Weighted Centroid Amorphous Algorithm for Position Error Minimization in WSN

Abstract

Wireless Sensor Networks (WSNs) have numerous applications, one of which is localization. Localization is crucial for determining the position of unknown sensor nodes in the deployment environment. Localization techniques are broadly classified into two categories: range based and range‐free. Range‐free localization techniques are gaining popularity as they are easy to implement and do not require external hardware. In this proposed work, a hybrid localization algorithm named the Weighted Centroid Amorphous algorithm is proposed to reduce the position error in WSN. Instead of the conventional centroid algorithm, a weighted centroid algorithm is used. The weight in this work is considered as a function of the hop value and hop size estimated by the Amorphous algorithm. Ten nearest beacon nodes are considered to determine the coordinates of a single unknown node. The hop value and hop size of that unknown node are calculated from the 10 nearest beacon nodes, and by using the hop value and hop size, the weight is calculated. After the weight estimation, the weighted sum is calculated, and using the weighted sum, the coordinates of an unknown node are determined. Simulation results indicate that the proposed Weighted Centroid Amorphous method achieves superior accuracy, with rates of 90.41%, 89.57%, and 86.10% compared to the traditional Amorphous, improved Amorphous, and Ensemble approach, respectively.