CN117057537A - Task scheduling method, device, equipment and storage medium - Google Patents
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Abstract
The disclosure provides a task scheduling method, device, equipment and storage medium, and relates to the technical field of task scheduling. In some embodiments of the present disclosure, a target allocation task is obtained; determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor; selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executives; according to the method and the device, the matching degree of the target allocation task and the executors is determined, the first executor matched with the target allocation task is automatically selected, the target allocation task is automatically allocated, the task execution efficiency is improved, and the task scheduling speed is improved.
Description
Technical Field
The disclosure relates to the technical field of task scheduling, and in particular relates to a task scheduling method, device, equipment and storage medium.
Background
A task scheduling process, in which time and behavior are contracted, needs to go from acquisition of a task to finding a task object to completion of task scheduling.
When a transmission fixed network, a home network and personal communication in the communication service field fail, service personnel often need to provide different business marketing services for users in the processing process of the work orders after receiving the maintenance work orders. Under the automatic task allocation scene of work order scheduling, marketing scheduling and the like of the current main stream, the task acquisition scheme is a mapping task and a reduction task, wherein the mapping task is a scheme for generating one or more output task data by executing mapping operation. The reduction task is a scheme for finally outputting the task data of the same type by processing various mapping tasks in the same application program. The tasks acquired based on mapping or reduction are all required to be scheduled to related objects through a subscription message model, so that the whole scheduling process is completed.
In the current task scheduling scheme, the mapping task and the reduction task are limited by the quantity of system resources, and if a large number of tasks needing to be scheduled occur in a short time, the problems of low execution efficiency and low scheduling speed occur in task scheduling.
Disclosure of Invention
The disclosure provides a task scheduling method, device, equipment and storage medium, which at least solve the problems of low execution efficiency and low scheduling speed of the existing task scheduling.
The technical scheme of the present disclosure is as follows:
the embodiment of the disclosure provides a task scheduling method, which comprises the following steps:
acquiring a target allocation task;
determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor;
and selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executors.
Optionally, the task key information includes: task type, task difficulty and task urgency, the capability information of the executor includes: task preference, promotion experience, promotion capability, capability authentication, working state and execution force; the determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor comprises the following steps:
Determining a first matching degree of the target allocation task and each executor according to the task type of the target allocation task and the task preference of each executor;
determining a second matching degree of the target allocation task and each executor according to the task difficulty of the target allocation task, the popularization experience, the popularization capability and the capability authentication of each executor;
determining a third matching degree of the target allocation task and each executor according to the task urgency of the target allocation task, the working state and the execution force of each executor;
and determining the matching degree of the target allocation task and each executor according to the first matching degree, the second matching degree and the third matching degree.
Optionally, the method further comprises:
determining the similarity between the first executor and each other executor according to the capacity information of the first executor and the capacity information of the other executors, wherein the other executives are executives except the first executor in the plurality of executives;
Selecting a second executor meeting a similarity condition from the other executives;
and distributing the target distribution task to the second executor.
Optionally, the assigning the target assignment task to the second executor includes:
and in the case that the task allocation to the first executor fails, the task allocation to the second executor fails.
Optionally, the assigning the target assignment task to the second executor includes:
and distributing the target distribution task to the first executor and the second executor so that the first executor and the second executor cooperatively execute the target distribution task.
Optionally, the capability information of the executor includes: task preferences, the method further comprising:
counting task operation records of each executor;
and determining the task preference of each executor according to the task operation record.
Optionally, the matching degree is a matching degree score, and the selecting, from the plurality of executives, a first executor whose matching degree satisfies a matching degree condition includes:
and selecting the executor with the highest matching degree score from the executives as the first executor.
The embodiment of the disclosure also provides a task scheduling device, which comprises:
the acquisition module is used for acquiring a target allocation task;
the determining module is used for determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor;
and the selection module is used for selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executives.
Optionally, the task key information includes: task type, task difficulty and task urgency, the capability information of the executor includes: task preference, promotion experience, promotion capability, capability authentication, working state and execution force; the determining module is used for determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor, wherein the determining module is used for:
determining a first matching degree of the target allocation task and each executor according to the task type of the target allocation task and the task preference of each executor;
determining a second matching degree of the target allocation task and each executor according to the task difficulty of the target allocation task, the popularization experience, the popularization capability and the capability authentication of each executor;
Determining a third matching degree of the target allocation task and each executor according to the task urgency of the target allocation task, the working state and the execution force of each executor;
and determining the matching degree of the target allocation task and each executor according to the first matching degree, the second matching degree and the third matching degree.
Optionally, the determining module is further configured to:
determining the similarity between the first executor and each other executor according to the capacity information of the first executor and the capacity information of the other executors, wherein the other executives are executives except the first executor in the plurality of executives;
selecting a second executor meeting a similarity condition from the other executives;
and distributing the target distribution task to the second executor.
Optionally, the determining module is configured, when assigning the target assignment task to the second executive, to:
and in the case that the task allocation to the first executor fails, the task allocation to the second executor fails.
Optionally, the determining module is configured, when assigning the target assignment task to the second executive, to:
and distributing the target distribution task to the first executor and the second executor so that the first executor and the second executor cooperatively execute the target distribution task.
Optionally, the capability information of the executor includes: task preference, the determining module may be further configured to:
counting task operation records of each executor;
and determining the task preference of each executor according to the task operation record.
Optionally, the matching degree is a matching degree score, and the selecting module is configured to, when selecting a first executor, from a plurality of executives, the matching degree meets a matching degree condition:
and selecting the executor with the highest matching degree score from the executives as the first executor.
The embodiment of the disclosure also provides an electronic device, including:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the steps in the method described above.
The disclosed embodiments also provide a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described method.
The technical scheme provided by the embodiment of the disclosure at least brings the following beneficial effects:
in some embodiments of the present disclosure, a target allocation task is obtained; determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor; selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executives; according to the method and the device, the matching degree of the target allocation task and the executors is determined, the first executor matched with the target allocation task is automatically selected, the target allocation task is automatically allocated, the task execution efficiency is improved, and the task scheduling speed is improved.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure and do not constitute an undue limitation on the disclosure.
Fig. 1 is a flow chart of a task scheduling method according to an exemplary embodiment of the present application;
FIG. 2 is a block diagram of a task scheduling method provided by an exemplary embodiment of the present disclosure;
FIG. 3 is a schematic diagram of a dispatch center provided in accordance with an exemplary embodiment of the present disclosure;
FIG. 4 is a schematic diagram of a radar capability map provided by an exemplary embodiment of the present disclosure;
FIG. 5 is a schematic diagram of matching a target allocation task with a executor according to an exemplary embodiment of the present disclosure;
FIG. 6 is a schematic flow chart of collaborative filtering recommendation tasks provided by an exemplary embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of a task scheduling device according to an exemplary embodiment of the present application;
fig. 8 is a schematic structural diagram of an electronic device according to an exemplary embodiment of the present application.
Detailed Description
In order to enable those skilled in the art to better understand the technical solutions of the present disclosure, the technical solutions of the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings.
It should be noted that the terms "first," "second," and the like in the description and claims of the present disclosure and in the foregoing figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments of the disclosure described herein may be capable of operation in sequences other than those illustrated or described herein. The implementations described in the following exemplary examples are not representative of all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with aspects of the present disclosure.
It should be noted that, the user information related to the present disclosure includes, but is not limited to: user equipment information and user personal information; the processes of collecting, storing, using, processing, transmitting, providing, disclosing and the like of the user information in the present disclosure all conform to the regulations of the relevant laws and regulations and do not violate the well-known and popular public order.
In the current task scheduling scheme, the mapping task and the reduction task are limited by the quantity of system resources, and if a large number of tasks needing to be scheduled occur in a short time, the problems of low execution efficiency and low scheduling speed occur in task scheduling.
In view of the foregoing technical problems, in some embodiments of the present disclosure, a target allocation task is obtained; determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor; selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executives; according to the method and the device, the matching degree of the target allocation task and the executors is determined, the first executor matched with the target allocation task is automatically selected, the target allocation task is automatically allocated, the task execution efficiency is improved, and the task scheduling speed is improved.
The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.
Fig. 1 is a flow chart of a task scheduling method according to an exemplary embodiment of the present application. As shown in fig. 1, the method includes:
s101: acquiring a target allocation task;
s102: determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor;
s103: and selecting a first executor with the matching degree meeting the matching degree condition from the plurality of executives.
In this embodiment, the execution body of the method may be an intelligent terminal or a server.
In this embodiment, the type of the intelligent terminal is not limited, including but not limited to the following: personal computers, notebook computers, cell phones, smart bracelets, smart watches and smart speakers.
In this embodiment, the server is implemented. For example, the server may be a conventional server, a cloud host, a virtual center, or the like server device. The server mainly comprises a processor, a hard disk, a memory, a system bus and the like, and a general computer architecture type.
In this embodiment, a target allocation task is acquired; determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor; selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executives; according to the method and the device, the matching degree of the target allocation task and the executors is determined, the first executor matched with the target allocation task is automatically selected, the target allocation task is automatically allocated, the task execution efficiency is improved, and the task scheduling speed is improved.
Fig. 2 is a block diagram of a task scheduling method according to an exemplary embodiment of the present disclosure. As shown in fig. 2, when a target is assigned to a task input, task key information and tag data are extracted and input to a pedestrian representation center and a dispatch center, wherein the tag data include: task tags and executive portrait tags. And the executive portrait center calculates the similarity of the task labels and the executive portrait labels, recommends different executive portrait labels to the dispatching center according to the dispatching rules configured by the dispatching center, and executes the dispatching rules.
In some embodiments of the present disclosure, a executive portrait center includes a data source layer, a data acquisition storage layer, a label portrait computing layer, and a management computing layer.
Data source layer: the method comprises the steps of reading business data, log data, buried point data, basic data and the like of operators of different types of tasks from an application program.
And the data acquisition layer is used for counting the operation of a user on an interface based on the service data, the log data, the embedded point data and the basic data, such as the service page use frequency, the stay time and the like. And accessing a service table and log data, and carrying out standardized processing of the structure, wherein the processing process comprises streaming calculation and off-line batch calculation. Based on batch and stream data processing calculations, optimizations are performed on the data writing, storing, interfacing calculation components. Wherein, write layer: and generating a NEW DATE library from the read and collected data, writing the NEW DATE library into a batch and stream processing system, and presenting data upper-layer application through calculation logic. Storage layer: the continuously updated data source can only keep the data updated in a way that the full amount of snapshot is copied to HDFS periodically. Calculation layer: implemented and run in a stream batch framework, respectively.
The label portrait computing layer first models the executive labels. Comprises two parts: label system construction and label construction. The label system construction is mainly based on the basic information (name, age and working age) information of the executives; matching the current executive state (working state, task to be handled), the capacity authentication (professional authentication, punishment information), the capacity experience (working experience, marketing experience) of the executive, combining the executive perception information acquisition executive force (time rate of work order processing, time length of executing work order, and the like), the execution result (marketing capacity) (call out completing rate, entrance marketing success rate, entrance pendulum marketing frequency, and the like), generating corresponding labels, processing the labels, and constructing a label library of the executive. The label construction is to define each type of label, including label normalization definition and calculation rule definition.
Management and calculation layer: management of the executive portrait tags or export to a dispatch center.
Fig. 3 is a schematic structural diagram of a dispatch center according to an exemplary embodiment of the present disclosure. As shown in fig. 3, in some embodiments of the present disclosure, a dispatch center includes: a dispatch plan making module and a dispatch plan management module.
In the above embodiment, the scheduling plan making module includes an intelligent scheduling rule sub-module and an intelligent recommendation sub-module. The intelligent scheduling rule sub-module is used for pushing the executives in the corresponding areas and types by the executives tag library to directly schedule the executives to the corresponding executives when the executives are selected to filter by configuring the intelligent scheduling rules; when selecting the executives to sort, the executives with corresponding types are pushed by the executives tag library, and task scheduling to the executives is completed by setting scheduling priority and scheduling priority. And the intelligent recommendation sub-module is used for acquiring the behavior data labels of the same type of executives through the executives and portrait center when the intelligent recommendation scheduling rule is selected, judging the silk fibroin of the behavior data labels, and recommending the business opportunity to the names of the executives with the similarity greater than 0.8.
In the above embodiment, the scheduling plan management module builds a distributed task scheduling platform and builds a task scheduling console, and the platform itself is not responsible for business logic, but is responsible for unified management and scheduling execution of tasks, and provides a task management platform. For the scheduling rule, whether to take effect, whether to notify after the scheduling is completed, the scheduling period, the scheduling time and the like can be set.
In some embodiments of the present disclosure, the policy configuration and instance description includes the steps of:
step one: task executives perceive information collection. The executives enter the home page and can see the task list to be processed which the executives are docked with. The tasks to be processed are distributed in an intelligent scheduling mode, and the system records the executor users matched with the tasks in the table, and meanwhile, the tasks are an operation behavior and are also recorded in the log table. The executor sees the task content to be processed of the butt joint, and the task content is processed piece by piece according to different processing modes.
Step two: and (5) processing the information label. Executing a tag instance: executing a speed I task, and marking an execution speed label:
a, collecting the weekly data of the behavior log for statistical analysis
b, field 1 is entry status
c, field 2 field is the time corresponding to each state
d, according to the executor 1, acquiring a time point with an item state of 1 and 2, and calculating an interval time with the state of 2 and the state of 1.
SUM (time (state 2) -time (state 1))/task number, average execution time per single task.
f, grouping the average time, and labeling fast, general and slow according to the grouping value. Wherein, the task execution time is 0< 2 hours or less; 2< task execution time is less than or equal to 4 hours, which is general; task execution time >4H, slow.
Step three: a library of human tags is executed. Information based on the executive's basic information (name, age, work age); matching the current executive state working state (working state, task to be handled), the capacity authentication (professional authentication, punishment information), capacity experience (working experience, marketing experience) of the executive, generating corresponding labels by combining the executive perception information acquisition executive force 3 (timeliness of work order processing, time length of executing work order and the like), execution result marketing capacity (call completion rate, entrance marketing success rate, entrance pendulum marketing frequency and the like), processing the labels, and constructing a label library of the executive.
Step four: label dimension scoring. Fig. 4 is a schematic diagram of a radar capability map provided by an exemplary embodiment of the present disclosure. As shown in fig. 4, based on the executor tag data collected by the tag library, a radar capability map of several modules of capability authentication, working state, execution force, marketing experience and marketing capability is constructed according to a weighted calculation model.
Capability authentication: based on the industry authentication and internal authentication of the executives, three grades are divided by each grade label according to professional authentication information (primary, medium and advanced), rewarding and punishing performance information (top three, top five and top ten of performance ranking in a grid) and working experience (1 year, 3 years and more than five years), and each grade score is weighted and summed according to the proportion of 3:3:4, and is divided into five times; the three types of labels are weighted and summed according to the proportion of 3:4:3, and the total is divided into five minutes.
Work tasks: currently, tasks to be completed (tasks to be handled are more than 20 sheets, tasks to be handled are more than 15 sheets, tasks to be handled are more than 10 sheets, tasks to be handled are more than 5 sheets, tasks to be handled are more than 3 sheets, tasks to be handled are less than 1 sheet), and the label attribute is divided into six grades, which correspond to 0, 1, 2, 3, 4 and 5 grades.
Execution force: the time rate of the work order (less than 60%, 60% -90%, more than 90%), the average time length of the work order execution (more than 8 hours, 2-8 hours, less than 2 hours), the time length of the work order feedback (more than 8 hours, 2-8 hours, less than 2 hours) divide three grades for each label, and the scores of each grade are weighted and summed according to the proportion of 3:3:4, and are divided into five times; the three types of labels are weighted and summed according to the proportion of 3:4:3, and the total is divided into five minutes.
Marketing experience: the number of outbound marketing tasks (less than 50 times, 50-200 times and more than 200 times), the number of inbound marketing tasks (less than 20 times, 20-100 times and more than 100 times), the number of swing marketing tasks (less than 30 times, 30-100 times and more than 100 times) and the number of each class of labels are divided into three grades, and the scores of each grade are weighted and summed according to the proportion of 3:3:4, and are divided into five times; the three types of labels are weighted and summed according to the proportion of 3:4:3, and the total is divided into five minutes.
Marketing ability: the outbound marketing success rate (lower than 10%, 10% -20%, greater than 20%), the going-to-the-door success rate (lower than 20%, 20% -40%, greater than 40%), and the swaying marketing success rate (lower than 20%, 20% -40%, greater than 40%) are divided into three grades for each label, and the scores of each grade are weighted and summed according to the proportion of 3:3:4, and are divided into five times; the three types of labels are weighted and summed according to the proportion of 3:4:3, and the total is divided into five minutes.
Task preference: a walking visit task, a marketing business machine task, a scene collaboration task, a carrying and saving task and an index tracking task; each class of tasks takes 1 minute and five minutes.
Step five: and (6) constructing an automatic recommendation rule base for matching the business opportunity task with the executor.
In some embodiments of the present disclosure, the matching degree of the target allocation task and each executor is determined according to the task key information of the target allocation task and the capability information of each executor. One implementation way is that according to the task type of the target allocation task and the task preference of each executor, the first matching degree of the target allocation task and each executor is determined; determining a second matching degree of the target allocation task and each executor according to the task difficulty of the target allocation task and the popularization experience, popularization capability and capability authentication of each executor; determining a third matching degree of the target allocation task and each executor according to the task urgency of the target allocation task and the working state and the execution force of each executor; and determining the matching degree of the target allocation task and each executor according to the first matching degree, the second matching degree and the third matching degree.
Fig. 5 is a schematic diagram of matching a target allocation task with an executor according to an exemplary embodiment of the present disclosure. As shown in fig. 5, for example, after the target is assigned to the task input, the system identifies and extracts the key labels of the task, including the task type, task difficulty and task urgency; the matching degree is calculated according to whether different subdivision types are matched or not by matching task preference (the task types can be divided into subdivision types such as external service, hardware maintenance, software debugging, client marketing and the like) in the executive portrait tag library, for example, the matching degree is 3 when the subdivision types are matched with 3 items, the sum of multidimensional task grading values such as marketing capacity, marketing experience, capacity authentication and the like in the executive portrait tag library is matched through task difficulty, and the sum of multidimensional task completion grading values of the execution capacity and the working task in the executive portrait tag library is matched through task urgency. And (5) selecting the best executor selected.
It should be noted that, the task type is provided when the upstream system inputs; the task difficulty is classified by the system according to the difficulty, medium and easy three-level of the task marketing guest group, task type and other factors; the task urgency is classified into high, medium and low levels according to factors such as task type, task time and the like.
In the above example, the task tag and the executive portrait tag match: the method comprises the steps that executives with corresponding task execution preference are matched according to task types, and the executives with difficulty, middle and easiness in tasks take scores of top ten with different weighted averages on marketing capability, marketing experience and capability authentication respectively, and the top three names with different weighted averages on execution force and work task are respectively taken according to urgent high-middle and low tasks; and finally, comparing the multidimensional scores among the three obtained executives to obtain the highest-scoring executives.
In some embodiments of the present disclosure, a first executor whose degree of matching satisfies a degree of matching condition is selected from a plurality of executives. One way to achieve this is to select the one with the highest score of matching from among the plurality of executives as the first executor.
In some embodiments of the present disclosure, a similarity between the first executor and each other executor is determined according to the capability information of the first executor and the capability information of the other executives, wherein the other executives are the executives except the first executor in the plurality of executives; selecting a second executor satisfying the similarity condition from other executives; the target allocation task is allocated to the second executor.
Fig. 6 is a schematic flow chart of collaborative filtering recommendation tasks according to an exemplary embodiment of the present disclosure. As shown in fig. 6, the perceived acquisition and event status of person a is performed by the acquisition; such as: log information such as stay time of a single task page of a business opportunity task pool, view details, evaluation and the like is obtained. And (3) determining the preference of the executor A for certain types of business task labels by returning the acquisition labels to the executor label library, and recommending according to the business task. Obtaining a executor A and a executor B through filtering, and calculating the similarity of the executor A and the executor B when the similarity is more than or equal to 0.8; the intelligent recommendation can be performed under the name of the executive B according to the business opportunity and the task preference label of the executive A. The similarity calculation manner for the executor a and the executor B may adopt cosine similarity calculation, where the feature vector a of the executor a: home zone, execution experience, success rate, task preference; feature vector B of executive B: home zone, execution experience, success rate, task preference. Similarity cos θ=a×b/(|a) b cos) =cos 35 ° =0.819.
In the above embodiment, the target allocation task is allocated to the second executor, including the following allocation manners:
In the first allocation mode, when allocation of the target allocation task to the first executor fails, the target allocation task is allocated to the second executor.
And in the second allocation mode, the target allocation task is allocated to the first executor and the second executor so that the first executor and the second executor cooperatively execute the target allocation task.
In some embodiments of the present disclosure, a task operation record is counted for each executor; and determining the task preference of each executor according to the task operation records.
With the development of internet technology, more and more information on the internet is used, how to mine useful information from massive information and how to utilize the useful information. The user portrait is constructed to accurately identify users, a scheduling algorithm and thousands of people, so that personalized scheduling and accurate scheduling are provided, and the operation efficiency is improved.
In the above-described method embodiments of the present disclosure, a target allocation task is acquired; determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor; selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executives; according to the method and the device, the matching degree of the target allocation task and the executors is determined, the first executor matched with the target allocation task is automatically selected, the target allocation task is automatically allocated, the task execution efficiency is improved, and the task scheduling speed is improved.
Fig. 7 is a schematic structural diagram of a task scheduling device 70 according to an exemplary embodiment of the present application. As shown in fig. 7, the task scheduler 70 includes: an acquisition module 71, a determination module 72 and a selection module 73.
Wherein, the obtaining module 71 is configured to obtain a target allocation task;
a determining module 72, configured to determine, according to the task key information of the target task and the capability information of each executor, a matching degree between the target task and each executor;
a selecting module 73, configured to select a first executor whose matching degree satisfies a matching degree condition from a plurality of executives.
Optionally, the mission critical information includes: the task type, task difficulty and task urgency, and the capability information of the executor includes: task preference, promotion experience, promotion capability, capability authentication, working state and execution force; the determining module 72 is configured to, when determining a matching degree between the target allocation task and each of the executives according to the task key information of the target allocation task and the capability information of each of the executives:
determining a first matching degree of the target allocation task and each executor according to the task type of the target allocation task and the task preference of each executor;
Determining a second matching degree of the target allocation task and each executor according to the task difficulty of the target allocation task and the popularization experience, popularization capability and capability authentication of each executor;
determining a third matching degree of the target allocation task and each executor according to the task urgency of the target allocation task and the working state and the execution force of each executor;
and determining the matching degree of the target allocation task and each executor according to the first matching degree, the second matching degree and the third matching degree.
Optionally, the determining module 72 may be further configured to:
determining the similarity between the first executor and each other executor according to the capacity information of the first executor and the capacity information of the other executors, wherein the other executives are executives except the first executor in the plurality of executives;
selecting a second executor satisfying the similarity condition from other executives;
the target allocation task is allocated to the second executor.
Optionally, the determining module 72 is configured, when assigning the target assignment task to the second actor, to:
in the event that the assignment of the target assignment task to the first executor fails, the target assignment task is assigned to the second executor.
Optionally, the determining module 72 is configured, when assigning the target assignment task to the second actor, to:
and distributing the target distribution task to the first executive and the second executive so that the first executive and the second executive cooperatively execute the target distribution task.
Optionally, the capability information of the executives includes: task preference, determination module 72, may also be used to:
counting task operation records of each executor;
and determining the task preference of each executor according to the task operation records.
Alternatively, the selecting module 73 is configured to, when selecting a first executor, from the plurality of executives, that the matching degree satisfies the matching degree condition:
and selecting the executor with the highest matching degree score from the plurality of executives as a first executor.
The specific manner in which the various modules perform the operations in the apparatus of the above embodiments have been described in detail in connection with the embodiments of the method, and will not be described in detail herein.
Fig. 8 is a schematic structural diagram of an electronic device according to an exemplary embodiment of the present application. As shown in fig. 8, the electronic device includes: a memory 81 and a processor 82. In addition, the electronic device further comprises a power supply component 83 and a communication component 84.
Memory 81 is used to store computer programs and may be configured to store various other data to support operations on the electronic device. Examples of such data include instructions for any application or method operating on an electronic device.
The memory 81 may be implemented by any type or combination of volatile or non-volatile memory devices, such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
A communication component 84 for data transmission with other devices.
A processor 82, executable computer instructions stored in memory 81, for: acquiring a target allocation task; determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor; and selecting a first executor with the matching degree meeting the matching degree condition from the plurality of executives.
Optionally, the mission critical information includes: the task type, task difficulty and task urgency, and the capability information of the executor includes: task preference, promotion experience, promotion capability, capability authentication, working state and execution force; the processor 82 is configured to, when determining a matching degree between the target allocation task and each of the executives according to the task key information of the target allocation task and the capability information of each of the executives:
Determining a first matching degree of the target allocation task and each executor according to the task type of the target allocation task and the task preference of each executor;
determining a second matching degree of the target allocation task and each executor according to the task difficulty of the target allocation task and the popularization experience, popularization capability and capability authentication of each executor;
determining a third matching degree of the target allocation task and each executor according to the task urgency of the target allocation task and the working state and the execution force of each executor;
and determining the matching degree of the target allocation task and each executor according to the first matching degree, the second matching degree and the third matching degree.
Optionally, the processor 82 may be further configured to:
determining the similarity between the first executor and each other executor according to the capacity information of the first executor and the capacity information of the other executors, wherein the other executives are executives except the first executor in the plurality of executives;
selecting a second executor satisfying the similarity condition from other executives;
the target allocation task is allocated to the second executor.
Optionally, the processor 82, when assigning the target assignment task to the second actor, is configured to:
In the event that the assignment of the target assignment task to the first executor fails, the target assignment task is assigned to the second executor.
Optionally, the processor 82, when assigning the target assignment task to the second actor, is configured to:
and distributing the target distribution task to the first executive and the second executive so that the first executive and the second executive cooperatively execute the target distribution task.
Optionally, the capability information of the executives includes: task preference, processor 82, may also be used to:
counting task operation records of each executor;
and determining the task preference of each executor according to the task operation records.
Optionally, the matching degree is a matching degree score, and the processor 82 is configured to, when selecting a first executor, from the plurality of executives, that the matching degree satisfies a matching degree condition:
and selecting the executor with the highest matching degree score from the plurality of executives as a first executor.
Accordingly, embodiments of the present application also provide a computer-readable storage medium storing a computer program. The computer-readable storage medium stores a computer program that, when executed by one or more processors, causes the one or more processors to perform the steps in the method embodiment of fig. 1.
Accordingly, embodiments of the present application also provide a computer program product comprising a computer program/instructions for executing the steps of the method embodiment of fig. 1 by a processor.
The communication assembly of fig. 8 is configured to facilitate wired or wireless communication between the device in which the communication assembly is located and other devices. The device where the communication component is located can access a wireless network based on a communication standard, such as a mobile communication network of WiFi,2G, 3G, 4G/LTE, 5G, etc., or a combination thereof. In one exemplary embodiment, the communication component receives a broadcast signal or broadcast-related information from an external broadcast management system via a broadcast channel. In one exemplary embodiment, the communication component further includes a Near Field Communication (NFC) module to facilitate short range communications. For example, the NFC module may be implemented based on Radio Frequency Identification (RFID) technology, infrared data association (IrDA) technology, ultra Wideband (UWB) technology, bluetooth (BT) technology, and other technologies.
The power supply assembly shown in fig. 8 provides power to various components of the device in which the power supply assembly is located. The power components may include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for the devices in which the power components are located.
The electronic device further comprises a display screen and an audio component.
The display screen includes a screen, which may include a Liquid Crystal Display (LCD) and a Touch Panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from a user. The touch panel includes one or more touch sensors to sense touches, swipes, and gestures on the touch panel. The touch sensor may sense not only the boundary of a touch or sliding action, but also the duration and pressure associated with the touch or sliding operation.
An audio component, which may be configured to output and/or input an audio signal. For example, the audio component includes a Microphone (MIC) configured to receive external audio signals when the device in which the audio component is located is in an operational mode, such as a call mode, a recording mode, and a speech recognition mode. The received audio signal may be further stored in a memory or transmitted via a communication component. In some embodiments, the audio assembly further comprises a speaker for outputting audio signals.
In the above-described apparatus, device, storage medium, and program product embodiments of the present disclosure, a target allocation task is obtained; determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor; selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executives; according to the method and the device, the matching degree of the target allocation task and the executors is determined, the first executor matched with the target allocation task is automatically selected, the target allocation task is automatically allocated, the task execution efficiency is improved, and the task scheduling speed is improved.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises an element.
The foregoing is merely exemplary of embodiments of the present application to enable those skilled in the art to understand or practice the application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (16)
1. A method for task scheduling, comprising:
acquiring a target allocation task;
determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor;
and selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executors.
2. The method of claim 1, wherein the mission-critical information comprises: task type, task difficulty and task urgency, the capability information of the executor includes: task preference, promotion experience, promotion capability, capability authentication, working state and execution force; the determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor comprises the following steps:
Determining a first matching degree of the target allocation task and each executor according to the task type of the target allocation task and the task preference of each executor;
determining a second matching degree of the target allocation task and each executor according to the task difficulty of the target allocation task, the popularization experience, the popularization capability and the capability authentication of each executor;
determining a third matching degree of the target allocation task and each executor according to the task urgency of the target allocation task, the working state and the execution force of each executor;
and determining the matching degree of the target allocation task and each executor according to the first matching degree, the second matching degree and the third matching degree.
3. The method according to claim 1, wherein the method further comprises:
determining the similarity between the first executor and each other executor according to the capacity information of the first executor and the capacity information of the other executors, wherein the other executives are executives except the first executor in the plurality of executives;
Selecting a second executor meeting a similarity condition from the other executives;
and distributing the target distribution task to the second executor.
4. The method of claim 3, wherein the assigning the target assignment task to the second executor comprises:
and in the case that the task allocation to the first executor fails, the task allocation to the second executor fails.
5. The method of claim 3, wherein the assigning the target assignment task to the second executor comprises:
and distributing the target distribution task to the first executor and the second executor so that the first executor and the second executor cooperatively execute the target distribution task.
6. The method of claim 1, wherein the capability information of the executive comprises: task preferences, the method further comprising:
counting task operation records of each executor;
and determining the task preference of each executor according to the task operation record.
7. The method of claim 1, wherein the degree of matching is a degree of matching score, wherein the selecting a first actor from a plurality of actors that the degree of matching satisfies a degree of matching condition comprises:
And selecting the executor with the highest matching degree score from the executives as the first executor.
8. A task scheduling device, comprising:
the acquisition module is used for acquiring a target allocation task;
the determining module is used for determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor;
and the selection module is used for selecting a first executor with the matching degree meeting the matching degree condition from a plurality of executives.
9. The apparatus of claim 8, wherein the mission-critical information comprises: task type, task difficulty and task urgency, the capability information of the executor includes: task preference, promotion experience, promotion capability, capability authentication, working state and execution force; the determining module is used for determining the matching degree of the target allocation task and each executor according to the task key information of the target allocation task and the capability information of each executor, wherein the determining module is used for:
determining a first matching degree of the target allocation task and each executor according to the task type of the target allocation task and the task preference of each executor;
Determining a second matching degree of the target allocation task and each executor according to the task difficulty of the target allocation task, the popularization experience, the popularization capability and the capability authentication of each executor;
determining a third matching degree of the target allocation task and each executor according to the task urgency of the target allocation task, the working state and the execution force of each executor;
and determining the matching degree of the target allocation task and each executor according to the first matching degree, the second matching degree and the third matching degree.
10. The apparatus of claim 8, wherein the determining module is further operable to:
determining the similarity between the first executor and each other executor according to the capacity information of the first executor and the capacity information of the other executors, wherein the other executives are executives except the first executor in the plurality of executives;
selecting a second executor meeting a similarity condition from the other executives;
and distributing the target distribution task to the second executor.
11. The apparatus of claim 10, wherein the determination module, when assigning the target assignment task to the second actor, is to:
and in the case that the task allocation to the first executor fails, the task allocation to the second executor fails.
12. The apparatus of claim 10, wherein the determination module, when assigning the target assignment task to the second actor, is to:
and distributing the target distribution task to the first executor and the second executor so that the first executor and the second executor cooperatively execute the target distribution task.
13. The apparatus of claim 8, wherein the capability information of the executive comprises: task preference, the determining module may be further configured to:
counting task operation records of each executor;
and determining the task preference of each executor according to the task operation record.
14. The apparatus of claim 8, wherein the match is a match score, and wherein the selection module is configured to, when selecting a first actor from a plurality of actors that the match satisfies a match condition:
And selecting the executor with the highest matching degree score from the executives as the first executor.
15. An electronic device, comprising:
a processor;
a memory for storing the processor-executable instructions;
wherein the processor is configured to execute the instructions to implement the steps in the method of any of claims 1-7.
16. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the method of any of claims 1-7.
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