Journal of Computer Applications (计算机应用) 2013/33:12 PP.3457-3459
In order to improve the accuracy of the estimated missing data in Wireless Sensor Network (WSN), a self-decision interpolation algorithm was proposed. The algorithm selected different estimation strategies of missing data according to the spatial correlation of the data sets and the continuity of missing data, then introduced the Auto-Regressive and Moving Average (ARMA) model into the study of missing data interpolation. In corresponding to the traditional missing value estimation algorithm, the proposed algorithm not only considered the characteristics of wireless sensor networks, but also took the characteristics of the data themselves into account. The experimental results on the real data sets show that the proposed algorithm improves the precision of the estimation for missing data.