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Hybrid Mutualism Mechanism-Inspired Butterfly and Flower Pollination Optimization Algorithm for Lifetime Improving Energy‐Efficient Cluster Head Selection in WSNs

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Abstract

Rapid advancement of technologies in Wireless Sensor Networks is attracting maximized attention across the scientific community due to its suitability and diversified coverage in real life applications. WSNs due to their features of resource limitation and infrastructure-less deployment introduces the most challenging issues of network lifetime improvement, energy stability and reliable cluster head selection, which is still a herculean task. Clustering is an indispensable mechanism employed for selecting an optimal cluster head with the objective of extending network lifetime with energy stability that achieves efficient data transmission. Cluster head selection through meta-heuristic algorithms introduces the merits of simplicity, flexibility, derivation free and prevents local optima. In this paper, Hybrid Mutualism Mechanism-inspired Butterfly and Flower Pollination Optimization Algorithm (HMMB-FPOA) is proposed for energy‐efficient cluster head selection that attributes towards better energy stability and sustained network lifetime. Mutualism phase includes the symbiosis organisms search over flower pollination optimization algorithm for incorporating strong exploitation capability into butterfly optimization algorithm that prevents losses of premature convergence as it may lose its diversity. This integration of FPOA and BOA improves the overall exploration ability to the expected level, such that convergence speed of the algorithms is accelerated. It also balances the capabilities of exploitation and exploration by dynamically increasing the adaptive switching probability that results in prolonged network lifetime. The simulation results of HMMB-FPOA confirmed an enhanced performance of the network in terms of alive nodes, dead nodes, residual energy, overall throughput, and convergence rate on par with the existing competitive cluster head selection algorithms.

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Correspondence to S. Jaya Pratha.

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Pratha, S.J., Asanambigai, V. & Mugunthan, S.R. Hybrid Mutualism Mechanism-Inspired Butterfly and Flower Pollination Optimization Algorithm for Lifetime Improving Energy‐Efficient Cluster Head Selection in WSNs. Wireless Pers Commun 128, 1567–1601 (2023). https://doi.org/10.1007/s11277-022-10010-x

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