Abstract
This paper proposes an optimized topology control scheme (GA-OTC) based on a genetic algorithm for clustering-based hierarchical wireless sensor networks (WSNs). By using a genetic algorithm, we can obtain optimal solutions to multiple objective functions according to the two criteria of both balanced energy consumption and minimized total energy consumption of cluster heads while the entire WSNs field is covered by clusters. Through performance evaluation studies, we show that GA-OTC achieves desirable properties.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 385-392 |
| Number of pages | 8 |
| Volume | 4490 LNCS |
| Edition | PART 4 |
| Publication status | Published - 2007 Dec 1 |
| Event | 7th International Conference on Computational Science, ICCS 2007 - Beijing, China Duration: 2007 May 27 → 2007 May 30 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Number | PART 4 |
| Volume | 4490 LNCS |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 7th International Conference on Computational Science, ICCS 2007 |
|---|---|
| Country | China |
| City | Beijing |
| Period | 07/5/27 → 07/5/30 |
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Keywords
- GA-OTC
- Multiple objective functions
- WSNs
ASJC Scopus subject areas
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science
Cite this
Genetic algorithmic topology control for two-tiered wireless sensor networks. / Lee, Donghwan; Lee, Wonjun; Kim, Joongheon.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4490 LNCS PART 4. ed. 2007. p. 385-392 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4490 LNCS, No. PART 4).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Genetic algorithmic topology control for two-tiered wireless sensor networks
AU - Lee, Donghwan
AU - Lee, Wonjun
AU - Kim, Joongheon
PY - 2007/12/1
Y1 - 2007/12/1
N2 - This paper proposes an optimized topology control scheme (GA-OTC) based on a genetic algorithm for clustering-based hierarchical wireless sensor networks (WSNs). By using a genetic algorithm, we can obtain optimal solutions to multiple objective functions according to the two criteria of both balanced energy consumption and minimized total energy consumption of cluster heads while the entire WSNs field is covered by clusters. Through performance evaluation studies, we show that GA-OTC achieves desirable properties.
AB - This paper proposes an optimized topology control scheme (GA-OTC) based on a genetic algorithm for clustering-based hierarchical wireless sensor networks (WSNs). By using a genetic algorithm, we can obtain optimal solutions to multiple objective functions according to the two criteria of both balanced energy consumption and minimized total energy consumption of cluster heads while the entire WSNs field is covered by clusters. Through performance evaluation studies, we show that GA-OTC achieves desirable properties.
KW - GA-OTC
KW - Multiple objective functions
KW - WSNs
UR - http://www.scopus.com/inward/record.url?scp=38149060096&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=38149060096&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:38149060096
SN - 9783540725893
VL - 4490 LNCS
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 385
EP - 392
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -