Design Data Fusion Model for Distributed Detection of Wireless Sensor Network using Improved Genetic Algorithm
Keywords:
WSN, Distributed Detection, IGA, Data Fusion, MATLAB, EnergyAbstract
The detection of the target node is a big issue in the wireless sensor network environment. the detection of the target node applies the process of distance estimation from the local sensor node to the target sensor node. Therefore, the data fusion methods play a vital role in detecting the target node in a wireless sensor network. The data fusion methods collect the local sensor data and make decisions for the target node. This paper design methods for the detection of the target node. The design model is based on an improved genetic algorithm and data fusion process. The design model reduces the possibility of false detection of the target node and improves energy utilization. However, the utilization of energy is compromised with the maximum distance of the target node with local sensor nodes. The applied model estimates the optimal distance of the target node. The design model simulates in MATLAB environments with standard simulation parameters. The design model compares with two algorithms is called DS and CWN. the analysis suggests that the design model is very efficient in compression with the existing algorithm.
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