresents the updated weight value of the task corresponding to sub-range i, W i,original represents the weight value of the task corresponding to sub-range i before the update, L queue,i represents the first load value of sub-range i, L max Indicates the maximum load value of sub-range i.

[0119] After the weight value corresponding to each user is updated, the probability of assigning each task to each user is determined based on the updated weight value corresponding to the user. Optionally, the probability of assigning each task is determined by referring to the following formula (5).

[0120] P i =W i / ∑ j=1 n W j (5)

[0121] Among them, P i represents the probability of assigning tasks to sub-range i, W i represents the weight value of the task corresponding to sub-range i, j represents the number of tasks corresponding to the user, n represents the number of sub-ranges within the target range, W j Indicates the weight value corresponding to the task corresponding to sub-range j.

[0122] After determining the probability of each task being assigned, the task with the highest probability is assigned to the user. Similarly, the task with the highest probability may not be the task for the current sub-range (a moderately crowded sub-range). This allows for the flow of users within the current sub-range to be controlled, ensuring efficient queuing and resource (sub-range) utilization, significantly improving the user experience.

[0123] In an embodiment of the present application, after determining that users within the target range need to be diverted and controlled based on the user information and task information corresponding to the target range, the weight value of the task corresponding to the sub-range is further determined to divert and control the users based on the weight value, thereby effectively avoiding the problem that the actual number corresponding to one sub-range is large and the actual number corresponding to another sub-range is small, to a certain extent, ensure the user queuing efficiency and resource (sub-range) utilization, and greatly improve the user experience.

[0124] It is worth noting that when the load balancing coefficient is less than the second threshold, that is, when the load balancing coefficient does not meet the diversion condition, there is no need to perform diversion control on the user. Optionally, when the load balancing coefficient does not meet the diversion condition, reference information of each user is obtained; wherein the reference information includes at least age, task participation, queuing behavior, and recommended behavior.

[0125] Based on age, task participation, queuing behavior, and recommendation behavior, the users corresponding to each sub-range are sorted to obtain a user queue. As an example, the queuing score of each user is calculated according to the following formula (6), and the users corresponding to each sub-range are sorted in descending order of queuing score to obtain a user queue.

[0126] Z= 𝑊0×A +𝑊1×𝐺+𝑊2×𝑄+𝑊3×𝑅 (6)

[0127] Among them, Z represents the user's queuing score, 𝑊0 represents the weight coefficient of age, A represents the sub-score corresponding to the user's age, 𝑊1 represents the weight coefficient of task participation, 𝐺 represents the sub-score corresponding to task participation, 𝑊2 represents the weight coefficient of queuing behavior, 𝑄 represents the sub-score corresponding to queuing behavior, 𝑊3 represents the weight coefficient of recommendation behavior, and 𝑅 represents the sub-score corresponding to recommendation behavior.

[0128] For example, for age, the sub-score could be set to 1.5 for users aged 1-12, 1.2 for users aged 13-17, 1.0 for users aged 18-59, and 1.4 for users aged 60 and above. For task engagement, if a user completes a task once, the sub-score is 1 point; if a user completes a task three times, the sub-score is 3 points. For queuing behavior, if a user arrives on time within a sub-range, the sub-score increases by 5 points; if a user voluntarily exits the queue, the sub-score decreases by 5 points; and if a user is late and removed from the official queue, the sub-score decreases by 20 points. For recommendation behavior, the sub-score increases by 10 points for each new player a user recommends who successfully receives a task within the sub-range. It should be noted that the sub-scores corresponding to the task participation and the sub-scores corresponding to the behavior points are all set with corresponding upper and lower limits. Of course, this is only one example, and the embodiments of the present application are not limited thereto.

[0129] In specific implementation, the queue score reset cycle is set according to the operation cycle of the target range. For example, if the operation cycle of the target range is 12 hours (such as the operation time is 9:00-21:00 every day), then the queue score reset cycle can be set to 24 hours, and the reset can be set at any time point from 21:00 of the current day to 9:00 of the next day to avoid users with high queue scores frequently giving priority to executing tasks in the sub-range, thereby affecting the experience of other users.

[0130] After obtaining the user queue, status information and / or user requests for the sub-range are obtained. The status information includes at least whether the task corresponding to the sub-range is pending, in progress, or completed, and the user request indicates that the user has requested to exit the user queue corresponding to the sub-range. The user queue is then updated based on the status information and / or user requests.

[0131] For example, if the status information for a sub-range is "To Be Executed," a specified number of users corresponding to that sub-range are selected from the user queue in descending order of queue scores to execute the tasks corresponding to that sub-range. At the same time, these specified number of users are removed from the user queue. If the status information for a sub-range is "In Progress" or "Completed," the user queue is updated at a preset frequency, where the preset frequency varies for different sub-ranges. If a user request is received to exit the user queue corresponding to that sub-range, the user is removed from the user queue.

[0132] In another example, the waiting time required for a user to execute a task corresponding to a sub-range can be determined based on the user queue, the rated number of users, and the corresponding task execution time. The required waiting time is then transmitted to the user's corresponding terminal, so that the terminal displays the required waiting time. The required waiting time is calculated as follows: (number of users in the user queue / rated number of users) * task execution time.

[0133] Accordingly, users can reasonably arrange their time according to the length of time they need to wait, effectively improving the user experience.

[0134] On the other hand, the present application also provides a control device corresponding to a control method. Since the principle of solving the problem by the control device in the present application is similar to the above-mentioned control method of the present application, the implementation of the control device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0135] Figure 5 The schematic diagram of the structure of the control device provided in the embodiment of the present application is shown, which specifically includes:

[0136] Acquisition module 501 is configured to acquire user information and task information corresponding to a target range; wherein the target range includes multiple sub-ranges, the user information includes at least the actual number and the rated number of users corresponding to each sub-range, and the task information includes at least the number of tasks issued and completed for each sub-range;

[0137] A first determination module 502 is configured to determine a first load value based on the actual quantity and the rated quantity, and to determine a second load value based on the published quantity and the completed quantity;

[0138] A second determining module 503 is configured to determine a load balancing coefficient corresponding to the target range based on the first load value and the second load value;

[0139] A third determining module 504 is configured to determine, for each sub-range, a weight value of the task corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and attribute information of the task corresponding to the sub-range, if the load balancing coefficient satisfies the diversion condition;

[0140] The control module 505 is configured to perform diversion control on users based on the weight value.

[0141] In yet another example, the traffic diversion condition includes that the load balancing coefficient is greater than or equal to a first threshold and that the load balancing coefficient is less than the first threshold and greater than or equal to a second threshold;

[0142] The control module 505 is specifically configured as follows:

[0143] When the load balancing coefficient is greater than or equal to a first threshold, performing diversion control on the user based on the weight value according to a first diversion strategy;

[0144] When the load balancing coefficient is less than the first threshold and greater than or equal to the second threshold, the user is diverted and controlled based on the weight value according to the second diversion strategy.

[0145] In yet another example, the control module 505 is further configured to:

[0146] For each sub-range, determining a sub-load balancing coefficient corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and the number of tasks issued and completed corresponding to the sub-range;

[0147] Determine the sub-range corresponding to the maximum sub-load balancing coefficient as the target sub-range;

[0148] From all users corresponding to the target sub-range, some users are screened out and determined as target users, so as to perform diversion control on the target users.

[0149] In yet another example, the control module 505 is further configured to:

[0150] For each user corresponding to the target sub-range, determining whether, among all weight values ​​corresponding to the user, there is a weight value whose difference with the weight value corresponding to the target sub-range is less than a threshold;

[0151] If so, determining that the user is the target user;

[0152] For each target user, determine a weight value having the smallest difference between all weight values ​​corresponding to the target user and the weight value corresponding to the target sub-range;

[0153] The task corresponding to the weight value having the smallest difference between the weight values ​​corresponding to the target sub-range is assigned to the target user.

[0154] In yet another example, the control module 505 is further configured to:

[0155] For each sub-range, determining a sub-load balancing coefficient corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and the number of tasks issued and completed corresponding to the sub-range;

[0156] Determine the sub-range corresponding to the maximum sub-load balancing coefficient as the target sub-range;

[0157] For each user corresponding to the target sub-range, updating the weight value corresponding to the user according to the first updating method;

[0158] Assign the task corresponding to the largest weight value among the updated weight values ​​to the user.

[0159] In yet another example, the control module 505 is further configured to:

[0160] For each user, update the weight value corresponding to the user according to the second updating method;

[0161] Determining the assignment probability of each of the tasks based on the updated weight value;

[0162] Assign the task with the highest probability to the user.

[0163] In yet another example, the control device further includes a queue module 506, which is configured to:

[0164] When the load balancing coefficient does not satisfy the diversion condition, obtaining reference information of each user; wherein the reference information includes at least age, task participation, queuing behavior, and recommended behavior;

[0165] sorting users corresponding to each sub-range based on the age, the task participation, the queuing behavior, and the recommendation behavior to obtain a user queue;

[0166] Obtaining status information and / or a user request of the sub-range; wherein the status information at least includes whether the task corresponding to the sub-range is pending, in progress, or completed; and the user request indicates that the user requests to exit the user queue corresponding to the sub-range;

[0167] The user queue is updated based on the status information and / or the user request.

[0168] In yet another example, the queue module 506 is further configured to:

[0169] Determining a waiting time for a user to execute a task corresponding to a sub-range based on the user queue, the rated number, and the execution time corresponding to the task;

[0170] The required waiting time is transmitted to the terminal corresponding to the user, so that the terminal displays the required waiting time.

[0171] In an embodiment of the present application, after determining that users within the target range need to be diverted and controlled based on the user information and task information corresponding to the target range, the weight value of the task corresponding to the sub-range is further determined to divert and control the users based on the weight value, thereby effectively avoiding the problem that the actual number corresponding to one sub-range is large and the actual number corresponding to another sub-range is small, to a certain extent, ensure the user queuing efficiency and resource (sub-range) utilization, and greatly improve the user experience.

[0172] An embodiment of the present application provides a storage medium, which is a computer-readable medium and stores a computer program. When the computer program is executed by a processor, the method provided in any embodiment of the present application is implemented, including the following steps S11 to S15:

[0173] S11, obtaining user information and task information corresponding to a target range; wherein the target range includes multiple sub-ranges, the user information includes at least the actual number and the rated number of users corresponding to each sub-range, and the task information includes at least the number of tasks issued and completed for each sub-range;

[0174] S12, determining a first load value based on the actual quantity and the rated quantity, and determining a second load value based on the published quantity and the completed quantity;

[0175] S13, determining a load balancing coefficient corresponding to the target range based on the first load value and the second load value;

[0176] S14, when the load balancing coefficient satisfies the diversion condition, for each sub-range, based on the actual number and rated number of users corresponding to the sub-range and attribute information of the task corresponding to the sub-range, determining a weight value of the task corresponding to the sub-range;

[0177] S15: Perform diversion control on users based on the weight value.

[0178] An embodiment of the present application provides an electronic device. The structural diagram of the electronic device can be as follows: Figure 6 As shown, the electronic device comprises at least a memory 601 and a processor 602. The memory 601 stores a computer program. The processor 602 implements the method provided by any embodiment of the present application when executing the computer program on the memory 601. Exemplarily, the electronic device computer program steps S21 to S25 are as follows:

[0179] S21, obtaining user information and task information corresponding to a target range; wherein the target range includes multiple sub-ranges, the user information includes at least the actual number and the rated number of users corresponding to each sub-range, and the task information includes at least the number of tasks issued and completed for each sub-range;

[0180] S22, determining a first load value based on the actual quantity and the rated quantity, and determining a second load value based on the published quantity and the completed quantity;

[0181] S23, determining a load balancing coefficient corresponding to the target range based on the first load value and the second load value;

[0182] S24, when the load balancing coefficient satisfies the diversion condition, determining, for each sub-range, a weight value of the task corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and attribute information of the task corresponding to the sub-range;

[0183] S25: Perform diversion control on users based on the weight value.

[0184] In an embodiment of the present application, after determining that users within the target range need to be diverted and controlled based on the user information and task information corresponding to the target range, the weight value of the task corresponding to the sub-range is further determined to divert and control the users based on the weight value, thereby effectively avoiding the problem that the actual number corresponding to one sub-range is large and the actual number corresponding to another sub-range is small, to a certain extent, ensure the user queuing efficiency and resource (sub-range) utilization, and greatly improve the user experience.

[0185] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as a USB flash drive, a read-only memory (ROM), a random access memory (RAM), a removable hard drive, a magnetic disk, or an optical disk. Optionally, in this embodiment, the processor executes the method steps described in the above embodiment according to the program code stored in the storage medium. Optionally, specific examples in this embodiment can refer to the examples described in the above embodiment and the optional implementation manner, and this embodiment will not be described in detail here. Obviously, those skilled in the art will understand that the modules or steps of the present application described above can be implemented using a general-purpose computing device. They can be centralized on a single computing device or distributed across a network consisting of multiple computing devices. Optionally, they can be implemented using program code executable by a computing device, and thus, they can be stored in a storage device and executed by the computing device. In some cases, the steps shown or described can be performed in a different order than shown here, or they can be fabricated into separate integrated circuit modules, or multiple modules or steps can be fabricated into a single integrated circuit module for implementation. Thus, this application is not limited to any specific combination of hardware and software.

[0186] Furthermore, although exemplary embodiments have been described herein, the scope includes any and all embodiments based on the present application with equivalent elements, modifications, omissions, combinations (e.g., solutions that intersect various embodiments), adaptations, or changes. The elements of the claims are to be interpreted broadly based on the language employed in the claims and are not limited to the examples described in this specification or during the prosecution of the application, which examples are to be construed as non-exclusive. Therefore, it is intended that this specification and examples be considered merely as examples, with the true scope and spirit being indicated by the following claims and their full scope of equivalents.

[0187] The above description is intended to be illustrative and not restrictive. For example, the above examples (or one or more of their embodiments) may be used in combination with each other. For example, a person of ordinary skill in the art may use other embodiments when reading the above description. In addition, in the above detailed description, various features may be grouped together to simplify the application. This should not be interpreted as an intention that a disclosed feature that is not claimed for protection is essential to any claim. On the contrary, the subject matter of the present application may have less than all the features of a particular disclosed embodiment. Thus, the following claims are incorporated into the detailed description as examples or embodiments, with each claim independently serving as a separate embodiment, and it is contemplated that these embodiments may be combined with each other in various combinations or arrangements. The scope of the present application should be determined with reference to the appended claims and the full scope of equivalents to which such claims are entitled.

[0188] The above describes in detail several embodiments of the present application, but the present application is not limited to these specific embodiments. Those skilled in the art can make various variations and modifications to the embodiments based on the concept of the present application, and these variations and modifications should all fall within the scope of protection claimed by the present application.

Claims

1. A control method, characterized in that: include: Obtaining user information and task information corresponding to a target range; wherein the target range includes multiple sub-ranges, the user information includes at least the actual number and the rated number of users corresponding to each sub-range, and the task information includes at least the number of tasks issued and completed for each sub-range, wherein the task is a queuing behavior generated for its corresponding sub-range; determining a first load value based on the actual quantity and the rated quantity, and determining a second load value based on the published quantity and the completed quantity; determining a load balancing coefficient corresponding to the target range based on the first load value and the second load value; When the load balancing coefficient satisfies the diversion condition, for each sub-range, based on the actual number and rated number of users corresponding to the sub-range and attribute information of the task corresponding to the sub-range, a weight value of the task corresponding to the sub-range is determined; Based on the weight value, the user is diverted and controlled.

2. The control method according to claim 1, characterized in that: The traffic diversion condition includes that the load balancing coefficient is greater than or equal to a first threshold value and that the load balancing coefficient is less than the first threshold value and greater than or equal to a second threshold value; The controlling of user diversion based on the weight value includes: When the load balancing coefficient is greater than or equal to a first threshold, performing diversion control on the user based on the weight value according to a first diversion strategy; When the load balancing coefficient is less than the first threshold and greater than or equal to the second threshold, the user is diverted and controlled based on the weight value according to the second diversion strategy.

3. The control method according to claim 2, characterized in that: The performing diversion control on the user based on the weight value according to the first diversion strategy includes: For each sub-range, determining a sub-load balancing coefficient corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and the number of tasks issued and completed corresponding to the sub-range; Determine the sub-range corresponding to the maximum sub-load balancing coefficient as the target sub-range; From all users corresponding to the target sub-range, some users are screened out and determined as target users, so as to perform diversion control on the target users.

4. The control method according to claim 3, characterized in that: The step of screening out some users from all users corresponding to the target sub-range to determine them as target users, so as to perform diversion control on the target users, includes: For each user corresponding to the target sub-range, determining whether, among all weight values ​​corresponding to the user, there is a weight value whose difference with the weight value corresponding to the target sub-range is less than a threshold; If so, determining that the user is the target user; For each target user, determine a weight value having the smallest difference between all weight values ​​corresponding to the target user and the weight value corresponding to the target sub-range; The task corresponding to the weight value having the smallest difference between the weight values ​​corresponding to the target sub-range is assigned to the target user.

5. The control method according to claim 2, characterized in that: The step of performing diversion control on users based on the weight values ​​according to the first diversion strategy further includes: For each sub-range, determining a sub-load balancing coefficient corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and the number of tasks issued and completed corresponding to the sub-range; Determine the sub-range corresponding to the maximum sub-load balancing coefficient as the target sub-range; For each user corresponding to the target sub-range, updating the weight value corresponding to the user according to the first updating method; Assign the task corresponding to the largest weight value among the updated weight values ​​to the user; The first updating method includes: W i,new = W i,original + k× (L queue,i / L max ) Among them, W i,new represents the updated weight value corresponding to the task corresponding to the target sub-range i, W i,original represents the weight value of the task corresponding to the target sub-range i before the update, k represents the adjustment coefficient, L queue,i represents the first load value of the target sub-range i, L max Indicates the maximum load value of target sub-range i.

6. The control method according to claim 3, characterized in that: The performing diversion control on the user based on the weight value according to the second diversion strategy includes: For each user, update the weight value corresponding to the user according to the second updating method; Determining the assignment probability of each of the tasks based on the updated weight value; Assign the task with the highest probability of assignment to the user; The second updating method includes: W i,new = W i,original × (1-L queue,i / L max ) Among them, W i,new represents the updated weight value corresponding to the task corresponding to the target sub-range i, W i,original represents the weight value of the task corresponding to the target sub-range i before the update, L queue,i represents the first load value of the target sub-range i, L max Indicates the maximum load value of target sub-range i.

7. The control method according to claim 1, characterized in that: Also includes: When the load balancing coefficient does not satisfy the diversion condition, obtaining reference information of each user; wherein the reference information includes at least age, task participation, queuing behavior, and recommended behavior; sorting users corresponding to each sub-range based on the age, the task participation, the queuing behavior, and the recommendation behavior to obtain a user queue; Obtaining status information and / or a user request of the sub-range; wherein the status information at least includes whether the task corresponding to the sub-range is pending, in progress, or completed; and the user request indicates that the user requests to exit the user queue corresponding to the sub-range; The user queue is updated based on the status information and / or the user request.

8. The control method according to claim 7, characterized in that: Also includes: Determining a waiting time for a user to execute a task corresponding to a sub-range based on the user queue, the rated number, and the execution time corresponding to the task; The required waiting time is transmitted to the terminal corresponding to the user, so that the terminal displays the required waiting time.

9. A control device, characterized in that: include: an acquisition module configured to acquire user information and task information corresponding to a target range; wherein the target range includes multiple sub-ranges, the user information includes at least the actual number and the rated number of users corresponding to each sub-range, and the task information includes at least the number of tasks issued and completed for each sub-range, wherein the task is a queuing behavior generated for its corresponding sub-range; a first determining module configured to determine a first load value based on the actual quantity and the rated quantity, and to determine a second load value based on the published quantity and the completed quantity; a second determining module configured to determine a load balancing coefficient corresponding to the target range based on the first load value and the second load value; a third determining module configured to, when the load balancing coefficient satisfies the diversion condition, determine, for each sub-range, a weight value of the task corresponding to the sub-range based on the actual number and rated number of users corresponding to the sub-range and attribute information of the task corresponding to the sub-range; The control module is configured to perform diversion control on users based on the weight value.

10. An electronic device, characterized in that: include: A processor and a memory, wherein the memory stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the memory communicate via a bus, and when the machine-readable instructions are executed by the processor, the steps of the control method according to any one of claims 1 to 8 are performed.

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