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

Abstract

This research work examines the foraging behavior of the Carnivorous plant called Venus flytrap. These plants derive their nutrients from trapping and consuming insects and another arthropod. Unlike swarm behavior, they forage independently and autonomously. Based on this, a new non-swarm intelligence algorithm called Discrete Venus Fly-Trap Search Algorithm (DVFS) is proposed for energy resource selection for sensor nodes in the Home Area Sensor Network (HASN). Discrete Venus Fly-Trap Search Algorithm is a population-based, non-swarm intelligence search algorithm that copycats the foraging behaviors of Venus Fly-Trap Plant. The search performance of DVFS algorithm is studied by simulating in Wireless Sensor Network Toolbox in Matlab2016. The results expose that the proposed algorithm 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.