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Efficient Energy Resource Selection in Home Area Sensor Networks using Non Swarm Intelligence Based Discrete Venus Flytrap Search Optimization Algorithm

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Abstract

A new non-swarm intelligence algorithm called discrete Venus fly-trap search algorithm (DVFS) is proposed for the optimal energy resource selection for sensor nodes in home area sensor network (HASN). DVFS algorithm is a population-based, non-swarm intelligence search algorithm that copycats the foraging behaviors of Venus fly-trap plant. The performance of DVFS based energy resource selection methodology is studied by simulating in wireless sensor network toolbox in Matlab2016. The simulation results exposed that the proposed approach can identify optimal energy resource selection from the energy source station to provide the power supply to the nodes in HASN for the network lifespan increment.

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Acknowledgements

The first author gratefully acknowledges financial support from UGC-RGNF (Rajiv Gandhi National Fellowship) and its award letter-number UGC No: F1-17.1/2014-15/RGNF-2014-15-SC-TAM-85083 (SA-III/Website) Dated: 26 Feb 2015.

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  1. Department of Computer Science, Periyar University, Salem, Tamilnadu, India

    S. Sivabalan & R. Rathipriya

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  1. S. Sivabalan
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Correspondence to R. Rathipriya.

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Sivabalan, S., Rathipriya, R. Efficient Energy Resource Selection in Home Area Sensor Networks using Non Swarm Intelligence Based Discrete Venus Flytrap Search Optimization Algorithm. Wireless Pers Commun 128, 249–265 (2023). https://doi.org/10.1007/s11277-022-09953-y

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