Improving prediction accuracy for WSN data reduction by applying multivariate spatio-temporal correlation.
Improving prediction accuracy for WSN data reduction by applying multivariate spatio-temporal correlation.
复制标题
DOI：
10.3390/s111110010
复制
发表时间：
2011
期刊：
影响因子：
--
通讯作者：
de Souza JN
中科院分区：
文献类型：
--
作者：
Carvalho C;Gomes DG;Agoulmine N;de Souza JN
This paper proposes a method based on multivariate spatial and temporal correlation to improve prediction accuracy in data reduction for Wireless Sensor Networks (WSN). Prediction of data not sent to the sink node is a technique used to save energy in WSNs by reducing the amount of data traffic. However, it may not be very accurate. Simulations were made involving simple linear regression and multiple linear regression functions to assess the performance of the proposed method. The results show a higher correlation between gathered inputs when compared to time, which is an independent variable widely used for prediction and forecasting. Prediction accuracy is lower when simple linear regression is used, whereas multiple linear regression is the most accurate one. In addition to that, our proposal outperforms some current solutions by about 50% in humidity prediction and 21% in light prediction. To the best of our knowledge, we believe that we are probably the first to address prediction based on multivariate correlation for WSN data reduction.
登录
查看更多内容
DOI：
10.1109/tpds.2010.174
发表时间：
2011-06-01
影响因子：
5.3
作者：
Jiang, Hongbo;Jin, Shudong;Wang, Chonggang
通讯作者：
Wang, Chonggang
DOI：
10.1109/tpds.2007.1046
发表时间：
2007-07-01
影响因子：
5.3
作者：
Liu, Chong;Wu, Kui;Pei, Jian
通讯作者：
Pei, Jian
影响因子：
2.8
作者：
Goel, S;Imielinski, T
通讯作者：
Imielinski, T
影响因子：
5.6
作者：
Vuran, MC;Akan, ÖB;Akyildiz, IF
通讯作者：
Akyildiz, IF
影响因子：
35.6
作者：
Kulkarni, Raghavendra V.;Foerster, Anna;Venayagamoorthy, Ganesh Kumar
通讯作者：
Venayagamoorthy, Ganesh Kumar