CS-FCDA: A Compressed Sensing-Based on Fault-Tolerant Data Aggregation in Sensor Networks

When the nodes in the network are deployed in the target area with an appropriate density, the effective aggregation and transmission of the data gathered in the monitoring area remain to be solved. The existing Compressed Sensing (CS) based on data aggregation schemes are accomplished in a centralized manner and the Sink node achieves the task of data aggregation. However, these existing schemes may suffer from load imbalance and coverage void issues. In order to address these problems, we propose a Compressed Sensing based on Fault-tolerant Correcting Data Aggregation (CS-FCDA) scheme to accurately reconstruct the compressed data. Therefore, the network communication overhead can be greatly reduced while maintaining the quality of the reconstructed data. Meanwhile, we adopt the node clustering mechanism to optimize and balance the network load. It is shown via simulation results, compared with other data aggregation schemes, that the proposed scheme shows obvious improvement in terms of the Fault-tolerant correcting capability and the network energy efficiency of the data reconstruction.