Coverage improvement Using MDBOSO for Wireless Sensor Deployment
Aparna Pradeep Laturkar, S. Bhavani · 2016
Wireless Sensor Network (WSN) is emerging technology and has wide range of applications, such as environment monitoring, home and assisted living medical care, industrial automation and numerous military applications. Therefore WSN is popular amongst researchers and scholars. WSN has several constraints such as restricted sensing range, communication range and limited battery capacity. Such limitations bring issues such as coverage, connectivity, network lifetime and scheduling & data aggregation. There are mainly three strategies for solving coverage problems which are, namely, force, grid and computational geometry based. This project implements the sensor deployment using grid based particle swarm optimization (PSO) based algorithms. PSO is a multidimensional optimization method inspired from the social behavior of birds called flocking. Basic version of PSO has the drawback of sometimes getting trapped in local optima as particles learn from each other and past solutions. This issue is solved by discrete version of PSO known as modified discrete binary PSO (MDBPSO) as it uses probabilistic approach. This project analyzes the performance of sensor deployment algorithms with different sensing radius, grid size on different size of region of interest (ROI).