A Weighted Centroid Localization Algorithm Based on DBSCAN Clustering Point Density
Journal Title: 河南科技大学学报（自然科学版） - Year 2018, Vol 39, Issue 2
Abstract
The weighted centroid localization algorithm was the most commonly used localization algorithm in wireless sensor network.In order to improve its positioning accuracy, the clustering algorithm was applied to the localization in wireless sensor networks. A weighted centroid localization algorithm based on densitly-based spatial clustering of application with noise ( DBSCAN) clustering point density was proposed.The parameter was chosen according to the degree of collinearity, and the set of localization triangle was established.Then a part of triangle which had better localization effectiveness in this set was chosen to locate unknown node, and the obtained result of initial positioning was clustered by DBSCAN. After the large error location coordinate was eliminated, the number of core points in each cluster was regarded as the weight, and the weighted centroid localization algorithm was used to obtain the final location of the unknown node. The simulation results show that compared with the traditional weighted centroid localization algorithm, the average localization error of the proposed algorithm is reduced by more than 80%. The localization accuracy of wireless sensor networks is improved effectively.
Authors and Affiliations
Yi LI, Liang ZHANG, Ran ZHANG, Shen ZHANG
Keywords
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