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Improving Network Longevity in Wireless Sensor Networks Using an Evolutionary Optimization Approach

V. Nivedhitha1,*, A. Gopi Saminathan2, P. Thirumurugan3

1 Department of Computer Science and Engineering, SSM Institute of Engineering and Technology, TamilNadu, 624002, India
2 Department of Electronics and Communication Engineering, NPR College of Engineering and Technology, Tamil Nadu, 624401, India
3 Department of Electronics and Communication Engineering, PSNA College of Engineering and Technology, TamilNadu, 624622, India

* Corresponding Author: V. Nivedhitha. Email: email

Intelligent Automation & Soft Computing 2021, 28(3), 603-616. https://doi.org/10.32604/iasc.2021.016780

Abstract

Several protocols strive to improve network longevity but fail to ameliorate the uneven overhead imparted upon the sensor nodes that lead to temporal deaths. The proposed work uses a metaheuristic approach that promotes load balancing and energy-efficient data transmission using the fruit fly optimization algorithm (FFOA). The approach combines the LEACH protocol with differential evolution (DE) to select an optimum cluster head in every cluster. The algorithm is designed to provide energy-efficient data transmissions based on the smell and vision foraging behavior of fruit flies. The approach considers the compactness of nodes, energy capacity, and the distance of sensor nodes from the base station and geocentric location, and other factors to select an optimal cluster head. It provides an optimal solution for the nodes in overlapping cluster heads and the energy problem that occurs due to uneven clustering. The metaheuristic approach implements multi-hop routing by finding an optimal path and allows the cluster head re-election strategy when the data transmission is intense. Simulations prove that FFOA-based LEACH increases the network lifetime through energy-efficient clustering and routing when compared with LEACH and DE-LEACH.

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APA Style
Nivedhitha, V., Saminathan, A.G., Thirumurugan, P. (2021). Improving network longevity in wireless sensor networks using an evolutionary optimization approach. Intelligent Automation & Soft Computing, 28(3), 603-616. https://doi.org/10.32604/iasc.2021.016780
Vancouver Style
Nivedhitha V, Saminathan AG, Thirumurugan P. Improving network longevity in wireless sensor networks using an evolutionary optimization approach. Intell Automat Soft Comput . 2021;28(3):603-616 https://doi.org/10.32604/iasc.2021.016780
IEEE Style
V. Nivedhitha, A.G. Saminathan, and P. Thirumurugan "Improving Network Longevity in Wireless Sensor Networks Using an Evolutionary Optimization Approach," Intell. Automat. Soft Comput. , vol. 28, no. 3, pp. 603-616. 2021. https://doi.org/10.32604/iasc.2021.016780



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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