[KSCI] Korea Science Citation Index Service

http://dx.doi.org/10.6109/jicce.2015.13.2.105

A New Estimation Model for Wireless Sensor Networks Based on the Spatial-Temporal Correlation Analysis

Ren, Xiaojun (Department of Ubiquitous IT, Dongseo University)
Sug, HyonTai (Department of Ubiquitous IT, Dongseo University)
Lee, HoonJae (Department of Ubiquitous IT, Dongseo University)

Publication Information

Journal of information and communication convergence engineering / v.13, no.2, 2015 , pp. 105-112 More about this Journal

Abstract

The estimation of missing sensor values is an important problem in sensor network applications, but the existing approaches have some limitations, such as the limitations of application scope and estimation accuracy. Therefore, in this paper, we propose a new estimation model based on a spatial-temporal correlation analysis (STCAM). STCAM can make full use of spatial and temporal correlations and can recognize whether the sensor parameters have a spatial correlation or a temporal correlation, and whether the missing sensor data are continuous. According to the recognition results, STCAM can choose one of the most suitable algorithms from among linear interpolation algorithm of temporal correlation analysis (TCA-LI), multiple regression algorithm of temporal correlation analysis (TCA-MR), spatial correlation analysis (SCA), spatial-temporal correlation analysis (STCA) to estimate the missing sensor data. STCAM was evaluated over Intel lab dataset and a traffic dataset, and the simulation experiment results show that STCAM has good estimation accuracy.

Keywords

Data mining; DESM; Missing sensor data; STCAM;

Citations & Related Records

Reference

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