Spline approximation-based data compression for sensor arrays in the wireless hydrologic monitoring system

Danyang Li, Wei Huangfu and Keping Long

International Journal of Distributed Sensor Networks, 2017, vol. 13, issue 2, 1550147717692584

Abstract: A sensor array produces lots of bits of data every sample period, which may cause a heavy burden on the long-distance wireless data transmission, especially in the scenarios of wireless sensor networks. A lossy but error-bounded sensor array data compression algorithm is proposed, in which the major part of the sensor array data are approximated by the Catmull-Rom spline curve and the residual errors are quantized and encoded with Huffman coding. The performance of this algorithm has been evaluated with a real data set from the wireless hydrologic monitoring system deployed in Qinhuangdao Port of China. The results show that the algorithm performs well for the hydrologic sensor array data.

Keywords: Catmull-Rom spline; data compression; sensor array; hydrologic monitoring; wireless sensor network (search for similar items in EconPapers)
Date: 2017
References: Add references at CitEc
Citations:

Downloads: (external link)
https://journals.sagepub.com/doi/10.1177/1550147717692584 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:sae:intdis:v:13:y:2017:i:2:p:1550147717692584

DOI: 10.1177/1550147717692584

Access Statistics for this article

More articles in International Journal of Distributed Sensor Networks
Bibliographic data for series maintained by SAGE Publications ().