Replica Node Detection using Metaheuristic Algorithms in Wireless Sensor Networks

Replica Node Detection using Metaheuristic Algorithms in Wireless Sensor Networks
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© 2022 by IJETT Journal
Volume-70 Issue-5
Year of Publication : 2022
Authors : R. Bhaskaran, K. Ramamoorthy, C. Fancy, T. Jayasankar
DOI :  10.14445/22315381/IJETT-V70I5P237

How to Cite?

R. Bhaskaran, K. Ramamoorthy, C. Fancy, T. Jayasankar, "Replica Node Detection using Metaheuristic Algorithms in Wireless Sensor Networks," International Journal of Engineering Trends and Technology, vol. 70, no. 5, pp. 339-345, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I5P237

Abstract
Clustering is one of the essential techniques to prolong the network life span in wireless sensor networks (WSNs). It comprises the clustering of mote into clusters and selecting cluster heads (CHs) for all the clusters. The main challenge in WSNs is to choose the proper CH. However, separate clusters are usually chosen; overlaying clusters are significant for the device to discover its importance in a certain process of device localization time-synchronization and inter-cluster routing. Detection of the replicate node is a significant task in overlaying clusters. This article seeks to detect replicate nodes in overlaying clusters depending on two techniques, adaptive weighted clustering (AWC) algorithm and hybrid bat algorithm with differential equation (BA-DE). The first method utilizes RFID for distinctive identification of the device, and the secondary process identifies to replicate through finding the location through Triangulation and RSSI (received signal strength) technique. These techniques are executed, and effectiveness is contrasted with non-clustered and multicast methods: Line selected multicast, Randomized multicast, K-coverage WSN, and FTVBT. The hybrid bat algorithm with differential equation (BA-DE) shows lesser communication overhead and an improved rate of detection, lesser storage cost, energy consumption, packet loss, and delay under diverse aspects because of its deterministic method.

Keywords
Clustering, Routing, Adaptive weighted clustering, Multicast, Differential equation.

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