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Malevolent Node Detection Based on Network Parameters Mining in Wireless Sensor Networks

Malevolent Node Detection Based on Network Parameters Mining in Wireless Sensor Networks

Sunitha R., Chandrika J.
Copyright: © 2021 |Volume: 13 |Issue: 5 |Pages: 15
ISSN: 1941-6210|EISSN: 1941-6229|EISBN13: 9781799867524|DOI: 10.4018/IJDCF.20210901.oa8
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MLA

Sunitha R., and Chandrika J. "Malevolent Node Detection Based on Network Parameters Mining in Wireless Sensor Networks." IJDCF vol.13, no.5 2021: pp.130-144. http://doi.org/10.4018/IJDCF.20210901.oa8

APA

Sunitha R. & Chandrika J. (2021). Malevolent Node Detection Based on Network Parameters Mining in Wireless Sensor Networks. International Journal of Digital Crime and Forensics (IJDCF), 13(5), 130-144. http://doi.org/10.4018/IJDCF.20210901.oa8

Chicago

Sunitha R., and Chandrika J. "Malevolent Node Detection Based on Network Parameters Mining in Wireless Sensor Networks," International Journal of Digital Crime and Forensics (IJDCF) 13, no.5: 130-144. http://doi.org/10.4018/IJDCF.20210901.oa8

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Abstract

The exponential growth of the internet of things and united applications have renewed the scholarly world to grow progressively proficient routing strategies. Quality of service (QoS) and reduced power consumption are the major requirements for effective data transmission. The larger part of the applications nowadays including internet of things (IoT) communication request power effective and QoS-driven WSN configuration. In this paper, an exceptionally strong and effective evolutionary computing allied WSN routing convention is designed for QoS and power effectiveness. The proposed routing convention includes proficient capacity called network condition-based malicious node detection. It adventures or mines the dynamic node/network parameters to recognize malignant nodes. Experimentation is done using network simulator tool NS2. Results ensure that the proposed routing model accomplishes higher throughput, low energy utilization, and low delay that sustains its suitability for real-time WSN.