Low-Power Task Scheduling Algorithm for the Multicore Processor System Based on the Genetic Algorithm

In order to solve the periodic hard real-time tasks with dependencies on multicore processors, the author proposes a low-power task scheduling algorithm for multicore processor systems based on the genetic algorithm. This method first uses the RDAG algorithm to separate the tasks and then takes the...

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Bibliographic Details
Published in:Wireless communications and mobile computing Vol. 2022; no. 1
Main Author: Li, Xianning
Format: Journal Article
Language:English
Published: Oxford Hindawi 2022
John Wiley & Sons, Inc
Subjects:
Communication
Completion time
Embedded systems
Energy consumption
Genetic algorithms
Heuristic
Microprocessors
Power consumption
Power management
Resource utilization
Response time (computers)
Scheduling
Supercomputers
Task scheduling
ISSN:1530-8669, 1530-8677
Online Access:Get full text
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Summary:In order to solve the periodic hard real-time tasks with dependencies on multicore processors, the author proposes a low-power task scheduling algorithm for multicore processor systems based on the genetic algorithm. This method first uses the RDAG algorithm to separate the tasks and then takes the lowest power consumption as the principle; a genetic algorithm is used to determine the task mapping. Experimental results show that based on the power consumption model of Intel PXA270, several random task sets are used for simulation experiments, which shows that this method saves 20% to 30% of the energy consumption compared with the existing methods. This method effectively shortens the completion time of tasks, improves the utilization efficiency of multicore system resources, improves the parallel computing capability of multicore systems, reduces the average response time of tasks, and improves the throughput and resource utilization of multicore systems.
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ISSN:1530-8669
1530-8677
DOI:10.1155/2022/4363937