Abstract
The embedded system is primarily designed for a particular piece of equipment and it varies on a case-by-case basis. The functionality is required to be specific to the equipment and consequently the application domain is limited. The software embedded in the system also faces problem due to the limitation of the hardware capacity. It is necessary for the designers to consider the hardware capacity and software specification simultaneously while an embedded system is developed. If hardware and software are taken into account concurrently, the design applicability and efficiency are decreased. The evolutionary computing (EC), which comprises techniques of evolutionary programming, evolution strategies, genetic algorithms, and genetic programming has been widely used to solve optimization problems for large scale and complex systems. It is capable to escape not only from local optima due to population based approach, but also from unbiased nature, which enables it to perform well in a situation with little domain knowledge. Therefore, this study proposes an evolutionary approach that applies the characteristics of software reuse, the metrics for the object-oriented concept, and the genetic algorithm to effectively manage and optimize the embedded system. This approach is implemented in the World Wide Web environment. Numerous results associated with performance enhancements of the algorithm are presented in this paper.
| Original language | English |
|---|---|
| Pages (from-to) | 621-635 |
| Number of pages | 15 |
| Journal | Computer Standards and Interfaces |
| Volume | 27 |
| Issue number | 6 |
| DOIs | |
| Publication status | Published - 2005 Jun 1 |
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All Science Journal Classification (ASJC) codes
- Software
- Hardware and Architecture
- Law
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Applying genetic algorithm for the development of the components-based embedded system. / Tseng, Tzu Laing; Liang, Wen-Yau; Huang, Chun Che; Chian, Tsung Yu.
In: Computer Standards and Interfaces, Vol. 27, No. 6, 01.06.2005, p. 621-635.Research output: Contribution to journal › Article
TY - JOUR
T1 - Applying genetic algorithm for the development of the components-based embedded system
AU - Tseng, Tzu Laing
AU - Liang, Wen-Yau
AU - Huang, Chun Che
AU - Chian, Tsung Yu
PY - 2005/6/1
Y1 - 2005/6/1
N2 - The embedded system is primarily designed for a particular piece of equipment and it varies on a case-by-case basis. The functionality is required to be specific to the equipment and consequently the application domain is limited. The software embedded in the system also faces problem due to the limitation of the hardware capacity. It is necessary for the designers to consider the hardware capacity and software specification simultaneously while an embedded system is developed. If hardware and software are taken into account concurrently, the design applicability and efficiency are decreased. The evolutionary computing (EC), which comprises techniques of evolutionary programming, evolution strategies, genetic algorithms, and genetic programming has been widely used to solve optimization problems for large scale and complex systems. It is capable to escape not only from local optima due to population based approach, but also from unbiased nature, which enables it to perform well in a situation with little domain knowledge. Therefore, this study proposes an evolutionary approach that applies the characteristics of software reuse, the metrics for the object-oriented concept, and the genetic algorithm to effectively manage and optimize the embedded system. This approach is implemented in the World Wide Web environment. Numerous results associated with performance enhancements of the algorithm are presented in this paper.
AB - The embedded system is primarily designed for a particular piece of equipment and it varies on a case-by-case basis. The functionality is required to be specific to the equipment and consequently the application domain is limited. The software embedded in the system also faces problem due to the limitation of the hardware capacity. It is necessary for the designers to consider the hardware capacity and software specification simultaneously while an embedded system is developed. If hardware and software are taken into account concurrently, the design applicability and efficiency are decreased. The evolutionary computing (EC), which comprises techniques of evolutionary programming, evolution strategies, genetic algorithms, and genetic programming has been widely used to solve optimization problems for large scale and complex systems. It is capable to escape not only from local optima due to population based approach, but also from unbiased nature, which enables it to perform well in a situation with little domain knowledge. Therefore, this study proposes an evolutionary approach that applies the characteristics of software reuse, the metrics for the object-oriented concept, and the genetic algorithm to effectively manage and optimize the embedded system. This approach is implemented in the World Wide Web environment. Numerous results associated with performance enhancements of the algorithm are presented in this paper.
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UR - http://www.scopus.com/inward/citedby.url?scp=18844441697&partnerID=8YFLogxK
U2 - 10.1016/j.csi.2004.12.001
DO - 10.1016/j.csi.2004.12.001
M3 - Article
AN - SCOPUS:18844441697
VL - 27
SP - 621
EP - 635
JO - Computer Standards and Interfaces
JF - Computer Standards and Interfaces
SN - 0920-5489
IS - 6
ER -