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Moth-Flame Optimization Algorithm for Efficient Cluster Head Selection in Wireless Sensor Networks

Moth-Flame Optimization Algorithm for Efficient Cluster Head Selection in Wireless Sensor Networks

Pitchaimanickam Bose
Copyright: © 2022 |Volume: 13 |Issue: 1 |Pages: 14
ISSN: 1947-9263|EISSN: 1947-9271|EISBN13: 9781683181514|DOI: 10.4018/IJSIR.302604
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MLA

Bose, Pitchaimanickam. "Moth-Flame Optimization Algorithm for Efficient Cluster Head Selection in Wireless Sensor Networks." IJSIR vol.13, no.1 2022: pp.1-14. http://doi.org/10.4018/IJSIR.302604

APA

Bose, P. (2022). Moth-Flame Optimization Algorithm for Efficient Cluster Head Selection in Wireless Sensor Networks. International Journal of Swarm Intelligence Research (IJSIR), 13(1), 1-14. http://doi.org/10.4018/IJSIR.302604

Chicago

Bose, Pitchaimanickam. "Moth-Flame Optimization Algorithm for Efficient Cluster Head Selection in Wireless Sensor Networks," International Journal of Swarm Intelligence Research (IJSIR) 13, no.1: 1-14. http://doi.org/10.4018/IJSIR.302604

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Abstract

Network lifetime and energy consumption are the important requirement of wireless sensor networks. The sensor network is mainly used for the military and civil applications, habitat monitoring. These tasks consume more energy for the data processing and directly affect the network lifetime. Clustering methodology provides a better solution for prolonging the network lifetime and reducing the energy consumption. In this paper, moth flame optimization algorithm is proposed in LEACH-C algorithm for identifying the suitable cluster head in wireless sensor networks. The proposed methodology uses the navigation method of moths for balancing the exploration and exploitation phases in the optimization process. The residual energy of the node and distance between the cluster head and sensor node are utilized to calculate the fitness function. The proposed methodology is evaluated with the help of performance metrics of network lifetime, energy consumption and number of alive nodes. The proposed methodology prolongs the network lifetime and reduces the energy consumption.

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