Big Data Reduction and Optimization in Sensor Monitoring Network
Joint Authors
Source
Journal of Applied Mathematics
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-8, 8 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-03-23
Country of Publication
Egypt
No. of Pages
8
Main Subjects
Abstract EN
Wireless sensor networks (WSNs) are increasingly being utilized to monitor the structural health of the underground subway tunnels, showing many promising advantages over traditional monitoring schemes.
Meanwhile, with the increase of the network size, the system is incapable of dealing with big data to ensure efficient data communication, transmission, and storage.
Being considered as a feasible solution to these issues, data compression can reduce the volume of data travelling between sensor nodes.
In this paper, an optimization algorithm based on the spatial and temporal data compression is proposed to cope with these issues appearing in WSNs in the underground tunnel environment.
The spatial and temporal correlation functions are introduced for the data compression and data recovery.
It is verified that the proposed algorithm is applicable to WSNs in the underground tunnel.
American Psychological Association (APA)
He, Bin& Li, Yonggang. 2014. Big Data Reduction and Optimization in Sensor Monitoring Network. Journal of Applied Mathematics،Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-461149
Modern Language Association (MLA)
He, Bin& Li, Yonggang. Big Data Reduction and Optimization in Sensor Monitoring Network. Journal of Applied Mathematics No. 2014 (2014), pp.1-8.
https://search.emarefa.net/detail/BIM-461149
American Medical Association (AMA)
He, Bin& Li, Yonggang. Big Data Reduction and Optimization in Sensor Monitoring Network. Journal of Applied Mathematics. 2014. Vol. 2014, no. 2014, pp.1-8.
https://search.emarefa.net/detail/BIM-461149
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-461149