Abstract
We present a light-weight event classification scheme, called Identifier based Graph Neuron (IGN). This scheme is based on highly distributed associative memory. The local state of an event is recognize through locally assigned identifiers. These nodes run an iterative algorithm to coordinate with other nodes to reach a consensus about the global state of the event. The proposed approach not only conserves the power resources of sensor nodes but is also effectively scalable to large scale WSNs.
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© 2012 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering
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Imran, N., Khan, A.I. (2012). Scalable and Efficient Pattern Recognition Classifier for WSN. In: Sénac, P., Ott, M., Seneviratne, A. (eds) Mobile and Ubiquitous Systems: Computing, Networking, and Services. MobiQuitous 2010. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 73. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29154-8_26
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DOI: https://doi.org/10.1007/978-3-642-29154-8_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29153-1
Online ISBN: 978-3-642-29154-8
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