Abstract
The use of the wireless sensor networks (WSNs) should be increasing in different fields. However, the sensor’s size is an important limitation in term of energetic autonomy, and thus of lifetime because battery must be very small. This is the reason why, today, research mainly carries on the energy management in the WSNs, taking into account communications, essentially. In this context, we compare different clustering methods used in the WSNs, particularly EECS, with an adaptive routing algorithm that we named LEA2C. This algorithm is based on topological self-organizing maps. We obtain important gains in term of energy and thus of network lifetime.
Chapter PDF
Similar content being viewed by others
Key words
8. References
Technology Review: 10 Emerging technologies that till change the world (February 2003); http://www.technologyreview.com.
G.J. Pottic and al. Wireless integrated network sensors; Communications of the ACM 43(5), pp. 551–558. (2000).
C. Perkins and E. Royer, Ad-Hoc on-demand distance vector (AODV) routing, The Second IEEE Workshop on Mobile Computing Systems and Applications (WMCSA’99). (1999)
K. Scott and N. Bambos, Routing and channel assignment for low power transmission in PCS; 5th IEEE Int. Conf. on Universal Personal Communications, volume 2. (1996)
S. Ghiasi et al. Optimal energy aware clustering in sensor networks; SENSORS Journal, Vol. 2, Issue 7, pp. 258–269, July 2002.
M. Ye, C. Li, G. Chen and J. Wu, EECS: An energy efficient clustering scheme in wireless sensor networks; IEEE IWSEEASN’05. (2005).
I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, A survey on sensor networks”; IEEE Communications Magazine, Vol. 40, No. 8, pp. 102–114, (2002).
W. Heinzelman, A.P. Chandrakasan and H. Balakrishnan; Energy-efficient communication protocol for wireless microsensor networks; Sensor 2002, 2, pp. 258–269. (2002)
W. Heinzelman, A.P. Chandrakasan and H. Balakrishnan, An application-specific protocol architecture for wireless microsensor networks; IEEE Transactions on Wireless Communications, Vol. 1, No. 4, pp. 660–670, (2002)
E.-S. Jung and N. H. Vaidya, A power control MAC protocol for ad-hoc networks; ACM MOBICOM. (2002).
V. Kawadia and P. R. Kumar, Power control and clustering in Ad Hoc networks; IEEE INFOCOM. (2003)
T. Murata and H. Ishibuchi, Performance evaluation of genetic algorithms for flowshop scheduling problems; 1st IEEE Conference Evolutionary Computation, volume 2. (1994)
A. Juha and A. Esa, Clustering of the self-organizing map; IEEE Tractions On Neural Networks, volume 11, no 3, (2000)
David L. Davies and Donald W. Bouldin, A cluster separation measure; IEEE Trans. on Pattern Analysis and Machine Intelligence, PAMI-1(2): pp. 224–227. (1979)
E. Alhoniemi and al. SOM Toolbox, (2000). http://www.cis.hut.fi/projects/somtoolbox/
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 International Federation for Information Processing
About this paper
Cite this paper
Dehni, L., Krief, F., Bennani, Y. (2006). Power Control and Clustering in Wireless Sensor Networks. In: Al Agha, K., Guérin Lassous, I., Pujolle, G. (eds) Challenges in Ad Hoc Networking. Med-Hoc-Net 2005. IFIP International Federation for Information Processing, vol 197. Springer, Boston, MA. https://doi.org/10.1007/0-387-31173-4_4
Download citation
DOI: https://doi.org/10.1007/0-387-31173-4_4
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-31171-5
Online ISBN: 978-0-387-31173-9
eBook Packages: Computer ScienceComputer Science (R0)