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NBA: novel bio-inspired algorithm for energy optimization in WSN for IoT applications

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Abstract

Wireless sensor networks (WSN) are the integral part of Internet of Things (IoT) applications. They consist of many sensor nodes energized by batteries. These batteries turn out to be dead after the usage of specific duration. The lifespan of the sensor devices depends on its battery life. So it is inevitable that the battery life is to be maintained optimally. Intensifying the data spread in a well-regulated mode helps to increase the lifespan of the sensor devices. Clustering is one of the techniques which help in enhancing the network lifetime of WSN. The optimal selection of cluster heads is a vital parameter. In view of this, a novel fusion cluster head selection algorithm is offered by combining the advantages of LEACH protocol and dragonfly algorithm. The swarm intelligent behavior of dragonfly is deployed to group the sensors and to choose the optimal route to reach the base station. The new algorithm is tested on diverse scenarios of WSNs, by varying the maximum runs and the total sum of sensor nodes. The performance appraisal is made with reference to number of live nodes, dead nodes, and packet transmission ratio. The proposed energy efficient, novel bio-inspired algorithm (NBA) is compared with other existing state-of-the-art algorithms which demonstrate that the new method is effective in broadening network life expectancy satisfactorily.

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Correspondence to Deepa Devassy.

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Devassy, D., Immanuel Johnraja, J. & Paulraj, G.J.L. NBA: novel bio-inspired algorithm for energy optimization in WSN for IoT applications. J Supercomput 78, 16118–16135 (2022). https://doi.org/10.1007/s11227-022-04505-4

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