Genetic Algorithm Approach improved by 2D Lifting Scheme for Sensor Node Placement in Optimal Position
T. Ganesan, P. Rajarajeswari · 2019
In this smart connected world, Sensors are scattered in the environment of interest in order to perform a surveillance monitoring activity for the target operational research. In order to cover the target, sensor node placement plays a crucial role to cover maximum target and minimum node connectivity with limited nodes. Sensor data gathering can be achieved by using important principle node connectivity. Signals in sensor network carry a large amount of data and retaining important information is often more difficult. To overcome this problem we propose a genetic algorithm based node placement the result is improved by wavelets to achieve a maximum coverage and connectivity. The experimental result is carried out to improve the quality of covered data with limited sensor in optimal positions.