首页|Real-Time Data Recovery in Wireless Sensor Networks Using Spatiotemporal Correlation Based on Sparse Representation
Real-Time Data Recovery in Wireless Sensor Networks Using Spatiotemporal Correlation Based on Sparse Representation
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NSTL
Wiley-Hindawi
Due to data loss and sparse sampling methods utilized in WSNs to reduce energy consumption, reconstructing the raw sensed data from partial data is an indispensable operation. In this paper, a real-time data recovery method is proposed using the spatiotemporal correlation among WSN data. Specifically, by introducing the historical data, joint low-rank constraint and temporal stability are utilized to further exploit the data spatiotemporal correlation. Furthermore, an algorithm based on the alternating direction method of multipliers is described to solve the resultant optimization problem efficiently. The simulation results show that the proposed method outperforms the state-of-the-art methods for different types of signal in the network.
Jingfei He、Yatong Zhou
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The School of Electronics and Information Engineering and Key Laboratory of Electronic Materials and Devices of Tianjin, Hebei University of Technology
NSTL
Wiley-Hindawi
