Journal
WIRELESS COMMUNICATIONS & MOBILE COMPUTING
Volume -, Issue -, Pages -Publisher
WILEY-HINDAWI
DOI: 10.1155/2019/2310730
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Funding
- National Natural Science Foundation of China [61801164]
- Natural Science Foundation of Tianjin City [18JCQNJC01700]
- Foundation of Hebei Educational Committee [QN2018092]
- Natural Science Foundation of Hebei Province [F2019202387]
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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.
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