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

Autor: De-gan Zhang, Ting Zhang, Jie Zhang, Yue Dong, Xiao-dan Zhang
Jazyk: angličtina
Rok vydání: 2018
Předmět:
Zdroj: EURASIP Journal on Wireless Communications and Networking, Vol 2018, Iss 1, Pp 1-15 (2018)
Druh dokumentu: article
ISSN: 1687-1499
DOI: 10.1186/s13638-018-1176-4
Popis: Abstract 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.
Databáze: Directory of Open Access Journals
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