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Using Kohonen’s Self-Organizing Map for Clustering in Sensor Networks
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 1 - Number 24 |
| Year of Publication: 2010 |
| Authors: Chiranjib Patra |
10.5120/552-722
|
Chiranjib Patra . Using Kohonen’s Self-Organizing Map for Clustering in Sensor Networks. International Journal of Computer Applications. 1, 24 ( February 2010), 80-81. DOI=10.5120/552-722
Abstract
Clustering is a technique that can be used to classify objects (e.g. individuals, quadrates, species etc). While Kohonen's Self-Organizing Map (SOM) networks have been successfully applied as a classification tool to various problem domains, including Mobile Ad-hoc networks, sensor networks, robot control and medical diagnosis, its potential as a robust substitute for clustering analysis remains relatively unresearched. In this paper, SOM is used to cluster the sensor nodes dispersed in non-homogeneous space so that efficient transmit power management of the nodes can be made.
References
- Narayanswamy.S, Kawada.V, Srenivas.R.S, and Kumar.R.S: Power Control in Ad-Hoc networks: Theory, Architecture, Algorithm, and Implementation of the COMPOW protocol, European Wireless Conference,(2002)
- SDL component Suite,"Kohonen Network-Background Information", http://www.lohninger.com/helpsuite/kohonen_network_background_information.htm.
- Simon Haykin, Neural Networks A comprehensive Foundation ,Pearson Education, New Delhi ,2007
- Kawadia.V, Kumar P.R.: power control and clustering Ad Hoc Networks. IEEE INFOCOM,(2003)
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