Abstract
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.
Highlights
The Wireless Sensor Networks (WSNs) solve the information gathering problem of the physical world for humans and associates the human logical society with the objective physical world [1,2,3]
A compressive sensing function was proposed in paper [15] which based on a proper function base, employs a modified Compressed Sensing (CS) technique to improve the data compression quality of the data gathered in the network
2. (Sensing matrix): The sensing used to describe dynamic environmental information t described as follows: X = x(i, j)n is monitored by the sensor network and its mathematical form where n and t mean the quantity of the nodes and the quantity of the data gathered at different times
Summary
The Wireless Sensor Networks (WSNs) solve the information gathering problem of the physical world for humans and associates the human logical society with the objective physical world [1,2,3]. It is generally used in industries, agriculture, medical treatment, environment monitoring, etc. A great deal of sensor nodes which integrate the functions of sensing, communication, computation, and even storage composes the WSN. In order to solve the coverage void issue caused by the different node load, we design a low-cost network clustering method which can greatly improve network service property according to the data communication, energy efficiency, load balance and data Fault-tolerant correcting capabilities. The network lifetime can be prolonged when the QoS is guaranteed
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