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ACS LEACH protocol using optimized clustering and improved orthogonal matching pursuit in WSN

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Abstract

An energy-efficient data gathering method for resource-constrained Wireless Sensor Networks (WSNs) is Compressive Sensing (CS). CS promises the construction of a meaningful sparse data matrix from the generated data packets in WSNs and recovers all data from the sparse data matrix at the sink node. Recent works incorporate the CS method with cluster-based algorithms to improve the power-saving capability of the CS algorithm. This paper proposes an Adaptive Compressed Sensing (ACS) to overcome the drawbacks of hybrid CS. The ACS decides an optimal size of clusters and considers the relation between the number of measurement M and the number of nodes. Moreover, the data aggregation process exploits the classical Fourier transform for attaining good stability with low computational complexity. Finally, an adaptive data recovery technique to clustered WSNs is used to improving the orthogonal matching pursuit. The ACS-LEACH is evaluated and compared with the existing schemes using NS2 to prove its superiority in WSNs. From the simulation results, the throughput of ACS-LEACH is 0.018 bits/s in 90 node topology, and in the same scenario, the LEACH-CS and IHCS stand only for 0.012 and 0.0011 bits/s, respectively.

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Authors and Affiliations

  1. K. B. N. College of Engineering, Kalaburagi, Karnataka, India

    Nandini S. Patil & Asma Parveen

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  1. Nandini S. Patil
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  2. Asma Parveen
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Correspondence to Nandini S. Patil.

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Patil, N.S., Parveen, A. ACS LEACH protocol using optimized clustering and improved orthogonal matching pursuit in WSN. Int. j. inf. tecnol. 14, 175–184 (2022). https://doi.org/10.1007/s41870-021-00791-y

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