DocumentCode
526977
Title
The preemptive EDF optimization based on DNA-Genetic Algorithm
Author
Zhao, Yuan-qing ; Jin, Xian-hua ; Liu, Yong
Author_Institution
Sch. of Comput. & Inf. Eng., Anyang Normal Univ., Anyang, China
Volume
2
fYear
2010
fDate
17-18 July 2010
Firstpage
121
Lastpage
124
Abstract
Earliest Deadline First (EDF) is a favorable algorithm in the field of dynamic scheduling which plans the task scheduling during system running. The CPU utilization of EDF algorithm may achieve to one hundred percent. Although EDF has many excellent performances and is used broadly in actual embedded real-time systems, it has many shortages. In order to reduce the release time of EDF scheduling algorithm and to decrease scheduling spending, the Deoxyribonucleic acid Genetic Algorithm (DNA-GA) is used to optimize the preemptive EDF scheduling algorithm in off-line model. Simulation experiments are carried out to compare the performances. Compared with the scheduling spending before optimized, the scheduling spending after optimized was reduced dramatically and the real-time performance was improved.
Keywords
genetic algorithms; scheduling; CPU utilization; deoxyribonucleic acid genetic algorithm; earliest deadline first; preemptive EDF optimization; task scheduling; Optimization; DNA-GA; EDF; real-time scheduling; real-time system; schedulability;
fLanguage
English
Publisher
ieee
Conference_Titel
Environmental Science and Information Application Technology (ESIAT), 2010 International Conference on
Conference_Location
Wuhan
Print_ISBN
978-1-4244-7387-8
Type
conf
DOI
10.1109/ESIAT.2010.5567289
Filename
5567289
Link To Document