Database Reference
In-Depth Information
and others. Finally, spectral clustering methods using eigen decomposi-
tion techniques have been proposed by Chatzigiannakis
et al.
[13].
5. Conclusions
Distributed data mining will continue to play an important role in
analysis of data in modern sensor networks. Since computation is sensor
networks is greatly constrained by the various challenges facing a mod-
ern WSN, a need breed of data mining algorithms need to be developed
which can co-analyze the data sensed by all the sensors by paying care-
ful attention to computation, communication and any other constraints.
To circumvent this problem, several algorithms have been proposed that
can effectively handle the harsh environments of WSNs. In this chapter
we have discussed three such topics related to data mining in sensor net-
works, viz., clustering, classification and outlier detection. Of course, we
have only been able to scratch the surface of this vast area of research.
With WSNs being deployed in many realms of life for monitoring pur-
poses, distributed data mining is likely to play a critical role and thus
offers plenty of opportunities for both novel algorithm development and
data analysis.
Acknowledgements
The second author acknowledges funding by the DFG, Collaborative
Research Center SFB 876, project B3.
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