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Cluster Computing

Erschienen in:

09.03.2018

Genetic algorithm based sensor node classifications in wireless body area networks (WBAN)

verfasst von: K. Kalaiselvi, G. R. Suresh, V. Ravi

Erschienen in: Cluster Computing | Sonderheft 5/2019

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Abstract

Wireless body area network (WBAN) is a promising methodology in present health care systems to monitor, detect, predict and diagnose the disease in people. The performance of the WBAN network is affected by un-trusted nodes in WBAN network. The un-trusted sensor nodes are formed in WBAN network due to the attackers from outside the world. In this paper, sensor node classification algorithm is proposed which incorporates ANFIS classifier based trusted and un-trusted sensor nodes detection and classification system is proposed inorder to improve the efficiency of the WBAN networks. This proposed system constitutes feature extraction and classification modules. The trust features are extracted from sensor nodes and these exracted features are optimized using genetic algorithm. The performance of the WBAN network is analyzed in terms of classification rate, packet delivery ratio and latency.

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Titel: Genetic algorithm based sensor node classifications in wireless body area networks (WBAN)
verfasst von: K. Kalaiselvi
G. R. Suresh
V. Ravi
Publikationsdatum: 09.03.2018
Verlag: Springer US
Erschienen in: Cluster Computing / Ausgabe Sonderheft 5/2019
Print ISSN: 1386-7857
Elektronische ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-018-1770-6

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