Research Article
Binary Monkey-King Evolutionary Algorithm for single objective target based WSN
@ARTICLE{10.4108/eai.29-7-2019.163970, author={D. Lubin Balasubramanian and V. Govindasamy}, title={Binary Monkey-King Evolutionary Algorithm for single objective target based WSN}, journal={EAI Endorsed Transactions on Internet of Things}, volume={5}, number={19}, publisher={EAI}, journal_a={IOT}, year={2019}, month={7}, keywords={Single objective WSN, Genetic Algorithm, Particle Swarm Optimization, Monkey King Evolution Algorithm}, doi={10.4108/eai.29-7-2019.163970} }- D. Lubin Balasubramanian
V. Govindasamy
Year: 2019
Binary Monkey-King Evolutionary Algorithm for single objective target based WSN
IOT
EAI
DOI: 10.4108/eai.29-7-2019.163970
Abstract
INTRODUCTION: Target based WSN faces coverage issue in which many targets could not be efficiently covered by static deployed sensors.
OBJECTIVES: This paper covers the issue of coverage problems by deploying the sensors to cover all the targets with minimized sensors in number.
METHODS: This paper proposes a Binary based Monkey King Evolutionary Algorithm for solving target based WSN problem, the proposed model consist a Binary method for converting the continuous values into binary form to solve the choice of potential position to place the sensors.
RESULTS: The proposed algorithm is evaluated in a 50x50 grid and 100x100 grid to track the performance and the performance of the proposed is compared with GA and PSO.
CONCLUSION: This paper utilized the MKE algorithm for improving the efficiency of the target coverage problem in WSN. It mainly focused on a single objective-based solution providing for small scale problems. From the simulation results, it is provided that the proposed MKE algorithm obtained 1.86 % of the F-value, which is higher than the other optimization algorithms such as GA and PSO.
Copyright © 2019 D. Lubin Balasubramanian et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.
