Partial Matrix Completion Algorithm for Efficient Data Gathering in Wireless Sensor Networks

To enable efficient data gathering in wireless sensor networks, a novel partial matrix completion algorithm is proposed by introducing historical data to the original data matrix. The recovery accuracy is further improved by making full use of the band-limited feature of the sensory data. We analyzed the recovery error of the proposed algorithm and derived a theoretical error upper bound. Experimental results on two real-world data sets show that the proposed algorithm achieves good recovery accuracy even when the sampling ratio is very low, which outperforms the state-of-the-art methods.