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Bacteria Foraging Algorithm for Optimal Topology Construction in Wireless Sensor Networks

Bacteria Foraging Algorithm for Optimal Topology Construction in Wireless Sensor Networks

Pitchaimanickam Bose
Copyright: © 2022 |Volume: 13 |Issue: 1 |Pages: 17
ISSN: 1947-8283|EISSN: 1947-8291|EISBN13: 9781799885405|DOI: 10.4018/IJAMC.292512
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MLA

Bose, Pitchaimanickam. "Bacteria Foraging Algorithm for Optimal Topology Construction in Wireless Sensor Networks." IJAMC vol.13, no.1 2022: pp.1-17. http://doi.org/10.4018/IJAMC.292512

APA

Bose, P. (2022). Bacteria Foraging Algorithm for Optimal Topology Construction in Wireless Sensor Networks. International Journal of Applied Metaheuristic Computing (IJAMC), 13(1), 1-17. http://doi.org/10.4018/IJAMC.292512

Chicago

Bose, Pitchaimanickam. "Bacteria Foraging Algorithm for Optimal Topology Construction in Wireless Sensor Networks," International Journal of Applied Metaheuristic Computing (IJAMC) 13, no.1: 1-17. http://doi.org/10.4018/IJAMC.292512

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Abstract

Topology control is a significant method to reduce energy consumption and prolong the network lifetime. Connected Dominated Sets (CDS) are the emerging technologies to construct the energy- efficient optimal topology. Traditional topology construction algorithms are not utilized suitable optimization techniques for finding the optimum location of the active nodes in the networks. In this paper, Bacteria Foraging Algorithm (BFA) identifies the optimal location for active nodes to form the virtual backbone of the network. Residual energy and network connectivity are considered to evaluate the fitness function. The performance of the BFA is compared with other algorithms namely A3, A1, Genetic Algorithm (GA), and Gravitational Search Algorithm (GSA) algorithms for considering the performance metrics of the active nodes, residual energy, and connected sensing area coverage. Simulation results show that the proposed methodology performs well for reducing energy consumption and improving the connected sensing coverage area in the wireless sensor network.