CN114755984A - Dispatching method and system of automatic flow robot and automatic flow robot - Google Patents

Abstract

The invention relates to a dispatching method of an automatic process robot, which is based on a multithreading concurrent pre-download dispatching algorithm of a maximum binary tree priority queue, integrates the priority queue and multithreading to ensure that the robot accurately, reliably and timely executes tasks, wherein a robot background comprises four threads which are concurrently operated, namely a task thread to be downloaded, a thread to be operated and a task thread to be operated; the dispatching system structurally comprises a console, a module to be downloaded, a task downloading module, a module to be operated, a task operating module, a LEVELDB, a downloading pool, a maximum binary heap queue and an operating pool. The scheduling method and the scheduling system of the invention combine the priority queue and the multithreading to ensure that the robot can accurately, reliably, timely and reasonably execute the task.

Description

Dispatching method and system of automatic flow robot and automatic flow robot

Technical Field

The invention relates to artificial intelligence, in particular to a scheduling method and a scheduling system of an automatic process robot.

Background

Robot Process Automation (RPA) requires a robot to flexibly and accurately schedule tasks issued thereto, and particularly to Process execution sequences of tasks with the same planning time. The robot simulating manual operation plays an important role in digital transformation, and the key for determining the quality of the robot lies in the reasonability of processing transactions, the smoothness of use and the large-scale concurrency. The robot needs to know when to obtain the issued task information from the console in advance, determine which task should be executed preferentially when the number of tasks in the same planning time is greater than the supported concurrent execution amount, and what should be executed when a part of tasks cannot be downloaded or run because the number of simultaneously downloaded tasks or the running number is too large.

Chinese patent application 202080004549 provides a system and method for performing Robotic Process Automation (RPA) workflows. An indication is received to execute a job scheduled to execute an RPA workflow for a user associated with a user group. The robots are identified from a group of robots associated with the job and having the same access privileges as the user group. The robot is dispatched to a computing device to perform a job for performing the RPA workflow. The method has the defects of unreasonable scheduling and low scheduling efficiency. If the task scheduling is unreasonable, the use of the robot is greatly influenced, including the above invention patents and other prior arts, the task scheduling mainly has the following problems:

1. How to reasonably schedule the multitask plan without causing blockage when the execution time of the multitask plan is the same.

2. How to timely remedy the failure of the downloading task can achieve the effect that a user does not feel.

3. How to consider the multiple functions of inquiring the task in advance, ensuring the task to be downloaded to the local, running the task and the like simultaneously by the robot.

Disclosure of Invention

The invention provides a multithreading concurrent pre-download scheduling algorithm based on a maximum binary tree priority queue in order to improve the capability of a robot for running tasks and enable the robot to be better applied to a flow automation running technology, which is different from a simple single-thread instant download robot scheduling method and ensures the robot to accurately, reliably, timely and reasonably execute the tasks by fusing the priority queue and the multithreading.

In order to achieve the purpose of the invention, the technical scheme provided by the invention is as follows:

the invention relates to a dispatching method of an automatic process robot, which is based on a multithread concurrent pre-download dispatching algorithm of a maximum binary tree priority queue, fuses the priority queue and the multithread to ensure that the robot accurately, reliably and timely executes tasks, wherein a robot background comprises four threads which are concurrently operated and are respectively a task thread to be inquired and downloaded, a task thread to be downloaded, a thread to be inquired and operated and a task thread to be operated, wherein,

Firstly, the task thread to be downloaded is inquired to obtain task information to be operated from a console in advance, the task information is stored in a LEVELDB database and is marked as a task to be processed;

secondly, the task to be processed is taken out of the LEVELDB by the task downloading thread, is put into a downloading pool and is downloaded to the local through the downloading pool;

thirdly, the thread to be operated is inquired from the console, the tasks to be operated are obtained and marked as operable tasks, the operable tasks are placed into a maximum cross-pile priority queue, and a plurality of tasks to be operated are operated in sequence according to the priority;

and fourthly, the task running thread obtains the highest priority task from the maximum binary heap priority queue, puts the highest priority task into a running pool, and runs the task with the highest current priority.

In the first step, the task thread to be downloaded is inquired, the console is accessed once every 10 seconds to perform routing inquiry, and the task with the scheduled running time being less than 30 minutes at present is obtained.

In the second step, the downloading task thread queries the tasks to be processed from the LEVELDB database once every 10 seconds, and sequentially puts the tasks into a downloading pool, wherein the downloading pool defaults to allow 10 tasks to be downloaded simultaneously, and the tasks are repeatedly put into the downloading pool until the tasks are successful due to the downloading failure caused by the capacity exceeding of the downloading pool.

In the third step, the thread to be operated is inquired from the control console every 10 seconds, tasks to be operated within 30 seconds are marked as operable and are placed into a queue, the queue arrangement is realized by a maximum binary tree algorithm, the task with the maximum priority is placed at the head of the queue forever, and the queue compares the newly placed task with the original task and rearranges the newly placed task to ensure that the head is the task with the highest priority; the thread to be operated is inquired from the control console every 10 seconds, tasks to be operated within 30 seconds are marked as operable and are placed into a queue, the queue arrangement is realized by a maximum binary tree algorithm, the task with the maximum priority is placed at the head of the queue forever, and the queue compares the newly placed task with the original task and rearranges the newly placed task to enable the head to be the task with the highest priority; the maximum binary tree algorithm is that maximum binary tree nodes are sequentially stored in a queue from top to bottom, the tree top of the maximum binary tree is the node with the highest priority in the nodes of the whole tree, each time a new task is issued and then enters the queue based on the principle, the queue can automatically sort according to the priority, the task executed firstly is placed at the head of the queue, when the execution time is up, the queue directly throws out the head of the queue to execute, and the rest tasks in the queue are rearranged.

In the fourth step, the running task thread checks whether a queue needing to run exists in the executable task queue every 10 seconds, if yes, the running task thread is taken out and put into a running pool to be executed, and if the execution is finished and no error exists, the task is deleted from the original queue.

In the fourth step, if the running pool is full, tasks are put into the running pool again, errors can occur, the default capacity of the running pool is 1, and a plurality of n tasks with priority degrees n before can be executed simultaneously can also be configured.

The invention also relates to a dispatching system of the automatic process robot, which structurally comprises a console, a module to be downloaded, a task downloading module, a module to be operated, a task operating module, a LEVELDB, a downloading pool, a maximum binary heap queue and an operating pool, wherein,

the query task module is connected with a console, acquires task information to be operated from the console, stores the task information into the LEVELDB, and marks the task information as a task to be processed;

the task downloading module takes out the tasks to be processed from the LEVELDB, puts the tasks into a downloading pool and stores the tasks from the downloading pool to the local;

the query to-be-operated module is connected with the console, queries and acquires a task to be operated from the console, marks the task to be operated as an operable task, and puts the operable task into the maximum cross pile priority queue;

And the task running module obtains a highest priority task from the maximum binary heap priority queue and places the highest priority task into a running pool to ensure that the task with the highest current priority is run.

Based on the technical scheme, compared with the prior art, the dispatching method and the dispatching system of the automatic process robot have the following technical advantages:

1. in the dispatching method of the automatic process robot, due to the existence of a retry mechanism, the task file is ensured not to be missed due to the factors such as excessive current downloaded files or unstable network and the like by continuously downloading again when the task downloading fails, so that the robot has reliability.

2. In the dispatching method of the automatic process robot, due to the existence of the pre-downloading mechanism, the task file is pre-inquired and downloaded to the local, so that the solution time is reserved for abnormal conditions such as downloading failure and the like, and the robot has use friendliness.

3. In the dispatching method of the automatic process robot, due to the existence of a multi-thread concurrent mechanism, the robot has high use efficiency by performing inquiry, downloading and operation in a multi-thread concurrent manner according to service requirements and fully utilizing resources.

4. In the dispatching method of the automatic process robot, due to the existence of the maximum binary heap priority queue, the current task to be executed is screened out through the maximum binary heap priority queue according to the task priority, the planned running time and other factors, so that the dispatching capability of the robot is improved, and the blocking possibility is greatly reduced.

Drawings

Fig. 1 is a schematic flow chart of a scheduling method of an automated flow robot according to the present invention.

Fig. 2 is a schematic flow chart of queue arrangement implemented by using a maximum binary tree algorithm in the scheduling method of the automated flow robot according to the present invention.

Detailed Description

The following describes the scheduling method and scheduling system of an automated flow robot in further detail with reference to the accompanying drawings and specific embodiments, but the scope of the invention is not limited thereby.

As shown in fig. 1 and fig. 2, the present invention relates to a scheduling method for an automated process robot, which integrates a priority queue and multiple threads to ensure accurate, reliable and timely execution of a task by the robot based on a multithread concurrent pre-download scheduling algorithm of a maximum binary tree priority queue, wherein a robot background comprises four threads which run concurrently, namely a task thread to be queried to be downloaded, a task thread to be downloaded, a thread to be queried to be run and a task thread to be run, respectively,

Firstly, the task thread to be downloaded is inquired to obtain task information to be operated from a console in advance, the task information is stored in a LEVELDB database and is marked as a task to be processed; and the task thread to be downloaded is inquired, the console is accessed once every 10 seconds for routing inquiry, and the task with the scheduled running time being less than 30 minutes at present is obtained.

Secondly, the task to be processed is taken out of the LEVELDB by the task downloading thread, is put into a downloading pool and is downloaded to the local through the downloading pool; the downloading task thread inquires the tasks to be processed from the LEVELDB database once every 10 seconds, and sequentially puts the tasks into a downloading pool, wherein the downloading pool defaults to allow 10 tasks to be downloaded simultaneously, and the tasks are repeatedly put into the downloading pool until the tasks are successful due to the downloading failure caused by the capacity exceeding of the downloading pool. By adopting the download failure infinite retry mechanism in the step, the task file is ensured not to be missed due to the factors such as excessive current downloaded files or unstable network, and the reliability of the robot is enhanced. In addition, by inquiring in advance and downloading the task file to the local, the solution time is reserved for abnormal conditions such as downloading failure and the like, and the use friendliness of the robot is improved.

And thirdly, the thread to be operated is inquired from the console, the tasks to be operated are obtained and marked as the operable tasks, the operable tasks are placed into the maximum cross pile priority queue, and the tasks to be operated are operated in sequence according to the priority. And querying the task to be operated in 30 seconds from the console every 10 seconds by the thread to be operated, marking the task to be operated as operable, putting the task into a queue, wherein the queue arrangement is realized by a maximum binary tree algorithm, the task with the maximum priority is always put at the head of the queue, and the newly put task is compared with the original task and rearranged by the queue so that the head is the task with the highest priority. As shown in fig. 2, the specific implementation process of the maximum binary tree priority queue scheduling method is as follows: the maximum binary tree nodes are sequentially stored in the queue from top to bottom, the tree top of the maximum binary tree is the node with the highest priority in the nodes of the whole tree, each new task is issued and then enters the queue based on the principle, the queue can automatically sort according to the priority, the task executed firstly is placed at the head of the queue, when the execution time is up, the queue directly throws out the head of the queue to execute, and the rest tasks in the queue are rearranged.

And fourthly, the running task thread obtains the highest priority task from the maximum binary heap priority queue, and the highest priority task is placed into a running pool to run the task with the highest current priority. And the running task thread checks whether a queue needing to run exists in the executable task queue every 10 seconds, if so, the queue is taken out and put into a running pool for execution, and if no error exists after the execution, the task is deleted from the original queue. If the running pool is full, tasks are put in again, errors can occur, the default capacity of the running pool is 1, and a plurality of n tasks with the priority n before can be executed at the same time.

According to the method, the maximum binary heap priority queue is used for comparatively screening out the tasks to be executed currently according to the task priority, the plan running time and other factors, so that the scheduling capability of the robot is improved, and the blocking possibility is reduced. In addition, according to the method, the functions of inquiry, downloading, operation and the like are executed in a multi-thread concurrent manner according to the service requirements, resources are fully utilized, and the service efficiency of the robot is improved.

The invention also relates to a dispatching system of the automatic process robot, which structurally comprises a console, a module to be downloaded, a task downloading module, a module to be operated, a task operating module, a LEVELDB database, a downloading pool, a maximum binary heap queue and an operating pool, wherein the LEVELDB database is a high-efficiency single-machine Key/Value storage system sourced by Google, and the storage system provides the ordered mapping from Key to Value.

The query task module is connected with a console, acquires task information to be operated from the console, stores the task information into the LEVELDB, and marks the task information as a task to be processed;

the task downloading module takes out the tasks to be processed from the LEVELDB, puts the tasks into a downloading pool and stores the tasks from the downloading pool to the local;

the query to-be-operated module is connected with the console, queries and acquires a task to be operated from the console, marks the task to be operated as an operable task, and puts the operable task into the maximum cross pile priority queue;

and the task running module obtains a highest priority task from the maximum binary heap priority queue and places the highest priority task into a running pool to ensure that the task with the highest current priority is run.

In practice, robot flow automation depends on robot scheduling, and priority queues and multi-thread concurrent scheduling are realized through a maximum binary tree, so that the flexibility and the reasonability of task scheduling are improved.

Claims (8)

1. A dispatching method of an automatic process robot is characterized in that the dispatching method ensures accurate, reliable and timely execution of tasks by the robot by fusing a priority queue and multiple threads based on a multithread concurrent pre-download dispatching algorithm of a maximum binary tree priority queue, a background of the robot comprises four threads which are concurrently operated, namely a task thread to be downloaded, a thread to be operated and a task thread to be operated, wherein,

Firstly, the inquiry task thread to be downloaded obtains task information to be operated from a console in advance, stores the task information into a LEVELDB, and marks the task information as a task to be processed;

step two, the task thread is used for taking out the task to be processed from the LEVELDB, putting the task into a download pool and downloading the task to the local through the download pool;

thirdly, the thread to be operated is inquired from the console, the tasks to be operated are obtained and marked as the operable tasks, the operable tasks are placed into the maximum cross pile priority queue, and the tasks to be operated are operated in sequence according to the priority;

and fourthly, the running task thread obtains the highest priority task from the maximum binary heap priority queue, and the highest priority task is placed into a running pool to run the task with the highest current priority.

2. The method as claimed in claim 1, wherein in the first step, the thread of task to be downloaded is queried to access the console once every 10 seconds to route the query to obtain the task with the scheduled running time less than 30 minutes.

3. The method as claimed in claim 1, wherein in the second step, the task downloading thread queries the task to be processed from the LEVELDB database once every 10 seconds, and sequentially puts the tasks into a downloading pool, the downloading pool allows 10 tasks to be downloaded simultaneously by default, and the failure of downloading due to exceeding the capacity of the downloading pool repeatedly puts the tasks into the downloading pool until the task is successful.

4. The scheduling method of an automated process robot according to claim 1, wherein in the third step, the thread to be queried is queried from the console for tasks to be executed within 30 seconds every 10 seconds, marked as executable, and placed in a queue, and the queue arrangement is implemented by a maximum binary tree algorithm, so that the task with the highest priority is always placed at the head of the queue, and the queue compares the newly placed task with the original task and rearranges the newly placed task so that the head is the task with the highest priority; the maximum binary tree algorithm is that maximum binary tree nodes are sequentially stored in a queue from top to bottom, the tree top of the maximum binary tree is the node with the highest priority in the nodes of the whole tree, each time a new task is issued and then enters the queue based on the principle, the queue can automatically sort according to the priority, the task executed firstly is placed at the head of the queue, when the execution time is up, the queue directly throws out the head of the queue to execute, and the rest tasks in the queue are rearranged.

5. The method according to claim 1, wherein in the fourth step, the task running thread checks every 10 seconds whether a queue that needs to be run exists in the executable task queue, if so, the executable task queue is taken out and put into a running pool for execution, and if the execution is finished and no error exists, the task is deleted from the original queue.

6. The method as claimed in claim 1, wherein in the fourth step, if the running pool is full, the task is put into the running pool again, the default capacity of the running pool is 1, and the running pool can be configured to implement n tasks with priority at the same time.

7. The dispatching system of the automatic process robot is characterized by comprising a console, a module to be downloaded, a task downloading module, a module to be operated, a task operating module, a LEVELDB, a downloading pool, a maximum binary heap queue and an operating pool, wherein the console is connected with the task downloading module,

the query task module is connected with a console, acquires task information to be operated from the console, stores the task information into the LEVELDB, and marks the task information as a task to be processed;

the task downloading module takes out the tasks to be processed from the LEVELDB, puts the tasks into a downloading pool and stores the tasks from the downloading pool to the local;

the query to-be-operated module is connected with the console, queries and acquires a task to be operated from the console, marks the task to be operated as an operable task, and puts the operable task into the maximum cross pile priority queue;

And the task running module obtains a highest priority task from the maximum binary heap priority queue and places the highest priority task into a running pool to ensure that the task with the highest current priority is run.

8. An automatic process robot is characterized in that the automatic process robot comprises a scheduling system, the structure of the scheduling system comprises a control console, a module to be downloaded, a task downloading module, a module to be operated, a task operating module, a LEVELDB database, a downloading pool, a maximum binary heap queue and an operating pool, wherein,

the query task module is connected with a console, acquires task information to be operated from the console, stores the task information into the LEVELDB, and marks the task information as a task to be processed;

the task downloading module takes out the tasks to be processed from the LEVELDB, puts the tasks into a downloading pool and stores the tasks from the downloading pool to the local;

the query to-be-operated module is connected with the console, queries and acquires a task to be operated from the console, marks the task to be operated as an operable task, and puts the operable task into the maximum cross pile priority queue;

and the task running module obtains a highest priority task from the maximum binary heap priority queue and places the highest priority task into a running pool to ensure that the task with the highest current priority is run.

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