Indian Journal of Public Health Research & Development
  • Year: 2018
  • Volume: 9
  • Issue: 8

Optimizing Coverage Area of Heterogeneous Wireless Sensor Network (WSN) Using Genetic Algorithm

1Research Scholar, ECE, St. Peter’s University, Avadi, Chennai

2Professor and Head, Department of Biomedical Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Thandalam, Chennai

Online published on 21 September, 2018.

Abstract

A wireless sensor network is a correspondence framework which detects and accumulates data from a specific zone and sends it to the base station or sink node. WSN can be very exceptionally valuable for target detection and recognizable proof by military and ecological applications like agrarian farm monitoring and woodland fire supervising. A genetic algorithm is a meta-heuristic approach propelled by the process of natural selection that belongs to the class of evolutionary algorithms. It is utilized to create high-quality solutions to optimization and search problem by relying on bio-inspired operators such as mutation, crossover, and selection. The goal is deploying a minimum number of sensor element nodes without overlapping each other based on antenna height and separation between sensor nodes. The experimental result shows that better coverage in heterogeneous wireless sensor network using NS2 software simulation.

Keywords

Crossover, Genetic algorithm, Mutation, Wireless sensor network