Application of Improved Region Growing Algorithm in WSNs Data Acquisition and Fusion

Abstract

Wireless sensor networks are widely used in various fields. How to use data fusion technology to effectively reduce network redundant data, improve data transmission efficiency, and reduce network energy consumption is one of the current research hotspots of wireless sensor networks. In this paper, the improved region growth method is used to divide the network into several similar areas. Dividing sub-regions is equivalent to dividing into several clusters. Selecting a representative node in the subregions selects a cluster head node, and implements data acquisition while letting other nodes sleep. The representative node should best reflect the data change trend of the sub-region, thereby reducing the collection of a large amount of redundant data in the data acquisition stage. The simulation experiment results verified the effectiveness and reliability of the algorithm. By comparison, the improved region growing algorithm is better than the traditional clustering-fusion method in the redundant data processing in the cluster.