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
optimisation 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
%0 Journal Article
%1 Tseng:2005:CSI
%A Tseng, Tzu-Laing (Bill)
%A Liang, Wen-Yau
%A Huang, Chun-Che
%A Chian, Tsung-Yu
%D 2005
%J Computer Standards & Interfaces
%K Embedded Software algorithms, components genetic programming, system,
%N 6
%P 621--635
%R doi:10.1016/j.csi.2004.12.001
%T Applying genetic algorithm for the development of the
components-based embedded system
%U http://www.sciencedirect.com/science/article/B6TYV-4F5S6C2-1/2/47d01c7228b5c5fa4f02db5227be3171
%V 27
%X 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
optimisation 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
@article{Tseng:2005:CSI,
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
optimisation 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},
added-at = {2008-06-19T17:46:40.000+0200},
author = {Tseng, Tzu-Laing (Bill) and Liang, Wen-Yau and Huang, Chun-Che and Chian, Tsung-Yu},
biburl = {https://www.bibsonomy.org/bibtex/2d825cf93776ae64cd9dc03e7f4dd6390/brazovayeye},
doi = {doi:10.1016/j.csi.2004.12.001},
interhash = {8ffc1d0e0073995aead3b002cfa09eef},
intrahash = {d825cf93776ae64cd9dc03e7f4dd6390},
journal = {Computer Standards \& Interfaces},
keywords = {Embedded Software algorithms, components genetic programming, system,},
month = {June},
number = 6,
owner = {wlangdon},
pages = {621--635},
timestamp = {2008-06-19T17:53:20.000+0200},
title = {Applying genetic algorithm for the development of the
components-based embedded system},
url = {http://www.sciencedirect.com/science/article/B6TYV-4F5S6C2-1/2/47d01c7228b5c5fa4f02db5227be3171},
volume = 27,
year = 2005
}