Multi-task priority scheduling method for attendance machine of internet of things

Abstract

The invention relates to a multi-task priority scheduling method for an attendance machine of the internet of things. The method comprises the following steps: setting Priority as a task importance factor for each task of the attendance machine, wherein Urgency represents emergency; when a new task arrives, judging whether the sum of the central processing unit (CPU) total occupation ratio of the new task and the original multiple tasks exceeds the upper bound by 1.0 by using a task admittance control module; if the sum of the CPU total occupation ratio of the new task and the original multiple tasks does not exceed the upper bound by 1.0, admitting the work; if the sum of the CPU total occupation ratio of the new task and the original multiple tasks exceeds the upper bound by 1.0, comparing the importance priority of the task with the highest priority between the new task and the original multiple tasks of the system; if the importance priority of the new task is low, refusing the new task; if the importance priority of the new task is high, removing the task at the tail of Priority_first in first out (FIFO) queue and supplementing a new task; and realizing task scheduling. The invention provides the multi-task priority scheduling method for the attendance machine of the internet of things, which takes importance and urgency into consideration and has high scheduling efficiency.

Description

technical field [0001] The invention relates to the field of attendance machines, in particular to a multi-task scheduling method for an Internet of Things attendance machine. Background technique [0002] Linux follows the POSIX.1003.1b real-time extension standard, realizes the concept of real-time processes, and supports two real-time scheduling strategies, SCHED_FIFO and SCHED_RR. However, the SCHED_FIFO policy simply schedules tasks based on the principle of first-come, first-served, without considering the execution time of tasks, so that urgent tasks cannot be executed first, thus missing their execution time, resulting in errors in running results or degradation of service quality. The SCHED_RR strategy embodies the idea of ​​resource sharing, which can ensure that each real-time task gets an equal execution opportunity, but also because the execution time of the task is not considered, the urgent task cannot be completed on schedule. When the system is overloaded, ...

AI Technical Summary

Problems solved by technology

[0004] (1) It is not possible to directly map the constraints on other importance of tasks to the scheduling priority. In the existing algorithms, the criteria used to determine the priority are relatively simple and one-sided. For example, the RM algorithm only uses The period of the task determines the priority, and the EDF algorithm only determines the priority by the execution time of the task;

[0005] (2) Important tasks are not necessarily urgent tasks, and urgent tasks are not necessarily important tasks. However, the implementation of the current priority scheduling algorithm generally separates the attributes of these two tasks, which easily leads to the failure to guarantee the execution performance of important tasks. For example, in a scheduling algorithm that determines priority based on task execution time; or it is easy to cause the execution time of urgent tasks to be unsatisfied, such as in a scheduling algorithm that determines priority based on inherent attributes such as periods, important tasks cannot be executed;