Unbalanced Threshold Based Distributed Data Collection Scheme in Multisink Wireless Sensor Networks

In multisink wireless sensor networks, synchronized data collection among multiple sinks is a significant and challenging task. In this paper, we propose an unbalanced threshold based distributed data collection scheme to reconstruct the synchronized sensed data of the whole sensor network in all sinks. The proposed scheme includes the unbalanced threshold based distributed top-K query algorithm and the distributed iterative hard thresholding algorithm. By computing unbalanced thresholds and pruning unnecessary element exchanging, each sink can synchronize the top-K aggregated values efficiently via the unbalanced threshold based distributed top-K query algorithm. After that, the synchronized sensed data of the whole sensor network can be reconstructed through the distributed iterative hard thresholding algorithm in a distributed and cooperative manner. We show through experiments that the proposed scheme can reduce the interaction times and decrease the number of transmitted data and that of computed data compared to the existing schemes while maintaining the similar data reconstruction accuracy. The communication and computational performances of the proposed scheme are also analyzed in detail in the paper.