IoT 19(19): e5

Research Article

Binary Monkey-King Evolutionary Algorithm for single objective target based WSN

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  • @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
D. Lubin Balasubramanian1,*, V. Govindasamy2
  • 1: Research Scholar, Department of Computer Science & Engineering, Pondicherry Engineering College, Puducherry, India
  • 2: Associate Professor, Department of Information Technology, Pondicherry Engineering College, Puducherry, India
*Contact email: balu.daya@gmail.com

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.