A One-dimensional Linear Regression Model Based Spatial and Temporal Data Compression Algorithm for Wireless Sensor Networks

Wang Lei-chun; Ma Chuan-xiang

doi:10.3724/SP.J.1146.2009.00704

Volume 32 Issue 3

Aug. 2010

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Article Navigation > Journal of Electronics & Information Technology > 2010 > 32(3): 755-758

Wang Lei-chun, Ma Chuan-xiang. A One-dimensional Linear Regression Model Based Spatial and Temporal Data Compression Algorithm for Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2010, 32(3): 755-758. doi: 10.3724/SP.J.1146.2009.00704

Citation:

Wang Lei-chun, Ma Chuan-xiang. A One-dimensional Linear Regression Model Based Spatial and Temporal Data Compression Algorithm for Wireless Sensor Networks[J]. Journal of Electronics & Information Technology, 2010, 32(3): 755-758. doi: 10.3724/SP.J.1146.2009.00704

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A One-dimensional Linear Regression Model Based Spatial and Temporal Data Compression Algorithm for Wireless Sensor Networks

doi: 10.3724/SP.J.1146.2009.00704

Received Date: 2009-05-12
Rev Recd Date: 2009-09-25
Publish Date: 2010-03-19

Abstract

Abstract

Considering spatial and temporal redundancy of data and demand of saving energy in Wireless Sensor Networks (WSN), a One-Dimensional Linear Regression model based Spatial and Temporal(ODLRST) data compression algorithm, is proposed. By eliminating temporal redundancy of data in single node and spatial redundancy of data among nodes respectively in WSN, ODLRST greatly compresses these data. Simulation results show that ODLRST can reduce data size sent by nodes and network traffic in WSN, and save and balance energy consumption in the network.

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