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Fuzzy Logic Based Hardware Faulty Node Detection And Redundancy Mechanism For Wireless Sensor Networks
N. Priya1, P.B. Pankajavalli2

1N. Priya*, Department of Computer Science, Bharathiar University, Coimbatore, India.
2P.B. Pankajavalli, Department of Computer Science, Bharathiar University, Coimbatore, India.

Manuscript received on September 21, 2020. | Revised Manuscript received on November 02, 2020. | Manuscript published on November 10, 2021. | PP: 45-52 | Volume-10 Issue-1, November 2020 | Retrieval Number: 100.1/ijitee.A80741110120| DOI: 10.35940/ijitee.A8074.1110120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: In recent years, applications of wireless sensor network (WSN) is emerged as the revolutionary phase in many functional areas such as industrial, environmental, business, military and many need based self-intelligent real time systems. Some of the applications require data communication from harsh physical environment which poses great challenges to wireless sensor networks. The deployment of these sensor nodes in the hostile environment cause sensor nodes failure. This demands fast, redundant fault tolerant, energy saving approaches which meet the requirements of most recurring failures and path disruption scenarios in wireless sensor networks. Hence there is need for fuzzy knowledge based fault detection because traditional fault detection methods are endured by low detection accuracy. The proposed fuzzy knowledge based faulty node detection and redundancy approach (FNDRA) is presented to identify the faulty nodes and provide the management method for nodes reusability. The effectiveness of the proposed approach was implemented using Matlab and the results shows that the proposed approach meets the constraints and requirements of most common and predicated critical failure scenarios. 
Keywords: Wireless sensor network (WSNs), Hardware faults, Fault Detection, Redundancy.
Scope of the Article: Fuzzy Logics