Abstract
This paper presents a new approach to optimization of an energy-constrained modulation scheme for wireless sensor networks by taking advantage of a novel bio-inspired optimization algorithm. The algorithm is inspired by Wright's shifting balance theory (SBT) of evolution in population genetics. The total energy consumption of an energy-constrained modulation scheme is minimized by using the new SBT-based optimization algorithm. The results obtained by this new algorithm are compared with other popular optimization algorithms. Numerical experiments are performed to demonstrate that the SBT-based algorithm could be used as an efficient optimizer for solving the optimization problems arising from currently emerging energy-efficient wireless sensor networks.
| Language | English |
|---|---|
| Title of host publication | CEC 2008 (IEEE World Congress on Computational Intelligence) |
| Subtitle of host publication | IEEE Congress on Evolutionary Computation |
| Publisher | IEEE |
| Pages | 2749-2756 |
| Number of pages | 8 |
| ISBN (Print) | 978-1-4244-1822-0 |
| DOIs | |
| Publication status | Published - 14 Nov 2008 |
| Event | 2008 IEEE Congress on Evolutionary Computation, CEC 2008 - Hong Kong, United Kingdom Duration: 1 Jun 2008 → 6 Jun 2008 |
Conference
| Conference | 2008 IEEE Congress on Evolutionary Computation, CEC 2008 |
|---|---|
| Country | United Kingdom |
| City | Hong Kong |
| Period | 1/06/08 → 6/06/08 |
Fingerprint
Keywords
- modulation
- optimisation
- wireless sensor networks
- home automation
- radio frequency
Cite this
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A novel shifting balance theory-based approach to optimization of an energy-constrained modulation scheme for wireless sensor networks. / Yang, Erfu; Barton, Nick H.; Arslan, Tughrol; Erdogan, Ahmel T.
CEC 2008 (IEEE World Congress on Computational Intelligence): IEEE Congress on Evolutionary Computation. IEEE, 2008. p. 2749-2756.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution book
TY - GEN
T1 - A novel shifting balance theory-based approach to optimization of an energy-constrained modulation scheme for wireless sensor networks
AU - Yang, Erfu
AU - Barton, Nick H.
AU - Arslan, Tughrol
AU - Erdogan, Ahmel T.
PY - 2008/11/14
Y1 - 2008/11/14
N2 - This paper presents a new approach to optimization of an energy-constrained modulation scheme for wireless sensor networks by taking advantage of a novel bio-inspired optimization algorithm. The algorithm is inspired by Wright's shifting balance theory (SBT) of evolution in population genetics. The total energy consumption of an energy-constrained modulation scheme is minimized by using the new SBT-based optimization algorithm. The results obtained by this new algorithm are compared with other popular optimization algorithms. Numerical experiments are performed to demonstrate that the SBT-based algorithm could be used as an efficient optimizer for solving the optimization problems arising from currently emerging energy-efficient wireless sensor networks.
AB - This paper presents a new approach to optimization of an energy-constrained modulation scheme for wireless sensor networks by taking advantage of a novel bio-inspired optimization algorithm. The algorithm is inspired by Wright's shifting balance theory (SBT) of evolution in population genetics. The total energy consumption of an energy-constrained modulation scheme is minimized by using the new SBT-based optimization algorithm. The results obtained by this new algorithm are compared with other popular optimization algorithms. Numerical experiments are performed to demonstrate that the SBT-based algorithm could be used as an efficient optimizer for solving the optimization problems arising from currently emerging energy-efficient wireless sensor networks.
KW - modulation
KW - optimisation
KW - wireless sensor networks
KW - home automation
KW - radio frequency
UR - http://www.scopus.com/inward/record.url?scp=55749109677&partnerID=8YFLogxK
U2 - 10.1109/CEC.2008.4631167
DO - 10.1109/CEC.2008.4631167
M3 - Conference contribution book
SN - 978-1-4244-1822-0
SP - 2749
EP - 2756
BT - CEC 2008 (IEEE World Congress on Computational Intelligence)
PB - IEEE
ER -