A kind of effective data aggregating method based on compressive sensing for wireless sensor network

• Published in: EURASIP journal on wireless communications and networking Vol. 2018; no. 1; pp. 1 - 15
• Main Authors: Zhang, De-gan, Zhang, Ting, Zhang, Jie, Dong, Yue, Zhang, Xiao-dan
• Format: Journal Article
• Language: English
• Published: Cham Springer International Publishing 19.06.2018; Springer Nature B.V; SpringerOpen
• Subjects: Clustering; Communications Engineering; Compressive sensing; Data aggregating; Data management; Detection; Effective; Energy consumption; Engineering; Information Systems Applications (incl.Internet); Internet of things; Mathematical analysis; Matrix algebra; Matrix methods; Networks; Remote sensors; Signal,Image and Speech Processing; Wireless networks; Wireless sensor networks; WSN; Internet of things; Compressive sensing; Data aggregating; WSN; Effective
• ISSN: 1687-1499; 1687-1472; 1687-1499
• DOI: 10.1186/s13638-018-1176-4

Wireless sensor network (WSN) in the Internet of Things consists of a large number of nodes. The proposal of compressive sensing technology provides a novel way for data aggregation in WSN. Based on the clustering structure of WSN, a kind of effective data aggregating method based on compressive sensing is proposed in this paper. The aggregating process is divided into two parts: in the cluster, the sink node sets the corresponding seed vector based on the distribution of network and then sends it to each cluster head. Cluster head can generate corresponding own random spacing sparse matrix based on its received seed vector and collect data through compressive sensing technology. Among clusters, clusters forward measurement values to the sink node along multi-hop routing tree. Performance analysis and comparison with the relative methods show that our method is effective and superior to other methods regardless of intra-cluster or inter-cluster on the total energy consumption of network.