Integrated Compressive Sensing based Clustering Approach to Improve Network Lifetime in WSN

Wireless Sensor Network aka WSN is utilized for various applications such as military agriculture and other commercial fields which causes a huge range of data generation; such large data causes the data redundancy and it’s difficult to analyse, hence data aggregation approach is used. A popular mechanism of data aggregation which has been used in reducing data redundancy has always been compressive sensing. Hence, this research uses the development and design of an ICCM (Integrated CS Clustering) mechanism, which is used in the incorporation of clusters and mechanism of compressive sensing for a design and an efficient WSN architecture. In ICCM, the heads of the clusters use an optimized CS mechanism in the transmission of data to the base station. Further, an approach of optimized clustering has been used for efficient clustering. A stand-alone logical link has been designed for the transmission of data. The ICCM is then evaluated, considering various parameters are considered such as consumption of energy, Communication overhead, and route length. There is also a comparative study and analysis of the existing model which suggests the ICCM outperforms the existing model with a nearly average improvisation of 45% in terms of energy consumption.