Spline approximation-based data compression for sensor arrays in the wireless hydrologic monitoring system. (February 2017)

• Record Type: Journal Article
• Authors: Li, Danyang; Huangfu, Wei; Long, Keping
• Is Part Of: International journal of distributed sensor networks. Volume 13:Number 2(2017)
• Publication Date: 2017-02
• Subjects: Catmull-Rom spline -- data compression -- sensor array -- hydrologic monitoring -- wireless sensor network; Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1177/1550147717692584
• Languages: English
• ISSNs: 1550-1329

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.