Abstract
In recent times, the wireless sensor network (WSN) has been designed to save energy for prolonging its lifetime. Minimize the implementation cost and energy utilization of sensors, and various data compression techniques have been used. We propose a new algorithm, semi-variance based compressive sensing (SCS), in this paper. The proposed scheme works with the spatio-temporal correlation of the signal and its performance investigated based on energy utilization and data quality. The new technique outperforms the existing data compression methods discussed in the literature survey. The simulation results prove that SCS effectively minimizes the computational and transmission cost of data and extends the life period of the WSN.
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