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A Fuzzy Knowledge Based Fault Tolerance Mechanism for Wireless Sensor Networks

A Fuzzy Knowledge Based Fault Tolerance Mechanism for Wireless Sensor Networks

Sasmita Acharya, C. R. Tripathy
Copyright: © 2018 |Volume: 5 |Issue: 1 |Pages: 18
ISSN: 2334-4598|EISSN: 2334-4601|EISBN13: 9781522547013|DOI: 10.4018/IJRSDA.2018010107
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MLA

Acharya, Sasmita, and C. R. Tripathy. "A Fuzzy Knowledge Based Fault Tolerance Mechanism for Wireless Sensor Networks." IJRSDA vol.5, no.1 2018: pp.99-116. http://doi.org/10.4018/IJRSDA.2018010107

APA

Acharya, S. & Tripathy, C. R. (2018). A Fuzzy Knowledge Based Fault Tolerance Mechanism for Wireless Sensor Networks. International Journal of Rough Sets and Data Analysis (IJRSDA), 5(1), 99-116. http://doi.org/10.4018/IJRSDA.2018010107

Chicago

Acharya, Sasmita, and C. R. Tripathy. "A Fuzzy Knowledge Based Fault Tolerance Mechanism for Wireless Sensor Networks," International Journal of Rough Sets and Data Analysis (IJRSDA) 5, no.1: 99-116. http://doi.org/10.4018/IJRSDA.2018010107

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Abstract

Wireless Sensor Networks (WSNs) are the focus of considerable research for different applications. This paper proposes a Fuzzy Knowledge based Artificial Neural Network Routing (ANNR) fault tolerance mechanism for WSNs. The proposed method uses an exponential Bi-directional Associative Memory (eBAM) for the encoding and decoding of data packets and application of Intelligent Sleeping Mechanism (ISM) to conserve energy. A combination of fuzzy rules is used to identify the faulty nodes in the network. The Cluster Head (CH) acts as the data aggregator in the network. It applies the fuzzy knowledge based Node Appraisal Technique (NAT) in order to identify the faulty nodes in the network. The performance of the proposed ANNR is compared with that of Low-Energy Adaptive Clustering Hierarchy (LEACH), Dual Homed Routing (DHR) and Informer Homed Routing (IHR) through simulation.

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