A Low-Power Scheduling Method for Periodically Dependent Tasks in Open Numerical Control Systems

A technology that depends on tasks and numerical control systems. It is applied in general control systems, control/regulation systems, and program control. It can solve problems such as not considering task dependencies, and achieve the goals of improving local search capabilities, low energy consumption, and reducing system energy consumption. Effect

Active Publication Date: 2022-05-31
SHENYANG GOLDING NC & INTELLIGENCE TECH CO LTD
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is not suitable for multi-core platform CNC systems because it does not consider the dependencies between tasks.

Method used

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  • A Low-Power Scheduling Method for Periodically Dependent Tasks in Open Numerical Control Systems
  • A Low-Power Scheduling Method for Periodically Dependent Tasks in Open Numerical Control Systems
  • A Low-Power Scheduling Method for Periodically Dependent Tasks in Open Numerical Control Systems

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Embodiment Construction

[0053] (1) In the system task set T, all the tasks whose predecessors are set as empty sets are added to the task set sTasks.

[0055] (3) When sTasks is an empty set, repeat steps 1 and 2 until the task set T is an empty set and end the operation.

[0057] (5) Repeat the above steps until an initial population with a population size of Psize is generated.

[0060]

[0061]

[0064]

[0066] The selection operation is to select high-quality individuals from the population and eliminate low-quality individuals according to fitness. The present invention is based on

[0074] (2) If the loop termination condition i

[0076] (4) If f(S')>f(S), then output k, BS=S', and a new solution with a larger fitness value replaces the initial solution,

[0078] (5) If k>4, then return to step 2; otherwise, return to step (3), enter the next neighborhood structure to search.

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Abstract

The invention discloses a low-power scheduling method suitable for periodic dependent tasks of an open numerical control system. The steps are as follows: Step 1: Initialize genetic algorithm parameters; Step 2: Use directed acyclic graph to construct periodic dependent tasks Step 3: Establish the objective function of scheduling tasks, set constraints, and obtain the optimization model; Step 4: Use the improved genetic algorithm to solve the optimization model, and obtain the task scheduling sequence and the power supply voltage that the processor needs to configure. The invention considers the periodic dependencies of tasks, and designs an initial population generation algorithm and cross operation that can maintain the topology of tasks. Compared with other algorithms, it not only has a faster search speed but also has a faster scheduling scheme corresponding to the optimal solution. low energy consumption. The invention performs a variable neighborhood search on the optimal individual generated by the genetic algorithm to improve the local search ability of the algorithm, and the algorithm can effectively reduce the energy consumption of the system under the premise of ensuring the schedulability of the system.

Description

A Low-Power Scheduling Method for Periodically Dependent Tasks in Open CNC Systems technical field The present invention relates to the real-time scheduling of multi-core platform real-time system field tasks, specifically applicable to open digital A low-power scheduling method for periodically dependent tasks in the control system. Background technique [0002] As a typical real-time system, the key functions of an open CNC system are realized by real-time tasks. CNC The system not only requires the completion of the task within the deadline, but also guarantees the correct execution of the task. With the various With the increase in functional requirements, the application of multi-core processors is becoming more and more extensive. Task scheduling on multi-core platforms compared to uniprocessors It needs to consider behaviors such as migration and communication between processors, so the system energy consumption is correspondingly higher and higher. high ene...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G05B19/408
CPCG05B19/4086G05B2219/35356Y02P70/10
Inventor 郭锐锋彭阿珍胡毅吴昊天王楚婷
Owner SHENYANG GOLDING NC & INTELLIGENCE TECH CO LTD
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