Localization Scheme Using Single Anchor Node for Mobile Wireless Sensor Nodes in WSNs

Abstract

Mobile wireless sensor networks (MWSNs) have revolutionized observing and tracking. Accurately locating mobile sensor nodes remains a challenging task. The precisely identifying event source location is very important. To locate mobile sensor nodes there is a need of developing an efficient localization method. Most of the researcher have used multiple anchor nodes for localization. Therefore, in resource constraint networks reducing number of anchor nodes is an open research issue. The main idea of this work is to propose a localization method using single anchor node. To achieve this, a novel coordinated auto-localization algorithm with particle swarm optimization (PSO) is introduced to enhance localization and tracking of mobile sensor nodes. A mathematical framework has been developed which uses parallel coordinate system to identify location and PSO to track movement pattern of sensor nodes. PSO minimized localization error by refining position accuracy through iterative convergence. It achieves 10% reduction in localization error and a 25% increase in correctly localized nodes, with an overall tracking precision of 80%. Comparative analysis with different techniques like mobile anchor positioning with mobile anchor & neighbor, fish swarm optimization algorithm, DV-hop localization, and autonomous groups particle swarm optimization shows that this method reduces the average localization error to 10% and improves localization efficiency by reducing the required time by 16% compared to other techniques. A pairwise Wilcoxon rank test with a 95% confidence interval shows the proposed method’s superior performance, with a mean of 2.6321E-18 and standard deviation of 3.2705E-19, compared to other metaheuristic algorithms.