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Clustering and Compressive Data Gathering for Transmission Efficient Wireless Sensor Networks

Clustering and Compressive Data Gathering for Transmission Efficient Wireless Sensor Networks

Utkarsha Sumedh Pacharaney, Ranjan Bala Jain, Rajiv Kumar Gupta
Copyright: © 2021 |Pages: 28
ISBN13: 9781522594932|ISBN10: 1522594930|EISBN13: 9781522594956
DOI: 10.4018/978-1-5225-9493-2.ch002
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MLA

Pacharaney, Utkarsha Sumedh, et al. "Clustering and Compressive Data Gathering for Transmission Efficient Wireless Sensor Networks." Managing Resources for Futuristic Wireless Networks, edited by Mamata Rath, IGI Global, 2021, pp. 28-55. https://doi.org/10.4018/978-1-5225-9493-2.ch002

APA

Pacharaney, U. S., Jain, R. B., & Gupta, R. K. (2021). Clustering and Compressive Data Gathering for Transmission Efficient Wireless Sensor Networks. In M. Rath (Ed.), Managing Resources for Futuristic Wireless Networks (pp. 28-55). IGI Global. https://doi.org/10.4018/978-1-5225-9493-2.ch002

Chicago

Pacharaney, Utkarsha Sumedh, Ranjan Bala Jain, and Rajiv Kumar Gupta. "Clustering and Compressive Data Gathering for Transmission Efficient Wireless Sensor Networks." In Managing Resources for Futuristic Wireless Networks, edited by Mamata Rath, 28-55. Hershey, PA: IGI Global, 2021. https://doi.org/10.4018/978-1-5225-9493-2.ch002

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Abstract

The chapter focuses on minimizing the amount of wireless transmission in sensory data gathering for correlated data field monitoring in wireless sensor networks (WSN), which is a major source of power consumption. Compressive sensing (CS) is a new in-node compression technique that is economically used for data gathering in an energy-constrained WSN. Among existing CS-based routing, cluster-based methods offer the most transmission-efficient architecture. Most CS-based clustering methods randomly choose nodes to form clusters, neglecting the topology structure. A novel base station (BS)-assisted cluster, spatially correlated cluster using compressive sensing (SCC_CS), is proposed to reduce number of transmissions in and form the cluster by exploiting spatial correlation based on geographical proximity. The proposed BS-assisted clustering scheme follows hexagonal deployment strategy. In SCC_CS, cluster heads are solely involved in data gathering and transmitting CS measurements to BS, saving intra-cluster communication cost, and thus, network life increases as proved by simulation.

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